Coarse-Grained Protein Models and Their Applications
- Sebastian Kmiecik
- ,
- Dominik Gront
- ,
- Michal Kolinski
- ,
- Lukasz Wieteska
- ,
- Aleksandra Elzbieta Dawid
- , and
- Andrzej Kolinski
View Author Information
† Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
‡ Bioinformatics Laboratory, Mossakowski Medical Research Center of the Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland
§ Department of Medical Biochemistry, Medical University of Lodz, Mazowiecka 6/8, 92-215 Lodz, Poland
*E-mail: [email protected]. Phone: +48 22 55 26 365. Fax: (+48) 22 55 26 364.
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Abstract
The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.
1 Introduction
ARTICLE SECTIONS
Living organisms are the most complex chemical systems whose function depends on a vast number of molecules, from simple monomers through many small and medium-size oligomers and copolymers (peptides, proteins, RNA, etc.) to huge copolymers such as DNA. With some exceptions, proteins are composed of 20 types of amino acids. Again with some exceptions, all amino acids in living organisms have left-handed conformations. Since typical protein chains consist of a few tens to hundreds of amino acids, the number of possible amino acid sequences of such copolymers is enormous. While sequences of amino acid units in natural proteins look at first glance random, they are certainly not. (1) The majority of known natural proteins fold into specific three-dimensional structures, while the vast majority of random polypeptides collapse to somewhat less dense unstructured states. Protein folding plays an essential functional role in living cells, although this process could be also observed at properly controlled in vitro experiments. Owing to the impressive progress in the experimental methods of molecular biology in the last decades we now know around 120 thousand three-dimensional native-like protein structures or their complexes, with resolutions from about 0.5 to 2–3 Å. This is still only a small fraction of proteins with known sequences, (2) although for a large fraction of sequenced proteins their three-dimensional structures can be predicted theoretically by various combinations of bioinformatics and molecular modeling techniques. (3) Theoretical prediction of folded (native-like) three-dimensional protein structures is just one of the key tasks of computational structural biology. Native structures are not completely fixed, (4-6) but they change when proteins perform their biological function, interact with other biomacromolecules, or undergo unfolding–folding transitions. Computational modeling of these processes is crucial for creating realistic molecular pictures of biological protein functions, interpretation of different experimental data, knowledge-based drug design and various aspects of biotechnology, etc. (7-13) Classical atom-level molecular modeling can address many of the these tasks, but its practical applications are still limited by its algorithmic efficiency and the available computing power. (14) Even using a special-purpose supercomputer dedicated to atomistic molecular dynamics (MD) simulations, (15) it is possible to simulate folding processes of only small, relatively fast folding proteins (16, 17) or their dimerization processes (18) (see Figure 1). Similar limitations apply to molecular docking, studies of dynamics of biomacromolecular systems, and other related tasks. This is a major reason why development and practical applications of coarse-grained protein modeling methods is needed. (19-33)
Figure 1
Figure 1. Application ranges for molecular modeling at different resolutions: quantum, all-atom, coarse-grained, and mesoscale. The plot shows approximate ranges of time scales and system sizes (lengths). The presented application ranges can be expanded by merging tools of different resolution into multiscale schemes.
The first coarse-grained protein models were proposed almost half a century ago, although only very recently did coarse-grained models become widely used, especially in multiscale modeling pipelines. In 2013, the Nobel Prize Committee awarded the Prize in Chemistry “for the development of multiscale models for complex chemical systems,” recognizing the early achievements of Michael Levitt, Ariel Warshel, and Martin Karplus that included the coarse-grained modeling of proteins (34, 35) as an important step in the investigation of large biomolecular systems. (36)
In the last ten years the number of publications on developments and applications of coarse-grained models of biomolecules has increased several times. (27) There are good reasons for this increasing role. First, experimental molecular biology provides enormous volumes of data that need interpretation. Second, as noted before, in spite of the rapid increase of computing power, applications of all-atom MD, the classical tool for molecular modeling, are still limited to relatively small systems and rather fast processes. Coarse-grained models are computationally more effective and enable simulations of much longer time-scales and/or larger sizes of the systems studied. Third, well-designed coarse-grained models of a not too low resolution enable reasonable reconstruction of modeled structures to all-atom resolution. This opens up a possibility of multiscale modeling, based on a combination of the computational speed of coarse-grained models with the high accuracy of classical all-atom MD. (25, 37-40)
Coarse-grained protein models assume various levels of reduced polypeptide chain representation (19-32) (see section 2.2). The protein main chain could be represented by all heavy atoms or by one or two united atoms per residue, while just one or two united atoms typically replace the side chain. Various definitions of models of interactions for coarse-grained representations are possible (see section 2.3). Perhaps more challenging “physics-based” derivations of coarse-grained force fields start from classical all-atom models of interactions and translate them into united atom potentials. (21, 30) Very different are “knowledge-based” interaction schemes derived from the statistical regularities seen in known protein structures. (41, 42) Both approaches to building interaction schemes have their weaknesses and advantages. Sampling procedures can be based on various versions of MD and/or Monte Carlo (MC) methods (see section 2.4). Sometimes heuristic approaches are also used. The majority of coarse-grained models use continuous representations of the geometry of modeled structures. Few coarse-grained models use lattice grids which enable significant computational speedup compared to continuous models. (43, 44) Obviously, to achieve good resolution of a model the lattice needs to be of dense spacing, which enables high coordination numbers for the location of neighboring united atoms.
Many useful applications of coarse-grained protein models have been described in the past few years. (19-32) Coarse-grained models have been successfully used in studying protein folding mechanisms based on either very generalized protein-like models or simulations of real proteins (see section 4.2). Another productive area for coarse-grained modeling is protein structure prediction. Every two years CASP (Critical Assessment of Protein Structure Prediction) experiments provide a good test of computational methods applied for structure prediction (see section 4.3.4). Most leading groups successfully use coarse-grained modeling tools, which are the methods of choice in the most difficult de novo modeling cases, although coarse-grained simulations also play a significant role in the advanced tools of comparative (homology based) modeling. (3, 45-48)
This review focuses on the prospective applications of coarse-grained models, including protein structure prediction, modeling of complex dynamic processes, protein interactions with other proteins and peptides and modeling of membrane proteins. Some of the most successful applications have been recently achieved by the combination of coarse-grained models with a wide range of computational techniques, including classical all-atom modeling and careful implementation of restraints derived from various sources of experimental data. Future developments are expected to continue on this integrative modeling trend. (33, 49-55)
2 Coarse-Grained Protein Models
ARTICLE SECTIONS
2.1 Brief History
It has been about half a century since we have been witnessing rapid progress of experimental structural biology. In particular, we learned that proteins adopt specific three-dimensional structures, essential for most of their biological functions. At the same time, due to the rapidly increasing computer power and progress in theoretical chemistry and physics, it became clear that molecular modeling of biomacromolecules could be essential for understanding molecular backgrounds of many biological processes. It also became clear some time ago, and at different levels it remains true today, that the productive applicability of classical atom-level molecular modeling of biological systems is limited to relatively small systems and biologically short time scales (see Figure 1). In this context it was crucial to solve the so-called Levinthal paradox. (56) It was known that globular proteins, or at least a large fraction of them, adopt well-defined three-dimensional structures. According to Levinthal, such a process, with a random search for all possible conformations of a protein chain consisting of one hundred residues, would take longer than the age of the universe. Therefore, the folding process could not be fully random, since proteins of such size form their unique structures usually in a time range of milliseconds. Today, thanks to many theoretical and experimental studies, it is well understood that local secondary structure preferences and other geometric features of protein chains drastically decrease the number of available conformations and therefore facilitate relatively fast folding to native tertiary structures.
Understanding the protein folding mechanisms was probably one of the main reasons for designing coarse-grained protein models to perform simulations at time scales important for biological processes. The first coarse-grained protein models were developed almost 40 years ago. The classical work of Levitt and Warshel (34) already cited in the introduction is a good example of successful early attempts at simulating an entire folding process. In their protein model, a chain of pseudoatoms (placed at Cα positions) replaced the main chain structure. United pseudoatoms at centers of their average conformations (see Figure 2) replaced the side chains, except for glycine. The planar angle between three consecutive Cα was assumed constant, equal to the statistical average seen in the known protein structures. This was crude simplification due to the significant difference between the average values of these angles observed in various secondary structure fragments. Positions of three consecutive Cα atoms defined the center position of the side chain for the second residue. The only degree of freedom in this model described rotation along the central pseudobond for the three consecutive Cα atoms. A simple Lennard-Jones potential described interactions between the united atoms. Brownian dynamics (BD) was used as the sampling scheme. A large series of BD simulations were performed for the bovine pancreatic trypsin inhibitor, a small protein, and in some runs native-like low resolution structure models were obtained. This work clearly demonstrated that the packing and pairwise interactions of side chains are one of the main forces leading to specific folded structures. A year later Levitt (57) proposed a slightly more accurate version of this model, accounting for the variable orientation of the united side chains. The torsional potential for the main chain (and a side chain, where applicable) degrees of freedom was developed from the statistical analysis of conformational properties of representative dipeptides. Similar models were studied by Hagler and Honig (58) and by Wilson and Doniach. (59) In the latter study the authors proposed interesting derivation of statistical potentials for residue–residue interactions and used the Monte Carlo method for simulated annealing simulations of the folding process. An interesting design of the side chain empirical potential was also proposed by Crippen and Ponnuswamy. (60) Related reduced models of small proteins, with various approaches to the force field problem and sampling strategies, including continuous and lattice representations, were published by many authors, (19-33, 43, 44, 61-70) and we cite only selected early reports.
Figure 2
Figure 2. All-atom representation of a tripeptide and the corresponding coarse-grained models. Various coarse-grained models are presented: Rosetta centroid mode (CEN) representation, (71)CABS, (72) UNRES, (73) SICHO, (74) and Levitt and Warshel model. (34) United side chain atoms are colored in orange. Pseudobonds of fluctuating length are shown as springs and lattice models are shown on the underlying lattice slide.
A different area of research focused on protein-like models. (75) Dill, (76) Shakhnovich, (77) Chan, (78) and many others studied simple cubic lattice chains and their folding to unique three-dimensional structures. (78, 79) Most of these models treated protein chains like sequences of two types of amino acids: hydrophobic (H) and polar (P), although somewhat more detailed models were also investigated. (80) It was clearly demonstrated (with exact statistics of all possible conformations of HP models) that specific sequences are needed for unique structures, and a rigorous description was formulated of dynamics and thermodynamics of folding processes in these idealized systems. Intermediate resolution lattice models (between idealistic “protein-like” and crude protein models) such as diamond lattice (81) or “chess-knight” (82, 83) models were also studied. As pointed out by Park and Levitt (84) and Godzik et al., (85) while very attractive for their simplicity and allowing exact statistical analysis, the low resolution lattice models of proteins could also be strongly biased due to their crude representation of mutual orientations of protein chain fragments. Nevertheless, these and other studies on low resolution models provided a strong foundation for the development of contemporary medium and high resolution coarse-grained models that we focus on in this review.
We hope that this short overview of the earlier studies of simplified protein models briefly explains various avenues that led to the present state of the art in coarse-grained protein modeling. In the main sections of this review we describe the recent advances in coarse-grained modeling, focusing on the models which are not only computationally attractive but also give realistic reconstruction of atom-level views of the structure and dynamics of protein systems. We also discuss promising applications of coarse-grained protein models in the multiscale modeling of large biomacromolecular systems.
2.2 Levels of Resolution
Proteins are particular semiflexible oligomers that form specific linear sequences of amino acids. Amino acids are linked by covalent peptide bonds, almost always adopting relatively rigid trans conformation. This imposes some limitations on the conformational space available for the protein backbone chain. With a couple of exceptions, orientations of the side chains of amino acids are asymmetric, and proteins of living organisms usually adopt the L-handed conformation. The side chains are of different size and geometry defined by their internal degrees of freedom and interactions with their environment. This results in additional biases in the polypeptide conformational space.
Characteristic three-dimensional protein structures are determined not only by the conformational properties of the main chain, but also by the resulting specific packing and interactions of the side chains. Interestingly, many (sometimes multiple) random mutations do not change the primary properties of natural proteins, while a different single mutation can not only destroy their biological functions, but also their structural properties. (86) In other words, natural proteins are very specific copolymers “edited” by evolution and the well-defined three-dimensional structures of many of them result from a very complex interplay of main chain flexibility, patterns of hydrogen bonds and interactions between amino acid side chains. Therefore, coarse-grained models, their representation of protein chains, force fields, and sampling techniques must be carefully designed, with the purposes and expected reliability of such models taken into deep consideration. (87)
A broad spectrum of coarse-grained protein chain representations were discussed in literature. (19-33) In all cases, the main purpose was to reduce the number of degrees of freedom treated in an explicit fashion. For this reason, pseudoatoms replace amino-acid fragments or even entire amino acids (an equivalent term used in literature for “pseudo-atom” is “united atom”). The conformational space of these reduced atoms could be also restricted, leading to additional reduction of the available degrees of freedom. The simple lattice protein-like HP models mentioned in the introduction are the extreme examples of this kind of simplification. In an HP cubic-lattice model (75) the two types of amino acids (H-hydrophobic and P-polar) are restricted to a single lattice position. Thereby the mutual orientations of all residues are also restricted to cubic lattice angles. The conformational space of such models (for chains of a limited length) could be exactly enumerated and the behavior of various sequences of HP units precisely studied. Although this level of simplification ignores many important features of real proteins, the studies of HP (and related) models explained some fundamental features of protein-like polymers. (75, 78) It is also possible to consider even lower resolution models that enable crude representation of huge protein systems. (88-94)
In contrast to simple HP models it is possible to design a structurally more realistic model based just on a single pseudoatom per amino acid residue. A practical example is the SICHO (side chain only) model in which only explicitly simulated pseudoatoms are placed near the centers of the amino acid side chains (74, 95) (see Figure 2). The excluded volume, distribution of distances between consecutive pseudoatoms, distribution of planar angles (dependent on amino acid identity), and torsional angles used in the model were derived from the statistical analysis of structural regularities observed in known protein structures. These distance and angle restrictions were additionally controlled by the crude approximation of main chain geometry automatically fitted to the positions of the side chain pseudoatoms of three consecutive amino acids. The SICHO resolution is about 2–3 Å and provides a crude although quite realistic representation of protein structure, including an acceptable picture of secondary structure. (96, 97) Since the side chains in proteins are most mobile and their contacts are crucial for the packing of protein structures, the modeling schemes led by SICHO pseudoatoms motion enable extremely efficient simulations of protein dynamics, especially in the dense (near-native) state. Unfortunately, this intermediate resolution coarse-grained model was not extensively studied, in spite of quite promising preliminary results. (98-100)
The first intermediate resolution coarse-grained models were developed a long time ago, providing much deeper understanding of protein physics and defining new directions in the development of novel methods of the multiscale modeling of proteins and other biomacromolecules. (19-32, 37-40) The efforts of Levitt and co-workers initiated this direction, (34, 35) see section 2.1. Typical intermediate resolution models use one or two united atoms to approximate the geometry of the main chain and side chains, respectively. Two examples of such models, which allow a very broad range of applications, from structure prediction to a study of protein dynamics and interactions, are UNRES (united residue) (73) and CABS (C-alpha, beta, and side chain) (72) models (see Figure 2 and section 2.5 for their discussion). UNRES and CABS enable quite realistic, although by no means exact, reconstruction to atomistic models. (101-103)
Almost exact coarse-grained protein models, like Rosetta (71, 104) or PRIMO, (105, 106) treat protein chain representation closely to the atomistic level by introducing only some small simplifications to speed up simulations but also for use in high-resolution modeling. Various versions of Rosetta models use interesting combinations of realistic coarse-grained resolution (see Figure 2) and all-atom representation designed specifically for efficient structure prediction and not for studying folding dynamics. For further details and examples of other coarse-grained representations, see section 2.5.
2.3 Force Fields
Designing force fields for coarse-grained models is to some extent directed by the chosen level of resolution and the expected ranges of applicability, although it is also the result of a different philosophy of thinking about the molecular picture of biological systems. On one hand, there are efforts to build classical coarse-grained force fields based on molecular physics. On the other hand, the force fields of coarse-grained models could be derived from the statistical analysis of structural (and dynamic) regularities seen in the growing databases of experimental structures, underestimating the atomic-level backgrounds. Various combinations of these two fundamentally different approaches are possible. (107) Typically, in comparison to its all-atom counterpart, the coarse-grained force field smoothens out the energy landscape, and thereby helps to avoid local energy minima “traps,” see Figure 3. Coarse-graining also affects thermodynamic properties of a modeled system, particularly the balance between enthalpy and entropy. Reduction of the degrees of freedom affects the entropy of the simulation system, which is compensated by reduced enthalpic terms. In turn, a coarse-grained model may accurately reproduce free energy differences but contributing enthalpy and entropy values may be inaccurate. Such limitations are typical for the majority of coarse-grained models.
Figure 3
Figure 3. All-atom versus coarse-grained energy landscape. The figure illustrates the effect of the smoothening of the energy landscape in a coarse-grained model as compared to an all-atom model. The flattening enables efficient exploration of the energy landscape in search for the global minima, while avoiding traps in the local minima.
2.3.1 Physics-Based Force Fields
A general formula for a classical physics-based all-atom force field consist of six terms (108)(eq 1). The first four of them, so-called “bonded” terms, describe bonds deformation (eq 1a), bond angles geometry (eq 1b), and rotation about certain dihedral angles (eq 1c and 1d). The last two “non-bonded” terms describe dispersion and repulsion effects (Lennard-Jones term, eq 1e) and electrostatic interactions (Coulombic term, eq 1f).
(1a)
(1b)
(1c)
(1d)
(1e)
(1f)
(1a)(1b)(1c)(1d)(1e)(1f)
The equation above looks relatively simple but we have to keep it in mind that the summations involve many different atom types and, therefore, many parameters have to be defined. These values are defined using quantum-mechanical calculations or experimental measurements (hence the name “experimental force field”). Bond lengths with corresponding stiffness values (b0 and Kb in eq 1a) as well as bond angle parameters (θ0 and Kθ in eq 1b) are usually obtained from crystallographic and spectroscopic data for small molecules. Parameters for the Lennard-Jones term are usually optimized using data from small molecule liquid density, heat of evaporation, or free energies of solvation. (109) Partial atomic charges (qk in eq 1f), necessary for the evaluation of the Coulombic term, are obtained from QM calculations. Therefore, from a certain perspective, these force fields may be seen already as coarse-grained with electronic degrees of freedom averaged out.
In general, a physical-based coarse-grained force field can be described by a similar formula as an all-atom force field (eq 1a–1f). In practice, a broad variety of additional expressions going beyond the classical formula are used to describe the energy of coarse-grained models. During the coarse-graining process some atoms are removed and the degrees of freedom related to them are averaged out. In this situation, internal correlations between groups of atoms (now represented as united atoms) must be introduced explicitly in the form of multibody terms. Most approaches keep the distinction between local energy terms and so-called contact potentials. The former describe spatial correlations between pseudobond vectors which no longer follow classical laws such as a harmonic function and are often expressed by a kind of an arbitrarily chosen function (like Chebyshev polynomials, (110) splines, or histograms). Nonbonded terms are usually represented by a single formula depending on the type of interacting atoms, the distance between them and, sometimes, their mutual orientation and local neighborhood. Due to the diffused nature of a spherical cloud representing a group of physical atoms, these interactions tend to be softer and the 12-6 exponents in the van der Waals equation may be substituted with more appropriate numbers. (111) How the final formulas of the coarse-grained force fields look depends not only on the specific model of coarse-graining but also on the chosen method of transferring atomistic formulas onto coarse-grained (united atoms) potentials; good examples can be found in recent reviews. (30, 112) Below we provide an overview of different approaches for derivation of physics-based different coarse-grained force field terms.
The least invasive step in coarse-graining is to neglect nonpolar hydrogen atoms. This yields up to 10-fold reduction of computational effort. CHARMM19 (113, 114) and GROMOS (115) are examples of such type of a commonly used force field. Parametrizations of these force fields were done in the same way as described above for the classical all-atom case. When further reducing a molecular representation it becomes necessary to determine physical parameters (as radii) for unphysical moieties (coarse-grained pseudo atoms). A remarkable example is the MARTINI force field, (116) which has been parametrized by reproducing the partitioning of free energies between polar and apolar phases of a large number of chemical compounds (see section 2.5).
The strategy to derive force field parameters from experimental data becomes increasingly difficult with an increasing number of distinct pseudoatom types in coarse-grained representation. Below we outline a few systematic approaches, proposed in the literature, to derive a coarse-grained force field from results of all atom simulations of a system (or systems) that were conducted with a reference (“true”) all-atom potential uAA(r). Parameters for the corresponding coarse-grained force field are derived to match some features of the atomistic ensemble. The latter are usually collected from all-atom molecular dynamics simulations but quantum-mechanical approaches have also been exploited. (117, 118)
In the iterative Boltzmann inversion (IBI) approach, which was first proposed by Schommers, (119) radial distribution function (RDF) or functions ρAA(r) are used as the target property. Starting from an initial form of a coarse-grained pair potential uCG(r), a coarse-grained RDF is calculated and used to improve the estimation of uCG(r) according to the formula:
(2)where T is the absolute temperature and subscript indexes denote iteration of the Boltzmann inversion procedure.
(2)where T is the absolute temperature and subscript indexes denote iteration of the Boltzmann inversion procedure.
This procedure is repeated until successful convergence is achieved, which, according to the Henderson theorem, (120) leads to the pair potential that is unique for a given ρ(r). In practice however many pair potentials are able to reproduce a target ρ(r) within an acceptable error. Reith et al. (121) applied the IBI procedure for two model systems of a known Hamiltonian (Weeks–Chandler–Andersen and Lennard-Jones potentials (121)) and concluded that, even though the procedure results in an RDF that is undistinguishable from the target, the resulting potential still differs from the true one. A possible remedy might be to use additional target properties that may be included in the IBI calculations, (122) such as pressure. (121) Nevertheless the IBI framework has become very popular due to its simplicity and quick convergence, and usually several iterations are required. In the most simplistic application of this method, only one iteration of Boltzmann inversion is conducted.
An all-atom RDF was also chosen as the target property in the original formulation of the inverse Monte Carlo (IMC) method (123) for deriving a coarse-grained Hamiltonian defined as a linear combination of terms. Similarly to IBI, initial approximation to the coarse-grained Hamiltonian is iteratively improved to minimize the difference between all-atom reference simulations and coarse-grained RDFs. When compared to IBI, the IMC method explicitly handles correlations between coarse-grained force field parameters. Coarse-grained force field parameters are calculated in an iterative process where at each step a set of linear equations is solved to find a better approximation to FF parameters. The subsequent generalization of the IMC method known as Newton inversion (124) may utilize virtually any property derived from all-atom simulation as the target distribution and the mathematical formulation of the coarse-grained energy function is no longer restricted to any particular form. The method uses the Newton–Raphson approach to iteratively solve a set of nonlinear equations.
The methods described above attempt to preserve the RDF as much as possible during coarse-graining. In turn, the force matching approach (118) derives pairwise forces acting on coarse-grained sites to match atomistic forces calculated for a set of reference conformations. In the seminal formulation of FM, ab initio calculations were used as the “true” potential. Cubic spline was used to represent the coarse-grained forces and the necessary spline parameters were fit by minimizing the mean-square error between coarse-grained and atomistic forces averaged over all trial configurations. The method was further developed by Voth (117, 125) (under the name of multiscale coarse-graining or MS-CG) who used MD trajectories as the reference. To improve the accuracy of resulting coarse-grained potentials, an alternative iterative scheme of force matching has been recently proposed. (126, 127) Convergence of the iterative procedure was reported as much faster than for the IBI approach (both IBI and iterative FM (128) may be derived on the grounds of Yvon-Born–Green theory).
Relative entropy minimization (REM) relies on minimizing the Kullback–Leibler divergence (relative entropy) between an all-atom and a coarse-grained system. (129) This parameter measures the degree of overlap between all-atom and coarse-grained distributions of states and has non-negative values with zero meaning a perfect overlap. Therefore, unlike IMC and IBI, the REM method in general may be used to quantitatively compare different coarse-grained schemes or different mathematical forms of a coarse-grained Hamiltonian. The actual minimization of relative entropy may be done by the steepest descent or Newton–Raphson (129) or stochastic (130) minimization. An even more efficient algorithm that uses statistics sampled from coarse-grained trajectories was recently proposed by Shell. (131) The formulation of the REM method is very general and may be applied to optimize coarse-grained structure mappings (132) and dynamics. (133) Correspondence between REM and other methods reported above is discussed in a couple of interesting publications. (131, 134)
Conditional reversible work (CRW), (135) yet another approach to coarse-grained force field parametrization, relies on a thermodynamic cycle to calculate energy of two coarse-grained sites. The energy (reversible work) is calculated between groups of atoms in their natural chemical environment when restrictions are imposed on the mutual orientations that can be adopted by these two groups due to surrounding chemical moieties. The CRW method was recently extended to derive dissipative particle dynamics friction functions. (136)
The coarse-graining approaches outlined above have been extensively used in various studies related to biomolecules in their natural environment. This most notably includes lipid bilayers and water. Coarse-grained approaches to membranes are described in section 4.5. Water coarse-grained models were recently reviewed elsewhere. (137) Despite the differences between the coarse-grained strategies described above, they all require a reference (“true”) ensemble of all-atom conformations. It is important to keep it in mind that the reference data were collected in particular conditions such as temperature, concentration or even size of the simulated system. These variables are implicitly incorporated into the resulting coarse-grained force field which in general may be not applicable to other conditions. The problem of transferability between different environments requires careful analysis. (30)
2.3.2 Knowledge-Based Statistical Force Fields
Designing effective transferable force fields for coarse-grained representations based on atom-level potentials is a challenging task, as outlined in the previous section. On the other hand, we know a huge number of experimentally determined protein structures. The details of conformational features and atomic packing, controlled by complex interactions, may be analyzed on the grounds of statistical analysis. This led to the idea of knowledge-based statistical potentials.
In their seminal work Tanaka and Scheraga (138) derived a coarse-grained potential based on their study of relative frequency of atomic contacts observed in the crystal structures of proteins. Interaction between two types of amino acid side chains was defined as
(3)where Nobserved is the observed frequency of contacts of specific side chains and Nreference is the expected frequency observed in the reference state.
(3)where Nobserved is the observed frequency of contacts of specific side chains and Nreference is the expected frequency observed in the reference state.
The procedure clearly resembles Iterative Boltzmann Inversion. Unlike IBI, however, the derivation of knowledge-based potentials is usually a single-step process. Thus, the choice of the reference state, which is a priori unknown, is crucial for this approach. Knowledge-based potentials can be also derived using the Bayes theorem. Following the RAPDF (residue-specific all-atom conditional probability discriminatory function) potential formulation given by Samudrala and Moult, (139) we can define energy as a logarithm of the probability that a particular conformation is “correct,” given its amino acid sequence A and a vector of structural features X (such as distances, contacts, angles, etc.):
(4)where P(X,A|C) is the distribution observed in the population of “correct” structures. Most commonly a nonredundant subset of PDB deposits is used for this purpose. The reference state should be interpreted as the a priori distribution P(X,A). A very similar formalism was applied by Baker and co-workers (140) to derive the Rosetta force field. The correspondence of Boltzmann and Bayesian approaches has been described by Xia and Levitt. (141)
(4)where P(X,A|C) is the distribution observed in the population of “correct” structures. Most commonly a nonredundant subset of PDB deposits is used for this purpose. The reference state should be interpreted as the a priori distribution P(X,A). A very similar formalism was applied by Baker and co-workers (140) to derive the Rosetta force field. The correspondence of Boltzmann and Bayesian approaches has been described by Xia and Levitt. (141)
The hypothetical reference states should be of the same volume (and shape) as the real (observed) structure. We could use, for instance, a set of similar protein structures with a random sequence of amino acids, but with the same composition. Miyazava and Jernigan (61) introduced the concept of quasi-chemical approximation: a perfect mixture of spheres representing the 20 amino acid types with their molar fractions corresponding to the probability of finding such an amino acid in a database. That concept was further formalized by Sippl. (142) In practice these molar fractions should account for the finite size of a protein sequence, and thus proper composition corrections are required. (143-146) All-atom knowledge-based contact potentials may be derived in the same manner (147) as in the case of DOPE, (148) dDFIRE, (149) GOAP, (150) or ROTAS (151) energy functions. In a similar way we can also define statistical potentials describing short-range interactions, (152) angular preferences (153) geometric aspects of hydrogen bonding, (154) etc.
Apart from those mentioned above, alternative methods for the derivation of knowledge-based force fields were also proposed based on direct optimization of force field performance. Various criteria of success were proposed, including: maximizing the energy gap between the “native” and “non-native” conformation, (155) maximizing the native energy z-score, (156, 157) maximizing the probability of successful prediction (158) or minimizing the free energy of the native state. (159) Several formalisms, interpretations, and extensions of knowledge-based force fields have been published (61, 140, 141, 143, 160-165) and recently reviewed. (107, 166, 167)
While the basic schemes of knowledge-based interaction models generally follow the structure of physic-based force fields, as defined by eq 1, their derivation can be conceptually more challenging. Depending on the level of coarse-grained representation, definition of the model force field, and the complexity of the experimental databases used, the final formulas may be composed from a significantly larger number of specific terms than that given in eq 1. Moreover, some terms of a knowledge-based force field can describe specific conditional combinations of bonds, angular and nonbonded interactions. One of the most extreme applications of the knowledge-based strategy is probably the statistical force field designed for the CABS model of single domain globular proteins. (72) The CABS force field treats amino acid interactions in a context-dependent way and takes into account very complex multibody effects, encoded in a large number of composition and structure encoding parameters (for details of CABS, see section 2.5). CABS and other coarse-grained models (168-170) based on context-dependent potentials, such as CAS (implemented in I-TASSER method (48)), are now one of the most effective tools in de novo structure prediction (171-173) (see also section 4.3).
The strength of knowledge-based force fields emerges from their simplicity and efficiency in protein structure prediction, modeling of protein folding pathways, and related tasks of computational biology. The weak point is a lack of transferability. While the force field derived for single domain globular proteins will work well for a vast majority of single protein and peptide structures, the interaction between independent domains, interactions between proteins and nucleic acids, etc. require derivation of a new component of knowledge-based force fields. Fortunately, rapidly growing structural databases make such derivations possible, although more rigorous strategies for building new efficient and widely applicable knowledge-based force fields remain one of the most challenging tasks of large scale molecular modeling in structural biology.
2.3.3 Structure-Based Models of Force Field
As pointed out in the Introduction, we know many experimentally determined protein structures. These could be used as a starting point for simulation studies. “Structure-based” models (SBMs), also called Go̅-type models, employ a specific force field approximation. (174, 175) Namely, only native-like interaction patterns, seen in a specific known and usually folded structure, are taken into account. In many cases, it is a significant simplification, since it is assumed that the folding process is directed by interactions that stabilize the known final structure. The folding intermediates of many proteins are certainly not necessarily native-like. Nevertheless, SBMs could be a quite useful tool for modeling near-native protein dynamics, especially when combined with non-native force field potentials. (176-180) There are also interesting modifications (extensions) of the SBMs patterns of interactions in which two, or another limited number, alternative basic structures are used for defining the subset of possible interactions, see section 4.2.1.
2.4 Sampling Schemes
Energy function transforms the flat world of conformational space accessible to a given biomolecular system into a very rugged hypersurface. The sampling scheme is a method of traveling through that hypersurface in search of desired conformations. Sampling schemes in biomolecular modeling were recently reviewed, (181-185) and here we only briefly describe the approaches commonly used in coarse-grained modeling. They belong to three broad categories: molecular dynamics (MD), Monte Carlo (MC), and heuristic approaches, such as Genetic Algorithm, (186) Taboo Search, (187) or Ant Colony Optimization. (188)
In MD, new configurations are generated by applying Newton’s equations of motion to all atoms (or pseudoatoms) simultaneously over a small time step. This determines the new atomic positions and velocities and provides a trajectory describing how a given system evolves in time. In coarse-grained modeling, in which solvent is most often treated in an implicit fashion, collisions and friction forces should be introduced to mimic collisions of a solute molecule with its environment. (189) Since united coarse-grained atoms form a body typically larger than a solvent molecule, the Brownian motions theory is often applied to mimic the solvent effects. The stochastic effect of solvent molecules is introduced by a random displacement vector resulting from Brownian motions with zero mean and variance-covariance defined by a diffusion tensor. The frictional term, defined by Stokes’ law, is often omitted, assuming that viscous force is much larger than the inertia tensor and the resulting formulation is referred as Brownian dynamics (BD). An important effect that must be included in BD algorithms to capture correctly the dynamics of the biomolecular chain is the hydrodynamic interaction (HI) between coarse-grained atoms. This in practice requires computing the square root of the 3N × 3N diffusion tensor every time the tensor is updated during a simulation. This can be achieved with Cholesky decomposition as proposed by Ermak and McCammon in their pioneering work (190) on the BD algorithm with HI.
Discrete molecular dynamics (DMD), recently reviewed in refs 191 and 192, may be considered another particular way of solving Newtonian equations of motion. In this case, however, all energy wells are flat, and energy gradients (i.e., forces) are always equal to zero. DMD simulation assumes ballistic motion at constant velocities and searches for the closest collision event, saving computational time. In fact, the discrete, event-driven implementation was published before the “classical” time-resolved MD. DMD has been successfully applied for CG models to studying protein structure (193) dynamics (194) and aggregation. (195)
Monte Carlo (MC) methods essentially provide a random sample of conformations coming from the desired distribution. Boltzmann distribution, the most important case, is achieved when the Metropolis criterion is applied to accept or deny a new randomly created configuration. Typically, the new configuration is constructed as a small modification of the previous one. These may include translation and rotation of a randomly selected molecule in the system, or a small change to a subset of its internal degrees of freedom. Such a structural modification (also termed “MC move”) must satisfy only very general rules: detailed balance and ergodicity. This opens up countless possibilities for introducing modifications that, while altering the structure as much as possible, attempt to avoid energy barriers and greatly reduce correlation between states (see Figure 4). Through a properly designed set of moves the Markovian property of the stochastic process leads to Markov chain Monte Carlo stochastic dynamics. Various aspects of the MC modeling of biomolecules have been recently reviewed. (196)
Figure 4
Figure 4. Example moves of a protein chain used for MC dynamics in the CABS model. (72) The upper panel shows local small-scale moves: two-bond and three-bond. The middle panel presents a large-scale move: small distance displacement of a chain fragment. The lower panel shows a “reptation” move in which a “bubble” on a protein chain is removed in one spot and randomly created somewhere else along the chain. A long random sequence of all moves provides an MC dynamics trajectory of the modeled protein chain. Large-scale and reptation moves are attempted less frequently than local moves. For clarity, the upper panel moves are shown with side chains (colored in orange), while the remaining panels without side chains. Positions of the alpha carbons are restricted to the underlying cubic lattice.
Both MC and MD procedures typically have the same system setup including representation of molecules, definition of force fields, implementation of (periodic) boundary conditions, etc. However, it is quite difficult to provide direct comparison between the two. The equations used by MD remain always the same and possibilities to speed up computation lie mainly in handling constrains and numerical optimization. The Monte Carlo approach may use virtually any structural modification which does not violate its basic assumptions. MC moves crafted for studying a particular system can be devised. Nevertheless, various studies (197, 198) indicate that MC is faster than MD, and sometimes many times faster. Another advantage of MC sampling is that the implementation of energy terms is not restricted to differentiable functions. This aspect may be important when the mathematical form of a force field is discrete, e.g. it is based on a histogram of a target property.
Finally, in the case of computationally demanding high-resolution models, the sampling problem can be circumvented by running a large number of independent simulations and their further joint analysis. (199-201)
2.5 Examples of Protein Coarse-Grained Models
In Table 1 we present a brief overview of various coarse-grained protein models. For some of the models typical for certain classes of modeling strategies and/or very successful in some applications, we provide a wider description. The first two of the described models (UNRES and CABS) are quite universal, allowing studies of protein structure, dynamics and interactions. Many other coarse-grained models fit in this class. The third model, PRIMO, is particularly interesting because it assumes more accurate representation of protein structures and thereby, by somewhat higher simulation cost in comparison with the first two models, provides an almost atomistic picture of protein structure and dynamics. The other two, MARTINI and Rosetta, are probably the most widely used coarse-grained models. MARTINI is typically used as a simulation tool for membrane proteins, and Rosetta as a core module in a wide array of methods dedicated for different protein types, systems, and modeling tasks.
Table 1. Selected Coarse-Grained Protein Modelsa
| coarse-grained model | model design (representation of a single amino acid and force field design) | example applications, additional notes and availability |
|---|---|---|
| AWSEM (associated memory, water mediated, structure and energy model) developed by Wolynes, Papoian and co-workers (236) | Up to three-bead representation: Cα, Cβ, and O. | Model used for ab initio structure prediction of globular proteins, (236) prediction of dimerization interfaces of protein–protein complexes, (237) modeling the mechanisms of misfolding and aggregation (238, 239) and the role of electrostatic effects in protein folding and binding. (240) AWSEM has been also extended to model α-helical transmembrane proteins. (241) |
| Mixed (knowledge-based and physics-based) potential | Available as open source software at http://code.google.com/p/awsemmd/ | |
| Bereau and Deresno model, developed by Deresno and co-workers (242) | Up to four-bead representation: three backbone beads (N, Cα and C′) and one side chain bead located at Cβ. | Model used for studying protein folding (243) and protein aggregation. (242) Studies show that additional model tuning is needed to improve the stability of proteins with β-type or α/β-mixed secondary structure. |
| Knowledge-based force field | Available as part of the ESPRESSO package: (244)http://espressomd.org/ | |
| CABS (C-alpha, c-beta, side chain) model, developed by Kolinski and co-workers (72) | Up to four-bead representation: Cα, Cβ, center of the side chain, and center of the peptide bond. Additionally, restriction of Cα positions to the cubic lattice (with 0.61 Å spacing) significantly speeds up the calculations. | Model used in template-based or ab initio protein structure prediction, validated in CASP competitions as one of the leading approaches; (171) loop structure prediction; (206) ab initio simulations of protein folding (101, 207-209) and binding of intrinsically disordered proteins. (212) Used as a simulation engine in multiscale methods for protein structure prediction, (205) modeling of protein flexibility (210) and flexible protein-peptide docking. (213) |
| Knowledge-based force field | Available with CABS-based tools at: http://biocomp.chem.uw.edu.pl/tools/ | |
| MARTINI model, developed by Marrink and co-workers (116) | Up to five-bead representation: one backbone bead (placed at the center of mass of the amino acid backbone), and up to four side chain beads. | Model originally developed for lipids (216, 228) and subsequently extended to proteins. (116) Clearly the most popular model for the coarse-grained modeling of membrane proteins in the membrane environment. Its numerous successful applications are summarized in this review in section 4.5 and have been recently reviewed. (225) |
| Physics-based force field | Available at: http://www.cgmartini.nl/, compatible with the GROMACS package: (245)http://www.gromacs.org/ | |
| OPEP (optimized potential for efficient protein structure prediction) model, developed by Derreumaux and co-workers (246, 247) | Up to six-bead representation: full-atom for the backbone (N, HN, Cα, C′, and O) and single-bead for side chains (with an exception of proline having three beads). | Model used for protein folding; (247-250) aggregation studies; (251, 252) structure prediction of peptides and small proteins; (253) modeling of the role of hydrodynamics in protein relaxation and peptide aggregation; (247) modeling of proteins, DNA-RNA complexes and amyloid fibril formation in a crowded environment; (246)ab initio peptide structure prediction. (254) |
| Mixed (knowledge-based and physics-based) potential | Available with OPEP-based tools at: http://www-lbt.ibpc.fr/ | |
| PaLaCe (Pasi-Lavery-Ceres) model, developed by Lavery and co-workers (255) | Two-tier representation (one for bonded and another one for nonbonded interactions). Three backbone beads (N, Cα, and C′) are used for backbone representation and one or two beads for the side chain | Model used to maintain structures of folded proteins, and model their dynamic fluctuations and large-scale force-induced conformational changes; (255) protein flexibility prediction. (256) |
| Physics-based force field | Available within the MMTK simulation package: (257)http://dirac.cnrs-orleans.fr/MMTK/ | |
| PRIMO model, developed by Feig and co-workers (106) | Up to seven-bead representation: three backbone beads (N, Cα, and combined CO) and one to five beads for the side chain (the representation was aimed to be sufficient for high resolution protein representation (105)) | Model used in peptide and small protein structure prediction; (106) has been extended to membrane environments. (215) |
| Physics-based force field | Available from the authors on request and distributed as part of the MMTSB Tool Set: (258)https://mmtsb.org/ | |
| Rosetta model, developed by Baker and co-workers (104) | Representation by all backbone atoms, Cβ and center of the side chain. Coarse-grained models are further refined in all atom representation (with explicit hydrogen atoms). | Model widely used for protein structure prediction, validated during CASP competitions as one of the leading approaches; (104) recent developments include improved protocols for high resolution refinement (46) and de novo blind predictions; (47) model implemented in numerous pipelines for protein–protein docking, (259) protein–ligand docking, (260) antibody modeling, (261) refinement of crystallographic structures, (262) refinement of NMR structures, (263) protein-peptide docking, (264, 265) modeling of protein–DNA interactions. (266) |
| Mixed (knowledge-based and physics-based) potential | Available at https://www.rosettacommons.org/ (RosettaCommons offers many web-interface servers for using Rosetta, including ROSIE, an easy-to-use web interface for selected Rosetta protocols (267)). | |
| Scorpion (solvated coarse-grained protein interaction) model, developed by Basdevant and co-workers (268) | Up to three-bead representation: single backbone bead and one to two side chain beads. | Model initially developed for scoring protein–protein complexes. (111) Later, the protein model was combined with a water model and used for protein–protein recognition in a solvated environment of the barnase/barstar complex (268) |
| Physics-based force field | ||
| UNRES (united residue) model, developed by Liwo and co-workers (73) | Three-bead representation: Cα, peptide-group, and side chain. | Used in numerous protein folding studies; (269-272) protein structure prediction (successfully used in the CASP competition (273)); loop structure prediction; (274) protein–protein interactions; (275) protein–DNA interactions; (202) mechanisms of protein fibrillation, (276) large-scale rearrangements of protein complexes. (277) |
| Physics-based force field | Available with accompanying tools at: http://www.unres.pl/ |
a
Models are presented in alphabetical order.
UNRES (united residues) is probably the most classical model of medium resolution, and it enables dependable and fast reconstruction of atom-level representation. (73) Three united atoms represent a single amino acid residue in this model (see Figure 2). The main chain is replaced by two atoms corresponding to Cα and the center of the Cα-Cα virtual bond and one pseudoatom of an ellipsoid shape of revolution representing specific side chains. Rotations of this ellipsoid mimic side chain conformational mobility. The force field of UNRES is rigorously derived from all-atom molecular mechanics models of interactions. Various MD and related methods have been used to sample the conformational space of model chains. The physics-based approach to force field and dynamic sampling enabled not only the structure prediction of small proteins but also the study of dynamics and interactions in larger systems. (202) Recently the range of UNRES applicability has been extended by careful implementation of structural restraints to some applications of the model. (202-204)
CABS (C-alpha, beta and side chain) is a medium resolution model. In comparison with UNRES, CABS provides similar resolution, but it is based on qualitatively different interaction and sampling concepts. (72) The choice of united atoms for modeling single amino acids is similar to that of UNRES except for the side chains which are represented by two spherical pseudoatoms, one centered on Cβ and the other placed in the center of mass of the remaining portion of the side chain, where applicable (see Figure 2). The main chain Cα positions are restricted to knots of a cubic lattice of small spacing, equal to 0.61 Å. This lattice Cα trace is used as the only independent variable that defines positions of other united atoms. The side chain positions are based on the local main chain Cα–Cα–Cα angle and the type of amino acid: the appropriate positions are derived from the statistical analysis of protein structures from the PDB database. Thanks to small fluctuations of the Cα–Cα distance and the rapid “pre-computing” of all possible local conformational transitions and associated changes of interactions, lattice representation enables extremely fast sampling of the conformational space, adding about 10-fold speedup of simulation compared to otherwise equivalent continuous space models. The force field of CABS is fully statistical, “knowledge-based” and probably quite unique, since interactions are treated as context dependent, and therefore take into account very complex multibody (including solvent) effects. For instance for single-domain globular proteins the interaction energy for contacts of two oppositely charged side chains depends on their mutual orientations. These interactions are strongly attractive for parallel orientations and weakly repulsive for antiparallel orientations. Indeed, polar amino acids are localized onto the surface of a globule, and thereby their close contact must be near-parallel. This regularity is reflected by statistical potentials derived from the analysis of a globular protein database. CABS sampling uses various Monte Carlo schemes. Since MC simulations use only local conformational changes (see Figure 4) long-time simulations mimic chain dynamics. A model has been successfully used in structure prediction (de novo and comparative modeling), (171, 205, 206) simulations of protein folding mechanisms (207-209) and flexibility of globular proteins, (210, 211) and molecular docking. (212-214)
PRIMO (protein intermediate model) is of higher resolution than CABS or UNRES and provides another level of coarse-grained resolution, closer to atomistic representation. (105, 106) The main chain is represented by three united atoms per residue, and the side chains by one or up to four united atoms, depending on their sizes and shapes. For instance, the phenylalanine side chain is represented by three pseudoatoms encoding size and orientation of the benzene fragment. This subtle level of coarse-graining is sufficient for ensuring noticeable simulation speedup in comparison to all-atom simulations. The force field of PRIMO is very rigorously constructed and maintains the structure of standard MD interaction models. The scaling of the force field has been done in a way that provides good transferability of protein systems. What is important, the PRIMO model enables productive studies of the solvent effect on protein dynamics, including simulations of membrane proteins (215) and reproducible folding simulations of small proteins.
The MARTINI coarse-grained model was initially designed by the Marrink group just for membranes composed of lipid molecules. (216) Further versions were subsequently extended to include peptides, proteins (116, 217) and other small biomolecules. (217, 218) Schulten (219) and Sansom (220) groups have also developed other protein coarse-grained force fields, compatible with the MARTINI lipid force field. Others also proposed several modifications to the model. (221-224) MARTINI modeling tools are now continuously refined by the research groups of Marrink and Tieleman. (116, 225) The MARTINI force field is based on one-to-four mapping, which means that on average four heavy atoms including associated hydrogens are represented by a single coarse-grained bead (see Figure 5). Consequently, one coarse-grained water bead corresponds to four water molecules. One coarse-grained ion bead mimics a single ion including its first hydration shell. Small ring-like fragments (e.g., aromatic amino acid side chains) or small molecules (e.g., benzene, cholesterol) are mapped with slightly higher resolution of up to two heavy atoms per one coarse-grained bead. To properly reproduce the chemical nature of the modeled systems, four main types of coarse-grained particles are defined: polar (P), nonpolar (N), apolar (C), and charged (Q). The four main types of coarse-grained particles are divided into subtypes based on hydrogen-bonding capabilities (donor, acceptor, both or none) and polarity (ranging from 1 = low polarity to 5 = high polarity) giving a total of 18 unique “building blocks”. The described mapping scheme provides a relatively straightforward and effective way of switching from all-atom to coarse-grained representation for a wide range of biological systems. Interactions between coarse-grained particles are described by a force field containing terms typical for other classical force fields. Nonbonded interactions are controlled by a Lennard-Jones (LJ) 12-6 potential, where εij depends on types of interacting coarse-graining particles. Electrostatic interactions are defined by the Coulombic energy function. The nonbonded parameters have been adjusted to reproduce experimental thermodynamics data of the free energy of hydration, free energy of vaporization and partition free energies between water and a number of organic phases for each of the 18 types of coarse-grained particles. (225) Interactions describing bond lengths, angles and dihedrals are controlled by a standard set of potential energy functions. Parameters were calculated based on structural data derived either from atomistic geometry or from an iterative procedure in which parameter values for coarse-grained representation were systematically adjusted to obtain satisfactory overlap with the distribution function resulting from all-atom MD simulations of corresponding atom groups. The practical application of the method is facilitated by a simple mapping procedure based on the “building block” concept, which allows generation of a unified set of parameters and topologies for systems of different types. What is very useful, MARTINI provides parameters for a large number of molecules including different lipid types, sterols, sugars, peptides, polymers, and more. The force field was originally developed to be used in the GROMACS simulation package (226) but the general form of the potential energy function also allowed its implementation in other well-known MD simulation codes such as Desmond, (227) GROMOS, (228) and NAMD. (219)
Figure 5
Figure 5. All-atom versus coarse-grained representation in the MARTINI model. (225) All-atom representation is shown in balls and sticks, while coarse-grained representation in large spheres. The figure shows an example lipid molecule, fragment of a protein chain, and water representations.
The Rosetta (104, 229) model uses two protein representations: coarse-grained (see Figure 2) and all-atom, with all hydrogen atoms present. Rosetta defines protein conformation in the dihedral space. Thus, a coarse-grained polypeptide chain has three degrees of freedom (phi, psi and omega) for each amino acid residue. All-atom representation also includes Chi angles for side chains. All the other internal degrees of freedom are fixed to “ideal” values, although they might be relaxed in some applications, e.g., at the final stage of high-resolution structure refinement. Unlike other approaches to protein modeling, the two representations in Rosetta are tightly connected and the program seamlessly switches from low to high resolution. The coarse-grained model includes all heavy atoms of the backbone, beta-carbons and virtual atoms representing amino acid side chains. A few dozens of energy terms have been defined in Rosetta depending on resolution (either coarse-grained or all-atom), experimental data included in modeling and the specific problem under study. The Rosetta source code is organized in a hierarchical manner. (229) Low-level classes provide procedures typical for macromolecular modeling such as evaluation of scoring terms or altering internal degrees of freedom. They are combined into protocols. Ab initio, (230) the historically first Rosetta protocol, is used to predict protein structure based solely on its sequence information. Modeling is conducted in coarse-grained representation. Conformational space is limited also by the sampling scheme. To create a new conformation from the previous one, a randomly selected fragment of known protein structure substitutes a local structural fragment. The fragments themselves are extracted from a nonredundant set of proteins based on sequence and secondary structure similarity. Three and nine amino acid fragments were originally used, but in the current implementation (231) their length is not restricted. After every MC move, Cartesian coordinates must be recovered for energy evaluation. The fragment assembly simulation is conducted in a hierarchical manner. In the first stage only nine residue fragments are used for sampling and the energy function is limited to VdW, hydrogen bonding and collapsing terms. Further stages introduce smaller changes to the structure while the energy function becomes more elaborated. Unlike other methods used for protein modeling, a single modeling Rosetta run results in a single low-energy conformation. The protocol must be therefore repeated many times to gather proper statistics. This approach, however, ensures that the conformations are statistically uncorrelated. Coarse-grained conformations are further subjected to side chain reconstruction and all-atom energy minimization (FastRelax protocol). To sample the conformational space, Rosetta uses several approaches to alter dihedral DOFs: fragment insertions, backrub moves, (232, 233) rotamer library (234) or small perturbations of particular internal coordinates. For example, the Rosetta ProteinDesign protocol (235) is based on the Monte Carlo search strategy to optimize a protein sequence by mutating one residue at a time. During a single step of the ProteinDesign protocol, backbone DOFs remain fixed and side chain Chi angles are modeled and assigned according to the rotamer library. This step is followed by backbone relaxation to accommodate the designed amino acids. A number of Rosetta applications are also outlined in Tables 1 and 3.
3 Multiscale Modeling
ARTICLE SECTIONS
3.1 Example Strategies
In principle, every simulation that allows transfer of information between at least two different levels of granularity can be considered multiscale. Multiscale methods are more efficient, and enable analysis of larger systems in a longer time scale with a simultaneous ability to preserve a high level of details when necessary. This idea was applied to biological objects perhaps for the first time by Levitt and Warshel in 1976 in their study of mechanisms of enzyme action. (35) Since then multiscale modeling has found successful applications in the modeling of proteins, (25, 38, 39, 278) membranes, (279, 280) ribonucleic acids, (281-283) and large protein–protein or protein–membrane complexes. (38, 284-287) Depending on the given scientific problem, several combinations of methods have been proposed. In practice, the most common are QM/MM (quantum mechanics/molecular mechanics) and all-atom/coarse-grained.
QM/MM modeling was historically the first multiscale approach used for chemical computation. Currently there are many different versions of the QM/MM approach; however, all of them combine QM calculations for the active site which is submerged in a simplified environment (full protein or solvent). (25) With time, QM/MM has become the most important computational method for studying enzyme function or other biomolecular processes that involve changes in electronic structure, (288-293) and it is the basis of modern enzymology. (294) For more information concerning the use of QM/MM, please refer to relevant reviews. (25, 38, 39, 295-298)
The all-atom/coarse-grained multiscale modeling approach (see Figure 6) has emerged as one of the most promising tools of computational biology, and it combines the efficiency of coarse-grained simulations and details of all-atom simulations for the characterization of a broad range of molecular systems. (299) In this methodology all-atom and coarse-grained energy is frequently calculated as the sum of atomistic, coarse-grained, and hybrid parts of the system:
(5)where the terms for every part may be evaluated in different ways. (300)
(5)where the terms for every part may be evaluated in different ways. (300)
Figure 6
Figure 6. Typical multiscale modeling scheme that merges coarse-grained and all-atom modeling. In specific tasks, the resulting all-atom structures could be used as an input for the next stage of coarse-grained simulations. Other multiscale schemes are briefly discussed in the text.
The coarse-grained potential is often highly simplified, and even electrostatic forces are mostly neglected. (301) The problem of all-atom/coarse-grained modeling has been addressed quite some time ago by Skolnick and co-workers. (302) In their study on folding pathways of the leucin zipper they discovered that the accuracy of coarse-grained modeling could be significantly improved when final structures from low-resolution simulations were additionally refined with a detailed atomistic model. This observation and further studies (303) led to a hypothesis that it should be achievable and beneficial to develop hybrid methods for protein structure prediction. Another study undertaken by Warshel and co-workers (304) also used a simplified potential as a reference potential for calculating all-atom free energies.
We can distinguish multiscale methods in which coarse-grained simulations are used at the initial stages of the modeling process to provide data for further all-atom simulations (44, 299, 304, 305) (see Figure 6), or conversely, information from all-atom simulations is transferred to coarse-grained models. (125, 306, 307) Such a strategy is called “serial multiscale modeling”. (37) There is also another group of methods which may be called “parallel multiscale modeling” that combine fine-grained and coarse-grained representations in a single mixed-resolution simulation. (308-310) A typical example of parallel multiscale modeling may be simultaneous calculation in both resolutions: simultaneous use of a coarse-grained model to identify the area of possible conformations with an all-atom method to improve accuracy of the resulting model. (311) A widely used strategy of parallel multiscale modeling is also treating a large part of the system with a coarse-grained model while the other, smaller section is treated with atomic resolution. (25) Some interesting applications of serial and parallel multiscale modeling are provided in section 4.1.
Successful multiscale modeling, regardless of the type, needs efficient and reliable algorithms for transferring information between calculations with different resolutions. (25) Multiscale dynamic modeling is even more demanding since proper calculation ought to be fast enough so as not to hinder the benefit of coarse-graining. To date many different approaches that define the concept of a boundary have emerged. However, since information exchange methods are the key limiting factors, new theories that would fill in these gaps are still of great need. The boundary between different levels of modeling can be arranged with fixed resolution as shown in the studies of lipid bilayer permeability to small molecules, (312) the large-scale motion impact on the function of outer membrane protease T (313) or membrane-bound ion channel studies. (308) Another approach is to make them adaptive, (314) which means that it is allowed to change granularity of a selected part of the system during the simulations on demand. Different methods for flexible linking have been developed over time: AdResS, (315) Adaptive partitioning, (316) Hot spot method (317, 318) and ONIOM-XS. (319) However, despite the efforts, there is still a need for developing better and faster algorithms that would allow changing the resolution on-the-flow.
3.2 Reconstruction of Atomic Representation from Coarse-Grained Models
Information transfer from coarse-grained to atomic representation is tightly connected with the task of reconstruction of atomic details (see Figure 6). The problem of determining protein structure only from the Cα trace or coarse-grained representation is not new and can be found in literature multiple times, and thus most algorithms are based on solutions developed originally for protein structure prediction, homology modeling or protein design. (299)
The process of protein reconstruction to atomistic structure can be divided into two separate steps: rebuilding the backbone and adjusting the side chain atoms. Several different approaches have been proposed to solve the first task. These algorithms may use analytical methods, (320, 321) statistical propensities (322-325) or even whole short peptide fragments (326, 327) extracted from known structures. Reliable side chain reconstruction is a more difficult task. It has been shown that the side chain positioning problem is NP-complete, (328) which means that the complexity of the calculation rises exponentially and no exact polynomial-time algorithms are known. (329) Most of the methods for side chain assignment use a rotamer library (330, 331) built from known structures and an energy function that allows finding a global energy minimum. Many methods for side chain reconstruction have been proposed: Monte Carlo sampling, (332, 333) dead-end elimination, (334-336) simulated annealing, (337) local optimization, (330) genetic algorithms, (338, 339) integer linear programming, (340) graph decomposition, (341, 342) and other combined approaches. (329, 343-348) In Table 2, the currently available methods are briefly outlined. Finally, it needs to be noted that protein conformations generated by coarse-grained models may exhibit some small unphysical distortions that are typical for specific coarse-grained models. Those distortions may be not well tolerated by a reconstruction algorithm. Therefore, before the application, the chosen reconstruction algorithm should be tested in combination with a particular coarse-grained model (see also the related comments in column 3 of Table 2).
Table 2. Example Reconstruction Algorithms
| program name | realized reconstruction task | additional comments and availability |
|---|---|---|
| BBQ (backbone building from quadrilaterals) (322) | BBQ performs main chain reconstruction from the C-alpha trace. | Method designed for robust and efficient backbone reconstruction. Tested on 81 nonredundant protein sets derived from PDB and generated near-native coarse-grained decoys. |
| Uses a library of backbone quadrilaterals. | Available as a standalone program, part of the Bioshell package. (349, 350) | |
| Modeller (351, 352) | Modeller enables reconstruction and refinement from the C-alpha trace or models with missing atoms. | The reconstruction procedure is available as part of the popular Modeller package for comparative modeling. |
| Reconstructs an all-atom model based on a protein template in coarse-grained representation. Energy minimization and all-atom scoring may follow the reconstruction procedure. | ||
| ModRefiner (102) | ModRefiner performs all-atom reconstruction from the C-alpha trace. | Method designed to handle unphysical local distortions in coarse-grained models and to improve the physical quality of a local structure. |
| After backbone reconstruction, ModRefiner optimizes the backbone H-bond network. Side chain reconstruction is followed by additional optimization with a composite physics- and knowledge- based force field. | Has an option to drive the refinement simulation toward the desired secondary structure. | |
| Available as a server or a standalone program. The standalone program has an option of ab initio structure refinement. | ||
| NCN (353) | NCN performs side chain reconstruction from the protein backbone. | Highly accurate algorithm for side chain reconstruction. Tested on 65 high resolution X-ray structures. Available as a standalone program. |
| Uses optimized OPLS parameters, simulated-annealing search strategy and a detailed rotamer library. | ||
| OPUS_Rota (354) | Opus_Rota performs side chain reconstruction from the protein backbone. | Accurate method for side chain reconstruction. Tested on 65 high resolution X-ray structures and the Wallner and Elofsson homology-modeling benchmark set. (355) Available as a stand-alone program. |
| It combines commonly used potential terms, solvation energy with unique orientation-sensitive potential (OPUS-PSP) and the Monte Carlo sampling scheme. | ||
| OSCAR (356) | OSCAR methods (-o, -star) perform side chain reconstruction from the protein backbone. | Accurate methods designed for side chain reconstruction to obtain a realistic all-atom protein model. Tested on 218 proteins and a RAPPER decoy set (loop side chains reconstruction). Available as a standalone program. |
| Combine accurate, orientation-depended, optimized side chain atomic energy with a flexible (OSCAR-o) or rigid (OSCAR-star) rotamer model. | ||
| PD2 (357) | PD2 performs main chain reconstruction from the C-alpha trace. | Method tested in all-atom reconstruction tasks in combination with Rosetta and SCWRL4.0. |
| Uses a library of short fixed length backbone fragments for constructing the structural alphabet with a Gaussian mixture model. | Available as a server or a standalone program. The program features an optional energy minimization step. | |
| Pulchra (323) | Pulchra performs all-atom reconstruction from the C-alpha trace. | Method designed for fast and robust calculations. Pulchra accepts even seriously distorted input structures. Tested on 500 random decoy structures from the prediction benchmark. |
| Uses a simple force field and steepest-descent minimization for backbone reconstruction based on a modified algorithm described by Milik et al. (325) | Available as a standalone command line application. | |
| RACOGS (299) | RACOGS performs all-atom reconstruction from the C-alpha trace. | Method designed for multiscale calculations and optimized to obtain a physically realistic all-atom model from coarse-grained models. Tested on 606,000 coarse-grained structures of the wild src-SH3 domain and ribosomal protein S6 and a misfolded mutant as well as on a subset of 2945 PDB structures. Available as a web server. |
| Uses backbone reconstruction based on the work of Feig (324) and Milik (325) with an efficient side chain reconstruction method by Xiang and Honig. (358) Further addition of hydrogen atoms and all-atom minimization is performed with AMBER 8. (359) | ||
| REMO (360) | REMO performs all-atom reconstruction from the C-alpha trace. | Method designed for refining I-TASSER coarse-grained models. Tested on 230 nonredundant proteins as well as coarse-grained models. Tested in a blind test in CASP8. Available as a web server and a standalone application. |
| Removes steric clashes in the C-alpha trace and rebuilds backbone heavy atoms from a backbone isomer library. The method predicts the hydrogen bond network and uses an SCWRL algorithm for side chain reconstruction. | ||
| Rosetta (catoallatom program) | Performs all-atom reconstruction from the C-alpha trace. | Program available as part of the Rosetta modeling suite. (104) Conformational search is guided by Rosetta energy functions and, optionally, by experimental data such as EM maps. |
| Uses a library of fragments extracted from known structure fragments by combining them as rigid bodies in the Cartesian space. | ||
| SABBAC (361) | SABBAC performs backbone reconstruction from the C-alpha trace. | Method tested on a subset of proteins from PDB. This robust method provides an answer even for degenerated C-alpha traces. Available as a web server. |
| Uses a small library of short fragments extracted from known protein structures and a greedy algorithm for fragment assembly and optimization. | ||
| SCATD (362) | SCATD performs side chain reconstruction from a protein backbone. | Method tested on 180 proteins (the same benchmark set as for SCWRL 3.0). Available as a standalone application. |
| Uses the rotamer library from SCWRL (version 3.0). SCATD computes interaction scores between atoms, uses dead-end elimination criteria and energy minimization via tree decomposition. | ||
| SCWRL (version 4.0) (363) | SCWRL performs side chain reconstruction from a protein backbone. | Method widely used in protein modeling pipelines. Tested on 379 proteins from PDB. |
| Uses a backbone dependent rotamer library, calculates self-and pairwise energies, builds and solves graphs with a modified tree decomposition algorithm. | Available as a standalone program and a dynamic-linked library for incorporation into other software programs. | |
| SidePRO (343) | SidePRO performs side chain reconstruction from the protein backbone. | Method designed for fast side chain reconstruction. Tested on 379 proteins (SCRWL4 benchmark set), 94 proteins from the CASP9 data set and 7 protein complexes. |
| Uses a knowledge-based energy function and artificial neural networks. | Available as a web server and computer code. |
4 Applications
ARTICLE SECTIONS
4.1 Coarse-Grained Models in Multiscale Modeling Pipelines
Over the years many research groups have undertaken studies on the use of the all-atom/coarse-grained multiscale modeling approach trying to answer different biophysical questions and develop highly specific tools. As described in section 3.1, these tools can be divided into parallel and serial multiscale modeling approaches. The parallel approaches usually require additional strategies for the integration and exchange between the different levels of resolution, while serial multiscale approaches are more common and straightforward.
MMTSB (258) is a good example of a toolset that enables custom parallel multiscale simulations. It combines packages that allow simulation with all-atom resolution such as CHARMM (113) or AMBER (364) combined with the coarse-grained modeling approach, MONNSTER (365) (based on a medium resolution SICHO lattice model (95)). This approach was successfully tested for scoring protein conformation, peptide folding and prediction of missing protein fragments. (258) Another computationally complex task for which the parallel multiscale approach has been successfully applied is modeling interactions of proteins submerged in solvents or lipid membranes. In this case solvents or membranes can be represented in a coarse-grained manner while proteins are treated with atomistic resolution. (20) In one of such force fields, named PACE (protein in atomistic details coupled with coarse-grained environment) and developed by Han et al., (366) the united atom representation of a protein is combined with the MARTINI coarse-grained model of a solvent or membrane. In the folding simulations the authors obtained satisfactory coherence with experimental data, comparable to fully atomistic approaches. (367) An interesting parallel multiscale approach has been also described by Machado et al. for simulating nucleic acids. (300) In this model the region of interest is treated with all atom details using the AMBER force field (368) while the rest of the system is approximated by coarse-grained representation. (369) For interaction calculations the method employs a common Hamiltonian function that serves for both the all-atom and the coarse-grained simulation level and makes further extension to QM/MM or a different level of coarse-granularity uncomplicated. Another parallel model that allows using the multiscale approach to simulate the crowding effect on peptides is described by Predeus et al. (370) In this simulation crowders (proteins G) are represented with the PRIMO (protein intermediate model) (105) coarse-grained model, while peptides of interest are accounted for in atomistic detail using the CHARMM force field. (113, 114)
Among serial multiscale methods it is worth to mention a model developed by Zacharias principally for studying protein–protein interactions. (371) It combines all-atom GROMOS (372) and coarse-grained ATTRACT (373) force fields. It allows for the exhaustive Monte Carlo sampling of coarse-grained representation of the interacting proteins followed by an accurate all-atom description of favorable protein–protein complex geometries. Another method that combines the GROMOS force field with the coarse-grained OPEP potential (374) was presented in the study of the amyloid-forming peptide. (252) In this example of serial multiscaling, coarse-grained simulation was used to simulate aggregation of amyloid peptides, and then the stability of the derived species was tested with all-atom resolution.
Table 3. Examples of Multiscale Modeling Web Servers
| server name (reference) | coarse-grained modeling task | method summary, availability |
|---|---|---|
| Protein Structure Prediction | ||
| I-TASSER (48, 173, 377) | Uses a coarse-grained protein model for the ab initio modeling of unaligned regions (mainly loops). (170) | I-TASSER performs comparative and ab initio prediction of protein structure. The method has been validated during several recent CASP competitions as the leading approach for protein structure prediction. (48, 173, 377) |
| Available at: http://zhanglab.ccmb.med.umich.edu/I-TASSER/ | ||
| CABS-fold (205) | Uses a CABS coarse-grained model as a conformational search engine. | CABS-fold performs ab initio and consensus-based prediction of protein structure. The methodology was validated during the CASP competition as one of the leading approaches. |
| Available at: http://biocomp.chem.uw.edu.pl/CABSfold/ | ||
| Robetta (378) | Uses coarse-grained Rosetta representation in the initial stage of structure prediction. | Robetta provides ab initio and comparative modeling prediction of protein structure. The method has been validated during several recent CASP competitions as one of the leading approaches. Other capabilities include prediction of the effects of mutations on protein–protein interaction, protein design and protein–protein docking. The server can also utilize NMR constraints data. |
| Available at: http://robetta.bakerlab.org/ | ||
| Phyre2 (379) | Uses a Poing (380) coarse-grained model for ab initio modeling. | Phyre2 performs comparative and ab initio prediction of protein structure. The method has been validated as one of the leading approaches in CASP competitions. The server provides a suite of tools to analyze protein structure, function and mutations. |
| Available at: http://www.sbg.bio.ic.ac.uk/phyre2 | ||
| Pep-fold (254) | Uses an OPEP coarse-grained model as a conformational search engine. | Pep-fold performs ab initio structure prediction of peptide structure (between 9 and 36 amino acids). The server allows user specified constraints such as disulfide bonds and inter-residue proximities. |
| Available at: http://bioserv.rpbs.univ-paris-diderot.fr/services/PEP-FOLD/ | ||
| Protein-Peptide Docking | ||
| CABS-dock (213, 214) | Uses a CABS coarse-grained model as a conformational search engine. | CABS-dock performs flexible protein-peptide docking without prior knowledge about the binding site. During on-the-flydocking, CABS-dock allows full flexibility of the peptide and moderate flexibility of the protein receptor structure. The method has been tested on a large benchmark set of protein-peptide complexes and has proven to be effective in building high and medium accuracy models. |
| Available at: http://biocomp.chem.uw.edu.pl/CABSdock/ | ||
| pepATTRACT (381) | Uses an ATTRACT coarse-grained model for rigid body docking and scoring. | pepATTRACT performs flexible protein-peptide docking without prior knowledge about the binding site. The best scored complexes are subjected to atomistic refinement using the iATTRACT (382) procedure and all-atom MD. The protocol was tested on 80 peptide–protein complexes. (381) |
| The web interface enables generation of input docking scripts and the docking can be performed on the user’s machine with a local installation of the ATTRACT program. | ||
| Available at: http://www.attract.ph.tum.de/peptide.html | ||
| Rosetta FlexPepDock (264, 383) | Uses coarse-grained Rosetta representation in the initial stage of docking. | Rosetta FlexPepDock is a high-resolution docking and refinement protocol for modeling protein-peptide interactions. The server requires an approximate specification of the peptide binding site (anchor residue). The method has been tested on a large benchmark set of protein-peptide complexes and has been shown to generate high-resolution models. (265) |
| Available at: http://flexpepdock.furmanlab.cs.huji.ac.il/index.php | ||
| Modeling the Flexibility of Globular Proteins | ||
| CABS-flex (210) | Uses a CABS coarse-grained model as a fast simulation engine. | The method has been shown to generate a similar picture of protein flexibility compared to all-atom MD (211) and NMR ensembles. (384) |
| Available at: http://biocomp.chem.uw.edu.pl/CABSflex/ | ||
| NMSim (385) | Uses coarse-grained normal-mode analysis | The method allows performing three simulation types: unbiased search of the conformational space; pathway generation by targeted simulation; and radius of gyration-guided simulation. NMSim has been shown to be a computationally efficient alternative to all-atom MD. |
| Available at: http://www.nmsim.de | ||
| FlexServ (386) | Uses three coarse-grained algorithms for simulations of protein flexibility: discrete dynamics, normal-mode analysis and Brownian dynamics. | FlexServ allows complete analysis of flexibility using a large variety of metrics. The server can also analyze user provided trajectories. |
| Available at: http://mmb.pcb.ub.es/FlexServ/ | ||
| Protein Design and Interactions | ||
| ATTRACT (387) | Uses the ATTRACT coarse-grained model for protein–protein docking | The web service supports systematic rigid-body protein–protein docking, as well as various kinds of protein flexibility. (387) ATTRACT has been successfully used to predict complex structures in various rounds of CAPRI. (388-390) |
| The web interface enables generation of input docking scripts and the docking can be performed on the user’s machine with a local installation of the ATTRACT program. | ||
| Available at: http://www.attract.ph.tum.de/ | ||
| BeAtMuSiC (391) | Uses statistical potentials (392, 393) adapted to coarse-grained protein representation to evaluate the energetic change induced by the mutation. | BeAtMuSiC allows fast assessment of changes in binding affinity between two proteins in the complex caused by point mutations. The method was evaluated within the 26. CAPRI round and stood among the top performers for the analysis of ∼2000 mutations in two designed inhibitors of influenza hemagglutinin. (391) |
| Available at: http://babylone.ulb.ac.be/beatmusic/ | ||
| DOCK/PIERR (394) | Uses coarse-grained scoring functions for protein docking. (395) | DOCK/PIERR performs docking of proteins given their individual tertiary structures. The docking algorithm has been tested on docking benchmark data sets and has proven to perform similarly as other state-of-the-art methods. (396) The server has ranked fourth in the 2013 CAPRI server assessment. |
| Available at: http://clsb.ices.utexas.edu/web/dock.html | ||
| ENCoM (397) | Uses coarse-grained normal-mode analysis. | ENCom allows prediction of the effect of point mutations on function, thermostability and dynamics of proteins with multiple chains. In addition, the method generates comprehensive, geometrically realistic conformational ensembles of mutated proteins. |
| Available at: http://bcb.med.usherbrooke.ca/encom.php | ||
| RosettaDock (398) | Uses coarse-grained Rosetta representation in the initial stage of docking. | RosettaDock predicts the structure of protein–protein complexes, such as antigen–antibody pairs, enzyme–inhibitor pairs or regulatory proteins. It has been successfully validated in the CAPRI blind challenge on diverse targets, also in combination with the Funhunt classifier (399) for selection of low-energy conformations close to the native conformation from other low-energy ensembles. |
| Available at:http://graylab.jhu.edu/docking/rosetta/ | ||
| RosettaAntibody (261, 400) | Uses coarse-grained Rosetta representation in the initial stage of modeling. | RosettaAntibody uses a comparative modeling approach to build structures of complementarity determining regions (CDRs). In the second stage, the CDR and H3 loop is remodeled ab initio and orientation of VL/VH domains is optimized using a Rosetta protocol. Paratope side chains and loop backbones are refined simultaneously. The procedure has been tested during the Antibody Modeling Assessment II experiment. (261) |
| Available at: http://antibody.graylab.jhu.edu/antibody | ||
Finally, among multiscale all-atom/coarse-grained tools there is a growing number of methods available as web servers that are especially useful for nonexpert users. This trend of making molecular modeling methods available as easy to use and accessible web servers (so-called “serverification” (267)) is expected to continue. Below we provide examples of multiscale modeling servers that use coarse-grained modeling tools. More detailed information concerning all-atom/coarse-grained multiscale modeling is available in recent reviews. (39, 375, 376)
4.2 Simulations of Protein Dynamics
So far, structural biology has focused mainly on the analysis of static X-ray structures. Recent advances in experimental techniques strongly indicated that protein function is in many cases dictated by dynamics. (5, 6) Thus, the classical “structure determines function” dogma has been extended to include dynamics. Consequently, the ultimate goal of contemporary structural biology is to add time, the fourth dimension, to the characterization of protein structure. Unfortunately, a protein energy landscape is highly multidimensional and tied to a specific set of conditions (e.g., temperature, pressure, and environment specifics). Therefore, the characterization of protein dynamics, either by theory or by experiment, is very challenging and the difficulty of the problem increases with the scale of mobility and size of protein systems.
4.2.1 Protein Folding and Large Scale Dynamics
For most proteins, the time scale of protein folding is beyond the possibilities of all-atom MD with explicit solvent. (16, 17) Recent advances in building specialized hardware dedicated to MD simulations enable us to reach the 1 ms time scale for a small protein, (401) which means significant (100 fold) speedup in comparison to the previous 10 μs record. (402) Because of the computational cost, unbiased (using no knowledge about the native structure) MD simulations of protein folding with explicit solvent are limited to small (up to ∼100 amino acids) fast-folding proteins, (16, 401, 402) while simulations of larger proteins are restricted to studies of near-native dynamics or high temperature unfolding. A few protein folding pathways have been described in detail at atomic resolution, thanks to combining experimental data with all-atom MD techniques. (403, 404) Coarse-grained models offer significant extension of the simulation time scale. For example, compared to all-atom MD with explicit solvent, the speedup can be between 103 and 104 times for the UNRES model (271) or the CABS model (211) and even 107 times for much simpler models. (27)
In the past two decades, the field of protein dynamics simulation was dominated by the native-centric view of protein folding. (200) This view was supported by experimental studies showing that, on a general level, folding can be described as a simple two-state process, and that transition state structures are very native-like. The assumption that native interactions only are sequence-dependent ensures that the native structure is always in the energy minimum. Introducing this assumption into molecular models offered the possibility of significant simulation speedup and unification of the protein folding picture. (174, 175, 177, 178) The models with such an interaction scheme, called structure-based models (SBM) or Go̅ models, have become widely used in simulations of folding mechanisms, folding kinetics and functional motions. (177-180, 405-407) Many variations of SBMs proved to be valuable in descriptions of conformational dynamics, which is interpreted by the native-like character of the key transition states. However, the SBM-based approach seems to be increasingly unsatisfying in the context of emerging studies on a significant role of non-native interactions in protein folding. (408-410) Importantly, functions of many proteins are associated with the existence of multiple different conformations. Thus, it is obvious that building an SBM force field based on a single native state structure may be insufficient for the complete exploration of a conformational landscape. (411) Therefore, modern SBMs have been extended by adding information about a few different conformational states (multibasin models). (411-413) Multibasin SBMs are built on the same concept as single SBMs with the exception that they use more than one conformational state (for example, two distinct structures crystallized in different, bound and unbound, states may be used) as references for simplified interaction patterns. SBMs are also extended by using additional information, for example enforcing protein motions (414) or coevolutionary information extracted from multiple sequence alignments. (411) Regardless of the extension of SBMs, the fundamental question arises of whether the interaction model based on a specific structure, or selected structures, is sufficient in a particular case to describe the real functional dynamics.
In principle, deep understanding of protein folding mechanisms requires simulation models that are not biased by structural information about the final native state, and that do not exclude different intermediates than fragments of the native-like structure. Based on the earlier advances (see reviews in refs 19−21 and 44), in recent years we have witnessed protein (or peptide) folding mechanism studies using various coarse-grained models that go beyond the SBM interaction scheme: UNRES (-269-272) (see Figure 7), OPEP, (247-250) PACE, (415, 416) the model by the Voth group, (417, 418) the Bereau and Deserno model, (243) CABS, (101, 207-209) or the TerItFix approach. (419, 420) These examples demonstrate the usefulness of models based on physics-based potentials, physics-based potentials combined with terms from statistical analysis of folded structures or solely on statistical potentials (CABS, TerItFix). While physics-based models present a straightforward approach to the investigation of folding dynamics, the application of statistical potentials raises questions about the validity of such an interaction scheme to the simulation of denatured structures. Nevertheless, it has been demonstrated that the evolution of folding events, from denatured to near-native states, guided by statistical potentials is consistent with experimental data (207, 208, 419, 421) or with all-atom MD simulations for small fast-folding proteins. (420) Consequently, these results strongly suggest that the nature of interactions (not necessarily the geometry) that controls the denatured state of proteins is qualitatively quite similar to the interaction patterns derived from the statistical analysis of folded structures.
Figure 7
Figure 7. Folding pathways obtained in ab initio simulations using the UNRES coarse-grained model and Langevin dynamics. (269) The pathways are presented for two proteins 1CLB and 1E0G. The protein models are marked with the RMSD values (root-mean-square deviation from the corresponding experimental structures, in Ångstroms) and simulation time. The simulations took a few hours of a single CPU time; therefore, the UNRES model provided a three to four-order-of-magnitude speed-up relative to all-atom MD simulations.
Proteins in the cellular environment encounter a multitude of interactions that do not result in the formation of complexes. The role of these nonspecific interactions is essential to the mechanisms of life and therefore actively investigated. (422) Cellular environments can be described at atomic resolution or using coarse-grained models at different levels of coarse-graining, (423) i.e. implicit solvent models, molecular-shape preserving coarse-grained models or spherical coarse-grained models of solute biomolecules. Integration of such models at different representation scales is the key challenge in the construction of integrated models, which can serve as a platform for in silico cellular models. (423)
Besides folding studies of single proteins/peptides, coarse-grained models are also applied to various specific aspects of protein folding. Example applications include studies of misfolding mechanisms; (238, 272, 424, 425) aggregation mechanisms (26, 31, 424, 426) (see section 4.4); the effect of post-translational modifications on protein folding and function; (427, 428) the role of interplay between specific interactions (local/nonlocal, non-native/native and other) in protein folding; (408, 427, 429, 430) or the mechanisms of chaperonin-assisted folding. (209, 431-433)
4.2.2 Protein Flexibility: Small-Scale Dynamics
Time scales of biologically relevant protein fluctuations remain computationally demanding or even beyond the reach of atomistic models, and therefore coarse-grained models have emerged as an inexpensive simulation alternative. (434) One of the main problems of large scale molecular modeling is that force fields are not accurate enough, even the all-atom ones. Consequently, modeling results may be different depending on the force field choice. (21, 435-437) In 2007, Orozco and colleagues examined whether different all-atom force fields provide a consistent picture of near-native dynamics in aqueous solution. (438) This comprehensive study of the most populated protein metafolds, using the four most popular force fields (OPLS, CHARMM, AMBER, and GROMOS) and explicit solvent, showed that the resulting dynamics picture is consistent among the force fields. The all-atom simulation data from the Orozco study (438) have been subsequently used as a reference for studies of different coarse-grained models as to whether they yielded comparable results. (211, 439, 440) These studies tested SBMs (439, 440) (employing Brownian dynamics, or discrete molecular dynamics, also with a simple pseudophysical force field variant being a hybrid between the physical potential and SBM) and a knowledge-based force field derived from known folded structures (CABS model). (211) All these coarse-grained models provided a picture of near-native dynamics in good agreement with the all-atom simulation data.
Moreover, it is important to highlight that the all-atom picture of near-native protein dynamics obtained by Orozco (438) was observed on a relatively short nanosecond time scale (10 ns). Current supercomputer capabilities encompass much longer time scales and it has been shown that some important conformational transitions of a folded protein may remain undetected in submicrosecond simulations. (17, 441) Future advances are expected to come with the availability of high-resolution experimental data and with developments in all-atom MD that will make this technique faster, and thus more approachable. (17) Nevertheless, in the nearest future, all-atom MD will not be suitable for flexibility analysis, and thus coarse-grained methods will continue to be the core of new efficient simulation tools. (434) Recently, several web servers using different coarse-grained modeling techniques have been proposed: CABS-flex, (210) NMSim, (385) and FlexServ (386) (see Table 3).
Functional motions of proteins can be also predicted using coarse-grained normal mode analysis (NMA). (442) Due to its success in the description of many systems and relatively simple implementation, NMA has found numerous applications in structural biology. However, certain issues about its limitations should be kept in mind, especially when large amplitude motions are considered. (256) The limitations and practicality of NMA are discussed in a review. (443)
The incorporation of protein flexibility in structure-based drug design (SBDD) is critical in many cases to obtain a valid picture of protein interaction sites. (444, 445) One of the important challenges in including flexibility in SBDD studies is to choose the right level of flexibility depending on system nature and specifics of the SBDD study. (446) Therefore, future developments call for integrative methods merging SBDD approaches with experimental data and with various simulation techniques enabling efficient modeling of near-native dynamics (434, 442) but also large distance movements of big macromolecules. (447)
4.3 Protein Structure Prediction
4.3.1 Importance of Computational Structure Prediction
Due to genome projects, we know a vast number of protein sequences that define their primary structure (the UniProt database currently contains around 80 million sequences and is growing exponentially (448)). Genome sequencing is now highly automated and relatively inexpensive. Experimental determination of three-dimensional (tertiary) protein structure is more challenging and still very expensive. In spite of a significant effort of many top laboratories, the number of experimentally determined structures is much smaller than the number of known sequences (PDB currently contains around 120 thousand structures (449)). This gap is still increasing. The knowledge of protein structures is one of the major requirements for understanding most of their biological functions, which is crucial for medical sciences and biotechnology. Therefore, theoretical prediction of protein native structure is one of the important challenges of molecular biology, theoretical chemistry and bioinformatics. While we can reliably predict a three-dimensional structure (structures) of small molecules and simple polymers, the problem of protein structure is significantly more challenging. Solvent properties and interactions with other molecules and macromolecules make the problem even more complicated and computationally demanding. Simulations of protein folding, from the denatured to the folded state based on all-atom MD, a classical simulation tool, remain generally impractical (see section 4.1). The application of coarse-grained models in protein structure prediction is therefore very appealing. Coarse-grained modeling plays an essential role not only in the ab initio prediction of protein structure (based on sequence only), but also in the most efficient strategies of comparative modeling (based on structural similarities resulting from protein homology).
4.3.2 Comparative Modeling
The comparative modeling of protein structures using their homology relations (homology modeling) is certainly one of the most successful tools of theoretical structural biology. Comparative modeling relies on the observation that proteins with similar sequences usually have similar 3D structures. This level of sequence similarity does not have to be high: even moderate sequence identity (∼30%) usually implies high similarity of 3D structures, provided that sequence alignment is correct. (450) The identification of template(s) (homologous protein(s) with known 3D structure) and their sequence alignment to the target sequence is a key stage of homology modeling. It provides a crude model of the core of the target structure. The missing fragments of the modeled structure (usually, but not always, the loops connecting secondary structure elements) need to be added. Plausible structures of short fragments (up to 10 amino acids) can usually be predicted with useful accuracy and connected with the template structure. This approach is very efficiently used in the Modeller method, (351, 352) a classical tool for comparative modeling based on high or moderate sequence similarity. With decreasing sequence similarity, alignment becomes less accurate and templates cover a smaller fraction of the target structure. In such cases, classical comparative modeling becomes very difficult and coarse-grained algorithms are used for modeling poorly aligned and missing fragments, (206, 274, 451-454) like for example in the I-TASSER automated structure prediction platform. (48)
I-TASSER is one of the most powerful tools for protein structure prediction today (see also section 4.3.4). This method is somewhat similar to the classical Modeller concept (351) in which fragments of homologous proteins are used as a core of the modeled structure. I-TASSER, (48) is based on a multilevel (multiscale modeling) approach that uses various bioinformatics and molecular modeling tools. I-TASSER uses a sophisticated sequence (target) to structure (template) three-dimensional “threading” schemes for selection of the most probable structure fragments. These fragments are used to build a core of the target structure. Subsequently a coarse-grained CAS method (173, 455) (similar to CABS (100, 170, 173)) is used for the Monte Carlo modeling of missing or ambiguous fragments, and finally the structure is carefully refined. The method is exceptionally successful in difficult comparative modeling based on very distant homology, and thereby low sequence similarity between the target and templates used in modeling. Modifications of this method work relatively well also in more difficult structure prediction tasks, including the modeling of protein–protein complexes. (456)
Alternative to restriction of coarse-grained modeling to difficult protein fragments, different alignments and several templates could be used (457) to build a set of distance restraints for the coarse-grained modeling of the entire structure. Such a strategy may be the best choice especially for a very distant homology of template structures and it is employed for example in Phyre2 (379) or CABS-fold (205) web servers for protein structure prediction.
4.3.3 Ab Initio Modeling
Using state-of-the-art tools of comparative modeling enables computational prediction of high resolution structures for a large fraction of newly sequenced proteins. (3) Nevertheless, structure prediction utilizing only the target sequence and no homology relations (termed: “ab initio” or “de novo” or “template free” modeling) is still the Holy Grail of theoretical structural biology. (47, 458, 459)
As mentioned in section 2.1, the first attempts at using coarse-grained models to study protein folding and to predict protein structure ab initio started about 40 years ago. Since then several similar and alternative reduced representations and sampling schemes have been used by others and in most cases it was possible to predict very low resolution structures of simple and small proteins, or protein-like systems, (170, 230) peptides (460, 461) or loop fragments. (206, 274, 451-453) Lattice models of various resolution played an important role in the early studies of protein folding. (43, 462) Hierarchical schemes, which employ coarse-grained lattice models of increasing resolution, have been successfully used for de novo simulations of the protein folding process in a few small proteins. (462-464)
Presently, realistic de novo structure predictions are possible for a significant fraction of small (up to 100, or so, amino acids) and structurally not too complex proteins. (465-467) However, it has to be pointed out that the most popular contemporary algorithms for ab initio structure prediction use some general information about natural proteins. This can be done on various levels. For example, Rosetta uses sequentially similar structural fragments extracted from other proteins, not necessarily homologous. (71, 378) The CABS algorithm can use secondary structure predictions and knowledge based statistical potentials derived from representative sets of protein structures. Secondary structure predictions are not necessary, although their use increases the accuracy and resolution of the resulting tertiary structures. The QUARK algorithm, (468) which proved to be most efficient in ab initio prediction in the CASP experiment (465) (see also the next section), combines the best features of Rosetta and CABS, i.e. structural fragments from known protein structures and knowledge based statistical potentials.
4.3.4 Critical Assessment of Protein Structure Prediction Methods
To validate the accuracy and efficiency of existing and newly developed methods for protein structure prediction CASP (critical assessment of methods for protein structure Prediction) experiments are organized every two years. (469) The experiment is worldwide and most research groups leading in the development of protein structure prediction methods participate (at least in some of its editions). The work scheme of CASP is the following: A couple of months before the meeting experimental structural biologists provide several sequences of proteins whose structures are near to be resolved or already resolved but not yet published. Modeling groups make theoretical predictions of the structures and deposit them on the CASP server. The organizers of the experiment collect the predictions and the experimental data on the new structures. Experts in the field evaluate the quality (accuracy) of the predicted structures. The evaluation methods are perhaps not perfect, and measurement rules of prediction accuracy have evolved slightly with time, but they definitely provide reasonable ranking of the accuracy of the submitted models.
Detailed discussions of successive CASP experiments can be found in dedicated issues of the Proteins journal; (469) however, some general observations are possible. First of all, the accuracy of theoretical structure prediction methods continuously (albeit rather slowly) increases. Much of this progress can be contributed to coarse-grained modeling methods, especially in the last years. The leading groups used for instance the Rosetta method, (71, 378) although methods using more free-space coarse-grained sampling techniques also achieved good results, like the CABS model. (171) In some of the last CASP editions impressive predictions were provided by the Zhang group using I-TASSER (see section 4.3.2) and QUARK methods. (455, 458, 465)
Several other recently developed methods of multiscale modeling in structure prediction were also successful in the last CASP experiments. (470-472) Another, and less obvious, trend could also be noted. In the early CASP exercises, the best predictions were achieved by comparative modeling methods, where the key issue was the best sequence alignment and the modeling of the missing fragments was relatively simple, usually based on Modeller (351, 352) (or similar) software. Difficult de novo targets were rarely predicted with realistic low-resolution accuracy. In the recent CASP experiments, the methods combining comparative modeling with tools for de novo modeling have become the most effective.
4.4 Protein Interactions
Protein–protein interactions (PPIs) play a fundamental role in controlling a wide range of biological processes including cell-to-cell interactions, signaling transduction pathways and regulatory cascades inside the cell. PPIs are responsible for protein affinity and recognition, protein–protein assembly, protein oligomerization and aggregation, and many more. Moreover, it is estimated that over 80% proteins do not operate alone but in complexes. (473) Therefore, detailed understanding of PPIs is becoming one of the major objectives of system biology. The recent development of coarse-grained techniques makes them a promising and powerful tool for PPI modeling. (29) In this section, we focus on the overview of coarse-grained methods used in modeling protein–protein or protein-peptide interactions. What’s important to note, there are also lively fields of research dedicated solely to the coarse-grained modeling of specific protein interactions, for example with DNA, (202, 407, 474, 475) RNA, (476, 477) or other ligands. (478, 479)
Coarse-grained models for PPI description should efficiently sample the evolution of large multiprotein systems over long time scales. On the other hand the level of coarse-graining should maintain a realistic description of side chain physicochemical properties and their interactions that control the formation of protein complexes. Moreover, modeling the protein–protein interface may require realistic prediction of induced conformational changes of interacting molecules, or even prediction of protein folding pathways. Sometimes the binding mode of two proteins may be modulated by interactions with other small molecules present in the surrounding environment. (480) Recent developments in the field of coarse-grained PPI modeling focused mainly on three areas: (29) knowledge-based molecular docking (using structural databases, bioinformatics and/or experimental data to guide the assembly of complex subunits), de novo molecular docking without the a priori localization of the binding site, and the modeling of large scale protein assembles and aggregates.
A growing amount of various experimental data provide a valuable source of information for knowledge-based molecular docking. (52) In the most favorable circumstances, the available crystal structures of protein complexes may be used as templates for the comparative structure prediction of other homologous complexes and subsequently coarse-grained techniques, often combined with all-atom scoring, can be applied for efficient refinement. (373, 390, 396, 481, 482) Such a situation is rare and in most cases very limited data are available. Fortunately, even partial structural information which allows the identification of only small fragments (or even single residues) of the interface of two interacting proteins is of great importance for PPI prediction because it largely reduces the conformational space that needs to be sampled. A variety of experimental data can be used for derivation of spatial restraints that may significantly enrich the coarse-grained modeling procedure. (483) Periole and co-workers used AMF pictures showing organization of rhodopsin in disk membranes as a starting configuration for the coarse-grained MD simulation of interacting rows of dimers. (484) Restraints derived from comparative modeling were used in the CABS coarse-grained model (72) to predict a three-dimensional structural model of a partial telomerase elongation complex composed of three essential protein domains bound to a single-stranded telomeric DNA fragment in the form of a heteroduplex. (485) The experimental data may guide the docking process by localizing protein binding interfaces or by identification of interacting conformations. Even weak distance restrains facilitated more accurate structure prediction of complex systems in the CABS method. (171) Structural restrains could be also used to validate predicted protein assemblies (486) and to improve the template-based docking procedure. (487) Guerois and co-workers proposed InterEvScore, (488) a scoring function using a coarse-grained statistical potential including two- and three-body interactions, for protein–protein docking evaluation. Combination of this potential with evolutionary information considerably improved scoring results compared to other methods (ZDOCK, ZRANK, and SPIDER) on the protein docking benchmarks tested. Due to the complexity of the PPI prediction problem the availability of experimental data that can enrich the coarse-grained modeling procedure is the decisive factor for prediction accuracy for a vast majority of protein complexes.
The de novo docking methods for PPI prediction aim at the identification of the protein–protein contact interface. This task becomes computationally extremely demanding when structural changes on docking have to be considered. Given the high computational cost of flexible docking, coarse-grained models offer an efficient and promising alternative to all-atom docking approaches. For example, Fernandez-Recio et al. developed pyDockCG, (489) a new coarse-grained potential for protein–protein docking scoring and refinement, based on the coarse-grained UNRES model. (73) In this work, new terms accounting for Coulomb electrostatics and solvation energy were proposed and tested. The pyDockCG yielded similar results to those produced by all-atom scoring function but at much lower computational cost. Another coarse-grained force field, the SCORPION, (268) was used in a series of coarse-grained MD simulations of protein–protein recognition in water for the barnase/barstar complex. The method employed coarse-grained potentials derived from the AMBER all atom force field with implementation of the new polarizable coarse-grained solvent (PCGS) model, whereas protein internal flexibility was accounted for by the elastic network model (ENM). The method was able to reproduce conformations very close to the native bound structures in five of a total of seven coarse-grained MD simulations. In the work of Frembgen-Kesner and Elcock, (490) application of coarse-grained Brownian dynamics (BD) simulations that included description of intermolecular hydrodynamic interactions reproduced the experimental values of association rate constants for the formation of the barnase-barstar complex. In the context of discrete molecular dynamics, a new coarse-grained force field has been recently introduced to investigate PPI and conformational sampling of multiprotein systems. (491) Interestingly, it was also reported that coarse-grained models can accurately reproduce interaction strength for protein complexes of known structure. (492)
An interesting example of a coarse-grained approach to protein docking is the ATTRACT model. (371) Starting from 2003, the ATTRACT model has been systematically improved and evolved in several docking applications. Initially, the ATTRACT force field was a molecular-shape preserving coarse-grained model with no internal main chain connectivity, with only nonbonded intermolecular terms. (371) The protein side chains were treated as an ensemble of rotamers that were discriminated during the search of relative association geometry. (371) Flexible interfacial loops, allowing for large amplitude movements, were further treated by using an ensemble of pregenerated loop conformations and a mean field approach. (493) These choices allowed very rapid search while preserving good accuracy for the search results. The initial force field was further modified for better efficiency using a different functional form for van der Waals terms. (494) Global protein flexibility was introduced along normal modes of deformation in a Gaussian network. (373) Recently, a multiscale method (ATTRACT combined with all-atom) was proposed for the refinement of protein complexes. (481) ATTRACT has been also applied to the analysis of the internal mechanics of proteins and detection of rigid amino acids using Brownian MD simulations within a Gaussian network, (495) protein–DNA docking, (496) protein-peptide docking, (381) integrative serial multiscale modeling using interactive simulations with the Biospring engine (497, 498) and to investigate large oligomeric assemblies. (498) Importantly, the ATTRACT has been successfully used for the prediction of protein complexes in different rounds of CAPRI experiments (388-390) that are discussed in the next paragraph.
The ongoing progress in protein–protein docking and PPI identification is addressed in the Critical Assessment of Prediction of Interactions (CAPRI). (499, 500) CAPRI is a community-wide experiment for prediction of the molecular structure of protein complexes. From 2001 until now, 34 rounds took place. In each round, a number of protein–protein complexes whose crystal structures have been solved recently are designated as targets for blind prediction using computational methods. In various CAPRI rounds, the ATTRACT coarse-grained model (described above) proved to be successful as an ensemble docking approach that involves an implicit flexibility of protein complexes (388-390) (the classification of protein docking approaches with regard to the treatment of protein flexibility is presented in the review (445)). CAPRI results show that the main problem in docking strategies lies in the search algorithms, especially in the treatment of large-scale conformational changes, and in the scoring functions. (501-503) The coarse-grained strategies are considered promising alternatives for the future implementation of large-scale protein flexibility into on-the-fly docking (explicit flexibility) algorithms. (445, 504) Such trends are represented by two methods based on Rosetta (104) and CABS (72) coarse-grained models that allow for significant structural changes during on-the-fly protein-peptide docking (213, 214, 383, 505, 506) (see Figure 8). Coarse-grained methods also remain an effective solution for an ensemble docking approach, as demonstrated by a pepATTRACT method for fully blind protein-peptide docking (381) (see Table 3).
Figure 8
Figure 8. Protein-peptide docking with full flexibility of a protein loop region close to the binding site. The upper panel shows protein receptor flexibility during docking simulation. The starting protein structure (experimental structure in an unbound form) is shown in green. Simulated protein models are presented in blue while the flexible loop region in orange. The lower panel presents comparison of the predicted protein-peptide complex (blue) with the experimental structure of the complex (red) and the starting structure (green). Docking was performed using a coarse-grained CABS-dock method with no knowledge about the binding site or peptide conformation. During docking simulation the peptide was allowed to be fully mobile and flexible. The RMSD between the predicted and experimental peptide structure (after the best superposition of the receptor structure) was 2.03 Å. The example is described in detail elsewhere. (214)
The modeling of large scale protein assemblies and aggregates is another area in which applications of coarse-grained modeling have shown promising results. (53, 89) A good example is the application of coarse-grained modeling techniques for the investigation of large complexes of membrane proteins (see section 4.5). In a recent work the coarse-grained MD approach with a push–pull-release (PPR) sampling strategy was used for a set of five well-known protein–protein complexes to describe the energy landscape and molecular forces that stabilize protein association. (507) Hansmann and co-workers (275) used the UNRES force field with MD replica exchange simulations to study the self-assembly and PPI of a homotetrameric ββα (BBAT1) protein. They found that the folding and association pathway could be described by three separate steps, whereby association to a tetramer precedes and facilitates the folding of the four chains. Misfolded or partially unfolded proteins may lead to large scale aggregates, responsible for many pathological conditions. The molecular basis of aggregation-linked diseases is actively investigated using computer simulations. (251) In the reviews of Shea and co-workers (31, 426) the most recent computational approaches to protein aggregation are presented, from coarse-grained models to atomistic simulations. A wide range of coarse-grained methods with different resolutions and parametrization schemes have been described. (246, 508-514) Coarse-grained models can explain different aggregation pathways and cover long time scale stages of the aggregation process that are beyond the reach of atomistic simulations (see Figure 9).
Figure 9
Figure 9. Comparison of all-atom and coarse-grained modeling capabilities applied in simulations of the aggregation processes. The upper panel emphasizes the ability of coarse-grained models to model a full spectrum of aggregates that occur on different aggregation pathways, from a single monomer to a highly ordered fibril, including: (1) elongation by prestructured monomer addition, (2) lateral growth by templated protofilament assembly, (3) elongation by dock-lock monomer addition, and (4) growth by dock-lock oligomer addition. The lower panel highlights the capabilities of all-atom approaches limited to the forming of small oligomers or the short-scale dynamics of formed aggregates. The “Under Construction” sign emphasize the inaccessibility of the intermediate aggregation stages to all-atom modeling. Adapted from ref. (31) Copyright 2014 American Chemical Society.
Finally, a growing application area for coarse-grained modeling techniques are binding studies of intrinsically disordered proteins (IDPs) (515) or intrinsically disordered regions (IDRs) of other biomolecules. (516) There is growing evidence on IDPs or IDRs playing important functions in cellular mechanisms. (517-520) These functions are frequently involved with large-scale conformational transitions, for example from a disordered to a folded/bound state. Since the experimental characterization of IDP/IDR binding is extremely challenging, (521) simulation techniques—including coarse-grained models—have emerged as an alternative or supplementary approach. (522-525) Similarly as in the field of protein folding, the major challenge in IDP simulation is the efficient treatment of large time scale dynamics, while maintaining sufficient accuracy. (525) In the past decade, the KIX/pKID system (526) has become a model protein complex for computational studies of the folding and binding of a disordered protein. Despite a small size of the pKID/KIX complex, atomistic MD simulations are rather limited to the conformational search in the neighborhood of the native complex or to high-temperature unfolding. (23, 527) Most of the computational studies of the pKID-KIX binding process used coarse-grained structure-based models (with a natively biased force field, see section 4.2.1). (528-532) Some of those studies used coarse-grained structure-based models extended by an additional non-native interaction component (530, 531) and resulted in showing the possible important role of non-native interactions in the binding mechanism. Recently, the pKID/KIX binding mechanism has been also studied by de novo simulations (without prior information about the pKID native arrangement) using the CABS coarse-grained model. (212) Those simulations, starting from random pKID structures, yielded an ensemble of transient encounter complexes in good agreement with experimental results. The general description of the observed folding and binding mechanism is provided in Figure 10. In general, since the interest in IDP/IDR functions is relatively new, the power of coarse-graining seems not to be sufficiently exploited in the field yet. However, we have been witnessing very recently a growing number of studies on coarse-grained-based methodologies dedicated to modeling IDPs (533-535) or IDRs, (536) including studies focused on the efficient parametrization of interaction models using available experimental data, (537, 538) simulation of IDP in a crowded environment, (539) or applications of coarse-grained modeling to particular IDP/IDR systems. (540-544)
Figure 10
Figure 10. Mechanism of coupled folding and binding of the pKID/KIX complex as revealed by coarse-grained modeling. (212) Docking simulations allowed full flexibility of the disordered pKID during a blind search for the binding site onto the KIX surface. During docking, the movement of the KIX backbone was limited to near-native fluctuations.
4.5 Membrane Proteins
Membrane proteins (MPs) are involved in a variety of important biological functions, such as transmitting stimuli from the outside to cell interior, transport of molecules across plasma membranes and cell adhesion. MPs are also targets for over half of the currently used drugs. (545) Due to the large size of transmembrane proteins and their specifically oriented environment that needs to be somehow taken into consideration, coarse-grained modeling strategies seem to be well suited for the computational studies of MPs. The support of coarse-grained modeling is especially useful and needed in MP structure prediction, since the experimental structure determination of MPs is a very challenging task. (545, 546) In this section we focus on applications of MARTINI, (116, 216, 217) the most popular coarse-grained model for the investigation of protein–membrane systems (see the description of MARTINI in section 2.5).
The first applications of the MARTINI model proved to be efficient during the simulation of self-assembly (547) and fusogenicity (548) of small lipid vesicles. Interestingly, the method allowed modeling rare and slowly occurring processes like flip-flop (549) and lipid desorption, (550) bending and deformation of asymmetric bilayers, (551) fusion of lipid membranes, (552) organization of proteins and peptides into lipid bilayers, protein–lipid interactions, protein oligomerization, conformational changes of tertiary protein structure and many more. The computational modeling of those phenomena requires a very large size of the modeled systems and long simulation time scales far beyond the accessible range of the current state-of-the-art atomistic simulations.
Despite the quite versatile character of the MARTINI model, it has a number of limitations that need to be taken into consideration for specific applications. (225) Due to the nature of the coarse-graining of proteins and the definition of protein topology (rather sophisticated side chain representation but a very simplified backbone) changes in protein secondary structures cannot be modeled. Moreover, accurate estimation of an effective time scale of an MD simulation depends on the particular system type and has to be considered with care.
The folding process and the structure and function of MPs are influenced by surrounding membrane environments. (553) The MARTINI model has proved to be very useful for probing protein–lipid interactions. The method was used for numerous simulations that enabled realistic prediction of binding modes in peptides and proteins to membranes, positioning proteins in lipid bilayers (554) as well as proper adaptation of membranes around proteins. (555-558) Sansom and co-workers used an extended MARTINI model for positioning a large number of proteins in lipid membranes. (559) The procedure involved a series of self-assembly MD simulations starting from systems containing protein surrounded by a random mixture of lipid and solvent molecules. In another study, multiscale simulations of a 40 amino acid C-terminal fragment of amyloid precursor protein (APP) in a DPC surfactant micelle and a POPC lipid bilayer were conducted to elucidate the role of membrane surface curvature in modulating the peptide structure. (560)
The lipids and other small molecules that make up the cell membrane may selectively bind to proteins (561) and may modulate their function. The MARTINI model was applied in numerous studies for the detection of these binding sites in MPs. Long time scale coarse-grained MARTINI MD simulations were used for the identification of the highly conserved cholesterol recognition/interaction sequence motif in the serotonin-1A receptor. (562) Other studies illustrated the binding mechanism of cholesteryl esters to cholesteryl ester transfer protein (CETP), (563) the interaction mode of heterodimeric actin-capping protein (CP) with two signaling phospholipids PA and PIP2, (564) PIP2 binding to the inwardly rectifying potassium (Kir) channel (565) and enrichment of short tail lipids near OmpA in mixtures of lipids with different tail lengths. (566) In yet another study, Arnarez and co-workers conducted an extensive set of coarse-grained MD simulations that allowed the identification of six binding sites of cardiolipin on respiratory chain complex III (cytochrome bc1, CIII). (567) A similar approach was used for the investigation of DPPC and DPPG lipid binding to the pore domain of potassium channels KcsA and chimeric KcsAKv1.3 on the structural and functional level. (568)
Studies of MP oligomerization are an important area of the application of coarse-grained protein/membrane models. The structural information on dimeric/oligomeric MPs is very important for understanding their function and mechanism of action. Sharma et al. used MARTINI to investigate the structure and assembly process of TCRα-CD3ε-CD3δ transmembrane domains, both in membrane and in micelle environments. (569) The T-cell receptor (TCR) together with the CD3 dimer is a key component in the primary function of T cells. MARTINI modeling of the trimeric structure allowed the identification of key interacting residues. In addition, a revised picture for the association of transmembrane domains of activating immune receptors in a membrane environment was proposed. In another study a multiscale approach employing coarse-grained MARTINI followed by all-atom MD simulations allowed the identification of the homodimer structure of two C-terminal fragments of amyloid precursor protein (C99) in the POPC bilayer and the DPC micelle. (570) Carpenter and co-workers performed coarse-grained MD simulation of the tetramerization of four transmembrane helices forming the transmembrane domain of influenza A M2 channel protein. (571) Comparison with the X-ray and NMR structures of the M2 bundle suggests that the resulting model may correspond to a closed state of the channel. Recently, the MARTINI model was applied in numerous studies describing the spontaneous self-assembly of GPCR (G-protein coupled receptor) dimers and oligomers in various types of cell membranes. For example Periole et al. carried out multiple self-assembly coarse-grained MD simulations of model membranes containing up to 64 molecules of the visual receptor rhodopsin over time scales reaching 100 μs. (484) The simulations allowed the identification of favored interaction interfaces between two receptors involving helices 1/8, 4/5, and 5. Furthermore, preferential interaction modes were characterized in terms of the potential of mean force (PMF) expressed as a function of interfacial distance between two receptors. A plausible picture describing the supramolecular organization of a row of dimers was also presented. In another study, Provasi and co-workers conducted extensive coarse-grained MD simulation to investigate preferred dimer interfaces of three opioid receptor subtypes: δ, κ and μ. They also addressed the possible role of interfacial lipids in modulating the rate of receptor association. (572) Coarse-grained MD simulations using the MARTINI model were also applied to assess the stability of two different dimer interfaces for β1 and β2 adrenergic receptors (573) and to explore the functional role of cholesterol concentration and its involvement in receptor organization. (480) These applications show that MARTINI, especially when combined with MD refinement, is a powerful engine for studying complex biomembrane systems.
As well as the MARTINI model or its numerous extensions, a wide range of other models have been proposed for MP simulation and modeling. (284, 545, 574-576) Several different coarse-grained models applying Monte Carlo simulation were used for studying the insertion of peptides into membranes (577-580) or proper description of protein interactions with lipid bilayers. (308, 581) Another coarse-grained model developed by Warshel and co-workers was applied to simulate the activation process of the Kv1.2 channel. (582, 583) The method was also used to analyze the energetics of translocon-assisted insertion of charged helical peptides into the membrane. (584) Recently, Feig and co-workers presented an extension of their PRIMO coarse-grained force field onto MPs. (215) The models were positively validated by comparing amino acid insertion free energy profiles with MD simulations of MPs and membrane-interacting peptides. A versatile method for modeling membrane proteins is also available in the RosettaMP framework. (585) RosettaMP allows the prediction of free energy changes upon mutation, high-resolution structural refinement, protein–protein docking and assembly of symmetric protein complexes in the membrane environment.
4.6 Integrative Modeling
Structures of large biomolecular systems are more and more often determined by integrative modeling techniques that use a combination of experimental data from various sources and different theoretical methods. (49-53) Integrative modeling approaches are also expected to provide not only static structures but also the view of conformational changes on assembly. (50, 51) In comparison with the classical modeling tools of structural biology, integrative models are more complex in many aspects. (50, 586) One of them is a multiscale representation requiring specific integration. (92, 93) For example, the same system fragments can be represented on different levels of structural detail, and different fragments of the system can be described in different representations. Such a multiscale description can be transformed to a set of spatial restraints and provides an input to hybrid coarse-grained/all-atom methods, which are expected to provide efficient sampling and scoring.
Computational methods using coarse-grained models have already shown a great promise for a better description of protein structures, or their complexes, when combined with experimental data from NMR, (263, 587-590) cryo-EM, (483, 590-596) X-ray (597, 598) or SAXS. (589, 599-601) In particular, recent combinations of the top performing multiscale structure prediction platforms, Rosetta and I-TASSER, with experimental measurements resulted in spectacular prediction results. For example, the refinement of protein NMR structures using Rosetta with experimental NMR restraints yielded more accurate structures than corresponding X-ray crystal structures. (263) Another interesting example is the performance of the NMR-I-TASSER method (an adaptation of the I-TASSER platform) in the recent critical assessment of automated structure determination of proteins from NMR Data (CASP-NMR) experiment. (590) It was shown that even using only the coarse-grained conformational search, NMR-I-TASSER can consistently produce good resolution models (<2 Å). This makes NMR-I-TASSER very promising for applications in combination with the classical all-atom refinement tools, in particular for the efficient structure determination of large proteins.
5 Concluding Remarks
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Most biomolecular systems, including proteins and their complexes, are too complicated to be efficiently handled by classical molecular modeling tools. This is caused not only by the large molecular size but also by the time-scale of important processes and specific interaction patterns. The coarse-grained modeling approaches outlined in this review seem to be the computational methods of choice in solving many fundamental problems of theoretical and practical molecular biology and medicinal chemistry. When using or designing coarse-grained-based modeling methods, it is necessary to consider several important choices, such as the resolution level and specific design of coarse-grained representation, model of interactions, sampling schemes, and finally the efficient use of experimental (and theoretical) data and effective connection of coarse-grained computations with atom level simulations.
When designing coarse-grained modeling methods, the representation of atomistic structures on a coarse-grained level requires precise definition. The choice of representation determines to a large extent the possible options of force field and sampling, i.e., the compromise between accuracy and computational efficiency. (87, 407) The smaller the number of explicitly treated united atoms (or pseudoatoms) representing fragments of protein chains, the faster simulation, and the lower accuracy. Very efficient models based on three/four united atoms per amino acid residue accelerate simulations by 3–4 orders of magnitude in comparison with classical all-atom MD simulations. (211, 271) Nevertheless, it is useful to develop even more simplified models dedicated to large protein systems with realistic connection with all-atom resolution schemes. (28, 225, 314, 407) On the other hand, some applications require a fine level of coarse-graining. (105, 602) For example, the coarse-grained modeling of solvent and protein interaction effects with small molecules is very challenging (603-605) and it very likely will be an important subject of future research. Dedicated hardware and specific programming may provide additional speedup factors. (606-608)
Improvement of interaction models is of primary importance in the protein modeling field. Current force fields are not accurate enough, and it is possible to obtain different results using different force fields, even the all-atom ones. (21, 435-437) The most straightforward, although definitely not trivial, interaction schemes for coarse-grained models could be derived from the atom-level force fields of classical molecular mechanics. (28, 30, 609) It is not easy to ensure “transferability” of such “physics-based” interaction schemes between different systems or different environments, although significant progress has been achieved recently. (30, 610) Alternatively to the “physics-based” approach it is possible to derive statistical “knowledge-based” force fields that generalize coarse-grained structural regularities seen in the known protein structures. In the past few years modeling schemes based on statistical force fields have proven to be most successful in protein structure prediction (I-TASSER, (48) Rosetta, (104) and CABS (205)). These methods use various combinations of statistical potentials in which sequence specific interactions are based on the statistical analysis of structural data, sometimes limited to sequentially analogous or homologous proteins. Surprisingly, models employing “knowledge-based” interactions derived from regularities observed in static experimental structures seem to provide quite realistic pictures of protein folding pathways and protein dynamics. Nevertheless, the problem of transferability, or rather the balance between specificity and accuracy of statistical potentials (for example between force fields for globular proteins versus force fields for membrane proteins, or for protein monomers and for protein–protein complexes, etc.) needs further studies. Finally, any of the interaction schemes of coarse-grained models could be combined with “restrains” derived from various, often fragmentary, experimental data, enabling their deeper interpretation.
Various sampling schemes, including Molecular Dynamics, Monte Carlo, or their combinations can be applied to coarse-grained models. (181-185) Coarse-grained representation enables (and in some sense enforces) significantly smoother energy curves for interaction schemes. Therefore, the apparent time step in coarse-grained MD (269) could be broader than required for atom-level simulations. This provides additional speedup of coarse-grained simulations. Very efficient Monte Carlo sampling schemes could also be used, and these are the natural choice for discrete models. Properly designed MC algorithms based on local conformational modifications can provide quite realistic pictures of long time dynamics. The replica-exchange and other multicopy schemes of MD (or MC) simulations could also be very useful in studies of coarse-grained models of biomacromolecules. (183, 184) Recent progress in sampling has also brought another “Big Data” challenge: how to merge and analyze the massive amounts of simulation data. (199-201)
The multiscale or integrative strategies of molecular modeling have been rapidly developing in the last years. The efficient use of coarse-grained models usually requires rigorous reconstruction of the atom-level representation. This is not a trivial task, and satisfactory solutions exist only for well-studied moderate resolution coarse-grained models. (101, 102, 360) Fast methods of dependable transitions between various levels of representation are needed, and probably require designing specific statistical potentials to ensure not only realistic spatial fidelity but also a reasonable switch between dynamics profiles. The existing coarse-grained modeling tools dedicated to particular types of macromolecules (e.g., lipids, (228, 280) DNA, (475, 611) RNA, (612, 613) or carbohydrates (614, 615)) require integration, or better integration, with coarse-grained protein models and within well-defined multiscale modeling schemes.
Over the last decades, we have learned about the power of coarse-grained molecular modeling of proteins and their complexes, (19-32) in particular when combined with higher resolution models. (25, 37-40) The application of coarse-grained modeling in combination with all-atom refinement tools, bioinformatics and fragmentary experimental data already plays a crucial role in protein structure prediction. (48, 104, 379) Similar progress is now being made in predicting the structure of protein complexes. (52, 55) The efficient multiscale modeling of long time biomolecular dynamics (50, 51) is the next challenge. A growing number of real-time measurements of how cell components (proteins, nucleic acids, lipids, and others) perform their functions is expected to be a further stimulus to construct new coarse-grained modeling tools, including whole-cell models. (54, 55, 423)
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Biographies
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Sebastian Kmiecik
Sebastian Kmiecik received his Ph.D. in 2007 from the Faculty of Chemistry, University of Warsaw, Poland. In 2007, he joined a biotechnology startup company, Selvita, where as a Project Manager and later the Head of Modeling, he helped to develop the company’s R&D programs and services. In 2010, he again joined the Faculty of Chemistry, University of Warsaw. Since that time his academic work has been focused on the development of multiscale methods for protein modeling and their application in studies of protein function. In 2015, he received a D.Sc. degree.
Dominik Gront
Dominik Gront received his Ph.D. in 2006 from the Faculty of Chemistry, University of Warsaw. After postdoctoral training at the University of Virginia, Charlottesville, VA and University of Washington, Seattle, WA, he rejoined the Faculty of Chemistry, University of Warsaw. In his research he focuses on novel coarse-grained methods for biomacromolecular modeling. He actively develops Rosetta and BioShell software packages.
Michal Kolinski
Michal Kolinski received his Ph.D. in 2010 from the Institute of Biochemistry and Biophysics, Polish Academy of Sciences in Warsaw. After that, he became a postdoc in the Laboratory of Medicinal Chemistry and Neuroengineering at the Medical University of Lublin, Poland. In 2011, he joined Bioinformatics Laboratory in the Mossakowski Medical Research Centre, Polish Academy of Sciences in Warsaw. Currently he is an Assistant Professor and his research interests include the application of computational methods for prediction of membrane protein structure, function, and ligand binding.
Lukasz Wieteska
Lukasz Wieteska received his Master’s degree from the Faculty of Pharmacy, Medical University of Lodz in 2009 and Bachelor’s degree from the Faculty of Mathematics and Computer Science, University of Lodz in 2011. In 2014, he defended his Ph.D. thesis at the Department of Medical Biochemistry, Medical University of Lodz. Currently he is a Postdoc in the Laboratory of Theory of Biopolymers, University of Warsaw. His scientific interests include application of computational methods in biophysical studies of proteins and protein modifications relevant to medicine and biotechnology.
Aleksandra Elzbieta Dawid
Aleksandra Dawid graduated from the Faculty of Chemistry, University of Warsaw, Poland in 2014. She is now a Ph.D. student at the Department of Chemistry, working in the Laboratory of Theory of Biopolymers on the development of knowledge-based statistical force fields for simulations of large biomacromolecular systems. She is also developing a new low resolution coarse-grained model for the long time multiscale modeling of proteins.
Andrzej Kolinski
Andrzej Kolinski studied chemistry at the University of Warsaw and completed his Ph.D. thesis on the computer modeling of polymerization processes at the Department of Chemistry, University of Warsaw in 1979. Then he was directly appointed by the same department first as an assistant professor and then later as a full professor. Between 1985 and 2005 he was also part time appointed at various research institutions in the U.S.A., mostly at the Department of Molecular Biology, Scripps Research Institute (San Diego, California), but also for shorter periods at the Department of Chemistry, Washington University (Saint Louis), at Donald Danforth Plant Science Center (Saint Louis), and at the Center of Excellence in Bioinformatics (Buffalo). Since 1998 he is the head of the Laboratory of Theory of Biopolymers at the Faculty of Chemistry, University of Warsaw. His current research interests include structural bioinformatics, development of a new modeling tool for simulations of complex biomacromolecules, and computer-aided rational drug design.
Acknowledgment
ARTICLE SECTIONS
S.K., D.G., L.W., A.D., and A.K. acknowledge support from the National Science Center (NCN, Poland) Grant [MAESTRO2014/14/A/ST6/00088]. M.K. acknowledges support from the Polish Ministry of Science and Higher Education Grant [IP2012 016372].
References
ARTICLE SECTIONS
This article references 615 other publications.
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5Chouard, T. Structural biology: Breaking the protein rules Nature 2011, 471, 151– 153 DOI: 10.1038/471151aGoogle Scholar5https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXivFyru7o%253D&md5=8bd1ecd40efc6da170010f305f15e7b2Structural biology: Breaking the protein rulesChouard, TanguyNature (London, United Kingdom) (2011), 471 (7337), 151-153CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)A review. A central tenet in mol. biol. states that the function of a protein depends on its fully folded 3-dimensional (3D) structure. In the new view, protein segments can function when transiently or durably disordered. In the conventional "lock-and-key" model, an enzyme protein folds up immediately into a unique 3D shape (the "key") and its shape perfectly matches and allows it to bind its substrate (the "lock"). In the partially disordered gene-regulatory protein, CREB, the disordered part uses the lock to mold itself into the shape of the key when the two meet, rather than folding beforehand. In the intrinsically disordered signaling protein, Sic1, the protein remains disordered in its bound state and each of 6 phosphate groups occupies the binding site in turn; the protein thus is a mix of different conformations shifting around in const. dynamic equil. Only when 6 phosphates are present is the av. electrostatic field that surrounds the protein strong enough for its binding partner Cdc4 to hold Sic1 close and force-feed it into the cell's disposal machinery. Thus, little by little a fundamentally new picture of the relations between protein sequence, structure, and function is emerging: a continuum running from the most rigid "lock-and-key" enzymes and mol. machines at one extreme through to durably unstructured "spaghetti" such as Sic1 at the other, and spanning all degrees of structural ambiguity in between.
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6Henzler-Wildman, K.; Kern, D. Dynamic personalities of proteins Nature 2007, 450, 964– 972 DOI: 10.1038/nature06522Google Scholar6https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhsVaqtr%252FL&md5=27ca36106100f487683d714de5335dc2Dynamic personalities of proteinsHenzler-Wildman, Katherine; Kern, DorotheeNature (London, United Kingdom) (2007), 450 (7172), 964-972CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)A review. Because proteins are central to cellular function, researchers have sought to uncover the secrets of how these complex macromols. execute such a fascinating variety of functions. Although static structures are known for many proteins, the functions of proteins are governed ultimately by their dynamic character (or 'personality'). The dream is to 'watch' proteins in action in real time at at. resoln. This requires the addn. of a fourth dimension, time, to structural biol. so that the positions in space and time of all atoms in a protein can be described in detail.
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7Schmidt, T.; Bergner, A.; Schwede, T. Modelling three-dimensional protein structures for applications in drug design Drug Discovery Today 2014, 19, 890– 897 DOI: 10.1016/j.drudis.2013.10.027Google Scholar7https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVKit77P&md5=a3b8cf16a54666c85194c2c5f4817840Modelling three-dimensional protein structures for applications in drug designSchmidt, Tobias; Bergner, Andreas; Schwede, TorstenDrug Discovery Today (2014), 19 (7), 890-897CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)A review. A structural perspective of drug target and anti-target proteins, and their mol. interactions with biol. active mols., largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimization. In the absence of exptl. 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homol. modeling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estn. deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately dets. its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modeling practice are also provided.
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8Schwede, T.; Sali, A.; Honig, B.; Levitt, M.; Berman, H. M.; Jones, D.; Brenner, S. E.; Burley, S. K.; Das, R.; Dokholyan, N. V. Outcome of a workshop on applications of protein models in biomedical research Structure 2009, 17, 151– 159 DOI: 10.1016/j.str.2008.12.014Google ScholarThere is no corresponding record for this reference.
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9Khoury, G. A.; Smadbeck, J.; Kieslich, C. A.; Floudas, C. A. Protein folding and de novo protein design for biotechnological applications Trends Biotechnol. 2014, 32, 99– 109 DOI: 10.1016/j.tibtech.2013.10.008Google Scholar9https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVWgu7vI&md5=52462613a2b3158ed8b7192c5b4670faProtein folding and de novo protein design for biotechnological applicationsKhoury, George A.; Smadbeck, James; Kieslich, Chris A.; Floudas, Christodoulos A.Trends in Biotechnology (2014), 32 (2), 99-109CODEN: TRBIDM; ISSN:0167-7799. (Elsevier Ltd.)A review. In the postgenomic era, the medical/biol. fields are advancing faster than ever. However, before the power of full-genome sequencing can be fully realized, the connection between amino acid sequence and protein structure, known as the protein folding problem, needs to be elucidated. The protein folding problem remains elusive, with significant difficulties still arising when modeling amino acid sequences lacking an identifiable template. Understanding protein folding will allow for unforeseen advances in protein design; often referred to as the inverse protein folding problem. Despite challenges in protein folding, de novo protein design has recently demonstrated significant success via computational techniques. We review advances and challenges in protein structure prediction and de novo protein design, and highlight their interplay in successful biotechnol. applications.
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10Lounnas, V.; Ritschel, T.; Kelder, J.; McGuire, R.; Bywater, R. P.; Foloppe, N. Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery Comput. Struct. Biotechnol. J. 2013, 5, e201302011 DOI: 10.5936/csbj.201302011Google ScholarThere is no corresponding record for this reference.
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11Ferreira, L. G.; Dos Santos, R. N.; Oliva, G.; Andricopulo, A. D. Molecular docking and structure-based drug design strategies Molecules 2015, 20, 13384– 13421 DOI: 10.3390/molecules200713384Google Scholar11https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXht1OjtLzJ&md5=b5f70b90e45098d0f0252a2926f9671eMolecular docking and structure-based drug design strategiesFerreira, Leonardo G.; dos Santos, Ricardo N.; Oliva, Glaucius; Andricopulo, Adriano D.Molecules (2015), 20 (7), 13384-13421CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)Pharmaceutical research has successfully incorporated a wealth of mol. modeling methods, within a variety of drug discovery programs, to study complex biol. and chem. systems. The integration of computational and exptl. strategies has been of great value in the identification and development of novel promising compds. Broadly used in modern drug design, mol. docking methods explore the ligand conformations adopted within the binding sites of macromol. targets. This approach also ests. the ligand-receptor binding free energy by evaluating crit. phenomena involved in the intermol. recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current mol. docking strategies used in drug discovery and medicinal chem., exploring the advances in the field and the role played by the integration of structure- and ligand-based methods.
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12Wang, T.; Wu, M. B.; Zhang, R. H.; Chen, Z. J.; Hua, C.; Lin, J. P.; Yang, L. R. Advances in Computational Structure-Based Drug Design and Application in Drug Discovery Curr. Top. Med. Chem. 2015, 16, 901– 916 DOI: 10.2174/1568026615666150825142002Google ScholarThere is no corresponding record for this reference.
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13Ozboyaci, M.; Kokh, D. B.; Corni, S.; Wade, R. C. Modeling and simulation of protein-surface interactions: achievements and challenges Q. Rev. Biophys. 2016, 49, e4 DOI: 10.1017/S0033583515000256Google Scholar13https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitVSrsbk%253D&md5=a99ab8677ef801d85ff7e2e0fa222528Modeling and simulation of protein-surface interactions: achievements and challengesOzboyaci, Musa; Kokh, Daria B.; Corni, Stefano; Wade, Rebecca C.Quarterly Reviews of Biophysics (2016), 49 (), e4/1-e4/87CODEN: QURBAW; ISSN:0033-5835. (Cambridge University Press)Understanding protein-inorg. surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnol. and nanomedicine. Although a significant amt. of exptl. research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomols. and inorg. surfaces are still unclear. Theor. modeling and simulations provide complementary approaches for exptl. studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodn. and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the phys. properties and interactions of material surfaces and biol. mols. differ. In particular, FF and water models designed for use in biomol. simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, resp., rendering the use of multi-scale approaches unavoidable. Further, changes in the at. structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed mols., can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theor. and computational methods in achieving accurate descriptions of the phys., chem. and mech. properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom mol. mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calcns. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.
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14Vendruscolo, M.; Dobson, C. M. Protein dynamics: Moore’s law in molecular biology Curr. Biol. 2011, 21, R68– 70 DOI: 10.1016/j.cub.2010.11.062Google Scholar14https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtVaqsrY%253D&md5=ee19a9e55e87dd77b8acc084bdff9194Protein Dynamics: Moore's Law in Molecular BiologyVendruscolo, Michele; Dobson, Christopher M.Current Biology (2011), 21 (2), R68-R70CODEN: CUBLE2; ISSN:0960-9822. (Cell Press)A review. The millisecond barrier has been broken in mol. dynamics simulations of proteins. Such simulations are increasingly revealing the inner workings of biol. systems by generating at.-level descriptions of their behavior that make testable predictions about key mol. processes.
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15Shaw, D. E.; Grossman, J. P.; Bank, J. A.; Batson, B.; Butts, J. A.; Chao, J. C.; Deneroff, M. M.; Dror, R. O.; Even, A.; Fenton, C. H. (2014) Anton 2: raising the bar for performance and programmability in a special-purpose molecular dynamics supercomputer. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis; IEEE Press: New Orleans; pp 41– 53.Google ScholarThere is no corresponding record for this reference.
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16Lindorff-Larsen, K.; Piana, S.; Dror, R. O.; Shaw, D. E. How fast-folding proteins fold Science 2011, 334, 517– 520 DOI: 10.1126/science.1208351Google Scholar16https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtlKjtrnL&md5=5a4eefa5b9d07b03819c491c105de75cHow fast-folding proteins foldLindorff-Larsen, Kresten; Piana, Stefano; Dror, Ron O.; Shaw, David E.Science (Washington, DC, United States) (2011), 334 (6055), 517-520CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)An outstanding challenge in the field of mol. biol. has been to understand the process by which proteins fold into their characteristic three-dimensional structures. Here, we report the results of at.-level mol. dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set of common principles underlying the folding of 12 structurally diverse proteins. In simulations conducted with a single physics-based energy function, the proteins, representing all three major structural classes, spontaneously and repeatedly fold to their exptl. detd. native structures. Early in the folding process, the protein backbone adopts a native-like topol. while certain secondary structure elements and a small no. of nonlocal contacts form. In most cases, folding follows a single dominant route in which elements of the native structure appear in an order highly correlated with their propensity to form in the unfolded state.
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17Piana, S.; Klepeis, J. L.; Shaw, D. E. Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations Curr. Opin. Struct. Biol. 2014, 24, 98– 105 DOI: 10.1016/j.sbi.2013.12.006Google Scholar17https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtVahurg%253D&md5=b15e49d29a51a4715d4e442d8e59d8e9Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulationsPiana, Stefano; Klepeis, John L.; Shaw, David E.Current Opinion in Structural Biology (2014), 24 (), 98-105CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Advances in computer hardware, software and algorithms have now made it possible to run atomistically detailed, physics-based mol. dynamics simulations of sufficient length to observe multiple instances of protein folding and unfolding within a single equil. trajectory. Although such studies have already begun to provide new insights into the process of protein folding, realizing the full potential of this approach will depend not only on simulation speed, but on the accuracy of the phys. models ('force fields') on which such simulations are based. While exptl. data are not available for comparison with all of the salient characteristics observable in long protein-folding simulations, we examine here the extent to which current force fields reproduce (and fail to reproduce) certain relevant properties for which such comparisons are possible.
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18Piana, S.; Lindorff-Larsen, K.; Shaw, D. E. Atomistic description of the folding of a dimeric protein J. Phys. Chem. B 2013, 117, 12935– 12942 DOI: 10.1021/jp4020993Google Scholar18https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFKrs7bJ&md5=ea6e10e1468aba7a4675dc309c613aa9Atomistic Description of the Folding of a Dimeric ProteinPiana, Stefano; Lindorff-Larsen, Kresten; Shaw, David E.Journal of Physical Chemistry B (2013), 117 (42), 12935-12942CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Equil. mol. dynamics simulations are increasingly being used to describe the folding of individual proteins and protein domains at an at. level of detail. Isolated protein domains, however, are rarely obsd. in vivo, where multidomain proteins and multimeric assemblies are far more common. It is clear that the folding of such proteins is often inextricably coupled with the process of dimerization; indeed, many protein monomers and protein domains are not stable in isolation, and fold to their native structures only when stabilized by interactions with other members of a protein complex. Here, we use equil. mol. dynamics simulations with an aggregate simulation length of 4 ms to elucidate key aspects of the folding mechanism, and of the assocd. free-energy surface, of the Top7-CFr dimer, a 114-amino-acid protein homodimer with a mixed α/β structure. In these simulations, we obsd. a no. of folding and unfolding events. Each folding event was characterized by the assembly of two unfolded Top7-CFr monomers to form a stable, folded dimer. We found that the isolated monomer is unstable but that, early in the folding pathway, nascent native structure is stabilized by contacts between the two monomer subunits. These contacts are in some cases native, as in an induced-folding model, and in other cases non-native, as in a fly-casting mechanism. Occasionally, folding by conformational selection, in which both subunits form independently before dimerization, was also obsd. Folding then proceeds through the sequential addn. of strands to the protein β sheet. Although the long-time-scale relaxation of the folding process can be well described by a single exponential, these simulations reveal the presence of a no. of kinetic traps, characterized by structures in which individual strands are added in an incorrect order.
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19Kolinski, A.; Skolnick, J. Reduced models of proteins and their applications Polymer 2004, 45, 511– 524 DOI: 10.1016/j.polymer.2003.10.064Google Scholar19https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXpvFGiur4%253D&md5=09479fe5bfdf8d30f3b849bbc876e3b0Reduced models of proteins and their applicationsKolinski, Andrzej; Skolnick, JeffreyPolymer (2004), 45 (2), 511-524CODEN: POLMAG; ISSN:0032-3861. (Elsevier Science Ltd.)A review. Reduced computer modeling of proteins now has a history of about 30 yr. In spite of the enormous increase in computing abilities, reduced models are still very important tools for theor. studies of protein structure, dynamics and thermodn. Very simple, highly idealized lattice (and recently also off-lattice) models could be studied in great detail, providing valuable insight into the most general factors governing structure stability, folding kinetics and interactions responsible for characteristic two-state behavior near the folding temp. More complex models now enable modeling of real proteins on the level of low to moderate resoln., allowing the authors to address more detailed questions. Ab initio protein structure predictions, still being far from a routine task, have become feasible. When supported by evolutionary information from multiple sequence alignments and potential local and/or global structural similarity to known structures, reduced modeling opens up new areas of comparative modeling, thereby complementing contemporary structural genomics.
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20Tozzini, V. Coarse-grained models for proteins Curr. Opin. Struct. Biol. 2005, 15, 144– 150 DOI: 10.1016/j.sbi.2005.02.005Google Scholar20https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjtlaltLk%253D&md5=edd46ef4ea767f1084991e8062dd4043Coarse-grained models for proteinsTozzini, ValentinaCurrent Opinion in Structural Biology (2005), 15 (2), 144-150CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Coarse-grained models for proteins and biomol. aggregates have recently enjoyed renewed interest. Coarse-grained representations combined with enhanced computer power currently allow the simulation of systems of biol. relevant size (submicrometric) and timescale (microsecond or millisecond). Although these techniques still cannot be considered as predictive as all-atom simulations, noticeable advances have recently been achieved, mainly concerning the use of more rigorous parameterization techniques and novel algorithms for sampling configurational space. Moreover, the simulation size scales and timescales coincide with those that can be reached with the most advanced spectroscopic techniques, making it possible to directly compare simulation and expt.
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21Scheraga, H. A.; Khalili, M.; Liwo, A. Protein-folding dynamics: overview of molecular simulation techniques Annu. Rev. Phys. Chem. 2007, 58, 57– 83 DOI: 10.1146/annurev.physchem.58.032806.104614Google Scholar21https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXlslSisbc%253D&md5=22f6b8a0c6be71dbc5235e9aa9af9919Protein-folding dynamics: Overview of molecular simulation techniquesScheraga, Harold A.; Khalili, Mey; Liwo, AdamAnnual Review of Physical Chemistry (2007), 58 (), 57-83CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Mol. dynamics (MD) simulation is an invaluable tool with which to study protein folding in silico. Although just a few years ago the dynamic behavior of a protein mol. could be simulated only in the neighborhood of the exptl. conformation (or protein unfolding could be simulated at high temp.), the advent of distributed computing, new techniques such as replica-exchange MD, new approaches (based on, e.g., the stochastic difference equation), and physics-based reduced models of proteins now make it possible to study protein folding pathways from completely unfolded structures. Here, the authors present algorithms for MD simulations and their extensions and applications to protein folding studies, using all-atom models with explicit and implicit solvent as well as reduced models of polypeptide chains.
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22Clementi, C. Coarse-grained models of protein folding: toy models or predictive tools? Curr. Opin. Struct. Biol. 2008, 18, 10– 15 DOI: 10.1016/j.sbi.2007.10.005Google Scholar22https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVGitr0%253D&md5=477bb414c5c4e5409ce7c1d67b6a9a2bCoarse-grained models of protein folding: toy models or predictive tools?Clementi, CeciliaCurrent Opinion in Structural Biology (2008), 18 (1), 10-15CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. Coarse-grained models are emerging as a practical alternative to all-atom simulations for the characterization of protein folding mechanisms over long time scales. While a decade ago minimalist toy models were mainly designed to test general hypotheses on the principles regulating protein folding, the latest coarse-grained models are increasingly realistic and can be used to characterize quant. the detailed folding mechanism of specific proteins. The ability of such models to reproduce the essential features of folding dynamics suggests that each single at. degree of freedom is not by itself particularly relevant to folding and supports a statistical mech. approach to characterize folding transitions. When combined with more refined models and with exptl. studies, the systematic investigation of protein systems and complexes using coarse-grained models can advance our theor. understanding of the actual organizing principles that emerge from the complex network of interactions among protein at. constituents.
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23Espinoza-Fonseca, L. M. Thermodynamic aspects of coupled binding and folding of an intrinsically disordered protein: a computational alanine scanning study Biochemistry 2009, 48, 11332– 11334 DOI: 10.1021/bi901705zGoogle ScholarThere is no corresponding record for this reference.
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24Rader, A. J. Coarse-grained models: getting more with less Curr. Opin. Pharmacol. 2010, 10, 753– 759 DOI: 10.1016/j.coph.2010.09.003Google Scholar24https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVals7vO&md5=b28f9aad085e660ba636f6026cfc8e18Coarse-grained models: getting more with lessRader, A. J.Current Opinion in Pharmacology (2010), 10 (6), 753-759CODEN: COPUBK; ISSN:1471-4892. (Elsevier Ltd.)A review. There has recently been a proliferation of simplified, coarse-grained models to study aspects of biomol. dynamics, binding, assembly and folding. Despite differences in construction these various coarse-grained models share a common underlying desire to identify the minimal set of variables required to realistically describe the essence of these mols. Recent results emphasizing common and distinctive features are highlighted. For someone not involved in developing such models it is a daunting task to decide which, if any, coarse-grained model would be appropriate for a given system. Although this decision ultimately depends upon what kinds of questions one is probing, suggestions about reaching a conclusion are provided.
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25Kamerlin, S. C.; Vicatos, S.; Dryga, A.; Warshel, A. Coarse-grained (multiscale) simulations in studies of biophysical and chemical systems Annu. Rev. Phys. Chem. 2011, 62, 41– 64 DOI: 10.1146/annurev-physchem-032210-103335Google Scholar25https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVWmsbY%253D&md5=b209237e5d504e7ed1dfd820fc410615Coarse-grained (multiscale) simulations in studies of biophysical and chemical systemsKamerlin, Shina C. L.; Vicatos, Spyridon; Dryga, Anatoly; Warshel, AriehAnnual Review of Physical Chemistry (2011), 62 (), 41-64CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Recent years have witnessed an explosion in computational power, leading to attempts to model ever more complex systems. Nevertheless, there remain cases for which the use of brute-force computer simulations is clearly not the soln. In such cases, great benefit can be obtained from the use of phys. sound simplifications. The introduction of such coarse graining can be traced back to the early usage of a simplified model in studies of proteins. Since then, the field has progressed tremendously. In this review, we cover both key developments in the field and potential future directions. Addnl., particular emphasis is given to two general approaches, namely the renormalization and ref. potential approaches, which allow one to move back and forth between the coarse-grained (CG) and full models, as these approaches provide the foundation for CG modeling of complex systems.
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26Wu, C.; Shea, J. E. Coarse-grained models for protein aggregation Curr. Opin. Struct. Biol. 2011, 21, 209– 220 DOI: 10.1016/j.sbi.2011.02.002Google Scholar26https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkt1Kis7o%253D&md5=679de0734e82b4a09ad11ea3c9661eebCoarse-grained models for protein aggregationWu, Chun; Shea, Joan-EmmaCurrent Opinion in Structural Biology (2011), 21 (2), 209-220CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The aggregation of sol. proteins into fibrillar species is a complex process that spans many lengths and time scales, and that involves the formation of numerous on-pathway and off-pathway intermediate species. Despite this complexity, several elements underlying the aggregation process appear to be universal. The kinetics typically follow a nucleation-growth process, and proteins with very different sequences aggregate to form similar fibril structures, populating intermediates with sufficient structural similarity to bind to a common antibody. Here, the authors focus on a computational approach that exploits the common features of aggregation to simplify or 'coarse-grain' the representation of the protein. The authors highlight recent developments in coarse-grained modeling and illustrate how these models have been able to shed new light into the mechanisms of protein aggregation and the nature of aggregation intermediates. The roles of aggregation-prone conformations in the monomeric state and the influence of inherent β-sheet and aggregation propensities in modulating aggregation pathways are discussed.
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27Takada, S. Coarse-grained molecular simulations of large biomolecules Curr. Opin. Struct. Biol. 2012, 22, 130– 137 DOI: 10.1016/j.sbi.2012.01.010Google Scholar27https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XjtFShsrY%253D&md5=bb72fc85efeeaf49eb9090bd3e66ebc4Coarse-grained molecular simulations of large biomoleculesTakada, ShojiCurrent Opinion in Structural Biology (2012), 22 (2), 130-137CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Recently, we saw a dramatic increase in the no. of researches that rely on coarse-grained (CG) simulations for large biomols. Here, first, we briefly describe recently developed and used CG models for proteins and nucleic acids. Balance between structure-based and physico-chem. terms is a key issue. We also discuss the multiscale algorithms used to derive CG parameters. Next, we comment on the dynamics used in CG simulations with an emphasis on the importance of hydrodynamic interactions. We then discuss the pros and cons of CG simulations. Finally, we overview recent exciting applications of CG simulations. Publicly available tools and software for CG simulations are also summarized.
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28Saunders, M. G.; Voth, G. A. Coarse-graining methods for computational biology Annu. Rev. Biophys. 2013, 42, 73– 93 DOI: 10.1146/annurev-biophys-083012-130348Google Scholar28https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFGrs7bN&md5=e1a9f1f7a2854af4d391d66a85386da9Coarse-graining methods for computational biologySaunders, Marissa G.; Voth, Gregory A.Annual Review of Biophysics (2013), 42 (), 73-93CODEN: ARBNCV; ISSN:1936-122X. (Annual Reviews)A review. Connecting the mol. world to biol. requires understanding how mol.-scale dynamics propagate upward in scale to define the function of biol. structures. To address this challenge, multiscale approaches, including coarse-graining methods, become necessary. We discuss here the theor. underpinnings and history of coarse-graining and summarize the state of the field, organizing key methodologies based on an emerging paradigm for multiscale theory and modeling of biomol. systems. This framework involves an integrated, iterative approach to couple information from different scales. The primary steps, which coincide with key areas of method development, include developing first-pass coarse-grained models guided by exptl. results, performing numerous large-scale coarse-grained simulations, identifying important interactions that drive emergent behaviors, and finally reconnecting to the mol. scale by performing all-atom mol. dynamics simulations guided by the coarse-grained results. The coarse-grained modeling can then be extended and refined, with the entire loop repeated iteratively if necessary.
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29Baaden, M.; Marrink, S. J. Coarse-grain modelling of protein-protein interactions Curr. Opin. Struct. Biol. 2013, 23, 878– 886 DOI: 10.1016/j.sbi.2013.09.004Google Scholar29https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs12ltLzE&md5=92149c04b75e0f627a47ae3219e1bec3Coarse-grain modelling of protein-protein interactionsBaaden, Marc; Marrink, Siewert J.Current Opinion in Structural Biology (2013), 23 (6), 878-886CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)Here, we review recent advances towards the modeling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behavior. PPI models of sol. proteins and membrane proteins are sep. described, but we note the parallel development that is present in both research fields with three important themes: firstly, combining CG modeling with knowledge-based approaches to predict and refine protein-protein complexes; secondly, using physics-based CG models for de novo prediction of protein-protein complexes; and thirdly modeling of large scale protein aggregates.
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30Kar, P.; Feig, M. Recent advances in transferable coarse-grained modeling of proteins Adv. Protein Chem. Struct. Biol. 2014, 96, 143– 180 DOI: 10.1016/bs.apcsb.2014.06.005Google Scholar30https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xht1yrtrfF&md5=dce9f8dac24bdf5addc50af8b0f045f6Recent advances in transferable coarse-grained modeling of proteinsKar, Parimal; Feig, MichaelAdvances in Protein Chemistry and Structural Biology (2014), 96 (Biomolecular Modelling and Simulations), 143-180CODEN: APCSG7; ISSN:1876-1623. (Elsevier Ltd.)Computer simulations are indispensable tools for studying the structure and dynamics of biol. macromols. Biochem. processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biol. systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chem. specificity. We restrict ourselves to CG models of sol. proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.
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31Morriss-Andrews, A.; Shea, J. E. Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained Models J. Phys. Chem. Lett. 2014, 5, 1899– 1908 DOI: 10.1021/jz5006847Google Scholar31https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXnvV2itL4%253D&md5=3ca8def9b53dd013ba5dd92005f3a166Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained ModelsMorriss-Andrews, Alex; Shea, Joan-EmmaJournal of Physical Chemistry Letters (2014), 5 (11), 1899-1908CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)A review. This Perspective highlights recent computational approaches to protein aggregation, from coarse-grained models to atomistic simulations, using the islet amyloid polypeptide (IAPP) as a case study. We discuss salient open questions where simulations can make an impact, discuss the successes and challenges met by simulations, and explore new directions.
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32Ingolfsson, H. I.; Lopez, C. A.; Uusitalo, J. J.; de Jong, D. H.; Gopal, S. M.; Periole, X.; Marrink, S. J. The power of coarse graining in biomolecular simulations Wiley Interdiscip. Rev. Comput. Mol. Sci. 2014, 4, 225– 248 DOI: 10.1002/wcms.1169Google Scholar32https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtl2isLo%253D&md5=42af65cc906e785223ce08e4284f1c41The power of coarse graining in biomolecular simulationsIngolfsson, Helgi I.; Lopez, Cesar A.; Uusitalo, Jaakko J.; de Jong, Djurre H.; Gopal, Srinivasa M.; Periole, Xavier; Marrink, Siewert J.Wiley Interdisciplinary Reviews: Computational Molecular Science (2014), 4 (3), 225-248CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)A review. Computational modeling of biol. systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resoln., coarse grained (CG), beads has opened the way to simulate large-scale biomol. processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomol. applications to date, focusing on models that retain chem. specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.
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33Voth, G. A. Coarse-Graining of Condensed Phase and Biomolecular Systems; CRC Press: Boca Raton, FL, 2008; p 456.Google ScholarThere is no corresponding record for this reference.
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34Levitt, M.; Warshel, A. Computer-Simulation of Protein Folding Nature 1975, 253, 694– 698 DOI: 10.1038/253694a0Google Scholar34https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE2MXkt1eksbw%253D&md5=fb6bbeb114d0c1a4d95d12a082e01ccfComputer simulation of protein foldingLevitt, Michael; Warshel, AriehNature (London, United Kingdom) (1975), 253 (5494), 694-8CODEN: NATUAS; ISSN:0028-0836.Computer simulation of protein folding was obtained by combining a simple representation of protein conformation, which averaged over the fine details, with convergent energy minimization and normal mode thermalization. Under certain conditions, the procedure reproduced the correct overall folding of bovine pancreatic trypsin inhibitor.
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35Warshel, A.; Levitt, M. Theoretical Studies of Enzymic Reactions - Dielectric, Electrostatic and Steric Stabilization of Carbonium-Ion in Reaction of Lysozyme J. Mol. Biol. 1976, 103, 227– 249 DOI: 10.1016/0022-2836(76)90311-9Google Scholar35https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28XktFKhtr0%253D&md5=f34df33b5971b6b02bd03be95dcd7ba5Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozymeWarshel, A.; Levitt, M.Journal of Molecular Biology (1976), 103 (2), 227-49CODEN: JMOBAK; ISSN:0022-2836.A general method for detailed study of enzymic reactions is presented. The method considers the complete enzyme-substrate complex together with the surrounding solvent and evaluates all the different quantum mech. and classical energy factors that can affect the reaction pathway. These factors include the quantum mech. energies assocd. with bond cleavage and charge redistribution of the substrate and the classical energies of steric and electrostatic interactions between the substrate and the enzyme. The electrostatic polarization of the enzyme atoms and the orientation of the dipoles of the surrounding H2O mols. is simulated by a microscopic dielec. model. The solvation energy resulting from this polarization is considerable and must be included in any realistic calcn. of chem. reactions involving anything more than an isolated mol. in vacuo. Without it, acidic groups can never become ionized and the charge distribution on the substrate will not be reasonable. The same dielec. model can also be used to study the reaction of the substrate in soln. In this way the reaction in soln. can be compared with the enzymic reaction. The stability of the carbonium ion intermediate formed in the cleavage of a glycosidic bond by lysozyme was studied. Electrostatic stabilization is an important factor in increasing the rate of the reaction step that leads to the formation of the carbonium ion intermediate. Steric factors, such as the strain of the substrate on binding to lysozyme, do not seem to contribute significantly.
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36Levitt, M. Birth and future of multiscale modeling for macromolecular systems (Nobel Lecture) Angew. Chem., Int. Ed. 2014, 53, 10006– 10018 DOI: 10.1002/anie.201403691Google Scholar36https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtlWmtLzO&md5=a6b7d9a8ed3910b062df2741f501d33fBirth and Future of Multiscale Modeling for Macromolecular Systems (Nobel Lecture)Levitt, MichaelAngewandte Chemie, International Edition (2014), 53 (38), 10006-10018CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)Michael Levitt won the 2013 Nobel Prize in Chem. for the development of multiscale models for complex chem. systems.
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37Ayton, G. S.; Noid, W. G.; Voth, G. A. Multiscale modeling of biomolecular systems: in serial and in parallel Curr. Opin. Struct. Biol. 2007, 17, 192– 198 DOI: 10.1016/j.sbi.2007.03.004Google Scholar37https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXksFehtLc%253D&md5=5ab3d305cc8ce10d211e843644aa8548Multiscale modeling of biomolecular systems: in serial and in parallelAyton, Gary S.; Noid, Will G.; Voth, Gregory A.Current Opinion in Structural Biology (2007), 17 (2), 192-198CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Considerable progress has been recently achieved in the multiscale modeling of complex biol. processes. Multiscale models have now investigated the structure and dynamics of lipid membranes, proteins, peptides and DNA over length and time scales ranging from the at. to the macroscopic. Serial multiscale methods that parameterize low-resoln. coarse-grained models with data from high-resoln. models have studied long time or length scale phenomena that cannot be investigated with atomically detailed models. Parallel multiscale methods that directly couple high- and low-resoln. models have efficiently explored slow structural transitions and the importance of long-wavelength fluctuations for biol. mols. The success of such models relies upon new theories and methods for constructing accurate multiscale bridges that transfer information between models with different resolns.
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38Tozzini, V. Multiscale modeling of proteins Acc. Chem. Res. 2010, 43, 220– 230 DOI: 10.1021/ar9001476Google Scholar38https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtFynsL%252FO&md5=c1487ea533c3bdc3be610265ab715984Multiscale Modeling of ProteinsTozzini, ValentinaAccounts of Chemical Research (2010), 43 (2), 220-230CODEN: ACHRE4; ISSN:0001-4842. (American Chemical Society)A review. The activity within a living cell is based on a complex network of interactions among biomols., exchanging information and energy through biochem. processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addn., a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, the author first reviews the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnol. and cell biol. strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomol. systems was recently confirmed by the assignment of two of the Nobel prizes in 2008: in chem. for the discovery of GFP and in medicine for the discovery of HIV. Accordingly, these proteins were studied with essentially all of the available modeling techniques, making them ideal examples for studying the details of multiscale approaches in protein modeling.
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39Kolinski, A. Multiscale Approaches to Protein Modeling; Springer: New York, 2011; p 355.Google ScholarThere is no corresponding record for this reference.
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40Zhou, H. X. Theoretical frameworks for multiscale modeling and simulation Curr. Opin. Struct. Biol. 2014, 25, 67– 76 DOI: 10.1016/j.sbi.2014.01.004Google Scholar40https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXovFCisr4%253D&md5=b6339e2ddb338638b5544663d320fd27Theoretical frameworks for multiscale modeling and simulationZhou, Huan-XiangCurrent Opinion in Structural Biology (2014), 25 (), 67-76CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Biomol. systems have been modeled at a variety of scales, ranging from explicit treatment of electrons and nuclei to continuum description of bulk deformation or velocity. Many challenges of interfacing between scales have been overcome. Multiple models at different scales have been used to study the same system or calc. the same property (e.g., channel conductance). Accurate modeling of biochem. processes under in vivo conditions and the bridging of mol. and subcellular scales will likely soon become reality.
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41Sippl, M. J. Knowledge-based potentials for proteins Curr. Opin. Struct. Biol. 1995, 5, 229– 235 DOI: 10.1016/0959-440X(95)80081-6Google Scholar41https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXlvVOrtro%253D&md5=114c7ee36aafe322305dbd86786cdbf9Knowledge-based potentials for proteinsSippl, Manfred J.Current Opinion in Structural Biology (1995), 5 (2), 229-35CODEN: COSBEF; ISSN:0959-440X. (Current Biology)A review, with 56 refs. Knowledge-based potentials and energy functions are extd. from a no. of databases of known protein structures. Recent developments have shown that this type of potential is successful in many areas of protein structure research. Among these are quality assessment and error recognition of folds and the prediction of unknown structures by fold-recognition techniques.
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42Carlsen, M.; Koehl, P.; Rogen, P. On the importance of the distance measures used to train and test knowledge-based potentials for proteins PLoS One 2014, 9, e109335 DOI: 10.1371/journal.pone.0109335Google ScholarThere is no corresponding record for this reference.
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43Kolinski, A.; Skolnick, J. Lattice models of protein folding, dynamics, and thermodynamics; R. G. Landes: Austin, TX, 1996.Google ScholarThere is no corresponding record for this reference.
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44Mirny, L.; Shakhnovich, E. Protein folding theory: from lattice to all-atom models Annu. Rev. Biophys. Biomol. Struct. 2001, 30, 361– 396 DOI: 10.1146/annurev.biophys.30.1.361Google Scholar44https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXkvVaqtr0%253D&md5=b36105834ba0ea25e55fa4d57297052fProtein folding theory: from lattice to all-atom modelsMirny, Leonid; Shakhnovich, EugeneAnnual Review of Biophysics and Biomolecular Structure (2001), 30 (), 361-396CODEN: ABBSE4; ISSN:1056-8700. (Annual Reviews Inc.)A review with 122 refs. This review focuses on recent advances in understanding protein folding kinetics in the context of nucleation theory. We present basic concepts such as nucleation, folding nucleus, and transition state ensemble and then discuss recent advances and challenges in theor. understanding of several key aspects of protein folding kinetics. We cover recent topol.-based approaches as well as evolutionary studies and mol. dynamics approaches to det. protein folding nucleus and analyze other aspects of folding kinetics. Finally, we briefly discuss successful all-atom Monte-Carlo simulations of protein folding and conclude with a brief outlook for the future.
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45Blaszczyk, M.; Gront, D.; Kmiecik, S.; Ziolkowska, K.; Panek, M.; Kolinski, A. In Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes: From Bioinformatics to Molecular Quantum Mechanics; Liwo, A., Ed.; Springer: Berlin, 2014.Google ScholarThere is no corresponding record for this reference.
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46Park, H.; DiMaio, F.; Baker, D. CASP11 refinement experiments with ROSETTA Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24862Google ScholarThere is no corresponding record for this reference.
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47Ovchinnikov, S.; Kim, D. E.; Wang, R. Y.; Liu, Y.; DiMaio, F.; Baker, D. Improved de novo structure prediction in CASP11 by incorporating Co-evolution information into rosetta Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24974Google ScholarThere is no corresponding record for this reference.
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48Yang, J. Y.; Yan, R. X.; Roy, A.; Xu, D.; Poisson, J.; Zhang, Y. The I-TASSER Suite: protein structure and function prediction Nat. Methods 2014, 12, 7– 8 DOI: 10.1038/nmeth.3213Google ScholarThere is no corresponding record for this reference.
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49Webb, B.; Lasker, K.; Velazquez-Muriel, J.; Schneidman-Duhovny, D.; Pellarin, R.; Bonomi, M.; Greenberg, C.; Raveh, B.; Tjioe, E.; Russel, D. Modeling of proteins and their assemblies with the Integrative Modeling Platform Methods Mol. Biol. 2014, 1091, 277– 295 DOI: 10.1007/978-1-62703-691-7_20Google Scholar49https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntFyisLo%253D&md5=a1ed8c1c96e5f5821574848c164f6546Modeling of Proteins and Their Assemblies with the Integrative Modeling PlatformWebb, Benjamin; Lasker, Keren; Velazquez-Muriel, Javier; Schneidman-Duhovny, Dina; Pellarin, Riccardo; Bonomi, Massimiliano; Greenberg, Charles; Raveh, Barak; Tjioe, Elina; Russel, Daniel; Sali, AndrejMethods in Molecular Biology (New York, NY, United States) (2014), 1091 (Structural Genomics), 277-295CODEN: MMBIED; ISSN:1940-6029. (Springer)To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resoln. structural characterization of these assemblies is frequently beyond the reach of current exptl. methods, such as X-ray crystallog., NMR spectroscopy, electron microscopy, footprinting, chem. crosslinking, FRET spectroscopy, small angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build models of the assembly structures that are consistent with all of the available datasets, and therefore more accurate, precise, and complete. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as well as possible. These generated models can then potentially inform about the precision and accuracy of structure detn., the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific use cases.
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50Sali, A.; Berman, H. M.; Schwede, T.; Trewhella, J.; Kleywegt, G.; Burley, S. K.; Markley, J.; Nakamura, H.; Adams, P.; Bonvin, A. M. Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop Structure 2015, 23, 1156– 1167 DOI: 10.1016/j.str.2015.05.013Google Scholar50https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtV2it7jI&md5=2d53115f311a1b407c3b4a77bb87f9c2Outcome of the First wwPDB Hybrid/Integrative Methods Task Force WorkshopSali, Andrej; Berman, Helen M.; Schwede, Torsten; Trewhella, Jill; Kleywegt, Gerard; Burley, Stephen K.; Markley, John; Nakamura, Haruki; Adams, Paul; Bonvin, Alexandre M. J. J.; Chiu, Wah; Dal Peraro, Matteo; Di Maio, Frank; Ferrin, Thomas E.; Grunewald, Kay; Gutmanas, Aleksandras; Henderson, Richard; Hummer, Gerhard; Iwasaki, Kenji; Johnson, Graham; Lawson, Catherine L.; Meiler, Jens; Marti-Renom, Marc A.; Montelione, Gaetano T.; Nilges, Michael; Nussinov, Ruth; Patwardhan, Ardan; Rappsilber, Juri; Read, Randy J.; Saibil, Helen; Schroder, Gunnar F.; Schwieters, Charles D.; Seidel, Claus A. M.; Svergun, Dmitri; Topf, Maya; Ulrich, Eldon L.; Velankar, Sameer; Westbrook, John D.Structure (Oxford, United Kingdom) (2015), 23 (7), 1156-1167CODEN: STRUE6; ISSN:0969-2126. (Elsevier Ltd.)Structures of biomol. systems are increasingly computed by integrative modeling that relies on varied types of exptl. data and theor. information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on Oct. 6 and 7, 2014. At the workshop, experts in various exptl. fields of structural biol., experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biol. How should integrative models be represented. How should the data and integrative models be validated. What data should be archived. How should the data and models be archived. What information should accompany the publication of integrative models.
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51Tamo, G. E.; Abriata, L. A.; Dal Peraro, M. The importance of dynamics in integrative modeling of supramolecular assemblies Curr. Opin. Struct. Biol. 2015, 31, 28– 34 DOI: 10.1016/j.sbi.2015.02.018Google Scholar51https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXktFOkt7w%253D&md5=c4a46436d0b6ded70f55833dc937e245The importance of dynamics in integrative modeling of supramolecular assembliesTamo, Giorgio E.; Abriata, Luciano A.; Dal Peraro, MatteoCurrent Opinion in Structural Biology (2015), 31 (), 28-34CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Revealing the atomistic architecture of supramol. complexes is a fundamental step toward a deeper understanding of cellular functioning. To date, this formidable task is facilitated by an emerging array of integrative modeling approaches that combine exptl. data from different sources. One major challenge these methods have to face is the treatment of the dynamic rearrangements of the individual subunits upon assembly. While this flexibility can be sampled at different levels, integrating native dynamic determinants with available exptl. inputs can provide an effective way to reveal the mol. recognition mechanisms at the basis of supramol. assembly.
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52Rodrigues, J. P.; Bonvin, A. M. Integrative computational modeling of protein interactions FEBS J. 2014, 281, 1988– 2003 DOI: 10.1111/febs.12771Google Scholar52https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmt1Wlsbo%253D&md5=40834335a6cf257d0509ac29728717f0Integrative computational modeling of protein interactionsRodrigues, Joao P. G. L. M.; Bonvin, Alexandre M. J. J.FEBS Journal (2014), 281 (8), 1988-2003CODEN: FJEOAC; ISSN:1742-464X. (Wiley-Blackwell)A review. Protein interactions define the homeostatic state of the cell. Our ability to understand these interactions and their role in both health and disease is tied to our knowledge of the 3D at. structure of the interacting partners and their complexes. Despite advances in exptl. method of structure detn., the majority of known protein interactions are still missing an at. structure. High-resoln. methods such as X-ray crystallog. and NMR spectroscopy struggle with the high-throughput demand, while low-resoln. techniques such as cryo-electron microscopy or small-angle X-ray scattering provide data that are too coarse. Computational structure prediction of protein complexes, or docking, was first developed to complement exptl. research and has since blossomed into an independent and lively field of research. Its most successful products are hybrid approaches that combine powerful algorithms with exptl. data from various sources to generate high-resoln. models of protein complexes. This minireview introduces the concept of docking and docking with the help of exptl. data, compares and contrasts the available integrative docking methods, and provides a guide for the exptl. researcher for what types of data and which particular software can be used to model a protein complex.
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53Reddy, T.; Sansom, M. S. Computational virology: From the inside out Biochim. Biophys. Acta, Biomembr. 2016, 1858, 1610 DOI: 10.1016/j.bbamem.2016.02.007Google Scholar53https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XisFWgsr8%253D&md5=570710fd4cb693d53bd54a99dd1345acComputational virology: From the inside outReddy, Tyler; Sansom, Mark S. P.Biochimica et Biophysica Acta, Biomembranes (2016), 1858 (7_Part_B), 1610-1618CODEN: BBBMBS; ISSN:0005-2736. (Elsevier B.V.)A review. Viruses typically pack their genetic material within a protein capsid. Enveloped viruses also have an outer membrane made up of a lipid bilayer and membrane-spanning glycoproteins. X-ray diffraction and cryoelectron microscopy provide high resoln. static views of viral structure. Mol. dynamics (MD) simulations may be used to provide dynamic insights into the structures of viruses and their components. There have been a no. of simulations of viral capsids and (in some cases) of the inner core of RNA or DNA packaged within them. These simulations have generally focussed on the structural integrity and stability of the capsid and/or on the influence of the nucleic acid core on capsid stability. More recently there have been a no. of simulation studies of enveloped viruses, including HIV-1, influenza A, and dengue virus. These have addressed the dynamic behavior of the capsid, the matrix, and/or of the outer envelope. Anal. of the dynamics of the lipid bilayer components of the envelopes of influenza A and of dengue virus reveals a degree of biophys. robustness, which may contribute to the stability of virus particles in different environments. Significant computational challenges need to be addressed to aid simulation of complex viruses and their membranes, including the need to integrate structural data from a range of sources to enable us to move towards simulations of intact virions. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.
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54Hyeon, C.; Thirumalai, D. Capturing the essence of folding and functions of biomolecules using coarse-grained models Nat. Commun. 2011, 2, 487 DOI: 10.1038/ncomms1481Google Scholar54https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3Mfms1Wrug%253D%253D&md5=3bedb98bb3c16049d69b19358577592cCapturing the essence of folding and functions of biomolecules using coarse-grained modelsHyeon Changbong; Thirumalai DNature communications (2011), 2 (), 487 ISSN:.The distances over which biological molecules and their complexes can function range from a few nanometres, in the case of folded structures, to millimetres, for example, during chromosome organization. Describing phenomena that cover such diverse length, and also time, scales requires models that capture the underlying physics for the particular length scale of interest. Theoretical ideas, in particular, concepts from polymer physics, have guided the development of coarse-grained models to study folding of DNA, RNA and proteins. More recently, such models and their variants have been applied to the functions of biological nanomachines. Simulations using coarse-grained models are now poised to address a wide range of problems in biology.
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55Spiga, E.; Degiacomi, M. T.; Dal Peraro, M. New strategies for integrative dynamic modeling of macromolecular assembly Adv. Protein Chem. Struct. Biol. 2014, 96, 77– 111 DOI: 10.1016/bs.apcsb.2014.06.008Google Scholar55https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MzktVGnsg%253D%253D&md5=e61fecd39b9e290080c05ba899117711New strategies for integrative dynamic modeling of macromolecular assemblySpiga Enrico; Degiacomi Matteo Thomas; Dal Peraro MatteoAdvances in protein chemistry and structural biology (2014), 96 (), 77-111 ISSN:.Data reporting on structure and dynamics of cellular constituents are growing with increasing pace enabling, as never before, the understanding of fine mechanistic aspects of biological systems and providing the possibility to affect them in controlled ways. Nonetheless, experimental techniques do not yet allow for an arbitrary level of resolution on cellular processes in situ. By consistently integrating a variety of diverse experimental data, molecular modeling is optimally poised to enhance to near-atomistic resolution our understanding of molecular recognition in large assemblies. Within this integrative modeling context, we briefly review in this chapter the recent progresses of molecular simulations at the atomistic and coarse-grained level of resolution to explore protein-protein interactions. In particular, we discuss our recent contributions in this field, which aim at providing a robust bridge between novel optimization algorithms and multiscale molecular simulations for a consistent integration of experimental inputs. We expect that, with the ever-growing sampling ability of molecular simulations and the tireless progress of experimental methods, the impact of such dynamic-based approach could only be more effective with time, contributing to provide detailed description of cellular organization.
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56Levinthal, C. Are There Pathways for Protein Folding J. Chim. Phys. Pcb. 1968, 65, 44Google ScholarThere is no corresponding record for this reference.
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57Levitt, M. A simplified representation of protein conformations for rapid simulation of protein folding J. Mol. Biol. 1976, 104, 59– 107 DOI: 10.1016/0022-2836(76)90004-8Google Scholar57https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28XksFygtrY%253D&md5=cb52d597eedeac8aeade3c9263c103e2A simplified representation of protein conformations for rapid simulation of protein foldingLevitt, MichaelJournal of Molecular Biology (1976), 104 (1), 59-107CODEN: JMOBAK; ISSN:0022-2836.A new and highly simplified treatment of protein conformations is introduced. The representation of peptide renaturation is given in some detail. The concept of time-averaged forces are used to simplify conformational energy calcns. on globular proteins. A detailed description is given of the simplified mol. geometry, the parameterization of suitable force fields, the best energy minimization procedure, and the techniques for escaping from local minima. Extensive tests of the method on the native conformation of pancreatic trypsin inhibitor showed that the simplifications work well in representing the stable native conformation of this globular protein. Further tests show that simulated folding of pancreatic trypsin inhibitor from open chain conformations gives compact calcd. conformations that have many features in common with the actual native conformation. Folding simulations are done under a variety of conditions and the relevance of such calcns. to the actual in vitro folding process is discussed at some length. These same techniques have many potential applications including enzyme-substrate binding, changes in protein tertiary and quaternary structure, and protein-protein interactions.
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58Hagler, A. T.; Honig, B. On the formation of protein tertiary structure on a computer Proc. Natl. Acad. Sci. U. S. A. 1978, 75, 554– 558 DOI: 10.1073/pnas.75.2.554Google ScholarThere is no corresponding record for this reference.
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59Wilson, C.; Doniach, S. A computer model to dynamically simulate protein folding: studies with crambin Proteins: Struct., Funct., Genet. 1989, 6, 193– 209 DOI: 10.1002/prot.340060208Google ScholarThere is no corresponding record for this reference.
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60Crippen, G. M.; Ponnuswamy, P. K. Determination of an empirical energy function for protein conformational analysis by energy embedding J. Comput. Chem. 1987, 8, 972– 981 DOI: 10.1002/jcc.540080707Google ScholarThere is no corresponding record for this reference.
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61Miyazawa, S.; Jernigan, R. L. Estimation of effective inter-residue contact energies from protein crystal structures: quasi-chemical approximation Macromolecules 1985, 18, 534– 552 DOI: 10.1021/ma00145a039Google ScholarThere is no corresponding record for this reference.
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62Sun, S. Reduced representation model of protein structure prediction: statistical potential and genetic algorithms Protein Sci. 1993, 2, 762– 785 DOI: 10.1002/pro.5560020508Google Scholar62https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3sXlslOjtLY%253D&md5=960b68be09f30ffddc8b266c1101a8f5Reduced representation model of protein structure prediction: statistical potential and genetic algorithmsSun, ShaojianProtein Science (1993), 2 (5), 762-85CODEN: PRCIEI; ISSN:0961-8368.A reduced representation model, which has been described in previous reports, was used to predict the folded structures of proteins from their primary sequences and random starting conformations. The mol. structure of each protein has been reduced to its backbone atoms (with ideal fixed bond lengths and valence angles) and each side chain approximated by a single virtual united-atom. The coordinate variables were the backbone dihedral angles φ and ψ. A statistical potential function, which included local and nonlocal interactions and was computed from known protein structures, was used in the structure minimization. A novel approach, employing the concepts of genetic algorithms, has been developed to simultaneously optimize a population of conformations. With the information of primary sequence and the radius of gyration of the crystal structure only, and starting from randomly generated initial conformations, the author have been able to fold melittin, a protein of 26 residues, with high computational convergence. The computed structures have a root mean square error of 1.66 Å (distance matrix error = 0.99 Å) on av. to the crystal structure. Similar results for avian pancreatic polypeptide inhibitor, a protein of 36 residues, are obtained. Application of the method to apamin, an 18-residue polypeptide with two disulfide bonds, shows that it folds apamin to native-like conformations with the correct disulfide bonds formed.
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63Wallqvist, A.; Ullner, M. A simplified amino acid potential for use in structure predictions of proteins Proteins: Struct., Funct., Genet. 1994, 18, 267– 280 DOI: 10.1002/prot.340180308Google ScholarThere is no corresponding record for this reference.
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64Honeycutt, J. D.; Thirumalai, D. Metastability of the Folded States of Globular-Proteins Proc. Natl. Acad. Sci. U. S. A. 1990, 87, 3526– 3529 DOI: 10.1073/pnas.87.9.3526Google ScholarThere is no corresponding record for this reference.
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65Covell, D. G. Folding Protein Alpha-Carbon Chains into Compact Forms by Monte-Carlo Methods Proteins: Struct., Funct., Genet. 1992, 14, 409– 420 DOI: 10.1002/prot.340140310Google ScholarThere is no corresponding record for this reference.
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66Krigbaum, W. R.; Lin, S. F. Monte-Carlo Simulation of Protein Folding Using a Lattice Model Macromolecules 1982, 15, 1135– 1145 DOI: 10.1021/ma00232a035Google ScholarThere is no corresponding record for this reference.
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67Skolnick, J.; Kolinski, A. Simulations of the folding of a globular protein Science 1990, 250, 1121– 1125 DOI: 10.1126/science.250.4984.1121Google ScholarThere is no corresponding record for this reference.
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68Hinds, D. A.; Levitt, M. A Lattice Model for Protein-Structure Prediction at Low Resolution Proc. Natl. Acad. Sci. U. S. A. 1992, 89, 2536– 2540 DOI: 10.1073/pnas.89.7.2536Google ScholarThere is no corresponding record for this reference.
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69Taketomi, H.; Kano, F.; Go, N. The effect of amino acid substitution on protein-folding and -unfolding transition studied by computer simulation Biopolymers 1988, 27, 527– 559 DOI: 10.1002/bip.360270402Google ScholarThere is no corresponding record for this reference.
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70Voegler Smith, A.; Hall, C. K. alpha-helix formation: discontinuous molecular dynamics on an intermediate-resolution protein model Proteins: Struct., Funct., Genet. 2001, 44, 344– 360 DOI: 10.1002/prot.1100Google ScholarThere is no corresponding record for this reference.
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71Rohl, C.; Strauss, C.; Misura, K.; Baker, D. In Numerical Computer Methods, Part D; Elsevier: Amsterdam, 2004; Vol. 383.Google ScholarThere is no corresponding record for this reference.
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72Kolinski, A. Protein modeling and structure prediction with a reduced representation Acta Biochim. Polym. 2004, 51, 349– 371Google Scholar72https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXnslWjt78%253D&md5=9eeabaa4295d62c5f6ecf2e197f8a15fProtein modeling and structure prediction with a reduced representationKolinski, AndrzejActa Biochimica Polonica (2004), 51 (2), 349-371CODEN: ABPLAF; ISSN:0001-527X. (Polish Biochemical Society)Protein modeling can be done on various levels of structural detail, from simplified lattices or continuous representations, through high resoln. reduced models, employing the united atom representation, to all-atom models of the mol. mechanics. Here I describe a new high resoln.-reduced model, its force field and applications in structural proteomics. The model uses a lattice representation with 800 possible orientations of the virtual alpha carbon-alpha carbon bonds. The sampling scheme of the conformational space employs the Replica Exchange Monte Carlo method. Knowledge-based potentials of the force field include: generic protein-like conformational biases, statistical potentials for the short-range conformational propensities, a model of the main chain hydrogen bonds and context-dependent statistical potentials describing the side group interactions. The model is more accurate than the previously designed lattice models, and in many applications, it is complementary and competitive in respect to the all-atom techniques. The test applications include: an ab initio structure prediction, multitemplate comparative modeling and structure prediction based on sparse exptl. data. Esp., the new approach to comparative modeling could be a valuable tool for structural proteomics. It is shown that the new approach goes beyond the range of applicability of the traditional methods of protein comparative modeling.
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73Liwo, A.; Baranowski, M.; Czaplewski, C.; Golas, E.; He, Y.; Jagiela, D.; Krupa, P.; Maciejczyk, M.; Makowski, M.; Mozolewska, M. A. A unified coarse-grained model of biological macromolecules based on mean-field multipole-multipole interactions J. Mol. Model. 2014, 20, 2306 DOI: 10.1007/s00894-014-2306-5Google Scholar73https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cbisVOltQ%253D%253D&md5=8c08629d36e08def25f51c717ab89812A unified coarse-grained model of biological macromolecules based on mean-field multipole-multipole interactionsLiwo Adam; Baranowski Maciej; Czaplewski Cezary; Golas Ewa; He Yi; Jagiela Dawid; Krupa Pawel; Maciejczyk Maciej; Makowski Mariusz; Mozolewska Magdalena A; Niadzvedtski Andrei; Oldziej Stanislaw; Scheraga Harold A; Sieradzan Adam K; Slusarz Rafal; Wirecki Tomasz; Yin Yanping; Zaborowski BartlomiejJournal of molecular modeling (2014), 20 (8), 2306 ISSN:.A unified coarse-grained model of three major classes of biological molecules--proteins, nucleic acids, and polysaccharides--has been developed. It is based on the observations that the repeated units of biopolymers (peptide groups, nucleic acid bases, sugar rings) are highly polar and their charge distributions can be represented crudely as point multipoles. The model is an extension of the united residue (UNRES) coarse-grained model of proteins developed previously in our laboratory. The respective force fields are defined as the potentials of mean force of biomacromolecules immersed in water, where all degrees of freedom not considered in the model have been averaged out. Reducing the representation to one center per polar interaction site leads to the representation of average site-site interactions as mean-field dipole-dipole interactions. Further expansion of the potentials of mean force of biopolymer chains into Kubo's cluster-cumulant series leads to the appearance of mean-field dipole-dipole interactions, averaged in the context of local interactions within a biopolymer unit. These mean-field interactions account for the formation of regular structures encountered in biomacromolecules, e.g., α-helices and β-sheets in proteins, double helices in nucleic acids, and helicoidally packed structures in polysaccharides, which enables us to use a greatly reduced number of interacting sites without sacrificing the ability to reproduce the correct architecture. This reduction results in an extension of the simulation timescale by more than four orders of magnitude compared to the all-atom representation. Examples of the performance of the model are presented.
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74Kolinski, A.; Jaroszewski, L.; Rotkiewicz, P.; Skolnick, J. An efficient Monte Carlo model of protein chains. Modeling the short-range correlations between side group centers of mass J. Phys. Chem. B 1998, 102, 4628– 4637 DOI: 10.1021/jp973371jGoogle Scholar74https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXjtVWiu7o%253D&md5=77338f48247fad6b125ebeb50dcc86a1An Efficient Monte Carlo Model of Protein Chains. Modeling the Short-Range Correlations between Side Group Centers of MassKolinski, Andrzej; Jaroszewski, Lukasz; Rotkiewicz, Piotr; Skolnick, JeffreyJournal of Physical Chemistry B (1998), 102 (23), 4628-4637CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)A new high-coordination lattice model of polypeptide chains has been designed and tested. The model employs a single united atom representation of amino acid residues. These atoms are centered on protein side groups. Characteristic short-range distance correlations have been built into the model, thereby providing a rather accurate description of protein-like conformational stiffness. Sequence-specific interaction schemes have been derived from sequence similarity and sequence-structure compatibility criteria. The conformations of the model chain obsd. in isothermal Monte Carlo simulations reproduce protein secondary structure with high fidelity. Implications for structural studies of protein systems are briefly discussed.
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75Shakhnovich, E. Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet Chem. Rev. 2006, 106, 1559– 1588 DOI: 10.1021/cr040425uGoogle Scholar75https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjsFKitbc%253D&md5=5de8c7b04e3f51a8450ba1475be1c61aProtein folding thermodynamics and dynamics: Where physics, chemistry, and biology meetShakhnovich, EugeneChemical Reviews (Washington, DC, United States) (2006), 106 (5), 1559-1588CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review. First, the author summarizes basic questions and presents simple, coarse-grained models that provide a basis for a fundamental understanding of protein folding thermodn. and kinetics. Then, the author discusses more recent developments (over the last 5 yr) that focus on detailed studies of folding mechanisms of specific proteins, and finally, he briefly discusses some outstanding questions and future directions.
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76Dill, K. A.; MacCallum, J. L. The protein-folding problem, 50 years on Science 2012, 338, 1042– 1046 DOI: 10.1126/science.1219021Google Scholar76https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs12itrnF&md5=bd73e6103d437b24594ce4cd86ad25dcThe protein-folding problem, 50 years onDill, Ken A.; MacCallum, Justin L.Science (Washington, DC, United States) (2012), 338 (6110), 1042-1046CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)A review. The protein-folding problem was 1st posed about one half-century ago. The term refers to 3 broad questions: (1) What is the phys. code by which an amino acid sequence dictates a protein's native structure (2) How can proteins fold so fast and (3) Can one devise a computer algorithm to predict protein structures from their sequences. Here, the authors review progress on these problems. In a few cases, computer simulations of the phys. forces in chem. detailed models have now achieved the accurate folding of small proteins. It has been learned that proteins fold rapidly because random thermal motions cause conformational changes leading energetically downhill toward the native structure, a principle that is captured in funnel-shaped energy landscapes. And thanks in part to the large Protein Data Bank of known structures, predicting protein structures is now far more successful than was thought possible in earlier days. What began as 3 questions of basic science one half-century ago has now grown into the full-fledged research field of protein phys. science.
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77Yue, K.; Fiebig, K. M.; Thomas, P. D.; Chan, H. S.; Shakhnovich, E. I.; Dill, K. A. A test of lattice protein folding algorithms Proc. Natl. Acad. Sci. U. S. A. 1995, 92, 325– 329 DOI: 10.1073/pnas.92.1.325Google Scholar77https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXjtVensL0%253D&md5=c0b3e6cb5cc4eb468fb0ed4af12e1e58A test of lattice protein folding algorithmsYue, Kaizhi; Fiebig, Klaus M.; Thomas, Paul D.; Chan, Hue Sun; Shakhnovich, Eugene I.; Dill, Ken A.Proceedings of the National Academy of Sciences of the United States of America (1995), 92 (1), 325-9CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We report a blind test of lattice-model-based search strategies for finding global min. of model protein chains. One of us (E.I.S.) selected 10 compact conformations of 48-mer chains on the three-dimensional cubic lattice and used their inverse folding algorithm to design HP (H, hydrophobic; P, polar) sequences that should fold to those "target" structures. The sequences, but not the structures, were sent to the UCSF group (K.Y., K.M.F., P.D.T., H.S.C., and K.A.D.), who used two methods to attempt to find the globally optimal conformations: "hydrophobic zippers" and a constraint-based hydrophobic core construction (CHCC) method. The CHCC method found global min. in all cases, and the hydrophobic zippers method found global min. in some cases, in minutes to hours on workstations. In 9 out of 10 sequences, the CHCC method found lower energy conformations than the 48-mers were designed to fold to. Thus the search strategies succeed for the HP model but the design strategy dose not. For every sequence the global energy min. was found to have multiple degeneracy with 103 to 106 conformations. We discuss the implications of these results for (i) searching conformational spaces of simple models of proteins and (ii) how these simple models relate to proteins.
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78Dill, K. A.; Bromberg, S.; Yue, K.; Fiebig, K. M.; Yee, D. P.; Thomas, P. D.; Chan, H. S. Principles of protein folding--a perspective from simple exact models Protein Sci. 1995, 4, 561– 602 DOI: 10.1002/pro.5560040401Google Scholar78https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXltFynur0%253D&md5=647bf25d9a62383f1be493a2aac8600fPrinciples of protein folding - a perspective from simple exact modelsDill, Ken A.; Bromberg, Sarina; Yue, Kaizhi; Fiebig, Klaus M.; Yee, David P.; Thomas, Paul D.; Chan, Hue SunProtein Science (1995), 4 (4), 561-602CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)A review, with ≈420 refs. General principles of protein structure, stability, and folding kinetics have recently been explored in computer simulations of simple exact lattice models. These models represent protein chains at a rudimentary level, but the involve few parameters, approxns., or implicit biases, and they allow complete explorations of conformational and sequence spaces. Such simulations have resulted in testable predictions that are sometimes unanticipated: The folding code is mainly binary and delocalized throughout the amino acid sequence. The secondary and tertiary structures of a protein are specified mainly by the sequence of polar and nonpolar monomers. More specific interactions may refine the structure, rather than dominate the folding code. Simple exact models can account for the properties that characterize protein folding: two-state cooperativity, secondary and tertiary structures, and multistage folding kinetics-fast hydrophobic collapse followed by slower annealing. These studies suggest the possibility of creating "foldable" chain mols. other than proteins. The encoding of a unique compact chain conformation may not require amino acids; it may require only the ability to synthesize specific monomer sequences in which at least one monomer type is solvent-averse.
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79Shakhnovich, E. I.; Gutin, A. M. Formation of Unique Structure in Polypeptide-Chains Theoretical Investigation with the Aid of a Replica Approach Biophys. Chem. 1989, 34, 187– 199 DOI: 10.1016/0301-4622(89)80058-4Google ScholarThere is no corresponding record for this reference.
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80Bechini, A. On the Characterization and Software Implementation of General Protein Lattice Models. PLoS One 2013, 8. e59504 DOI: 10.1371/journal.pone.0059504Google ScholarThere is no corresponding record for this reference.
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81Skolnick, J.; Kolinski, A.; Yaris, R. Monte Carlo simulations of the folding of beta-barrel globular proteins Proc. Natl. Acad. Sci. U. S. A. 1988, 85, 5057– 5061 DOI: 10.1073/pnas.85.14.5057Google ScholarThere is no corresponding record for this reference.
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82Skolnick, J.; Kolinski, A. Dynamic Monte Carlo simulations of a new lattice model of globular protein folding, structure and dynamics J. Mol. Biol. 1991, 221, 499– 531 DOI: 10.1016/0022-2836(91)80070-BGoogle ScholarThere is no corresponding record for this reference.
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83Hao, M. H.; Scheraga, H. A. Monte-Carlo Simulation of a First-Order Transition for Protein-Folding J. Phys. Chem. 1994, 98, 4940– 4948 DOI: 10.1021/j100069a028Google ScholarThere is no corresponding record for this reference.
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84Park, B. H.; Levitt, M. The Complexity and Accuracy of Discrete State Models of Protein-Structure J. Mol. Biol. 1995, 249, 493– 507 DOI: 10.1006/jmbi.1995.0311Google ScholarThere is no corresponding record for this reference.
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85Godzik, A.; Kolinski, A.; Skolnick, J. Lattice Representations of Globular-Proteins - How Good Are They J. Comput. Chem. 1993, 14, 1194– 1202 DOI: 10.1002/jcc.540141009Google ScholarThere is no corresponding record for this reference.
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86Alexander, P. A.; He, Y.; Chen, Y.; Orban, J.; Bryan, P. N. A minimal sequence code for switching protein structure and function Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 21149– 21154 DOI: 10.1073/pnas.0906408106Google Scholar86https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXjvFOiu7o%253D&md5=6ba6060550fae5ae68474eedbfb99a10A minimal sequence code for switching protein structure and functionAlexander, Patrick A.; He, Yanan; Chen, Yihong; Orban, John; Bryan, Philip N.Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (50), 21149-21154, S21149/1-S21149/7CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)A structural and mechanistic description of how a protein changes its fold and function, mutation by mutation, is presented. The approach was to create 2 proteins that (i) are stably folded into 2 different folds, (ii) have 2 different functions, and (iii) are very similar in sequence. In this simplified sequence space, the mutational path from one fold to another is explored. It is shown that an IgG-binding, 4β+α fold can be transformed into an albumin-binding, 3-α fold via a mutational pathway in which neither function nor native structure is completely lost. The stabilities of all mutants along the pathway are evaluated, key high-resoln. structures are detd. by NMR, and an explanation of the switching mechanism is provided. It is shown that the conformational switch from 4β+α to 3-α structure can occur via a single amino acid substitution. On one side of the switch point, the 4β+α fold is > 90% populated (pH 7.2, 20 °C). A single mutation switches the conformation to the 3-α fold, which is > 90% populated (pH 7.2, 20 °C). It is further shown that a bifunctional protein exists at the switch point with affinity for both IgG and albumin.
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87Riniker, S.; Allison, J. R.; van Gunsteren, W. F. On developing coarse-grained models for biomolecular simulation: a review Phys. Chem. Chem. Phys. 2012, 14, 12423– 12430 DOI: 10.1039/c2cp40934hGoogle Scholar87https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1Cis7vO&md5=8f362f16e11bb9587daedac96acacb32On developing coarse-grained models for biomolecular simulation: a reviewRiniker, Sereina; Allison, Jane R.; van Gunsteren, Wilfred F.Physical Chemistry Chemical Physics (2012), 14 (36), 12423-12430CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)A review. So-called coarse-grained models are a popular type of model for accessing long time scales in simulations of biomol. processes. Such models are coarse-grained with respect to at. models. But any modeling of processes or substances involves coarse-graining, i.e. the elimination of non-essential degrees of freedom and interactions from a more fine-grained level of modeling. The basic ingredients of developing coarse-grained models based on the properties of fine-grained models are reviewed, together with the conditions that must be satisfied to preserve the correct phys. mechanisms in the coarse-graining process. This overview should help the reader to det. how realistic a coarse-grained model of a biomol. system is, i.e., whether it reflects the underlying phys. mechanisms or merely provides a set of pretty pictures of the process or substances of interest.
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88Trylska, J. Coarse-grained models to study dynamics of nanoscale biomolecules and their applications to the ribosome J. Phys.: Condens. Matter 2010, 22, 453101 DOI: 10.1088/0953-8984/22/45/453101Google Scholar88https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFartL3I&md5=a8c9f7a7dc4a1d26abd0e352e3652a6eCoarse-grained models to study dynamics of nanoscale biomolecules and their applications to the ribosomeTrylska, JoannaJournal of Physics: Condensed Matter (2010), 22 (45), 453101/1-453101/13CODEN: JCOMEL; ISSN:0953-8984. (Institute of Physics Publishing)A review. Biopolymers are of dynamic nature and undergo functional motions spanning a large spectrum of timescales. To study the internal dynamics of nano-sized mol. complexes that exceed hundred thousands of atoms with at. detail is computationally inefficient. Therefore, to achieve both the spatial and temporal scales of biol. interest coarse-grained models of macromols. are often used. By uniting groups of atoms into single interacting centers one decreases the resoln. of the system and gets rid of the irrelevant degrees of freedom. This simplification, even though it requires parameterization, makes the studies of biomol. dynamics computationally tractable and allows the authors to reach beyond the microsecond time frame. Here, the author reviews the coarse-grained models of macromols. composed of proteins and nucleic acids. The author gives examples of one-bead models that were developed to investigate the internal dynamics and focuses on their applications to the ribosome - the nanoscale protein synthesis machine.
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89Saunders, M. G.; Voth, G. A. Coarse-graining of multiprotein assemblies Curr. Opin. Struct. Biol. 2012, 22, 144– 150 DOI: 10.1016/j.sbi.2012.01.003Google Scholar89https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XltVamtbY%253D&md5=cedef5bf4f66fcadcfc15bdb005ce2b4Coarse-graining of multiprotein assembliesSaunders, Marissa G.; Voth, Gregory A.Current Opinion in Structural Biology (2012), 22 (2), 144-150CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Multiscale models are important tools to elucidate how small changes in local subunit conformations may propagate to affect the properties of macromol. complexes. We review recent advances in coarse-graining methods for poly-protein assemblies, systems that are composed of many copies of relatively few components, with a particular focus on viral capsids and cytoskeletal filaments. These methods are grouped into two broad categories - mapping methods, which use information from one scale of representation to parameterize a lower resoln. model, and bridging methods, which repeatedly connect different scales during simulation - and we provide examples of both classes at different levels of complexity. Collectively, these models illustrate the numerous approaches to information transfer between scales and demonstrate that the complexity required of the model depends in general on the nature of the information sought.
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90Mills, Z. G.; Mao, W.; Alexeev, A. Mesoscale modeling: solving complex flows in biology and biotechnology Trends Biotechnol. 2013, 31, 426– 434 DOI: 10.1016/j.tibtech.2013.05.001Google Scholar90https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXovVClu74%253D&md5=8c3cb32830268deaea4d516044ff082aMesoscale modeling: solving complex flows in biology and biotechnologyMills, Zachary Grant; Mao, Wenbin; Alexeev, AlexanderTrends in Biotechnology (2013), 31 (7), 426-434CODEN: TRBIDM; ISSN:0167-7799. (Elsevier Ltd.)A review. Fluids are involved in practically all physiol. activities of living organisms. However, biol. and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnol.
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91Coulon, A.; Beslon, G.; Gandrillon, O. Large multiprotein structures modeling and simulation: the need for mesoscopic models Methods Mol. Biol. 2008, 484, 537– 558 DOI: 10.1007/978-1-59745-398-1_32Google Scholar91https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFSgsLjF&md5=346be7c017efbb2bf784b6219f5bf169Large multiprotein structures modeling and simulation: the need for mesoscopic modelsCoulon, Antoine; Beslon, Guillaume; Gandrillon, OlivierMethods in Molecular Biology (Totowa, NJ, United States) (2008), 484 (Functional Proteomics), 537-558CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)Recent observational techniques based upon confocal microscopy make it possible to observe cells at a scale that has never been probed before: the mesoscopic scale. In the eukaryotic cell nucleus, many objects demonstrating phenomena occurring at this scale, such as nuclear bodies, are current subjects of investigations. But from a modeling perspective, this scale has not been widely explored, and hence there is a lack of suitable models for such studies. By reviewing higher and lower scale modeling techniques, we analyze their relevance in the context of mesoscale phenomena. We emphasize important characteristics that should be included in a mesoscopic model: an explicit continuous three-dimensional space with discrete simplified mols. that still have the characteristics of steric vol. exclusion and realistic distant interaction forces. Then we present 3DSPI, a model dedicated to studies of nuclear bodies based on a simple formalism inspired from mol. dynamics and coarse-grained models: particles interacting through a potential energy function and driven by an overdamped Langevin equation. Finally, we present the features expected to be included in the model, pointing out the difficulties that might arise.
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92Dama, J. F.; Sinitskiy, A. V.; McCullagh, M.; Weare, J.; Roux, B.; Dinner, A. R.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 1. General Principles J. Chem. Theory Comput. 2013, 9, 2466– 2480 DOI: 10.1021/ct4000444Google Scholar92https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXktlyltLc%253D&md5=ed47184bb04790726e3f95f630defb87The Theory of Ultra-Coarse-Graining. 1. General PrinciplesDama, James F.; Sinitskiy, Anton V.; McCullagh, Martin; Weare, Jonathan; Roux, Benoit; Dinner, Aaron R.; Voth, Gregory A.Journal of Chemical Theory and Computation (2013), 9 (5), 2466-2480CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grained (CG) models provide a computationally efficient means to study biomol. and other soft matter processes involving large nos. of atoms correlated over distance scales of many covalent bond lengths and long time scales. Variational methods based on information from simulations of finer-grained (e.g., all-atom) models, for example the multiscale coarse-graining (MS-CG) and relative entropy minimization methods, provide attractive tools for the systematic development of CG models. However, these methods have important drawbacks when used in the "ultra-coarse-grained" (UCG) regime, e.g., at a resoln. level coarser or much coarser than one amino acid residue per effective CG particle in proteins. This is due to the possible existence of multiple metastable states "within" the CG sites for a given UCG model configuration. In this work, systematic variational UCG methods are presented that are specifically designed to CG entire protein domains and subdomains into single effective CG particles. This is accomplished by augmenting existing effective particle CG schemes to allow for discrete state transitions and configuration-dependent resoln. Addnl., certain conclusions of this work connect back to single-state force matching and open up new avenues for method development in that area. These results provide a formal statistical mech. basis for UCG methods related to force matching and relative entropy CG methods and suggest practical algorithms for constructing optimal approx. UCG models from fine-grained simulation data.
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93Davtyan, A.; Dama, J. F.; Sinitskiy, A. V.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 2. Numerical Implementation J. Chem. Theory Comput. 2014, 10, 5265– 5275 DOI: 10.1021/ct500834tGoogle Scholar93https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFKqtbbN&md5=258cfd9c6f3e298f769682f3fc7e052fThe Theory of Ultra-Coarse-Graining. 2. Numerical ImplementationDavtyan, Aram; Dama, James F.; Sinitskiy, Anton V.; Voth, Gregory A.Journal of Chemical Theory and Computation (2014), 10 (12), 5265-5275CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The increasing interest in the modeling of complex macromol. systems in recent years has spurred the development of numerous coarse-graining (CG) techniques. However, many of the CG models are constructed assuming that all details beneath the resoln. of CG degrees of freedom are fast and av. out, which sets limits on the resoln. of feasible coarse-grainings and on the range of applications of the CG models. Ultra-coarse-graining (UCG) makes it possible to construct models at any desired resoln. while accounting for discrete conformational or chem. changes within the CG sites that can modulate the interactions between them. Here, we discuss the UCG methodol. and its numerical implementation. We pay particular attention to the numerical mechanism for including state transitions between different conformations within CG sites because this has not been discussed previously. Using a simple example of 1,2-dichloroethane, we demonstrate the ability of the UCG model to reproduce the multiconfigurational behavior of this mol. liq., even when each mol. is modeled with only one CG site. The methodol. can also be applied to other mol. liqs. and macromol. systems with time scale sepn. between conformational transitions and other intramol. motions and rotations.
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94Chen, J.; Xie, Z. R.; Wu, Y. Elucidating the general principles of cell adhesion with a coarse-grained simulation model Mol. BioSyst. 2016, 12, 205– 218 DOI: 10.1039/C5MB00612KGoogle Scholar94https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhslyqsLnP&md5=ae2e12e7d046e733655f29912cf06d28Elucidating the general principles of cell adhesion with a coarse-grained simulation modelChen, Jiawen; Xie, Zhong-Ru; Wu, YinghaoMolecular BioSystems (2016), 12 (1), 205-218CODEN: MBOIBW; ISSN:1742-2051. (Royal Society of Chemistry)Cell adhesion plays an indispensable role in coordinating physiol. functions in multicellular organisms. During this process, specific types of cell adhesion mols. interact with each other from the opposite sides of neighboring cells. Following this trans-interaction, many cell adhesion mols. further aggregate into clusters through cis interactions. Beyond the mol. level, adhesion can be affected by multiple cellular factors due to the complexity of membrane microenvironments, including its interplay with cell signaling. However, despite tremendous advances in exptl. developments, little is understood about the general principles of cell adhesion and its functional impacts. Here a mesoscopic simulation method is developed to tackle this problem. We illustrated that specific spatial patterns of membrane protein clustering are originated from different geometrical arrangements of their binding interfaces, while the size of clusters is closely regulated by mol. flexibility. Different scenarios of cooperation between trans and cis interactions of cell adhesion mols. were further tested. Addnl., impacts of membrane environments on cell adhesion were evaluated, such as the presence of a cytoskeletal meshwork, the membrane tension and the size effect of different membrane proteins on cell surfaces. Finally, by simultaneously simulating adhesion and oligomerization of signaling receptors, we found that the interplay between these two systems can be either pos. or neg., closely depending on the spatial and temporal patterns of their mol. interactions. Therefore, our computational model pave the way for understanding the mol. mechanisms of cell adhesion and its biol. functions in regulating cell signaling pathways.
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95Kolinski, A.; Skolnick, J. Assembly of protein structure from sparse experimental data: An efficient Monte Carlo model Proteins: Struct., Funct., Genet. 1998, 32, 475– 494 DOI: 10.1002/(SICI)1097-0134(19980901)32:4<475::AID-PROT6>3.3.CO;2-BGoogle ScholarThere is no corresponding record for this reference.
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96Kolinski, A.; Betancourt, M. R.; Kihara, D.; Rotkiewicz, P.; Skolnick, J. Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement Proteins: Struct., Funct., Genet. 2001, 44, 133– 149 DOI: 10.1002/prot.1080Google ScholarThere is no corresponding record for this reference.
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97Kolinski, A.; Ilkowski, B.; Skolnick, J. Dynamics and thermodynamics of beta-hairpin assembly: insights from various simulation techniques Biophys. J. 1999, 77, 2942– 2952 DOI: 10.1016/S0006-3495(99)77127-4Google ScholarThere is no corresponding record for this reference.
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98Boniecki, M.; Rotkiewicz, P.; Skolnick, J.; Kolinski, A. Protein fragment reconstruction using various modeling techniques J. Comput.-Aided Mol. Des. 2003, 17, 725– 738 DOI: 10.1023/B:JCAM.0000017486.83645.a0Google Scholar98https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2c7nslyruw%253D%253D&md5=43f4acdbacf57fbc6358faf3f65c4b78Protein fragment reconstruction using various modeling techniquesBoniecki Michal; Rotkiewicz Piotr; Skolnick Jeffrey; Kolinski AndrzejJournal of computer-aided molecular design (2003), 17 (11), 725-38 ISSN:0920-654X.Recently developed reduced models of proteins with knowledge-based force fields have been applied to a specific case of comparative modeling. From twenty high resolution protein structures of various structural classes, significant fragments of their chains have been removed and treated as unknown. The remaining portions of the structures were treated as fixed - i.e., as templates with an exact alignment. Then, the missed fragments were reconstructed using several modeling tools. These included three reduced types of protein models: the lattice SICHO (Side Chain Only) model, the lattice CABS (Calpha + Cbeta + Side group) model and an off-lattice model similar to the CABS model and called REFINER. The obtained reduced models were compared with more standard comparative modeling tools such as MODELLER and the SWISS-MODEL server. The reduced model results are qualitatively better for the higher resolution lattice models, clearly suggesting that these are now mature, competitive and complementary (in the range of sparse alignments) to the classical tools of comparative modeling. Comparison between the various reduced models strongly suggests that the essential ingredient for the sucessful and accurate modeling of protein structures is not the representation of conformational space (lattice, off-lattice, all-atom) but, rather, the specificity of the force fields used and, perhaps, the sampling techniques employed. These conclusions are encouraging for the future application of the fast reduced models in comparative modeling on a genomic scale.
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99Stumpff-Kane, A. W.; Maksimiak, K.; Lee, M. S.; Feig, M. Sampling of near-native protein conformations during protein structure refinement using a coarse-grained model, normal modes, and molecular dynamics simulations Proteins: Struct., Funct., Genet. 2008, 70, 1345– 1356 DOI: 10.1002/prot.21674Google ScholarThere is no corresponding record for this reference.
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100Kihara, D.; Zhang, Y.; Lu, H.; Kolinski, A.; Skolnick, J. Ab initio protein structure prediction on a genomic scale: application to the Mycoplasma genitalium genome Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 5993– 5998 DOI: 10.1073/pnas.092135699Google Scholar100https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XjslWgurg%253D&md5=f76d1902fcb122e6553b63971007d7d3Ab initio protein structure prediction on a genomic scale: application to the Mycoplasma genitalium genomeKihara, Daisuke; Zhang, Yang; Lu, Hui; Kolinski, Andrzej; Skolnick, JeffreyProceedings of the National Academy of Sciences of the United States of America (2002), 99 (9), 5993-5998CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)An ab initio protein structure prediction procedure, TOUCHSTONE, was applied to all 85 small proteins of the Mycoplasma genitalium genome. TOUCHSTONE is based on a Monte Carlo refinement of a lattice model of proteins, which uses threading-based tertiary restraints. Such restraints are derived by extg. consensus contacts and local secondary structure from at least weakly scoring structures that, in some cases, can lack any global similarity to the sequence of interest. Selection of the native fold was done by using the convergence of the simulation from two different conformational search schemes and the lowest energy structure by a knowledge-based at.-detailed potential. Among the 85 proteins, for 34 proteins with significant threading hits, the template structures were reasonably well reproduced. Of the remaining 51 proteins, 29 proteins converged to five or fewer clusters. In the test set, 84.8% of the proteins that converged to five or fewer clusters had a correct fold among the clusters. If this statistic is simply applied, 24 proteins (84.8% of the 29 proteins) may have correct folds. Thus, the topol. of a total of 58 proteins probably has been correctly predicted. Based on these results, ab initio protein structure prediction is becoming a practical approach.
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101Kmiecik, S.; Gront, D.; Kouza, M.; Kolinski, A. From coarse-grained to atomic-level characterization of protein dynamics: transition state for the folding of B domain of protein A J. Phys. Chem. B 2012, 116, 7026– 7032 DOI: 10.1021/jp301720wGoogle Scholar101https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xlt1aqsr8%253D&md5=0ac48f6b6153b0f09f651f0d5dff5463From Coarse-Grained to Atomic-Level Characterization of Protein Dynamics: Transition State for the Folding of B Domain of Protein AKmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Kolinski, AndrzejJournal of Physical Chemistry B (2012), 116 (23), 7026-7032CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Atomic-level mol. dynamics simulations are widely used for the characterization of the structural dynamics of proteins; however, they are limited to shorter time scales than the duration of most of the relevant biol. processes. Properly designed coarse-grained models that trade at. resoln. for efficient sampling allow access to much longer time-scales. In-depth understanding of the structural dynamics, however, must involve at. details. In this study, we tested a method for the rapid reconstruction of all-atom models from α carbon atom positions in the application to convert a coarse-grained folding trajectory of a well described model system: the B domain of protein A. The results show that the method and the spatial resoln. of the resulting coarse-grained models enable computationally inexpensive reconstruction of realistic all-atom models. Addnl., by means of structural clustering, we detd. the most persistent ensembles of the key folding step, the transition state. Importantly, the anal. of the overall structural topologies suggests a dominant folding pathway. This, together with the all-atom characterization of the obtained ensembles, in the form of contact maps, matches the exptl. results well.
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102Xu, D.; Zhang, Y. Improving the physical realism and structural accuracy of protein models by a two-step atomic-level energy minimization Biophys. J. 2011, 101, 2525– 2534 DOI: 10.1016/j.bpj.2011.10.024Google Scholar102https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsV2msb7E&md5=04fae8474e9816669a8e4e45850fb3efImproving the Physical Realism and Structural Accuracy of Protein Models by a Two-Step Atomic-Level Energy MinimizationXu, Dong; Zhang, YangBiophysical Journal (2011), 101 (10), 2525-2534CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Most protein structural prediction algorithms assemble structures as reduced models that represent amino acids by a reduced no. of atoms to speed up the conformational search. Building accurate full-atom models from these reduced models is a necessary step toward a detailed function anal. However, it is difficult to ensure that the at. models retain the desired global topol. while maintaining a sound local at. geometry because the reduced models often have unphys. local distortions. To address this issue, the authors developed a new program, called ModRefiner, to construct and refine protein structures from Cα traces based on a two-step, at.-level energy minimization. The main-chain structures are first constructed from initial Cα traces and the side-chain rotamers are then refined together with the backbone atoms with the use of a composite physics- and knowledge-based force field. The authors tested the method by performing an at. structure refinement of 261 proteins with the initial models constructed from both ab initio and template-based structure assemblies. Compared with other state-of-art programs, ModRefiner shows improvements in both global and local structures, which have more accurate side-chain positions, better hydrogen-bonding networks, and fewer at. overlaps. ModRefiner is freely available at http://zhanglab.ccmb.med.umich.edu/ModRefiner.
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103Kazmierkiewicz, R.; Liwo, A.; Scheraga, H. A. Addition of side chains to a known backbone with defined side-chain centroids Biophys. Chem. 2002, 100, 261– 280 DOI: 10.1016/S0301-4622(02)00285-5Google ScholarThere is no corresponding record for this reference.
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104Das, R.; Baker, D. Macromolecular modeling with rosetta Annu. Rev. Biochem. 2008, 77, 363– 382 DOI: 10.1146/annurev.biochem.77.062906.171838Google Scholar104https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXos1ekurw%253D&md5=17d4f1cef8eb03c399a4e3b65c83dde0Macromolecular modeling with RosettaDas, Rhiju; Baker, DavidAnnual Review of Biochemistry (2008), 77 (), 363-382CODEN: ARBOAW; ISSN:0066-4154. (Annual Reviews Inc.)A review. Advances over the past few years have begun to enable prediction and design of macromol. structures at near-at. accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of mol. modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodol. enables the creation of novel mols. with useful functions and holds promise for accelerating exptl. structural inference. Emerging connections to crystallog. phasing, NMR modeling, and lower-resoln. approaches are described and critically assessed.
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105Gopal, S. M.; Mukherjee, S.; Cheng, Y. M.; Feig, M. PRIMO/PRIMONA: a coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracy Proteins: Struct., Funct., Genet. 2010, 78, 1266– 1281 DOI: 10.1002/prot.22645Google Scholar105https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhvFCqur4%253D&md5=a79b7eb92cd81853531d2d1ede857136PRIMO/PRIMONA: A coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracyGopal, Srinivasa M.; Mukherjee, Shayantani; Cheng, Yi-Ming; Feig, MichaelProteins: Structure, Function, and Bioinformatics (2010), 78 (5), 1266-1281CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)The new coarse graining model PRIMO/PRIMONA for proteins and nucleic acids is proposed. This model combines one to several heavy atoms into coarse-grained sites that are chosen to allow an anal., high-resoln. reconstruction of all-atom models based on mol. bonding geometry constraints. The accuracy of proposed reconstruction method in terms of structure and energetics is tested and compared with other popular reconstruction methods for a variety of protein and nucleic acid test sets. Proteins 2010. © 2009 Wiley-Liss, Inc.
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106Kar, P.; Gopal, S. M.; Cheng, Y. M.; Predeus, A.; Feig, M. PRIMO: A Transferable Coarse-grained Force Field for Proteins J. Chem. Theory Comput. 2013, 9, 3769– 3788 DOI: 10.1021/ct400230yGoogle Scholar106https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVWht7rM&md5=7fd81d83f708b223a00d0bfb707bd5d0PRIMO: A Transferable Coarse-Grained Force Field for ProteinsKar, Parimal; Gopal, Srinivasa Murthy; Cheng, Yi-Ming; Predeus, Alexander; Feig, MichaelJournal of Chemical Theory and Computation (2013), 9 (8), 3769-3788CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors describe here the PRIMO (protein intermediate model) force field, a physics-based fully transferable additive coarse-grained potential energy function that is compatible with an all-atom force field for multiscale simulations. The energy function consists of std. mol. dynamics energy terms plus a hydrogen-bonding potential term and is mainly parametrized based on the CHARMM22/CMAP force field in a bottom-up fashion. The solvent was treated implicitly via the generalized Born model. The bonded interactions are either harmonic or distance-based spline interpolated potentials. These potentials are defined on the basis of all-atom mol. dynamics (MD) simulations of dipeptides with the CHARMM22/CMAP force field. The nonbonded parameters are tuned by matching conformational free energies of diverse set of conformations with that of CHARMM all-atom results. PRIMO is designed to provide a correct description of conformational distribution of the backbone (φ/ψ) and side chains (χ1) for all amino acids with a CMAP correction term. The CMAP potential in PRIMO is optimized based on the new CHARMM C36 CMAP. The resulting optimized force field has been applied in MD simulations of several proteins of 36-155 amino acids and showed that the root-mean-squared-deviation of the av. structure from the corresponding crystallog. structure varies between 1.80 and 4.03 Å. PRIMO is shown to fold several small peptides to their native-like structures from extended conformations. These results suggest the applicability of the PRIMO force field in the study of protein structures in aq. soln., structure predictions, as well as ab initio folding of small peptides.
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107Skolnick, J. In quest of an empirical potential for protein structure prediction Curr. Opin. Struct. Biol. 2006, 16, 166– 171 DOI: 10.1016/j.sbi.2006.02.004Google Scholar107https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xjs1Grs7w%253D&md5=77640214385bc60a67e0c0ab171537a7In quest of an empirical potential for protein structure predictionSkolnick, JeffreyCurrent Opinion in Structural Biology (2006), 16 (2), 166-171CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Key to successful protein structure prediction is a potential that recognizes the native state from misfolded structures. Recent advances in empirical potentials based on known protein structures include improved ref. states for assessing random interactions, sidechain-orientation-dependent pair potentials, potentials for describing secondary or supersecondary structural preferences and, most importantly, optimization protocols that sculpt the energy landscape to enhance the correlation between native-like features and the energy. Improved clustering algorithms that select native-like structures on the basis of cluster d. also resulted in greater prediction accuracy. For template-based modeling, these advances allowed improvement in predicted structures relative to their initial template alignments over a wide range of target-template homol. This represents significant progress and suggests applications to proteome-scale structure prediction.
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108Vanommeslaeghe, K.; MacKerell, A. D., Jr. CHARMM additive and polarizable force fields for biophysics and computer-aided drug design Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 861– 871 DOI: 10.1016/j.bbagen.2014.08.004Google Scholar108https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVakt7fO&md5=5a4794d8d54c6fb181c1ba4487d48cfbCHARMM additive and polarizable force fields for biophysics and computer-aided drug designVanommeslaeghe, K.; MacKerell, A. D.Biochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 861-871CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Mol. Mechanics (MM) is the method of choice for computational studies of biomol. systems owing to its modest computational cost, which makes it possible to routinely perform mol. dynamics (MD) simulations on chem. systems of biophys. and biomedical relevance. As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomol. force fields. Addnl., we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodol. Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approxn. is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1 μs on proteins, DNA, lipids and carbohydrates. Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calcns. that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying phys. forces driving macromol. structures and dynamics. This article is part of a Special Issue entitled "Recent developments of mol. dynamics".
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109Oostenbrink, C.; Villa, A.; Mark, A.; van Gunsteren, W. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6 J. Comput. Chem. 2004, 25, 1656– 1676 DOI: 10.1002/jcc.20090Google Scholar109https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXmvVOhtr4%253D&md5=f2c0be6f44fe768128989c9031957e4eA biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6Oostenbrink, Chris; Villa, Alessandra; Mark, Alan E.; van Gunsteren, Wilfred F.Journal of Computational Chemistry (2004), 25 (13), 1656-1676CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Successive parameterizations of the GROMOS force field have been used successfully to simulate biomol. systems over a long period of time. The continuing expansion of computational power with time makes it possible to compute ever more properties for an increasing variety of mol. systems with greater precision. This has led to recurrent parameterizations of the GROMOS force field all aimed at achieving better agreement with exptl. data. Here we report the results of the latest, extensive reparameterization of the GROMOS force field. In contrast to the parameterization of other biomol. force fields, this parameterization of the GROMOS force field is based primarily on reproducing the free enthalpies of hydration and apolar solvation for a range of compds. This approach was chosen because the relative free enthalpy of solvation between polar and apolar environments is a key property in many biomol. processes of interest, such as protein folding, biomol. assocn., membrane formation, and transport over membranes. The newest parameter sets, 53A5 and 53A6, were optimized by first fitting to reproduce the thermodn. properties of pure liqs. of a range of small polar mols. and the solvation free enthalpies of amino acid analogs in cyclohexane (53A5). The partial charges were then adjusted to reproduce the hydration free enthalpies in water (53A6). Both parameter sets are fully documented, and the differences between these and previous parameter sets are discussed.
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110Fain, B.; Xia, Y.; Levitt, M. Design of an optimal Chebyshev-expanded discrimination function for globular proteins Protein Sci. 2002, 11, 2010– 2021 DOI: 10.1110/ps.0200702Google Scholar110https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XlslKntrc%253D&md5=1ddc1f776ff1b3c0a340428952bc3704Design of an optimal Chebyshev-expanded discrimination function for globular proteinsFain, Boris; Xia, Yu; Levitt, MichaelProtein Science (2002), 11 (8), 2010-2021CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)We describe the construction of a scoring function designed to model the free energy of protein folding. An optimization technique is used to det. the best functional forms of the hydrophobic, residue-residue and hydrogen-bonding components of the potential. The scoring function is expanded by use of Chebyshev polynomials, the coeffs. of which are detd. by minimizing the score, in units of std. deviation, of native structures in the ensembles of alternate decoy conformations. The derived effective potential is then tested on decoy sets used conventionally in such studies. Using our scoring function, we achieve a high level of discrimination between correct and incorrect folds. In addn., our method is able to represent functions of arbitrary shape with fewer parameters than the usual histogram potentials of similar resoln. Finally, our representation can be combined easily with many optimization methods, because the total energy is a linear function of the parameters. Our results show that the techniques of Z-score optimization and Chebyshev expansion work well.
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111Basdevant, N.; Borgis, D.; Ha-Duong, T. A coarse-grained protein-protein potential derived from an all-atom force field J. Phys. Chem. B 2007, 111, 9390– 9399 DOI: 10.1021/jp0727190Google Scholar111https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXns1CktrY%253D&md5=b79b8ceaeedd230e8a10debdf982d3f3A Coarse-Grained Protein-Protein Potential Derived from an All-Atom Force FieldBasdevant, Nathalie; Borgis, Daniel; Ha-Duong, TapJournal of Physical Chemistry B (2007), 111 (31), 9390-9399CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)In order to study protein-protein nonbonded interactions, we present the development of a new reduced protein model that represents each amino acid residue with one to three coarse grains, whose phys. properties are derived in a consistent bottom-up procedure from the higher-resoln. all-atom AMBER force field. The resulting potential energy function is pairwise additive and includes distinct van-der-Waals and Coulombic terms. The van-der-Waals effective interactions are deduced from preliminary mol. dynamics simulations of all possible amino acid homodimers. They are best represented by a soft 1/r6 repulsion and a Gaussian attraction, with parameters obeying Lorentz-Berthelot mixing rules. For the Coulombic interaction, coarse grain charges are optimized for each sep. protein in order to best represent the all-atom electrostatic potential outside the protein core. This approach leaves the possibility of using any implicit solvent model to describe solvation effects and electrostatic screening. The coarse-grained force field is tested carefully for a small homodimeric complex, the magainin. It is shown to reproduce satisfactorily the specificity of the all-atom underlying potential, in particular within a PB/SA solvation model. The coarse-grained potential is applied to the redocking prediction of three different protein-protein complexes: the magainin dimer, the barnase-barstar, and the trypsin-BPTI complexes. It is shown to provide per se an efficient and discriminating scoring energy function for the protein-protein docking problem that remains pertinent at both the global and refinement stage.
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112Cascella, M.; Vanni, S. In Chemical Modelling: Vol. 12; The Royal Society of Chemistry: London, 2016; Vol. 12.Google ScholarThere is no corresponding record for this reference.
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113Brooks, B.; Bruccoleri, R.; Olafson, B.; States, D.; Swaminathan, S.; Karplus, M. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations J. Comput. Chem. 1983, 4, 187– 217 DOI: 10.1002/jcc.540040211Google Scholar113https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaL3sXit1aiu7w%253D&md5=bd639b4299ac9934f4497c1a9fe750d2CHARMM: a program for macromolecular energy, minimization, and dynamics calculationsBrooks, Bernard R.; Bruccoleri, Robert E.; Olafson, Barry D.; States, David J.; Swaminathan, S.; Karplus, MartinJournal of Computational Chemistry (1983), 4 (2), 187-217CODEN: JCCHDD; ISSN:0192-8651.CHARMM (Chem. at HARvard Macromol. Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromol. systems. The program can read or model build structures, energy minimize them by first- or second-deriv. techniques, perform a normal mode or mol. dynamics simulation, and analyze the structural, equil., and dynamic properties detd. in these calcns. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.
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114Lee, S.; Tran, A.; Allsopp, M.; Lim, J. B.; Henin, J.; Klauda, J. B. CHARMM36 united atom chain model for lipids and surfactants J. Phys. Chem. B 2014, 118, 547– 556 DOI: 10.1021/jp410344gGoogle Scholar114https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFCjur%252FK&md5=4efa293c0ecf6be13a1c8d2b3299891aCHARMM36 United Atom Chain Model for Lipids and SurfactantsLee, Sarah; Tran, Alan; Allsopp, Matthew; Lim, Joseph B.; Henin, Jerome; Klauda, Jeffery B.Journal of Physical Chemistry B (2014), 118 (2), 547-556CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Mol. simulations of lipids and surfactants require accurate parameters to reproduce and predict exptl. properties. Previously, a united atom UA chain model was developed for the CHARMM27/27r lipids (Henin, J., et al. J. Phys. Chem. B. 2008, 112, 7008-7015) but suffers from the flaw that bilayer simulations using the model require an imposed surface area ensemble, which limits its use to pure bilayer systems. A UA-chain model has been developed based on the CHARMM36 C36 all-atom lipid parameters, termed C36-UA, and agreed well with bulk, lipid membrane, and micelle formation of a surfactant. Mol. dynamics MD simulations of alkanes heptane and pentadecane were used to test the validity of C36-UA on d., heat of vaporization, and liq. self-diffusion consts. Then, simulations using C36-UA resulted in accurate properties surface area per lipid, X-ray and neutron form factors, and chain order parameters of various satd.- and unsatd.-chain bilayers. When mixed with the all-atom cholesterol model and tested with a series of 1,2-dimyristoyl-sn-glycero-3-phosphocholine DMPC/cholesterol mixts., the C36-UA model performed well. Simulations of self-assembly of a surfactant dodecylphosphocholine, DPC using C36-UA suggest an aggregation no. of 53 ± 11 DPC mols. at 0.45 M of DPC, which agrees well with exptl. ests. Therefore, the C36-UA force field offers a useful alternative to the all-atom C36 lipid force field by requiring less computational cost while still maintaining the same level of accuracy, which may prove useful for large systems with proteins.
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115Schmid, N.; Eichenberger, A. P.; Choutko, A.; Riniker, S.; Winger, M.; Mark, A. E.; van Gunsteren, W. F. Definition and testing of the GROMOS force-field versions 54A7 and 54B7 Eur. Biophys. J. 2011, 40, 843– 856 DOI: 10.1007/s00249-011-0700-9Google Scholar115https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXnsVCgs74%253D&md5=a1cd133f1e663da949324060e00c950dDefinition and testing of the GROMOS force-field versions 54A7 and 54B7Schmid, Nathan; Eichenberger, Andreas P.; Choutko, Alexandra; Riniker, Sereina; Winger, Moritz; Mark, Alan E.; Gunsteren, Wilfred F.European Biophysics Journal (2011), 40 (7), 843-856CODEN: EBJOE8; ISSN:0175-7571. (Springer)New parameter sets of the GROMOS biomol. force field, 54A7 and 54B7, are introduced. These parameter sets summarize some previously published force field modifications: The 53A6 helical propensities are cor. through new φ/ψ torsional angle terms and a modification of the N-H, C=O repulsion, a new atom type for a charged -CH3 in the choline moiety is added, the Na+ and Cl- ions are modified to reproduce the free energy of hydration, and addnl. improper torsional angle types for free energy calcns. involving a chirality change are introduced. The new helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide. The stability of the proteins is improved in comparison with the 53A6 force field, and good agreement with a range of primary exptl. data is obtained.
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116de Jong, D. H.; Singh, G.; Bennett, W. F. D.; Arnarez, C.; Wassenaar, T. A.; Schafer, L. V.; Periole, X.; Tieleman, D. P.; Marrink, S. J. Improved Parameters for the Martini Coarse-Grained Protein Force Field J. Chem. Theory Comput. 2013, 9, 687– 697 DOI: 10.1021/ct300646gGoogle Scholar116https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1OnsrbO&md5=ffad32e5e861a8e1fdf62491d39d8450Improved Parameters for the Martini Coarse-Grained Protein Force Fieldde Jong, Djurre H.; Singh, Gurpreet; Bennett, W. F. Drew; Arnarez, Clement; Wassenaar, Tsjerk A.; Schaefer, Lars V.; Periole, Xavier; Tieleman, D. Peter; Marrink, Siewert J.Journal of Chemical Theory and Computation (2013), 9 (1), 687-697CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The Martini coarse-grained force field has been successfully used for simulating a wide range of (bio)mol. systems. Recent progress in our ability to test the model against fully atomistic force fields, however, has revealed some shortcomings. Most notable, phenylalanine and proline were too hydrophobic, and dimers formed by polar residues in apolar solvents did not bind strongly enough. Here, we reparametrize these residues either through reassignment of particle types or by introducing embedded charges. The new parameters are tested with respect to partitioning across a lipid bilayer, membrane binding of Wimley-White peptides, and dimerization free energy in solvents of different polarity. In addn., we improve some of the bonded terms in the Martini protein force field that lead to a more realistic length of α-helixes and to improved numerical stability for polyalanine and glycine repeats. The new parameter set is denoted Martini version 2.2.
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117Izvekov, S.; Parrinello, M.; Burnham, C.; Voth, G. Effective force fields for condensed phase systems from ab initio molecular dynamics simulation: A new method for force-matching J. Chem. Phys. 2004, 120, 10896– 10913 DOI: 10.1063/1.1739396Google Scholar117https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXksVCqt7w%253D&md5=604e711721e915c2dfbd6da3542c4faaEffective force fields for condensed phase systems from ab initio molecular dynamics simulation: A new method for force-matchingIzvekov, Sergei; Parrinello, Michele; Burnham, Christian J.; Voth, Gregory A.Journal of Chemical Physics (2004), 120 (23), 10896-10913CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)A novel least-squares fitting approach is presented to obtain classical force fields from trajectory and force databases produced by ab initio (e.g., Car-Parrinello) mol. dynamics (MD) simulations. The method was applied to derive effective nonpolarizable three-site force fields for liq. water at ambient conditions from Car-Parrinello MD simulations in the Becke-Lee-Yang-Parr approxn. to the electronic d. functional theory. The force-matching procedure includes a fit of short-ranged nonbonded forces, bonded forces, and at. partial charges. The various parameterizations of the water force field differ by an enforced smooth cut-off applied to the short-ranged interaction term. These were obtained by fitting to the trajectory and force data produced by Car-Parrinello MD simulations of systems of 32 and 64 H2O mols. The new water force fields were developed assuming both flexible or rigid mol. geometry. The simulated structural and self-diffusion properties of liq. water using the fitted force fields are in close agreement with those obsd. in the underlying Car-Parrinello MD simulations. The resulting empirical models compare to expt. much better than many conventional simple point charge (SPC) models. The fitted potential is also shown to combine well with more sophisticated intramol. potentials. Importantly, the computational cost of the new models is comparable to that for SPC-like potentials.
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118Ercolessi, F.; Adams, J. B. Interatomic Potentials from First-Principles Calculations: The Force-Matching Method Europhys. Lett. 1994, 26, 583 DOI: 10.1209/0295-5075/26/8/005Google Scholar118https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXks1KisLc%253D&md5=876903808d34a9bcacac16517e331480Interatomic potentials from first-principles calculations: the force-matching methodErcolessi, F.; Adams, J. B.Europhysics Letters (1994), 26 (8), 583-8CODEN: EULEEJ; ISSN:0295-5075.The authors present a new scheme to ext. numerically «optimal» interat. potentials from large amts. of data produced by first-principles calcns. The method is based on fitting the potential to ab initio at. forces of many at. configurations, including surfaces, clusters, liqs. and crystals at finite temp. The extensive data set overcomes the difficulties encountered by traditional fitting approaches when using rich and complex analytic forms, allowing to construct potentials with a degree of accuracy comparable to that obtained by ab initio methods. A glue potential for aluminum obtained with this method is presented and discussed.
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119Schommers, W. Pair potentials in disordered many-particle systems: A study for liquid gallium Phys. Rev. A: At., Mol., Opt. Phys. 1983, 28, 3599– 3605 DOI: 10.1103/PhysRevA.28.3599Google Scholar119https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaL2cXis1amsg%253D%253D&md5=6078da0587a429c9afd45a98c0bec882Pair potentials in disordered many-particle systems: A study for liquid galliumSchommers, W.Physical Review A: Atomic, Molecular, and Optical Physics (1983), 28 (6), 3599-605CODEN: PLRAAN; ISSN:0556-2791.Several methods are compared which connect the effective pair potential to the pair-correlation function. These methods are a self-consistent method using mol. dynamics, the so-called modified STLS (Singwi-Tosi-Land-Sjoelander) theory, the Weeks-Chandler-Andersen approach, the Percus-Yevick theory, the hypernetted-chain approxn., and the Born-Green equation. Since the pair potential is, in general, very sensitive to small variations in the pair-correlation functions, structure data were used with sufficient accuracy in the detn. of the pair potentials from the pair-correlation function. A. H. Narten (1972) performed measurements on liq. Ga with high precision, and, therefore, all calcns. were performed on the basis of his structure data. The self-consistent method and the Weeks-Chandler-Andersen approach led to reasonable results. The results for the pair potential obtained from the other methods are unsatisfactory and cannot be used in the detn. of liq.-Ga properties.
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120Henderson, R. L. A uniqueness theorem for fluid pair correlation functions Phys. Lett. A 1974, 49, 197– 198 DOI: 10.1016/0375-9601(74)90847-0Google ScholarThere is no corresponding record for this reference.
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121Reith, D.; Pütz, M.; Müller-Plathe, F. Deriving effective mesoscale potentials from atomistic simulations J. Comput. Chem. 2003, 24, 1624– 1636 DOI: 10.1002/jcc.10307Google Scholar121https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXntFentL4%253D&md5=304cc4acd956aaa71f476992e656fd13Deriving effective mesoscale potentials from atomistic simulationsReith, Dirk; Puetz, Mathias; Mueller-Plathe, FlorianJournal of Computational Chemistry (2003), 24 (13), 1624-1636CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liq. systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few interactions. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 redn. of the degrees of freedom. This procedure was performed for PI solns. as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concn. regimes.
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122Moore, T. C.; Iacovella, C. R.; McCabe, C. Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion J. Chem. Phys. 2014, 140, 224104 DOI: 10.1063/1.4880555Google Scholar122https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpsFKmt7g%253D&md5=0897e6378ed6caabc10916c52a020312Derivation of coarse-grained potentials via multistate iterative Boltzmann inversionMoore, Timothy C.; Iacovella, Christopher R.; McCabe, ClareJournal of Chemical Physics (2014), 140 (22), 224104/1-224104/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)An extension is proposed to the std. iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodn. states than the std. IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the std. IBI method. Addnl., through the examn. of alkane monolayers, it is shown that the relative wt. given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of ref. atomistic and/or exptl. systems. (c) 2014 American Institute of Physics.
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123Lyubartsev, A.; Laaksonen, A. Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 1995, 52, 3730– 3737 DOI: 10.1103/PhysRevE.52.3730Google Scholar123https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXovVSgsrw%253D&md5=294e69e8830aeaa4ffb1cd17cc7af20eCalculation of effective interaction potentials from radial distribution functions: a reverse Monte Carlo approachLyubartsev, Alexander; Laaksonen, AattoPhysical Review E: Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics (1995), 52 (4-A), 3730-7CODEN: PLEEE8; ISSN:1063-651X. (American Physical Society)An approach is presented to solve the reverse problem of statistical mechanics: reconstruction of interaction potentials from radial distribution functions. The method consists of the iterative adjustment of the interaction potential to known radical distribution functions using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical avs. with Hamiltonian parameters. The method consists of the iterative adjustment of the interaction potential to known radical distribution functions using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical avs. with Hamiltonian parameters. The method is applied to calc. the effective interaction potentials between the ions in aq. NaCl solns. at two different concns. The ref. ion-ion radial distribution functions, calcd. in sep. mol. dynamics simulations with water mols., are reproduced in Monte Carlo simulations, using the effective interaction potentials for the hydrated ions. Applications of the present method should provide an effective and economical way to simulate equil. properties for very large mol. systems (e.g., polyelectrolytes) in the presence of hydrated ions, as well as to offer an approach to reduce a complexity in studies of various assocd. and aggregated systems in soln.
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124Lyubartsev, A.; Mirzoev, A.; Chen, L.; Laaksonen, A. Systematic coarse-graining of molecular models by the Newton inversion method. Faraday Discuss. 2010, 144, 43 DOI: 10.1039/B901511FGoogle Scholar124https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht12htrfL&md5=8da608a1d6b4259e79982e5be0c8bce4Systematic coarse-graining of molecular models by the Newton inversion methodLyubartsev, Alexander; Mirzoev, Alexander; Chen, Li-Jun; Laaksonen, AattoFaraday Discussions (2010), 144 (), 43-56CODEN: FDISE6; ISSN:1359-6640. (Royal Society of Chemistry)Systematic construction of coarse-grained mol. models from detailed atomistic simulations, and even from ab initio simulations is discussed. Atomistic simulations are first performed to ext. structural information about the system, which is then used to det. effective potentials for a coarse-grained model of the same system. The statistical-mech. equations expressing the canonical properties in terms of potential parameters can be inverted and solved numerically according to the iterative Newton scheme. In our previous applications, known as the Inverse Monte Carlo, radial distribution functions were inverted to reconstruct pair potential, while in a more general approach the targets can be other canonical avs. We have considered several examples of coarse-graining; for the united atom water model we suggest an easy way to overcome the known problem of high pressure. Further, we have developed coarse-grained models for L- and D-prolines, dissolved here in an org. solvent (dimethylsulfoxide), keeping their enantiomeric properties from the corresponding all-atom proline model. Finally, we have revisited the previously developed coarse-grained lipid model based on an updated all-at. force field. We use this model in large-scale meso-scale simulations demonstrating spontaneous formation of different structures, such as vesicles, micelles, and multi-lamellar structures, depending on thermodynamical conditions.
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125Izvekov, S.; Voth, G. A Multiscale Coarse-Graining Method for Biomolecular Systems J. Phys. Chem. B 2005, 109, 2469– 2473 DOI: 10.1021/jp044629qGoogle Scholar125https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXmtVSntQ%253D%253D&md5=3dd30b57cd2523f23d89ffc0c1782ac2A Multiscale Coarse-Graining Method for Biomolecular SystemsIzvekov, Sergei; Voth, Gregory A.Journal of Physical Chemistry B (2005), 109 (7), 2469-2473CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A new approach is presented for obtaining coarse-grained (CG) force fields from fully atomistic mol. dynamics (MD) trajectories. The method is demonstrated by applying it to derive a CG model for the dimyristoylphosphatidylcholine (DMPC) lipid bilayer. The coarse-graining of the interparticle force field is accomplished by an application of a force-matching procedure to the force data obtained from an explicit atomistic MD simulation of the biomol. system of interest. Hence, the method is termed a "multiscale" CG (MS-CG) approach in which explicit atomistic-level forces are propagated upward in scale to the coarse-grained level. The CG sites in the lipid bilayer application were assocd. with the centers-of-mass of at. groups because of the simplicity in the evaluation of the forces acting on them from the atomistic data. The resulting CG lipid bilayer model is shown to accurately reproduce the structural properties of the phospholipid bilayer.
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126Cho, H.; Chu, J.-W. Inversion of radial distribution functions to pair forces by solving the Yvon–Born–Green equation iteratively J. Chem. Phys. 2009, 131, 134107 DOI: 10.1063/1.3238547Google ScholarThere is no corresponding record for this reference.
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127Lu, L.; Dama, J.; Voth, G. Fitting coarse-grained distribution functions through an iterative force-matching method J. Chem. Phys. 2013, 139, 121906 DOI: 10.1063/1.4811667Google Scholar127https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVOjsLvI&md5=96fbee0c60c3130726d6c07e068188c0Fitting coarse-grained distribution functions through an iterative force-matching methodLu, Lanyuan; Dama, James F.; Voth, Gregory A.Journal of Chemical Physics (2013), 139 (12), 121906/1-121906/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)An iterative coarse-graining method is developed for systematically converting an atomistic force field to a model at lower resoln. that is able to accurately reproduce the distribution functions defined in the coarse-grained potential. The method starts from the multiscale coarse-graining (MS-CG) approach, and it iteratively refines the distribution functions using repeated applications of the MS-CG algorithm. It is justified on the basis of the force matching normal equation, which can be considered a discrete form of the Yvon-Born-Green equation in liq. state theory. Numerical results for mol. systems involving pairwise nonbonded and three-body bonded interactions are obtained, and comparison with other approaches in literature is provided. (c) 2013 American Institute of Physics.
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128Mullinax, J. W.; Noid, W. G. A Generalized-Yvon–Born–Green Theory for Determining Coarse-Grained Interaction Potentials† J. Phys. Chem. C 2010, 114, 5661– 5674 DOI: 10.1021/jp9073976Google ScholarThere is no corresponding record for this reference.
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129Shell, S. The relative entropy is fundamental to multiscale and inverse thermodynamic problems J. Chem. Phys. 2008, 129, 144108 DOI: 10.1063/1.2992060Google Scholar129https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1KlsLnI&md5=6f0951ee8fc7308e822a1efadac0d713The relative entropy is fundamental to multiscale and inverse thermodynamic problemsShell, M. ScottJournal of Chemical Physics (2008), 129 (14), 144108/1-144108/7CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The relative entropy, Srel ≡ .sum.pT ln(pT/pM), provides a fundamental and unifying framework for multiscale anal. and for inverse mol.-thermodn. problems involving optimization of a model system (M) to reproduce the properties of a target one (T). The relative entropy serves as a generating function for principles in variational mean-field theory and uniqueness and gives intuitive results for simple case scenarios in model development. Moreover, the relative entropy provides a rigorous framework for multiscale simulations and offers new numerical techniques for linking models at different scales. Finally, by using it to quantify the deviations of a three-site model of water from simple liqs., it even predicts water's kinetic anomalies. (c) 2008 American Institute of Physics.
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130Bilionis, I.; Zabaras, N. A stochastic optimization approach to coarse-graining using a relative-entropy framework J. Chem. Phys. 2013, 138, 044313 DOI: 10.1063/1.4789308Google Scholar130https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFCkuro%253D&md5=bf925cd878859b24722ab884dd561cf3A stochastic optimization approach to coarse-graining using a relative-entropy frameworkBilionis, Ilias; Zabaras, NicholasJournal of Chemical Physics (2013), 138 (4), 044313/1-044313/12CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Relative entropy has been shown to provide a principled framework for the selection of coarse-grained potentials. Despite the intellectual appeal of it, its application has been limited by the fact that it requires the soln. of an optimization problem with noisy gradients. When using deterministic optimization schemes, one is forced to either decrease the noise by adequate sampling or to resolve to ad hoc modifications in order to avoid instabilities. The former increases the computational demand of the method while the latter is of questionable validity. In order to address these issues and make relative entropy widely applicable, we propose alternative schemes for the soln. of the optimization problem using stochastic algorithms. (c) 2013 American Institute of Physics.
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131Chaimovich, A.; Shell, S. Coarse-graining errors and numerical optimization using a relative entropy framework J. Chem. Phys. 2011, 134, 094112 DOI: 10.1063/1.3557038Google Scholar131https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXislentLs%253D&md5=4de895cbb35fda9c00d6dbec8a26b255Coarse-graining errors and numerical optimization using a relative entropy frameworkChaimovich, Aviel; Shell, M. ScottJournal of Chemical Physics (2011), 134 (9), 094112/1-094112/15CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The ability to generate accurate coarse-grained models from ref. fully at. (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex mol. systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, Srel, that measures the information lost upon coarse-graining. Here, we develop a broad theor. framework for this methodol. and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodol. and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theor. considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework. (c) 2011 American Institute of Physics.
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132Chaimovich, A.; Shell, S. Relative entropy as a universal metric for multiscale errors. Phys. Rev. E 2010, 81, DOI: 10.1103/PhysRevE.81.060104Google ScholarThere is no corresponding record for this reference.
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133Espanol, P.; Zuniga, I. Obtaining fully dynamic coarse-grained models from MD Phys. Chem. Chem. Phys. 2011, 13, 10538– 10545 DOI: 10.1039/c0cp02826fGoogle Scholar133https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsFams7o%253D&md5=f1abb6b57b51940aebf9ab3a550d6e7cObtaining fully dynamic coarse-grained models from MDEspanol, Pep; Zuniga, IgnacioPhysical Chemistry Chemical Physics (2011), 13 (22), 10538-10545CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)We present a general method to obtain parametrised models for the drift and diffusion terms of the Fokker-Planck equation of a coarse-grained description of mol. systems. The method is based on the minimisation of the relative entropy defined in terms of the two-time joint probability and thus captures the full dynamics of the coarse-grained description. In addn., we show an alternative Bayesian argument that starts from the path probability of a diffusion process which allows one to obtain the best parametrised model that fits an actual obsd. path of the coarse-grained variables. Both approaches lead to exactly the same optimization function giving strong support to the methodol. We provide an heuristic argument that explains how both approaches are connected.
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134Murtola, T.; Karttunen, M.; Vattulainen, I. Systematic coarse graining from structure using internal states: application to phospholipid/cholesterol bilayer. J. Chem. Phys. 2009, 131, 055101 DOI: 10.1063/1.3167405Google ScholarThere is no corresponding record for this reference.
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135Brini, E.; van der Vegt, N. F. Chemically transferable coarse-grained potentials from conditional reversible work calculations. J. Chem. Phys. 2012, 137, 154113 DOI: 10.1063/1.4758936Google Scholar135https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFCnsLjN&md5=6032a2473dc78d055c8e80a48200ce42Chemically transferable coarse-grained potentials from conditional reversible work calculationsBrini, E.; van der Vegt, N. F. A.Journal of Chemical Physics (2012), 137 (15), 154113/1-154113/8CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The representability and transferability of effective pair potentials used in multiscale simulations of soft matter systems is ill understood. In this paper, we study liq. state systems composed of n-alkanes, the coarse-grained (CG) potential of which may be assumed pairwise additive and has been obtained using the conditional reversible work (CRW) method. The CRW method is a free-energy-based coarse-graining procedure, which, by means of performing the coarse graining at pair level, rigorously provides a pair potential that describes the interaction free energy between two mapped atom groups (beads) embedded in their resp. chem. environments. The pairwise nature of the interactions combined with their dependence on the chem. bonded environment makes CRW potentials ideally suited in studies of chem. transferability. We report CRW potentials for hexane using a mapping scheme that merges two heavy atoms in one CG bead. It is shown that the model is chem. and thermodynamically transferable to alkanes of different chain lengths in the liq. phase at temps. between the melting and the b.p. under atm. (1 atm) pressure conditions. It is further shown that CRW-CG potentials may be readily obtained from a single simulation of the liq. state using the free energy perturbation method, thereby providing a fast and versatile mol. coarse graining method for aliph. mols. (c) 2012 American Institute of Physics.
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136Deichmann, G.; Marcon, V.; van der Vegt, N. Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method J. Chem. Phys. 2014, 141, 224109 DOI: 10.1063/1.4903454Google Scholar136https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFahs7fI&md5=8db8867e8a8bf48ae7b85947d9e4ef4eBottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work methodDeichmann, Gregor; Marcon, Valentina; van der Vegt, Nico F. A.Journal of Chemical Physics (2014), 141 (22), 224109/1-224109/9CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Mol. simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodn. properties can be quite accurately represented while the prediction of dynamic properties remains difficult, esp. for multi-component systems. In this work, we use constraint mol. dynamics simulations for calcg. dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived from fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These mol. liqs. are simulated with atomistic mol. dynamics, coarse-grained mol. dynamics, and DPD. We find that the CRW-DPD models reproduce the liq. structure and diffusive dynamics of the liq. systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads contg. five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale sepn. can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics. (c) 2014 American Institute of Physics.
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137Hadley, K.; McCabe, C. Coarse-Grained Molecular Models of Water: A Review Mol. Simul. 2012, 38, 671– 681 DOI: 10.1080/08927022.2012.671942Google Scholar137https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XpvVSmtr8%253D&md5=6501a25b1713de1bda758faf959ae6f9Coarse-grained molecular models of water: a reviewHadley, Kevin R.; McCabe, ClareMolecular Simulation (2012), 38 (8-9), 671-681CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)A review. Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems involving large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger time steps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biol. importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regard to how many waters each CG group or bead represents, whether anal. or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. How the models are parameterised, which typically depends on their application, is also discussed.
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138Tanaka, S.; Scheraga, H. A. Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins Macromolecules 1976, 9, 945– 950 DOI: 10.1021/ma60054a013Google Scholar138https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE2sXht1Kh&md5=74701630ff1fddd501492dd3075fa91fMedium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteinsTanaka, Seiji; Scheraga, Harold A.Macromolecules (1976), 9 (6), 945-50CODEN: MAMOBX; ISSN:0024-9297.A hypothesis for protein folding is discussed, in which the native structure is formed by a 3-step mechanism: (A) formation of ordered backbone structures by short-range interactions, (B) formation of small contact regions by medium-range interactions, and (C) assocn. of the small contact regions into the native structure by long-range interactions. The empirical interaction parameters, used as a measure of the medium- and long-range interactions (the std. free energy, ΔG°k,l, of formation of a contact between amino acids of species k and l) that include the role of the solvent (water) and det. the conformation of a protein in steps B and C are evaluated from the frequency of contacts in the x-ray structures of native proteins. The numerical values of ΔG°k,l for all possible pairs of the 20 naturally occurring amino acids are presented. Contacts between highly nonpolar side chains of amino acids such as isoleucine, phenylalanine, tryptophan, and leucine are shown quant. to be stable. On the contrary, contacts involving polar side chains of amino acids such as serine, aspartate, lysine, and glutamate are significantly less stable. While this implies, in a quant. manner, that it is generally more favorable for nonpolar groups to lie in the interior of the protein mol. and for the polar side chains to be exposed to the solvent (water) rather than to form contacts with other amino acids, many exceptions to this generalization are obsd.
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139Samudrala, R.; Moult, J. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction J. Mol. Biol. 1998, 275, 895– 916 DOI: 10.1006/jmbi.1997.1479Google Scholar139https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXhs12jtLc%253D&md5=b9b6226434dfe70a5b96d43d67c5097dAn all-atom distance-dependent conditional probability discriminatory function for protein structure predictionSamudrala, Ram; Moult, JohnJournal of Molecular Biology (1998), 275 (5), 895-916CODEN: JMOBAK; ISSN:0022-2836. (Academic Press Ltd.)We present a formalism to compute the probability of an amino acid sequence conformation being native-like, given a set of pairwise atom-atom distances. The formalism is used to derive three discriminatory functions with different types of representations for the atom-atom contacts obsd. in a database of protein structures. These functions include two virtual atom representations and one all-heavy atom representation. When applied to six different decoy sets contg. a range of correct and incorrect conformations of amino acid sequences, the all-atom distance-dependent discriminatory function is able to identify correct from incorrect more often than the discriminatory functions using approx. representations. We illustrate the importance of using a detailed at. description for obtaining the most accurate discrimination, and the necessity for testing discriminatory functions against a wide variety of decoys. The discriminatory function is also shown to be capable of capturing the fine details of atom-atom preferences. These results suggest that the all-atom distance-dependent discriminatory function will be useful for protein structure prediction and model refinement.
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140Simons, K. T.; Ruczinski, I.; Kooperberg, C.; Fox, B. A.; Bystroff, C.; Baker, D. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins Proteins: Struct., Funct., Genet. 1999, 34, 82– 95 DOI: 10.1002/(SICI)1097-0134(19990101)34:1<82::AID-PROT7>3.0.CO;2-AGoogle ScholarThere is no corresponding record for this reference.
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141Xia, Y.; Levitt, M. Extracting knowledge-based energy functions from protein structures by error rate minimization: Comparison of methods using lattice model J. Chem. Phys. 2000, 113, 9318– 9330 DOI: 10.1063/1.1320823Google Scholar141https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXnvFaiu7g%253D&md5=9a749625cdf3ea2dfb1119109e14d564Extracting knowledge-based energy functions from protein structures by error rate minimization: Comparison of methods using lattice modelXia, Yu; Levitt, MichaelJournal of Chemical Physics (2000), 113 (20), 9318-9330CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)We describe a general framework for extg. knowledge-based energy function from a set of native protein structures. In this scheme, the energy function is optimal when there is least chance that a random structure has a lower energy than the corresponding native structure. We first show that subject to certain approxns., most current database-derived energy functions fall within this framework, including mean-field potentials, Z-score optimization, and constraint satisfaction methods. We then propose a simple method for energy function parametrization derived from our anal. We go on to compare our method to other methods using a simple lattice model in the context of three different energy function scenarios. We show that our method, which is based on the most stringent criteria, performs best in all cases. The power and limitations of each method for deriving knowledge-based energy function is examd.
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142Sippl, M. J. Boltzmann’s principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures J. Comput.-Aided Mol. Des. 1993, 7, 473– 501 DOI: 10.1007/BF02337562Google ScholarThere is no corresponding record for this reference.
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143Skolnick, J.; Kolinski, A.; Ortiz, A. Derivation of protein-specific pair potentials based on weak sequence fragment similarity Proteins: Struct., Funct., Genet. 2000, 38, 3– 16 DOI: 10.1002/(SICI)1097-0134(20000101)38:1<3::AID-PROT2>3.0.CO;2-SGoogle Scholar143https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXis1OmsQ%253D%253D&md5=8ceddaaf101fe7e269464144b91a1bd7Derivation of protein-specific pair potentials based on weak sequence fragment similaritySkolnick, Jeffrey; Kolinski, Andrzej; Ortiz, AngelProteins: Structure, Function, and Genetics (2000), 38 (1), 3-16CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)A method is presented for the derivation of knowledge-based pair potentials that corrects for the various compns. of different proteins. The resulting statistical pair potential is more specific than that derived from previous approaches as assessed by gapless threading results. Addnl., a methodol. is presented that interpolates between statistical potentials when no homologous examples to the protein of interest are in the structural database used to derive the potential, to a Go-like potential (in which native interactions are favorable and all nonnative interactions are not) when homologous proteins are present. For cases in which no protein exceeds 30% sequence identity, pairs of weakly homologous interacting fragments are employed to enhance the specificity of the potential. In gapless threading, the mean z score increases from -10.4 for the best statistical pair potential to -12.8 when the local sequence similarity, fragment-based pair potentials are used. Examn. of the ab initio structure prediction of four representative globular proteins consistently reveals a qual. improvement in the yield of structures in the 4 to 6 Å rmsd from native range when the fragment-based pair potential is used relative to that when the quasichem. pair potential is employed. This suggests that such protein-specific potentials provide a significant advantage relative to genetic quasichem. potentials.
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144Godzik, A.; Kolinski, A.; Skolnick, J. Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets Protein Sci. 1995, 4, 2107– 2117 DOI: 10.1002/pro.5560041016Google Scholar144https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXoslygt78%253D&md5=b6eb3c3c9e36bd2db5bf98e4bb9fd90bAre proteins ideal mixtures of amino acids? Analysis of energy parameter setsGodzik, Adam; Kolinski, Andrzej; Skolnick, JeffreyProtein Science (1995), 4 (10), 2107-17CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)Various existing derivations of the effective potentials of mean force for the two-body interactions between amino acid side chains in proteins are reviewed and compared to each other. The differences between different parameters sets can be traced to the ref. state used to define the zero of energy. Depending on the ref. state, the transfer free energy or other pseudo-one-body contributions can be present to various extents in two-body parameters sets. It is, however, possible to compare various derivations directly by concg. on the "excess" energy - a term that describes the difference between a real protein and an ideal soln. of amino acids. Furthermore, the no. of protein structures available for anal. allows one to check the consistency of the derivation and the errors by comparing parameters derived from various subsets of the whole database. It is shown that pair interaction preferences are very consistent throughout the database. Independently derived parameter sets have correlation coeffs. on the order of 0.8, with the mean difference between equiv. entries of 0.1 kT. Also, the low-quality (low resoln., little or no refinement) structures show similar regularities. There are, however, large differences between interaction parameters derived on the basis of crystallog. structures and structures obtained by the NMR refinement. The origin of the latter difference is not yet understood.
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145Skolnick, J.; Jaroszewski, L.; Kolinski, A.; Godzik, A. Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct? Protein Sci. 1997, 6, 676– 688 DOI: 10.1002/pro.5560060317Google Scholar145https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXhvVyjtLY%253D&md5=000d63b0a6f7eca713917b07d714031eDerivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct?Skolnick, Jeffrey; Jaroszewski, Lukasz; Kolinski, Andrzej; Godzik, AdamProtein Science (1997), 6 (3), 676-688CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)Many existing derivations of knowledge-based statistical pair potentials invoke the quasichem. approxn. to est. the expected side-chain contact frequency if there were no amino acid pair-specific interactions. At first glance, the quasichem. approxn. that treats the residues in a protein as being disconnected and expresses the side-chain contact probability as being proportional to the product of the mole fractions of the pair of residues would appear to be rather severe. To investigate the validity of this approxn., we introduce two new ref. states in which no specific pair interactions between amino acids are allowed, but in which the connectivity of the protein chain is retained. The first ests. the expected no. of side-chain contacts by treating the protein as a Gaussian random coil polymer. The second, more realistic ref. state includes the effects of chain connectivity, secondary structure, and chain compactness by estg. the expected side-chain contact probability by placing the sequence of interest in each member of a library of structures of comparable compactness to the native conformation. The side-chain contact maps are not allowed to readjust to the sequence of interest, i.e., the side chains cannot repack. This situation would hold rigorously if all amino acids were the same size. Both ref. states effectively permit the factorization of the side-chain contact probability into sequence-dependent and structure-dependent terms. Then, because the sequence distribution of amino acids in proteins is random, the quasichem. approxn. to each of these ref. states is shown to be excellent. Thus, the range of validity of the quasichem. approxn. is detd. by the magnitude of the side-chain repacking term, which is, at present, unknown. Finally, the performance of these two sets of pair interaction potentials as well as side-chain contact fraction-based interaction scales is assessed by inverse folding tests both without and with allowing for gaps.
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146Majek, P.; Elber, R. A coarse-grained potential for fold recognition and molecular dynamics simulations of proteins Proteins: Struct., Funct., Genet. 2009, 76, 822– 836 DOI: 10.1002/prot.22388Google ScholarThere is no corresponding record for this reference.
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147Zhou, Y.; Zhou, H.; Zhang, C.; Liu, S. What is a desirable statistical energy function for proteins and how can it be obtained? Cell Biochem. Biophys. 2006, 46, 165– 174 DOI: 10.1385/CBB:46:2:165Google Scholar147https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht1yks7zP&md5=e1fbf180781f9d4a021e758a87998ca2What is a desirable statistical energy function for proteins and how can it be obtained?Zhou, Yaoqi; Zhou, Hongyi; Zhang, Chi; Liu, SongCell Biochemistry and Biophysics (2006), 46 (2), 165-174CODEN: CBBIFV; ISSN:1085-9195. (Humana Press Inc.)A review. Can one obtain a phys. energy function for proteins from statistical anal. of protein structures. A direct answer to this question is likely "no.". A less demanding question is whether one can produce a statistical energy function that has the desirable features of a phys.-based energy function. Such a desirable energy function would be founded on a phys. basis with few or no adjustable parameters, reproduce the known phys. characters of amino acid residues, be mostly database independent and transferable, and, more importantly, reasonably accurate in various applications. In this review, we show how such a desirable energy function can be obtained via introducing a simple phys.-based ref. state called DFIRE (Distance-scaled, Finite, Ideal-gas Ref. state).
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148Shen, M.-Y.; Sali, A. Statistical potential for assessment and prediction of protein structures Protein Sci. 2006, 15, 2507– 2524 DOI: 10.1110/ps.062416606Google Scholar148https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtFygsrfO&md5=f4e7ef56cd100164e347103a6888ee8eStatistical potential for assessment and prediction of protein structuresShen, Min-Yi; Sali, AndrejProtein Science (2006), 15 (11), 2507-2524CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Protein structures in the Protein Data Bank provide a wealth of data about the interactions that det. the native states of proteins. Using the probability theory, the authors derive an at. distance-dependent statistical potential from a sample of native structures that does not depend on any adjustable parameters (Discrete Optimized Protein Energy, or DOPE). DOPE is based on an improved ref. state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on a sample native structure; it thus accounts for the finite and spherical shape of the native structures. The DOPE potential was extd. from a nonredundant set of 1472 crystallog. structures. The authors tested DOPE and five other scoring functions by the detection of the native state among six multiple target decoy sets, the correlation between the score and model error, and the identification of the most accurate nonnative structure in the decoy set. For all decoy sets, DOPE is the best performing function in terms of all criteria, except for a tie in one criterion for one decoy set. To facilitate its use in various applications, such as model assessment, loop modeling, and fitting into cryo-electron microscopy mass d. maps combined with comparative protein structure modeling, DOPE was incorporated into the modeling package MODELLER-8.
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149Yang, Y.; Zhou, Y. Specific interactions for ab initio folding of protein terminal regions with secondary structures Proteins: Struct., Funct., Genet. 2008, 72, 793– 803 DOI: 10.1002/prot.21968Google Scholar149https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnvVWhtLY%253D&md5=76ea31cb102de1f066ef595662b70b86Specific interactions for ab initio folding of protein terminal regions with secondary structuresYang, Yuedong; Zhou, YaoqiProteins: Structure, Function, and Bioinformatics (2008), 72 (2), 793-803CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Proteins fold into unique three-dimensional structures by specific, orientation-dependent interactions between amino acid residues. Here, we ext. orientation-dependent interactions from protein structures by treating each polar atom as a dipole with a direction. The resulting statistical energy function successfully refolds 13 out of 16 fully unfolded secondary-structure terminal regions of 10-23 amino acid residues in 15 small proteins. Dissecting the orientation-dependent energy function reveals that the orientation preference between hydrogen-bonded atoms is not enough to account for the structural specificity of proteins. The result has significant implications on the theor. and exptl. searches for specific interactions involved in protein folding and mol. recognition between proteins and other biol. active mols.
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150Zhou, H.; Skolnick, J. GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction Biophys. J. 2011, 101, 2043– 2052 DOI: 10.1016/j.bpj.2011.09.012Google Scholar150https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtlarsLrN&md5=01a3d1248a993dd67b576813be074460GOAP: A Generalized Orientation-Dependent, All-Atom Statistical Potential for Protein Structure PredictionZhou, Hongyi; Skolnick, JeffreyBiophysical Journal (2011), 101 (8), 2043-2052CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)An accurate scoring function is a key component for successful protein structure prediction. To address this important unsolved problem, the authors develop a generalized orientation and distance-dependent all-atom statistical potential. The new statistical potential, generalized orientation-dependent all-atom potential (GOAP), depends on the relative orientation of the planes assocd. with each heavy atom in interacting pairs. GOAP is a generalization of previous orientation-dependent potentials that consider only representative atoms or blocks of side-chain or polar atoms. GOAP is decompd. into distance- and angle-dependent contributions. The DFIRE distance-scaled finite ideal gas ref. state is employed for the distance-dependent component of GOAP. GOAP was tested on 11 commonly used decoy sets contg. 278 targets, and recognized 226 native structures as best from the decoys, whereas DFIRE recognized 127 targets. The major improvement comes from decoy sets that have homol.-modeled structures that are close to native (all within ∼4.0 Å) or from the ROSETTA ab initio decoy set. For these two kinds of decoys, orientation-independent DFIRE or only side-chain orientation-dependent RWplus performed poorly. Although the OPUS-PSP block-based orientation-dependent, side-chain atom contact potential performs much better (recognizing 196 targets) than DFIRE, RWplus, and dDFIRE, it is still ∼15% worse than GOAP. Thus, GOAP is a promising advance in knowledge-based, all-atom statistical potentials. GOAP is available for download at http://cssb.biol.gatech.edu/GOAP/index.html.
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151Park, J.; Saitou, K. ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures BMC Bioinf. 2014, 15, 307 DOI: 10.1186/1471-2105-15-307Google Scholar151https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXmsVeitw%253D%253D&md5=cd6522b7bc813721e763fbf079dc17f2ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structuresPark, Jungkap; Saitou, KazuhiroBMC Bioinformatics (2014), 15 (), 307/1-307/16, 16 pp.CODEN: BBMIC4; ISSN:1471-2105. (BioMed Central Ltd.)Background: Multibody potentials accounting for cooperative effects of mol. interactions have shown better accuracy than typical pairwise potentials. The main challenge in the development of such potentials is to find relevant structural features that characterize the tightly folded proteins. Also, the side-chains of residues adopt several specific, staggered conformations, known as rotamers within protein structures. Different mol. conformations result in different dipole moments and induce charge reorientations. However, until now modeling of the rotameric state of residues had not been incorporated into the development of multibody potentials for modeling non-bonded interactions in protein structures. Results: In this study, we develop a new multibody statistical potential which can account for the influence of rotameric states on the specificity of at. interactions. In this potential, named "rotamer-dependent at. statistical potential" (ROTAS), the interaction between two atoms is specified by not only the distance and relative orientation but also by two state parameters concerning the rotameric state of the residues to which the interacting atoms belong. It was clearly found that the rotameric state is correlated to the specificity of at. interactions. Such rotamer-dependencies are not limited to specific type or certain range of interactions. The performance of ROTAS was tested using 13 sets of decoys and was compared to those of existing at.-level statistical potentials which incorporate orientation-dependent energy terms. The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coeffs. between energy and model quality. Conclusions: A new multibody statistical potential, ROTAS accounting for the influence of rotameric states on the specificity of at. interactions was developed and tested on decoy sets. The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials. The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation anal., and docking simulation.
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152Gront, D.; Kolinski, A. A new approach to prediction of short-range conformational propensities in proteins Bioinformatics 2005, 21, 981– 987 DOI: 10.1093/bioinformatics/bti080Google ScholarThere is no corresponding record for this reference.
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153Amir, E.-A.; Kalisman, N.; Keasar, C. Differentiable, multi-dimensional, knowledge-based energy terms for torsion angle probabilities and propensities Proteins: Struct., Funct., Genet. 2008, 72, 62– 73 DOI: 10.1002/prot.21896Google ScholarThere is no corresponding record for this reference.
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154Levy-Moonshine, A.; Amir, E.-a.; Keasar, C. Enhancement of beta-sheet assembly by cooperative hydrogen bonds potential Bioinformatics 2009, 25, 2639– 2645 DOI: 10.1093/bioinformatics/btp449Google ScholarThere is no corresponding record for this reference.
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155Liwo, A.; Arlukowicz, P.; Czaplewski, C.; Oldziej, S.; Pillardy, J.; Scheraga, H. A. A method for optimizing potential-energy functions by a hierarchical design of the potential-energy landscape: application to the UNRES force field Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 1937– 1942 DOI: 10.1073/pnas.032675399Google Scholar155https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XitVSrs7g%253D&md5=b15e4aabda4291e16ed7f32ae383b506A method for optimizing potential-energy functions by a hierarchical design of the potential-energy landscape: application to the UNRES force fieldLiwo, Adam; Arlukowicz, Piotr; Czaplewski, Cezary; Oldziej, Stanislaw; Pillardy, Jaroslaw; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2002), 99 (4), 1937-1942CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)A method for optimizing potential-energy functions of proteins is proposed. The method assumes a hierarchical structure of the energy landscape, which means that the energy decreases as the no. of native-like elements in a structure increases, being lowest for structures from the native family and highest for structures with no native-like element. A level of the hierarchy is defined as a family of structures with the same no. of native-like elements (or degree of native likeness). Optimization of a potential-energy function is aimed at achieving such a hierarchical structure of the energy landscape by forcing appropriate free-energy gaps between hierarchy levels to place their energies in ascending order. This procedure is different from methods developed thus far, in which the energy gap and/or the Z score between the native structure and all non-native structures are maximized, regardless of the degree of native likeness of the non-native structures. The advantage of this approach lies in reducing the no. of structures with decreasing energy, which should ensure the searchability of the potential. The method was tested on two proteins, PDB ID codes 1FSD and 1IGD, with an off-lattice united-residue force field. For 1FSD, the search of the conformational space with the use of the conformational space annealing method and the newly optimized potential-energy function found the native structure very quickly, as opposed to the potential-energy functions obtained by former optimization methods. After even incomplete optimization, the force field obtained by using 1IGD located the native-like structures of two peptides, 1FSD and betanova (a designed three-stranded β-sheet peptide), as the lowest-energy conformations, whereas for the 46-residue N-terminal fragment of staphylococcal protein A, the native-like conformation was the second-lowest-energy conformation and had an energy 2 kcal/mol above that of the lowest-energy structure.
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156Mirny, L. A.; Shakhnovich, E. I. How to Derive a Protein Folding Potential? A New Approach to an Old Problem J. Mol. Biol. 1996, 264, 1164– 1179 DOI: 10.1006/jmbi.1996.0704Google Scholar156https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXnt12h&md5=07dd006c009b51f8572b6ad4189d50bfHow to drive a protein folding potential? A New approach to an old problemMirny, Leonid A.; Shakhnovich, Eugene I.Journal of Molecular Biology (1996), 264 (5), 1164-1179CODEN: JMOBAK; ISSN:0022-2836. (Academic)In this paper we introduce a novel method of deriving a pairwise potential of protein folding. The potential is obtained by an optimization procedure that simultaneously maximizes thermodn. stability for all proteins in the database. When applied to the representative dataset of proteins and with the energy function taken in pairwise contact approxn., our potential scored somewhat better than existing ones. However, the discrimination of the native structure from decoys is still not strong enough to make the potential useful for ab initio folding. Our results suggest that the problem lies with pairwise amino acid contact approxn. and/or simplified presentation of proteins rather than with the derivation of potential. We argue that more detail of protein structure and energetics should be taken into account to achieve energy gaps. The suggested method is general enough to allow us to systematically derive parameters for more sophisticated energy functions. The internal control of validity for the potential derived by our method is convergence to a unique soln. upon addn. of new proteins to the database. The method is tested on simple model systems where sequences are designed, using the preset "true" potential, to have low energy in a dataset of structures. Our procedure is able to recover the potential with correlation r ≈ 91% with the true one and we were able to old all model structures using the recovered potential. Other statistical knowledge-based approaches were tested using this model and the results indicate that they also can recover the true potential with high degree of accuracy.
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157Maiorov, V. N.; Grippen, G. M. Contact Potential That Recognizes the Correct Folding of Globular-Proteins J. Mol. Biol. 1992, 227, 876– 888 DOI: 10.1016/0022-2836(92)90228-CGoogle ScholarThere is no corresponding record for this reference.
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158Chiu, T.-L.; Goldstein, R. A. Optimizing energy potentials for success in protein tertiary structure prediction Folding Des. 1998, 3, 223– 228 DOI: 10.1016/S1359-0278(98)00030-3Google Scholar158https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXktVShsbw%253D&md5=deaeba089948a4fd8bc09ad7f042051dOptimizing energy potentials for success in protein tertiary structure predictionChiu, Ting-Lan; Goldstein, Richard A.Folding & Design (1998), 3 (3), 223-228CODEN: FODEFH; ISSN:1359-0278. (Current Biology Ltd.)Success in solving the protein structure prediction problem relies on the choice of an accurate potential energy function. For a single protein sequence, it has been shown that the potential energy function can be optimized for predictive success by maximizing the energy gap between the correct structure and the ensemble of random structures relative to the distribution of the energies of these random structures (the Z-score). Different methods have been described for implementing this procedure for an ensemble of database proteins. Here, we demonstrate a new approach. For a single protein sequence, the probability of success (i.e. the probability that the folded state is the lowest energy state) is derived. We then maximize the av. probability of success for a set of proteins to obtain the optimal potential energy function. This results in max. attention being focused on the proteins whose structures are difficult but not impossible to predict. Using a lattice model of proteins, we show that the optimal interaction potentials obtained by our method are both more accurate and more likely to produce successful predictions than those obtained by other averaging procedures.
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159Hao, M.-H.; Scheraga, H. A. Optimizing Potential Functions for Protein Folding J. Phys. Chem. 1996, 100, 14540– 14548 DOI: 10.1021/jp960856jGoogle ScholarThere is no corresponding record for this reference.
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160Sippl, M. J. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins J. Mol. Biol. 1990, 213, 859– 883 DOI: 10.1016/S0022-2836(05)80269-4Google Scholar160https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXkvFCgs7Y%253D&md5=e675356b4ab5e0114cd027ea92c00d90Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteinsSippl, Manfred J.Journal of Molecular Biology (1990), 213 (4), 859-83CODEN: JMOBAK; ISSN:0022-2836.A prototype of a new approach to the folding problem of polypeptide chains is presented. This approach is based on the anal. of known protein structures. It derives the energy potentials for the at. interactions of all amino acid residue pairs as a function of the distance between the involved atoms. These potentials are then used to calc. the energies of all conformations that exist in the data base with respect to a given sequence. Then, by using only the most stable conformations, clusters of the most probable conformations for the given sequence are obtained. The use of the method is demonstrated in the discussion of the identical oligopeptide sequences found in different conformations is unrelated proteins. VNTFV, for example, adopts a β-strand in RNase but it is found in an α-helical conformation in erythrocruorin. In the case of VNTFV the ensemble obtained consists of a single cluster of β-strand conformations, indicating that this may be the preferred conformation for the pentapeptide. When the flanking residues are included in the calcn. the hepapeptide P-VNTFV-H (RNase) again yields an ensemble of β-strands. However, in the ensemble of D-VNTFV-A (erythrocruorin) the major cluster is of α-helical type. The present study concs. on the local aspects of protein conformations. However, the theory presented is quite general and not restricted to oligopeptides. Extensions of the approach to the calcn. of global conformations of proteins as well as conceivable applications to a no. of mol. systems are discussed.
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161Hamelryck, T.; Borg, M.; Paluszewski, M.; Paulsen, J.; Frellsen, J.; Andreetta, C.; Boomsma, W.; Bottaro, S.; Ferkinghoff-Borg, J. Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized PLoS One 2010, 5, e13714 DOI: 10.1371/journal.pone.0013714Google ScholarThere is no corresponding record for this reference.
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162Gniewek, P.; Leelananda, S. P.; Kolinski, A.; Jernigan, R. L.; Kloczkowski, A. Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models Proteins: Struct., Funct., Genet. 2011, 79, 1923– 1929 DOI: 10.1002/prot.23015Google ScholarThere is no corresponding record for this reference.
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163Elhefnawy, W.; Chen, L.; Han, Y.; Li, Y. ICOSA: A Distance-Dependent, Orientation-Specific Coarse-Grained Contact Potential for Protein Structure Modeling J. Mol. Biol. 2015, 427, 2562– 2576 DOI: 10.1016/j.jmb.2015.05.022Google Scholar163https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVWgu7bI&md5=dfedad9b22d1ad603e31ccc4389cbb2cICOSA: A Distance-Dependent, Orientation-Specific Coarse-Grained Contact Potential for Protein Structure ModelingElhefnawy, Wessam; Chen, Lin; Han, Yun; Li, YaohangJournal of Molecular Biology (2015), 427 (15), 2562-2576CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The relative distance and orientation in contacting residue pairs plays a significant role in protein folding and stabilization. We hereby devise a new knowledge-based, coarse-grained contact potential, so-called ICOSA, by correlating inter-residue contact distance and orientation in evaluating pair-wise inter-residue interactions. The rationale of our approach is to establish icosahedral local coordinates to est. the statistical residue contact distributions in all spherical triangular shells within a sphere. We extend the theory of finite ideal gas ref. state to icosahedral local coordinates. ICOSA incorporates long-range contact interactions, which is crit. to ICOSA sensitivity and is justified in statistical rigor. With only backbone atoms information, ICOSA is at least comparable to all-atom, fine-grained potentials such as Rosetta, DFIRE, I-TASSER, and OPUS in discriminating near-natives from misfold protein conformations in the Rosetta and I-TASSER protein decoy sets. ICOSA also outperforms a set of widely used coarse-grained potentials and is comparable to all-atom, fine-grained potentials in identifying CASP10 models.
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164Sankar, K.; Liu, J.; Wang, Y.; Jernigan, R. L. Distributions of experimental protein structures on coarse-grained free energy landscapes J. Chem. Phys. 2015, 143, 243153 DOI: 10.1063/1.4937940Google Scholar164https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVyns7nK&md5=90126ec718f1c24f3d6ce08968a54d58Distributions of experimental protein structures on coarse-grained free energy landscapesSankar, Kannan; Liu, Jie; Wang, Yuan; Jernigan, Robert L.Journal of Chemical Physics (2015), 143 (24), 243153/1-243153/12CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Predicting conformational changes of proteins is needed to fully comprehend functional mechanisms. With the large no. of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component anal. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. The authors use principal component anal. of exptl. structures of 50 diverse proteins to ext. the most important directions of their motions, sample structures along these directions, and est. their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ ATPase (SERCA), as examples, such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, also Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. (c) 2015 American Institute of Physics.
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165Zaborowski, B.; Jagieła, D.; Czaplewski, C.; Hałabis, A.; Lewandowska, A.; Żmudzińska, W.; Ołdziej, S.; Karczyńska, A.; Omieczynski, C.; Wirecki, T. A Maximum-Likelihood Approach to Force-Field Calibration J. Chem. Inf. Model. 2015, 55, 2050– 2070 DOI: 10.1021/acs.jcim.5b00395Google Scholar165https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlWiu73J&md5=13f2e4c5fa16d448e9019771678c2bb5A Maximum-Likelihood Approach to Force-Field CalibrationZaborowski, Bartlomiej; Jagiela, Dawid; Czaplewski, Cezary; Halabis, Anna; Lewandowska, Agnieszka; Zmudzinska, Wioletta; Oldziej, Stanislaw; Karczynska, Agnieszka; Omieczynski, Christian; Wirecki, Tomasz; Liwo, AdamJournal of Chemical Information and Modeling (2015), 55 (9), 2050-2070CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A new approach to the calibration of the force fields is proposed, in which the force-field parameters were obtained by max.-likelihood fitting of the calcd. conformational ensembles to the exptl. ensembles of training system(s). The max.-likelihood function is composed of logarithms of the Boltzmann probabilities of the exptl. conformations, calcd. with the current energy function. Because the theor. distribution is given as the simulated conformations only, the contributions from all of the simulated conformations, with Gaussian wts. in the distances from a given exptl. conformation, were added to give the contribution to the target function from this conformation. In contrast to earlier methods for force-field calibration, the approach does not suffer from the arbitrariness of dividing the decoy set into native-like and non-native structures; however, if such a division is made instead of using Gaussian wts., application of the max.-likelihood method results in the known energy-gap maximization. The computational procedure consists of cycles of decoy generation and max.-likelihood-function optimization, which are iterated until convergence is reached. The method was tested with Gaussian distributions and then applied to the physics-based coarse-grained UNRES force field for proteins. The NMR structures of the tryptophan cage, a small α-helical protein, detd. at three temps. (T = 280, 305, and 313 K) by Halabis et al., were used. Multiplexed replica-exchange mol. dynamics was used to generate the decoys. The iterative procedure exhibited steady convergence. Three variants of optimization were tried: optimization of the energy-term wts. alone and use of the exptl. ensemble of the folded protein only at T = 280 K (run 1); optimization of the energy-term wts. and use of exptl. ensembles at all three temps. (run 2); and optimization of the energy-term wts. and the coeffs. of the torsional and multibody energy terms and use of exptl. ensembles at all three temps. (run 3). The force fields were subsequently tested with a set of 14 α-helical and two α + β proteins. Optimization run 1 resulted in better agreement with the exptl. ensemble at T = 280 K compared with optimization run 2 and in comparable performance on the test set but poorer agreement of the calcd. folding temp. with the exptl. folding temp. Optimization run 3 resulted in the best fit of the calcd. ensembles to the exptl. ones for the tryptophan cage but in much poorer performance on the training set, suggesting that use of a small α-helical protein for extensive force-field calibration resulted in overfitting of the data for this protein at the expense of transferability. The optimized force field resulting from run 2 was found to fold 13 of the 14 tested α-helical proteins and one small α + β protein with the correct topologies; the av. structures of 10 of them were predicted with accuracies of ∼5 Å Cα root-mean-square deviation or better. Test simulations with an addnl. set of 12 α-helical proteins demonstrated that this force field performed better on α-helical proteins than the previous parametrizations of UNRES. The proposed approach is applicable to any problem of max.-likelihood parameter estn. when the contributions to the max.-likelihood function cannot be evaluated at the exptl. points and the dimension of the configurational space is too high to construct histograms of the exptl. distributions.
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166Rykunov, D.; Fiser, A. New statistical potential for quality assessment of protein models and a survey of energy functions BMC Bioinf. 2010, 11, 128 DOI: 10.1186/1471-2105-11-128Google Scholar166https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3c3lsVCjug%253D%253D&md5=a1288fb0ef40c65460b01e315d22c132New statistical potential for quality assessment of protein models and a survey of energy functionsRykunov Dmitry; Fiser AndrasBMC bioinformatics (2010), 11 (), 128 ISSN:.BACKGROUND: Scoring functions, such as molecular mechanic forcefields and statistical potentials are fundamentally important tools in protein structure modeling and quality assessment. RESULTS: The performances of a number of publicly available scoring functions are compared with a statistical rigor, with an emphasis on knowledge-based potentials. We explored the effect on accuracy of alternative choices for representing interaction center types and other features of scoring functions, such as using information on solvent accessibility, on torsion angles, accounting for secondary structure preferences and side chain orientation. Partially based on the observations made, we present a novel residue based statistical potential, which employs a shuffled reference state definition and takes into account the mutual orientation of residue side chains. Atom- and residue-level statistical potentials and Linux executables to calculate the energy of a given protein proposed in this work can be downloaded from http://www.fiserlab.org/potentials. CONCLUSIONS: Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality.
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167Fornes, O.; Garcia-Garcia, J.; Bonet, J.; Oliva, B. On the use of knowledge-based potentials for the evaluation of models of protein-protein, protein-DNA, and protein-RNA interactions Adv. Protein Chem. Struct. Biol. 2014, 94, 77– 120 DOI: 10.1016/B978-0-12-800168-4.00004-4Google Scholar167https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2crjs1ehsA%253D%253D&md5=24ac1ef22f2e5f88f0020f4c62ba3c28On the use of knowledge-based potentials for the evaluation of models of protein-protein, protein-DNA, and protein-RNA interactionsFornes Oriol; Garcia-Garcia Javier; Bonet Jaume; Oliva BaldoAdvances in protein chemistry and structural biology (2014), 94 (), 77-120 ISSN:.Proteins are the bricks and mortar of cells, playing structural and functional roles. In order to perform their function, they interact with each other as well as with other biomolecules such as DNA or RNA. Therefore, to fathom the function of a protein, we require knowing its partners and the atomic details of its interactions (i.e., the structure of the complex). However, the amount of protein interactions with an experimentally determined three-dimensional structure is scarce. Therefore, computational techniques such as homology modeling are foremost to fill this gap. Protein interactions can be modeled using as templates the interactions of homologous proteins, if the structure of the complex is known, or using docking methods. In both approaches, the estimation of the quality of models is essential. There are several ways to address this problem. In this review, we focus on the use of knowledge-based potentials for the analysis of protein interactions. We describe the procedure to derive statistical potentials and split them into different energetic terms that can be used for different purposes. We extensively discuss the fields where knowledge-based potentials have been successfully applied to (1) model protein-protein, protein-DNA, and protein-RNA interactions and (2) predict binding sites (in the protein and in the DNA). Moreover, we provide ready-to-use resources for docking and benchmarking protein interactions.
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168Lu, M.; Dousis, A. D.; Ma, J. OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing J. Mol. Biol. 2008, 376, 288– 301 DOI: 10.1016/j.jmb.2007.11.033Google Scholar168https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXpt1ymug%253D%253D&md5=739d2650194c03c57c2a93a18de75e4eOPUS-PSP: An Orientation-dependent Statistical All-atom Potential Derived from Side-chain PackingLu, Mingyang; Dousis, Athanasios D.; Ma, JianpengJournal of Molecular Biology (2008), 376 (1), 288-301CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Here we report an orientation-dependent statistical all-atom potential derived from side-chain packing, named OPUS-PSP. It features a basis set of 19 rigid-body blocks extd. from the chem. structures of all 20 amino acid residues. The potential is generated from the orientation-specific packing statistics of pairs of those blocks in a non-redundant structural database. The purpose of such an approach is to capture the essential elements of orientation dependence in mol. packing interactions. Tests of OPUS-PSP on commonly used decoy sets demonstrate that it significantly outperforms most of the existing knowledge-based potentials in terms of both its ability to recognize native structures and consistency in achieving high Z-scores across decoy sets. As OPUS-PSP excludes interactions among main-chain atoms, its success highlights the crucial importance of side-chain packing in forming native protein structures. Moreover, OPUS-PSP does not explicitly include solvation terms, and thus the potential should perform well when the solvation effect is difficult to det., such as in membrane proteins. Overall, OPUS-PSP is a generally applicable potential for protein structure modeling, esp. for handling side-chain conformations, one of the most difficult steps in high-accuracy protein structure prediction and refinement.
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169Buchete, N. V.; Straub, J. E.; Thirumalai, D. Anisotropic coarse-grained statistical potentials improve the ability to identify nativelike protein structures J. Chem. Phys. 2003, 118, 7658– 7671 DOI: 10.1063/1.1561616Google ScholarThere is no corresponding record for this reference.
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170Zhang, Y.; Kolinski, A.; Skolnick, J. TOUCHSTONE II: a new approach to ab initio protein structure prediction Biophys. J. 2003, 85, 1145– 1164 DOI: 10.1016/S0006-3495(03)74551-2Google Scholar170https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXmtVyksLo%253D&md5=fc9f9be1925dfac8010d81ff268792edTOUCHSTONE II: A new approach to Ab initio protein structure predictionZhang, Yang; Kolinski, Andrzej; Skolnick, JeffreyBiophysical Journal (2003), 85 (2), 1145-1164CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting Cα atoms, with attached Cβ atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical anal. of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30×60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36∼120 residues) with predicted structures having a RMSD from native below 6.5 Å in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36∼174 residues) with structures having a RMSD to native below 6.5 Å in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, esp. when the accuracy of side-chain contact prediction is >20%. For native fold selection, we introduce quantities dependent on the cluster d. and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.
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171Kolinski, A.; Bujnicki, J. M. Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models Proteins: Struct., Funct., Genet. 2005, 61, 84– 90 DOI: 10.1002/prot.20723Google ScholarThere is no corresponding record for this reference.
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172Xu, D.; Zhang, J.; Roy, A.; Zhang, Y. Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement Proteins: Struct., Funct., Genet. 2011, 79, 147– 160 DOI: 10.1002/prot.23111Google ScholarThere is no corresponding record for this reference.
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173Roy, A.; Kucukural, A.; Zhang, Y. I-TASSER: a unified platform for automated protein structure and function prediction Nat. Protoc. 2010, 5, 725– 738 DOI: 10.1038/nprot.2010.5Google Scholar173https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXksVahs74%253D&md5=1ee011981433cbe8a3a6dae8cb6f68f7I-TASSER: a unified platform for automated protein structure and function predictionRoy, Ambrish; Kucukural, Alper; Zhang, YangNature Protocols (2010), 5 (4), 725-738CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) at. models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission nos. and Gene Ontol. terms. An est. of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.
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174Taketomi, H.; Ueda, Y.; Go, N. Studies on protein folding, unfolding and fluctuations by computer simulation. I. The effect of specific amino acid sequence represented by specific inter-unit interactions Int. J. Pept. Protein Res. 1975, 7, 445– 459 DOI: 10.1111/j.1399-3011.1975.tb02465.xGoogle Scholar174https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28Xht1agsbg%253D&md5=fc31efb875d283eec9d07308a9ea5611Studies on protein folding, unfolding, and fluctuations by computer simulation. I. Effect of specific amino acid sequence represented by specific interunit interactionsTaketomi, Hiroshi; Ueda, Yuzo; Go, NobuhiroInternational Journal of Peptide & Protein Research (1975), 7 (6), 445-59CODEN: IJPPC3; ISSN:0367-8377.A lattice model of proteins with specific inter-unit interactions provided an effective method for studying the statistical mech. properties of conformations of globular proteins. The inter-unit interactions of strong limit, intermediate, and weak limit, resp., were studied. In the cases of the strong limit and intermediate specificities, denaturations were of the all or none type, whereas in the case of the weak limit specificity, denaturation was of the graded type.
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175Go, N.; Taketomi, H. Studies on protein folding, unfolding and fluctuations by computer simulation. IV. Hydrophobic interactions Int. J. Pept. Protein Res. 1979, 13, 447– 461 DOI: 10.1111/j.1399-3011.1979.tb01907.xGoogle Scholar175https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE1MXkvVGlu7Y%253D&md5=3fda0c140b409fb07ae35b3fa03430c8Studies on protein folding, unfolding and fluctuations by computer simulation. IV. Hydrophobic interactionsGo, Nobuhiro; Taketomi, HiroshiInternational Journal of Peptide & Protein Research (1979), 13 (5), 447-61CODEN: IJPPC3; ISSN:0367-8377.The theor. model of proteins on a 2-dimensional square lattice was extended to include hydrophobic interactions. Two proteins, with native conformations in different folded patterns, were studied. Units in the protein chains were classified into polar and nonpolar units. A vacant lattice point next to a nonpolar unit was interpreted as being occupied by solvent water and the entropy of the system was assumed to decrease by a certain amt. Besides these hydrophobic free energies, specific long-range interactions previously studied were assumed to be operative. Equil. properties of the folding and unfolding transitions of the 2 proteins were similar, even though 1 of them was predicted to unfold through a significant intermediate state when the hydrophobic interactions were strongly weighted. The failure of this prediction led to the development of a more refined model of transitions, a noninteracting local structure model. The assumed hydrophobic interactions have a character of nonspecific long-range interactions which decelerate the folding kinetics. The deceleration effect is less pronounced in the protein whose native conformation is stabilized by many pairs of medium-range interactions. Thus, medium-range interactions can cope with the decelerating effect of the nonspecific hydrophobic interactions.
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176Hills, R. D.; Brooks, C. L. Insights from Coarse-Grained Go Models for Protein Folding and Dynamics Int. J. Mol. Sci. 2009, 10, 889– 905 DOI: 10.3390/ijms10030889Google Scholar176https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXjtV2qt70%253D&md5=e622abb05cc31b984233b5d7a7a627e9Insights from coarse-grained Go models for protein folding and dynamicsHills, Ronald D., Jr.; Brooks, Charles L., IIIInternational Journal of Molecular Sciences (2009), 10 (3), 889-905CODEN: IJMCFK; ISSN:1422-0067. (Molecular Diversity Preservation International)A review. Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topol.-based Go models, which constitute a smooth and funnel-like approxn. to the folding landscape. We review the many variations of the Go model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topol. in folding. The role of local contact d. in detg. protein dynamics is also discussed and is used to explain the ability of Go-like models to capture sequence effects in folding and elucidate conformational transitions.
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177Bryngelson, J. D.; Onuchic, J. N.; Socci, N. D.; Wolynes, P. G. Funnels, pathways, and the energy landscape of protein folding: a synthesis Proteins: Struct., Funct., Genet. 1995, 21, 167– 195 DOI: 10.1002/prot.340210302Google Scholar177https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXks12qtrk%253D&md5=6ac46330d0690939667bac09f7cdd829Funnels, pathways, and the energy landscape of protein folding: a synthesisBryngelson, Joseph D.; Onuchic, Jose Nelson; Socci, Nicholas D.; Wolynes, Peter G.Proteins: Structure, Function, and Genetics (1995), 21 (3), 167-95CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss)A review, with 132 refs. The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking, a statistical approach to the energetics of protein conformation, i.e., the energy landscape. The statistical energy landscape approach explains when and why unique behaviors, such as specific folding pathways, occur in some proteins and more generally explains the distinction between folding processes common to all sequences and those peculiar to individual sequences. This approach also gives new, quant. insights into the interpretation of expts. and simulations of protein folding thermodn. and kinetics. Specifically, the picture provides simple explanations for folding as a two-state first-order phase transition, for the origin of metastable collapsed unfolded states and for the curved Arrhenius plots obsd. in both lab. expts. and discrete lattice simulations. The relation of these quant. ideas to folding pathways, to uniexponential vs. multiexponential behavior in protein folding expts. and to the effect of mutations on folding is also discussed. The success of energy landscape approach for analyzing data is illustrated with a quant. anal. of some recent simulations, and a qual. anal. of expts. on the folding of three proteins. The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodn. conditions.
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178Hills, R. D., Jr.; Brooks, C. L., 3rd Insights from coarse-grained Go models for protein folding and dynamics Int. J. Mol. Sci. 2009, 10, 889– 905 DOI: 10.3390/ijms10030889Google Scholar178https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXjtV2qt70%253D&md5=e622abb05cc31b984233b5d7a7a627e9Insights from coarse-grained Go models for protein folding and dynamicsHills, Ronald D., Jr.; Brooks, Charles L., IIIInternational Journal of Molecular Sciences (2009), 10 (3), 889-905CODEN: IJMCFK; ISSN:1422-0067. (Molecular Diversity Preservation International)A review. Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topol.-based Go models, which constitute a smooth and funnel-like approxn. to the folding landscape. We review the many variations of the Go model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topol. in folding. The role of local contact d. in detg. protein dynamics is also discussed and is used to explain the ability of Go-like models to capture sequence effects in folding and elucidate conformational transitions.
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179Lammert, H.; Schug, A.; Onuchic, J. N. Robustness and generalization of structure-based models for protein folding and function Proteins: Struct., Funct., Genet. 2009, 77, 881– 891 DOI: 10.1002/prot.22511Google Scholar179https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlSru7nF&md5=4f5d8b3f1a51933c5529ff5527b97962Robustness and generalization of structure-based models for protein folding and functionLammert, Heiko; Schug, Alexander; Onuchic, Jose N.Proteins: Structure, Function, and Bioinformatics (2009), 77 (4), 881-891CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Functional dynamics of native proteins share the energy landscape that guides folding into the native state. Folding simulations of structure-based protein models, using an minimally frustrated energy landscape dominated by native interactions, can describe the geometrical aspects of the folding mechanism. Tech. limitations imposed by the fixed shape of conventional contact potentials are a key obstacle toward advanced applications of structure-based models like allostery or ligand binding, which require multiple stable conformations. Generalizations of existing models, commonly using Lennard-Jones-like potentials, lead to inevitable clashes between their repulsive branches. To resolve these challenges, a new contact potential is developed that combines an attractive part based on Gaussians with a sep. repulsive term allowing flexibility for adjustments of the potential shape. With this new model multiple min. for studies of functional transitions can be introduced easily and consistently. A sensitivity anal. for five small proteins confirms the robust behavior of structure-based models with our adaptable potential and explores their capacity for quant. adjustment of the folding thermodn. We demonstrate its ability to incorporate alternative contact distances in simulations of structural transitions for the well-studied ROP dimer. Individual contact pairs can switch between distinct states to match the competing syn and anti structures. The flexibility of the new potential facilitates advanced uses of structure-based models. Depending on the application, features can be chosen from phys. considerations or to match expts. Generalized models can be built from multiple structures to study structural transitions or effects of disorder. Proteins 2009. © 2009 Wiley-Liss, Inc.
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180Hills, R. D., Jr. Balancing bond, nonbond, and go-like terms in coarse grain simulations of conformational dynamics Methods Mol. Biol. 2014, 1084, 123– 140 DOI: 10.1007/978-1-62703-658-0_7Google Scholar180https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnt1Crt7k%253D&md5=33c2aef7fa11efee13c071944336d390Balancing Bond, Nonbond, and G‾o-Like Terms in Coarse Grain Simulations of Conformational DynamicsHills, Ronald D., Jr.Methods in Molecular Biology (New York, NY, United States) (2014), 1084 (Protein Dynamics), 123-140CODEN: MMBIED; ISSN:1940-6029. (Springer)Characterization of the protein conformational landscape remains a challenging problem, whether it concerns elucidating folding mechanisms, predicting native structures or modeling functional transitions. Coarse-grained mol. dynamics simulation methods enable exhaustive sampling of the energetic landscape at resolns. of biol. interest. The general utility of structure-based models is reviewed along with their differing levels of approxn. Simple G‾o models incorporate attractive native interactions and repulsive nonnative contacts, resulting in an ideal smooth landscape. Non-G‾o coarse-grained models reduce the parameter set as needed but do not include bias to any desired native structure. While non-G‾o models have achieved limited success in protein coarse-graining, they can be combined with native structured-based potentials to create a balanced and powerful force field. Recent applications of such G‾o-like models have yielded insight into complex folding mechanisms and conformational transitions in large macromols. The accuracy and usefulness of reduced representations are also revealed to be a function of the math. treatment of the intrinsic bonded topol.
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181Christen, M.; van Gunsteren, W. On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: A review J. Comput. Chem. 2008, 29, 157– 166 DOI: 10.1002/jcc.20725Google Scholar181https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2sjktVOitQ%253D%253D&md5=c508200635d58b25f5ee678a9c016f87On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: A reviewChristen Markus; van Gunsteren Wilfred FJournal of computational chemistry (2008), 29 (2), 157-66 ISSN:0192-8651.Methods to search for low-energy conformations, to generate a Boltzmann-weighted ensemble of configurations, or to generate classical-dynamical trajectories for molecular systems in the condensed liquid phase are briefly reviewed with an eye to application to biomolecular systems. After having chosen the degrees of freedom and method to generate molecular configurations, the efficiency of the search or sampling can be enhanced in various ways: (i) efficient calculation of the energy function and forces, (ii) application of a plethora of search enhancement techniques, (iii) use of a biasing potential energy term, and (iv) guiding the sampling using a reaction or transition pathway. The overview of the available methods should help the reader to choose the combination that is most suitable for the biomolecular system, degrees of freedom, interaction function, and molecular or thermodynamic properties of interest.
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182Liwo, A.; Czaplewski, C.; Oldziej, S.; Scheraga, H. A. Computational techniques for efficient conformational sampling of proteins Curr. Opin. Struct. Biol. 2008, 18, 134– 139 DOI: 10.1016/j.sbi.2007.12.001Google Scholar182https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXkvFCmu7g%253D&md5=437b8d53b7fc1748852d75f842a10d20Computational techniques for efficient conformational sampling of proteinsLiwo, Adam; Czaplewski, Cezary; Oldziej, Stanislaw; Scheraga, Harold A.Current Opinion in Structural Biology (2008), 18 (2), 134-139CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. In this review, we summarize the computational methods for sampling the conformational space of biomacromols. We discuss the methods applicable to find only lowest energy conformations (global minimization of the potential-energy function) and to generate canonical ensembles (canonical Monte Carlo method and canonical mol. dynamics method and their extensions). Special attention is devoted to the use of coarse-grained models that enable simulations to be enhanced by several orders of magnitude.
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183Spiwok, V.; Sucur, Z.; Hosek, P. Enhanced sampling techniques in biomolecular simulations Biotechnol. Adv. 2015, 33, 1130– 1140 DOI: 10.1016/j.biotechadv.2014.11.011Google Scholar183https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVymu77J&md5=24cf1b57adcc4df3ed64bae3541266f2Enhanced sampling techniques in biomolecular simulationsSpiwok, Vojtech; Sucur, Zoran; Hosek, PetrBiotechnology Advances (2015), 33 (6_Part_2), 1130-1140CODEN: BIADDD; ISSN:0734-9750. (Elsevier)A review. Biomol. simulations are routinely used in biochem. and mol. biol. research; however, they often fail to match expectations of their impact on pharmaceutical and biotech industry. This is caused by the fact that a vast amt. of computer time is required to simulate short episodes from the life of biomols. Several approaches have been developed to overcome this obstacle, including application of massively parallel and special purpose computers or non-conventional hardware. Methodol. approaches are represented by coarse-grained models and enhanced sampling techniques. These techniques can show how the studied system behaves in long time-scales on the basis of relatively short simulations. This review presents an overview of new simulation approaches, the theory behind enhanced sampling methods and success stories of their applications with a direct impact on biotechnol. or drug design.
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184Bernardi, R. C.; Melo, M. C.; Schulten, K. Enhanced sampling techniques in molecular dynamics simulations of biological systems Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 872– 877 DOI: 10.1016/j.bbagen.2014.10.019Google Scholar184https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvVanurbN&md5=44e3ac1aa042c35ee08aa86a6a63e78eEnhanced sampling techniques in molecular dynamics simulations of biological systemsBernardi, Rafael C.; Melo, Marcelo C. R.; Schulten, KlausBiochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 872-877CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Mol. dynamics has emerged as an important research methodol. covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local min. sepd. by high-energy barriers, which govern the biomol. motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange mol. dynamics, metadynamics and simulated annealing. Here the authors present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biol. systems and the choice of a suitable method is connected to biol. and phys. characteristics of the system, in particular system size. While metadynamics and replica-exchange mol. dynamics are the most adopted sampling methods to study biomol. dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromol. complexes. Mol. dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biol. function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of mol. dynamics.
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185Hatfield, M. P.; Lovas, S. Conformational sampling techniques Curr. Pharm. Des. 2014, 20, 3303– 3313 DOI: 10.2174/13816128113199990603Google Scholar185https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpvVaks7g%253D&md5=3967e410c4bb073c425af1bbd26b0cbcConformational Sampling TechniquesHatfield, Marcus P. D.; Lovas, SandorCurrent Pharmaceutical Design (2014), 20 (20), 3303-3313CODEN: CPDEFP; ISSN:1381-6128. (Bentham Science Publishers Ltd.)A review. The potential energy hyper-surface of a protein relates the potential energy of the protein to its conformational space. This surface is useful in detg. the native conformation of a protein or in examg. a statistical-mech. ensemble of structures (canonical ensemble). In detg. the potential energy hyper-surface of a protein three aspects must be considered; reducing the degrees of freedom, a method to det. the energy of each conformation and a method to sample the conformational space. For reducing the degrees of freedom the choice of solvent, coarse graining, constraining degrees of freedom and periodic boundary conditions are discussed. The use of quantum mechanics vs. mol. mechanics and the choice of force fields are also discussed, as well as the sampling of the conformational space through deterministic and heuristic approaches. Deterministic methods include knowledge-based statistical methods, rotamer libraries, homol. modeling, the build-up method, self-consistent electrostatic field, deformation methods, tree-based elimination and eigenvector following routines. The heuristic methods include Monte Carlo chain growing, energy minimizations, metropolis monte carlo and mol. dynamics. In addn., various methods to enhance the conformational search including the deformation or smoothing of the surface, scaling of system parameters, and multi copy searching are also discussed.
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186Lee, J.; Scheraga, H. A.; Rackovsky, S. New optimization method for conformational energy calculations on polypeptides: Conformational space annealing J. Comput. Chem. 1997, 18, 1222– 1232 DOI: 10.1002/(SICI)1096-987X(19970715)18:9<1222::AID-JCC10>3.0.CO;2-7Google Scholar186https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXksVKmsLc%253D&md5=a340980c43561a4acc79ebbef01fee0aNew optimization method for conformational energy calculations on polypeptides: conformational space annealingLee, Jooyoung; Scheraga, Harold A.; Rackovsky, S.Journal of Computational Chemistry (1997), 18 (9), 1222-1232CODEN: JCCHDD; ISSN:0192-8651. (Wiley)A new optimization method is presented to search for the global min.-energy conformations of peptides. The method combines essential aspects of the build-up procedure and the genetic algorithm, and it introduces the important concept of "conformational space annealing.". Instead of considering a single conformation, attention is focused on a population of conformations while new conformations are obtained by modifying a "seed conformation.". The annealing is carried out by introducing a distance cutoff, Dcut, which is defined in the conformational space; Dcut effectively divides the whole conformational space of local min. into subdivisions. The value of Dcut is set to a large no. at the beginning of the algorithm to cover the whole conformational space, and annealing is achieved by slowly reducing it. Many distinct local min. designed to be distributed as far apart as possible in conformational space are investigated simultaneously. Therefore, the new method finds not only the global min.-energy conformation but also many other distinct local min. as byproducts. The method is tested on Met-enkephalin, a 24-dihedral angle problem. For all 100 independent runs, the accepted global min.-energy conformation was obtained after about 2600 minimizations on av.
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187Stein, A.; Kortemme, T. Improvements to robotics-inspired conformational sampling in rosetta PLoS One 2013, 8, e63090 DOI: 10.1371/journal.pone.0063090Google Scholar187https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXovVKgtro%253D&md5=9a319795b1e4add6bd12f5770e7ecb5eImprovements to robotics-inspired conformational sampling in RosettaStein, Amelie; Kortemme, TanjaPLoS One (2013), 8 (5), e63090CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)To accurately predict protein conformations in at. detail, a computational method must be capable of sampling models sufficiently close to the native structure. All-atom sampling is difficult because of the vast no. of possible conformations and extremely rugged energy landscapes. Here, we test three sampling strategies to address these difficulties: conformational diversification, intensification of torsion and omega-angle sampling and parameter annealing. We evaluate these strategies in the context of the robotics-based kinematic closure (KIC) method for local conformational sampling in Rosetta on an established benchmark set of 45 12-residue protein segments without regular secondary structure. We quantify performance as the fraction of sub-Angstrom models generated. While improvements with individual strategies are only modest, the combination of intensification and annealing strategies into a new "next-generation KIC" method yields a four-fold increase over std. KIC in the median percentage of sub-Angstrom models across the dataset. Such improvements enable progress on more difficult problems, as demonstrated on longer segments, several of which could not be accurately remodeled with previous methods. Given its improved sampling capability, next-generation KIC should allow advances in other applications such as local conformational remodeling of multiple segments simultaneously, flexible backbone sequence design, and development of more accurate energy functions.
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188Shmygelska, A.; Hoos, H. H. An ant colony optimization algorithm for the 2D and 3D hydrophobic polar protein folding problem BMC Bioinf. 2005, 6, 30 DOI: 10.1186/1471-2105-6-30Google Scholar188https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2M7ltFeitg%253D%253D&md5=c449e9eded1bbefad7d454fbcc8a9905An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problemShmygelska Alena; Hoos Holger HBMC bioinformatics (2005), 6 (), 30 ISSN:.BACKGROUND: The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model - the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model. RESULTS: We present an improvement of our previous ACO algorithm for the 2D HP model and its extension to the 3D HP model. We show that this new algorithm, dubbed ACO-HPPFP-3, performs better than previous state-of-the-art algorithms on sequences whose native conformations do not contain structural nuclei (parts of the native fold that predominantly consist of local interactions) at the ends, but rather in the middle of the sequence, and that it generally finds a more diverse set of native conformations. CONCLUSIONS: The application of ACO to this bioinformatics problem compares favourably with specialised, state-of-the-art methods for the 2D and 3D HP protein folding problem; our empirical results indicate that our rather simple ACO algorithm scales worse with sequence length but usually finds a more diverse ensemble of native states. Therefore the development of ACO algorithms for more complex and realistic models of protein structure holds significant promise.
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189Peter, E. K.; Lykov, K.; Pivkin, I. V. A polarizable coarse-grained protein model for dissipative particle dynamics Phys. Chem. Chem. Phys. 2015, 17, 24452– 24461 DOI: 10.1039/C5CP03479EGoogle Scholar189https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVahtLfJ&md5=d81eed1ffa5a3dac7369229f0bc5790eA polarizable coarse-grained protein model for dissipative particle dynamicsPeter, Emanuel K.; Lykov, Kirill; Pivkin, Igor V.Physical Chemistry Chemical Physics (2015), 17 (37), 24452-24461CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)The authors present a new coarse-grained polarizable protein model for dissipative particle dynamics (DPD) method. This method allows large timesteps in particle-based systems and speeds up sampling by many orders of magnitude. The authors' new model is based on the electrostatic polarization of the protein backbone and a detailed representation of the sidechains in combination with a polarizable water model. The authors define the authors' model parameters using the exptl. structures of two proteins, TrpZip2 and TrpCage. Backmapping and subsequent short replica-exchange mol. dynamics runs verify the authors' approach and show convergence to the exptl. structures on the atomistic level. The authors validate the authors' model on five different proteins: GB1, the WW-domain, the B-domain of Protein A, the peripheral binding subunit and villin headpiece.
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190Ermak, D.; McCammon, J. A. Brownian dynamics with hydrodynamic interactions J. Chem. Phys. 1978, 69, 1352– 1360 DOI: 10.1063/1.436761Google Scholar190https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE1cXls12huro%253D&md5=b11c679cdc7ac5bbecd8335b33f60e8fBrownian dynamics with hydrodynamic interactionsErmak, Donald L.; McCammon, J. A.Journal of Chemical Physics (1978), 69 (4), 1352-60CODEN: JCPSA6; ISSN:0021-9606.A method for simulating the Brownian dynamics of N particles with the inclusion of hydrodynamic interactions is described. The particles may also be subject to the usual interparticle or external forces (e.g., electrostatic) which were included in previous methods for simulating Brownian dynamics of particles in the absence of hydrodynamic interactions. The present method is derived from the Langevin equations for the N particle assembly, and the results are consistent with the corresponding Fokker-Planck results. Sample calcns. on small systems illustrate the importance of including hydrodynamic interactions in Brownian dynamics simulations. The method should be useful for simulation studies of diffusion limited reactions, polymer dynamics, protein folding, particle coagulation, and other phenomena in soln.
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191Proctor, E.; Dokholyan, N. Applications of Discrete Molecular Dynamics in biology and medicine Curr. Opin. Struct. Biol. 2016, 37, 9– 13 DOI: 10.1016/j.sbi.2015.11.001Google Scholar191https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVyqu7zM&md5=adf921c1d44f3597540eecc07746efa3Applications of Discrete Molecular Dynamics in biology and medicineProctor, Elizabeth A.; Dokholyan, Nikolay V.Current Opinion in Structural Biology (2016), 37 (), 9-13CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Discrete Mol. Dynamics (DMD) is a physics-based simulation method using discrete energetic potentials rather than traditional continuous potentials, allowing microsecond time scale simulations of biomol. systems to be performed on personal computers rather than supercomputers or specialized hardware. With the ongoing explosion in processing power even in personal computers, applications of DMD have similarly multiplied. In the past two years, researchers have used DMD to model structures of disease-implicated protein folding intermediates, study assembly of protein complexes, predict protein-protein binding conformations, engineer rescue mutations in disease-causative protein mutants, design a protein conformational switch to control cell signaling, and describe the behavior of polymeric dispersants for environmental cleanup of oil spills, among other innovative applications.
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192Urbanc, B.; Borreguero, J.; Cruz, L.; Stanley, E. Ab initio discrete molecular dynamics approach to protein folding and aggregation Methods Enzymol. 2006, 412, 314– 338 DOI: 10.1016/S0076-6879(06)12019-4Google Scholar192https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmtFKhsrc%253D&md5=298d035301793fc753c1b6032fdf5dbaAb initio discrete molecular dynamics approach to protein folding and aggregationUrbanc, Brigita; Borreguero, Jose M.; Cruz, Luis; Stanley, H. EugeneMethods in Enzymology (2006), 412 (Amyloid, Prions, and Other Protein Aggregates, Part B), 314-338CODEN: MENZAU; ISSN:0076-6879. (Elsevier)Understanding the toxicity of amyloidogenic protein aggregates and designing therapeutic approaches require the knowledge of their structure at. resoln. Although solid-state NMR, x-ray diffraction, and other exptl. techniques are capable of discerning the protein fibrillar structure, detg. the structures of early aggregates, called oligomers, is a challenging exptl. task. Computational studies by all-atom mol. dynamics, which provides a complete description of a protein in the solvent, are typically limited to study folding of smaller protein or aggregation of a small no. of short protein fragments. We reviewed an efficient ab initio computer simulation approach to protein folding and aggregation using discrete mol. dynamics (DMD) in combination with several coarse-grained protein models and implicit solvent. This approach involves different complexity levels in both the protein model and the interparticle interactions. Starting from the simplest protein model with minimal interactions, and gradually increasing its complexity, while guided by in vitro findings, we can systematically select the key features of the protein model and interactions that drive protein folding and aggregation. Because the method used in this DMD approach does not require any knowledge of the native or any other state of the protein, it can be applied to study degenerative disorders assocd. with protein misfolding and aberrant protein aggregation. The choice of the coarse-grained model depends on the complexity of the protein and specific questions to be addressed, which are mostly suggested by in vitro findings. Thus, we illustrate our approach on amyloid β-protein (Aβ) assocd. with Alzheimer's disease (AD). Despite the simplifications introduced in the DMD approach, the predicted Aβ conformations are in agreement with existing exptl. data. The in silico findings also provide further insights into the structure and dynamics of Aβ folding and oligomer formation that are amenable to in vitro testing.
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193Chen, Y.; Ding, F.; Dokholyan, N. V. Fidelity of the protein structure reconstruction from inter-residue proximity constraints J. Phys. Chem. B 2007, 111, 7432– 7438 DOI: 10.1021/jp068963tGoogle ScholarThere is no corresponding record for this reference.
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194Sfriso, P.; Hospital, A.; Emperador, A.; Orozco, M. Exploration of conformational transition pathways from coarse-grained simulations Bioinformatics 2013, 29, 1980– 1986 DOI: 10.1093/bioinformatics/btt324Google Scholar194https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFyhtLjM&md5=63745e42a6323f992e7a410b8f856886Exploration of conformational transition pathways from coarse-grained simulationsSfriso, Pedro; Hospital, Adam; Emperador, Agusti; Orozco, ModestoBioinformatics (2013), 29 (16), 1980-1986CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: A new algorithm to trace conformational transitions in proteins is presented. The method uses discrete mol. dynamics as engine to sample protein conformational space. A multiple min. Go-like potential energy function is used in combination with several enhancing sampling strategies, such as metadynamics, Maxwell Demon mol. dynamics and essential dynamics. The method, which shows an unprecedented computational efficiency, is able to trace a wide range of known exptl. transitions. Contrary to simpler methods our strategy does not introduce distortions in the chem. structure of the protein and is able to reproduce well complex non-linear conformational transitions. The method, called GOdMD, can easily introduce addnl. restraints to the transition (presence of ligand, known intermediate, known maintained contacts, ...) and is freely distributed to the community through the Spanish National Bioinformatics Institute (http://mmb.irbbarcelona.org/GOdMD).
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195Urbanc, B.; Cruz, L.; Ding, F.; Sammond, D.; Khare, S.; Buldyrev, S. V.; Stanley, H. E.; Dokholyan, N. V. Molecular dynamics simulation of amyloid beta dimer formation Biophys. J. 2004, 87, 2310– 2321 DOI: 10.1529/biophysj.104.040980Google Scholar195https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXot12nu7k%253D&md5=cbe7dd2a88a4e78d29da6c8e1ea3e819Molecular dynamics simulation of amyloid β dimer formationUrbanc, B.; Cruz, L.; Ding, F.; Sammond, D.; Khare, S.; Buldyrev, S. V.; Stanley, H. E.; Dokholyan, N. V.Biophysical Journal (2004), 87 (4), 2310-2321CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)Recent expts. with amyloid β (Aβ) peptide indicate that formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Aβ oligomers depends on their structure, which is governed by assembly dynamics. Due to limitations of current exptl. techniques, a detailed knowledge of oligomer structure at the at. level is missing. We introduce a mol. dynamics approach to study Aβ dimer formation. 1), We use discrete mol. dynamics simulations of a coarse-grained model to identify a variety of dimer conformations; and 2), we employ all-atom mol. mechanics simulations to est. thermodn. stability of all dimer conformations. Our simulations of a coarse-grained Aβ peptide model predicts 10 different planar β-strand dimer conformations. We then est. the free energies of all dimer conformations in all-atom mol. mechanics simulations with explicit water. We compare the free energies of Aβ(1-42) and Aβ(1-40) dimers. We find that 1), dimer conformations have higher free energies compared to their corresponding monomeric states; and 2), the free-energy difference between the Aβ(1-42) and the corresponding Aβ(1-40) dimer conformation is not significant. Our results suggest that Aβ oligomerization is not accompanied by the formation of thermodynamically stable planar β-strand dimers.
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196Vitalis, A.; Pappu, R. Methods for Monte Carlo simulations of biomacromolecules Annu. Rep. Comput. Chem. 2009, 5, 49– 76 DOI: 10.1016/S1574-1400(09)00503-9Google Scholar196https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhs1aiu7rN&md5=f2740f0aa97eee24e9dd4cecec45b5b6Methods for Monte Carlo simulations of biomacromoleculesVitalis, Andreas; Pappu, Rohit V.Annual Reports in Computational Chemistry (2009), 5 (), 49-76CODEN: ARCCC3; ISSN:1574-1400. (Elsevier B.V.)A review. The state-of-the-art for Monte Carlo (MC) simulations of biomacromols. is reviewed. Available methodologies for sampling conformational equil. and assocns. of biomacromols. in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves and the applicability of such methods to simulations of biomacromols. are discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, although underutilized in the biomacromol. simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, esp. when used in conjunction with implicit solvation models or other coarse-graining strategies.
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197Goujon, F.; Malfreyt, P.; Simon, J.-M.; Boutin, A.; Rousseau, B.; Fuchs, A. Monte Carlo versus molecular dynamics simulations in heterogeneous systems: An application to the n-pentane liquid-vapor interface J. Chem. Phys. 2004, 121, 12559– 12571 DOI: 10.1063/1.1819868Google Scholar197https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXhtFSnsrvP&md5=cbf1046208e13df79e04df4bb8660a72Monte Carlo versus molecular dynamics simulations in heterogeneous systems. An application to the n-pentane liquid-vapor interfaceGoujon, Florent; Malfreyt, Patrice; Simon, Jean-Marc; Boutin, Anne; Rousseau, Bernard; Fuchs, Alain H.Journal of Chemical Physics (2004), 121 (24), 12559-12571CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The Monte Carlo (MC) and mol. dynamics (MD) methodologies are now well established for computing equil. properties in homogeneous fluids. This is not yet the case for the direct simulation of 2-phase systems, which exhibit nonuniformity of the d. distribution across the interface. We have performed direct MC and MD simulations of the liq.-gas interface of n-pentane using a std. force-field model. We obtained d. and pressure components profiles along the direction normal to the interface that can be very different, depending on the truncation and long range correction strategies. We discuss the influence on predicted properties of different potential truncation schemes implemented in both MC and MD simulations. The MD and MC profiles can be made in agreement by a Lennard-Jones potential truncated via a polynomial function that makes the first and second derivs. of the potential continuous at the cutoff distance. In this case however, the predicted thermodn. properties (phase envelope, surface tension) deviate from expts., because of the changes made in the potential. A further readjustment of the potential parameters is needed if one wants to use this method. A straightforward use of bulk phase force fields in MD simulations may lead to some phys. inconsistencies when computing interfacial properties.
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198Schluttig, J.; Bachmann, M.; Janke, W. Comparative molecular dynamics and Monte Carlo study of statistical properties for coarse-grained heteropolymers J. Comput. Chem. 2008, 29, 2603– 2612 DOI: 10.1002/jcc.21003Google ScholarThere is no corresponding record for this reference.
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199Lane, T. J.; Shukla, D.; Beauchamp, K. A.; Pande, V. S. To milliseconds and beyond: challenges in the simulation of protein folding Curr. Opin. Struct. Biol. 2013, 23, 58– 65 DOI: 10.1016/j.sbi.2012.11.002Google Scholar199https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVWgtLjF&md5=76f625b813b7c85cfbcabac6659155cdTo milliseconds and beyond: challenges in the simulation of protein foldingLane, Thomas J.; Shukla, Diwakar; Beauchamp, Kyle A.; Pande, Vijay S.Current Opinion in Structural Biology (2013), 23 (1), 58-65CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Quant. accurate all-atom mol. dynamics (MD) simulations of protein folding have long been considered a holy grail of computational biol. Due to the large system sizes and long timescales involved, such a pursuit was for many years computationally intractable. Further, sufficiently accurate forcefields needed to be developed in order to realistically model folding. This decade, however, saw the first reports of folding simulations describing kinetics on the order of milliseconds, placing many proteins firmly within reach of these methods. Progress in sampling and forcefield accuracy, however, presents a new challenge: how to turn huge MD datasets into scientific understanding. Here, we review recent progress in MD simulation techniques and show how the vast datasets generated by such techniques present new challenges for anal. We critically discuss the state of the art, including reaction coordinate and Markov state model (MSM) methods, and provide a perspective for the future.
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200Bowman, G. R.; Voelz, V. A.; Pande, V. S. Taming the complexity of protein folding Curr. Opin. Struct. Biol. 2011, 21, 4– 11 DOI: 10.1016/j.sbi.2010.10.006Google Scholar200https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhvFKhur8%253D&md5=aa258139210e793fd6829527c52d7ee9Taming the complexity of protein foldingBowman, Gregory R.; Voelz, Vincent A.; Pande, Vijay S.Current Opinion in Structural Biology (2011), 21 (1), 4-11CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Protein folding is an important problem in structural biol. with significant medical implications, particularly for misfolding disorders like Alzheimer's disease. Solving the folding problem will ultimately require a combination of theory and expt., with theor. models providing a comprehensive view of folding and expts. grounding these models in reality. Here we review progress towards this goal over the past decade, with an emphasis on recent theor. advances that are empowering chem. detailed models of folding and the new results these technologies are providing. In particular, we discuss new insights made possible by Markov state models (MSMs), including the role of non-native contacts and the hub-like character of protein folded states.
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201Noe, F.; Fischer, S. Transition networks for modeling the kinetics of conformational change in macromolecules Curr. Opin. Struct. Biol. 2008, 18, 154– 162 DOI: 10.1016/j.sbi.2008.01.008Google ScholarThere is no corresponding record for this reference.
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202Yin, Y.; Sieradzan, A. K.; Liwo, A.; He, Y.; Scheraga, H. A. Physics-based potentials for coarse-grained modeling of protein-DNA interactions J. Chem. Theory Comput. 2015, 11, 1792– 1808 DOI: 10.1021/ct5009558Google Scholar202https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkt1Ohsrw%253D&md5=8b732d52174fb072b8c37e47f43ec78bPhysics-Based Potentials for Coarse-Grained Modeling of Protein-DNA InteractionsYin, Yanping; Sieradzan, Adam K.; Liwo, Adam; He, Yi; Scheraga, Harold A.Journal of Chemical Theory and Computation (2015), 11 (4), 1792-1808CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Physics-based potentials have been developed for the interactions between proteins and DNA for simulations with the UNRES + NARES-2P force field. The mean-field interactions between a protein and a DNA mol. can be divided into eight categories: (1) nonpolar side chain-DNA base, (2) polar uncharged side chain-DNA base, (3) charged side chain-DNA base, (4) peptide group-phosphate group, (5) peptide group-DNA base, (6) nonpolar side chain-phosphate group, (7) polar uncharged side chain-phosphate group, and (8) charged side chain-phosphate group. Umbrella-sampling mol. dynamics simulations in explicit TIP3P water using the AMBER force field were carried out to det. the potentials of mean force (PMF) for all 105 pairs of interacting components. Approx. anal. expressions for the mean-field interaction energy of each pair of the different kinds of interacting mols. were then fitted to the PMFs to obtain the parameters of the anal. expressions. These anal. expressions can reproduce satisfactorily the PMF curves corresponding to different orientations of the interacting mols. The results suggest that the physics-based mean-field potentials of amino acid-nucleotide interactions presented here can be used in coarse-grained simulation of protein-DNA interactions.
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203Krupa, P.; Mozolewska, M. A.; Joo, K.; Lee, J.; Czaplewski, C.; Liwo, A. Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field J. Chem. Inf. Model. 2015, 55, 1271– 1281 DOI: 10.1021/acs.jcim.5b00117Google Scholar203https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXotFChsro%253D&md5=192c72efc38618c63ced5432d5d06e7dPrediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force FieldKrupa, Pawel; Mozolewska, Magdalena A.; Joo, Keehyoung; Lee, Jooyoung; Czaplewski, Cezary; Liwo, AdamJournal of Chemical Information and Modeling (2015), 55 (6), 1271-1281CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange mol. dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the mol., is used to search the conformational space, and the weighted histogram anal. method and cluster anal. are applied to det. the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.
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204Mozolewska, M. A.; Krupa, P.; Scheraga, H. A.; Liwo, A. Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches Proteins: Struct., Funct., Genet. 2015, 83, 1414– 1426 DOI: 10.1002/prot.24824Google ScholarThere is no corresponding record for this reference.
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205Blaszczyk, M.; Jamroz, M.; Kmiecik, S.; Kolinski, A. CABS-fold: Server for the de novo and consensus-based prediction of protein structure Nucleic Acids Res. 2013, 41, W406– 411 DOI: 10.1093/nar/gkt462Google ScholarThere is no corresponding record for this reference.
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206Jamroz, M.; Kolinski, A. Modeling of loops in proteins: a multi-method approach BMC Struct. Biol. 2010, 10, 5 DOI: 10.1186/1472-6807-10-5Google Scholar206https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3c7nvF2gug%253D%253D&md5=8aacfca6f596ba6376691d007eb973a6Modeling of loops in proteins: a multi-method approachJamroz Michal; Kolinski AndrzejBMC structural biology (2010), 10 (), 5 ISSN:.BACKGROUND: Template-target sequence alignment and loop modeling are key components of protein comparative modeling. Short loops can be predicted with high accuracy using structural fragments from other, not necessairly homologous proteins, or by various minimization methods. For longer loops multiscale approaches employing coarse-grained de novo modeling techniques should be more effective. RESULTS: For a representative set of protein structures of various structural classes test predictions of loop regions have been performed using MODELLER, ROSETTA, and a CABS coarse-grained de novo modeling tool. Loops of various length, from 4 to 25 residues, were modeled assuming an ideal target-template alignment of the remaining portions of the protein. It has been shown that classical modeling with MODELLER is usually better for short loops, while coarse-grained de novo modeling is more effective for longer loops. Even very long missing fragments in protein structures could be effectively modeled. Resolution of such models is usually on the level 2-6 A, which could be sufficient for guiding protein engineering. Further improvement of modeling accuracy could be achieved by the combination of different methods. In particular, we used 10 top ranked models from sets of 500 models generated by MODELLER as multiple templates for CABS modeling. On average, the resulting molecular models were better than the models from individual methods. CONCLUSIONS: Accuracy of protein modeling, as demonstrated for the problem of loop modeling, could be improved by the combinations of different modeling techniques.
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207Kmiecik, S.; Kolinski, A. Characterization of protein-folding pathways by reduced-space modeling Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 12330– 12335 DOI: 10.1073/pnas.0702265104Google Scholar207https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXos1ehsbc%253D&md5=0085e0982f31abcefce8fd83bc2f2ce7Characterization of protein-folding pathways by reduced-space modelingKmiecik, Sebastian; Kolinski, AndrzejProceedings of the National Academy of Sciences of the United States of America (2007), 104 (30), 12330-12335CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Ab initio simulations of the folding pathways are currently limited to very small proteins. For larger proteins, some approxns. or simplifications in protein models need to be introduced. Protein folding and unfolding are among the basic processes in the cell and are very difficult to characterize in detail by expt. or simulation. Chymotrypsin inhibitor 2 (CI2) and barnase are probably the best characterized exptl. in this respect. For these model systems, initial folding stages were simulated by using CA-CB-side-chain (CABS), a reduced-space protein-modeling tool. CABS employs knowledge-based potentials that proved to be very successful in protein structure prediction. With the use of isothermal Monte Carlo (MC) dynamics, initiation sites with a residual structure and weak tertiary interactions were identified. Such structures are essential for the initiation of the folding process through a sequential redn. of the protein conformational space, overcoming the Levinthal paradox in this manner. Furthermore, nucleation sites that initiate a tertiary interactions network were located. The MC simulations corresponded perfectly to the results of exptl. and theor. research and brought insights into the CI2 folding mechanism: an unambiguous sequence of folding events was reported as well as cooperative substructures compatible with those obtained in recent mol. dynamics unfolding studies. The correspondence between the simulation and expt. showed that knowledge-based potentials are not only useful in protein structure predictions but are also capable of reproducing the folding pathways. Thus, the results of this work significantly extend the applicability range of reduced models in the theor. study of proteins.
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208Kmiecik, S.; Kolinski, A. Folding pathway of the b1 domain of protein G explored by multiscale modeling Biophys. J. 2008, 94, 726– 736 DOI: 10.1529/biophysj.107.116095Google Scholar208https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVahsrc%253D&md5=4793eb39e37f0fa9d875e6b0b1d8ed6fFolding pathway of the B1 domain of protein G explored by multiscale modelingKmiecik, Sebastian; Kolinski, AndrzejBiophysical Journal (2008), 94 (3), 726-736CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, the authors developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodn., and modeling of protein complexes. Here, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of exptl. facts and theor. findings for this protein. Performing unbiased, ab initio simulations, the authors demonstrated that GB1 folding proceeded via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions was found to drive the folding from the very beginning. The emerging comprehensive picture of GB1 folding was found to perfectly match and extend previous exptl. and theor. studies.
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209Kmiecik, S.; Kolinski, A. Simulation of chaperonin effect on protein folding: a shift from nucleation-condensation to framework mechanism J. Am. Chem. Soc. 2011, 133, 10283– 10289 DOI: 10.1021/ja203275fGoogle ScholarThere is no corresponding record for this reference.
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210Jamroz, M.; Kolinski, A.; Kmiecik, S. CABS-flex: Server for fast simulation of protein structure fluctuations Nucleic Acids Res. 2013, 41, W427– 431 DOI: 10.1093/nar/gkt332Google ScholarThere is no corresponding record for this reference.
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211Jamroz, M.; Orozco, M.; Kolinski, A.; Kmiecik, S. Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field J. Chem. Theory Comput. 2013, 9, 119– 125 DOI: 10.1021/ct300854wGoogle Scholar211https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhslOmu7jN&md5=880ab5fbba6f9beb9ec1d30d30f79a21Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-FieldJamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, SebastianJournal of Chemical Theory and Computation (2013), 9 (1), 119-125CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)It is widely recognized that atomistic Mol. Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theor. study showing that various MD force-fields provide a consensus picture of protein fluctuations in aq. soln. [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biol. relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale mol. modeling of protein systems with atomistic resoln.
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212Kurcinski, M.; Kolinski, A.; Kmiecik, S. Mechanism of Folding and Binding of an Intrinsically Disordered Protein As Revealed by ab Initio Simulations J. Chem. Theory Comput. 2014, 10, 2224– 2231 DOI: 10.1021/ct500287cGoogle Scholar212https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXns1Cgsbg%253D&md5=36ed5e48c9d3893d0cb9e708497666d8Mechanism of Folding and Binding of an Intrinsically Disordered Protein As Revealed by ab Initio SimulationsKurcinski, Mateusz; Kolinski, Andrzej; Kmiecik, SebastianJournal of Chemical Theory and Computation (2014), 10 (6), 2224-2231CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A complex of the phosphorylated kinase-inducible domain (pKID) from transcription factor CREB with its interacting domain (KIX) from CREB-binding protein (CBP) is a model system for studies of mechanisms by which intrinsically unfolded proteins perform their functions. These mechanisms are not fully understood. Using an efficient coarse-grained model, ab initio simulations were performed of the coupled folding and binding of the pKID to the KIX. The simulations start from an unbound, randomly positioned and disordered pKID structure. During the simulations the pKID chain and its position remain completely unrestricted, while the KIX backbone is limited to near-native fluctuations. Ab initio simulations of such large-scale conformational transitions, unaffected by any knowledge about the bound pKID structure, remain inaccessible to classical simulations. Our simulations recover an ensemble of transient encounter complexes in good agreement with exptl. results. We find that a key folding and binding step is linked to the formation of weak native interactions between a preformed nativelike fragment of a pKID helix and KIX surface. Once that nucleus forms, the pKID chain may condense from a largely disordered encounter ensemble to a natively bound and ordered conformation. The obsd. mechanism is reminiscent of a nucleation-condensation model, a common scenario for folding of globular proteins.
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213Kurcinski, M.; Jamroz, M.; Blaszczyk, M.; Kolinski, A.; Kmiecik, S. CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site Nucleic Acids Res. 2015, 43, W419– 424 DOI: 10.1093/nar/gkv456Google Scholar213https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtVymtbrK&md5=3d72a394eafb7869513e622e1b361d47CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding siteKurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, SebastianNucleic Acids Research (2015), 43 (W1), W419-W424CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Protein-peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein-peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of nonredundant protein-peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Addnl., as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments.
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214Blaszczyk, M.; Kurcinski, M.; Kouza, M.; Wieteska, L.; Debinski, A.; Kolinski, A.; Kmiecik, S. Modeling of protein-peptide interactions using the CABS-dock web server for binding site search and flexible docking Methods 2016, 93, 72– 83 DOI: 10.1016/j.ymeth.2015.07.004Google Scholar214https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtF2ksL%252FN&md5=cf994902770c92eed25bfe3b7aa3189aModeling of protein-peptide interactions using the CABS-dock web server for binding site search and flexible dockingBlaszczyk, Maciej; Kurcinski, Mateusz; Kouza, Maksim; Wieteska, Lukasz; Debinski, Aleksander; Kolinski, Andrzej; Kmiecik, SebastianMethods (Amsterdam, Netherlands) (2016), 93 (), 72-83CODEN: MTHDE9; ISSN:1046-2023. (Elsevier B.V.)Protein-peptide interactions play essential functional roles in living organisms and their structural characterization is a hot subject of current exptl. and theor. research. Computational modeling of the structure of protein-peptide interactions is usually divided into two stages: prediction of the binding site at a protein receptor surface, and then docking (and modeling) the peptide structure into the known binding site. This paper presents a comprehensive CABS-dock method for the simultaneous search of binding sites and flexible protein-peptide docking, available as a user's friendly web server. We present example CABS-dock results obtained in the default CABS-dock mode and using its advanced options that enable the user to increase the range of flexibility for chosen receptor fragments or to exclude user-selected binding modes from docking search. Furthermore, we demonstrate a strategy to improve CABS-dock performance by assessing the quality of models with classical mol. dynamics. Finally, we discuss the promising extensions and applications of the CABS-dock method and provide a tutorial appendix for the convenient anal. and visualization of CABS-dock results. The CABS-dock web server is freely available at http://biocomp.chem.uw.edu.pl/CABSdock/.
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215Kar, P.; Gopal, S. M.; Cheng, Y. M.; Panahi, A.; Feig, M. Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix-Helix Association J. Chem. Theory Comput. 2014, 10, 3459– 3472 DOI: 10.1021/ct500443vGoogle Scholar215https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpslygsbY%253D&md5=1d78a59c87cd1c45911beba8fe46f915Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix-Helix AssociationKar, Parimal; Gopal, Srinivasa Murthy; Cheng, Yi-Ming; Panahi, Afra; Feig, MichaelJournal of Chemical Theory and Computation (2014), 10 (8), 3459-3472CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)An extension of the recently developed PRIMO coarse-grained force field to membrane environments, PRIMO-M, is described. The membrane environment is modeled with the heterogeneous dielec. generalized Born (HDGB) methodol. that simply replaces the std. generalized Born model in PRIMO without further parametrization. The resulting model was validated by comparing amino acid insertion free energy profiles and application in mol. dynamics simulations of membrane proteins and membrane-interacting peptides. Membrane proteins with 148-661 amino acids show stable root-mean-squared-deviations (RMSD) between 2 and 4 Å for most systems. Transmembrane helical peptides maintain helical shape and exhibit tilt angles in good agreement with exptl. or other simulation data. The assocn. of two glycophorin A (GpA) helixes was simulated using replica exchange mol. dynamics simulations yielding the correct dimer structure with a crossing angle in agreement with previous studies. Finally, conformational sampling of the influenza fusion peptide also generates structures in agreement with previous studies. Overall, these findings suggest that PRIMO-M can be used to study membrane bound peptides and proteins and validates the transferable nature of the PRIMO coarse-grained force field.
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216Marrink, S. J.; de Vries, A. H.; Mark, A. E. Coarse grained model for semiquantitative lipid simulations J. Phys. Chem. B 2004, 108, 750– 760 DOI: 10.1021/jp036508gGoogle Scholar216https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXptlKjsb4%253D&md5=53c1ca266631af0122f3b5577e9efb0bCoarse Grained Model for Semiquantitative Lipid SimulationsMarrink, Siewert J.; De Vries, Alex H.; Mark, Alan E.Journal of Physical Chemistry B (2004), 108 (2), 750-760CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)This paper describes the parametrization of a new coarse grained (CG) model for lipid and surfactant systems. Redn. of the no. of degrees of freedom together with the use of short range potentials makes it computationally very efficient. Compared to atomistic models a gain of 3-4 orders of magnitude can be achieved. Micrometer length scales or millisecond time scales are therefore within reach. To encourage applications, the model is kept very simple. Only a small no. of coarse grained atom types are defined, which interact using a few discrete levels of interaction. Despite the computational speed and the simplistic nature of the model, it proves to be both versatile in its applications and accurate in its predictions. We show that densities of liq. alkanes from decane up to eicosane can be reproduced to within 5%, and the mutual solubilities of alkanes in water and water in alkanes can be reproduced within 0.5 kT of the exptl. values. The CG model for dipalmitoylphosphatidylcholine (DPPC) is shown to aggregate spontaneously into a bilayer. Structural properties such as the area per headgroup and the phosphate-phosphate distance match the exptl. measured quantities closely. The same is true for elastic properties such as the bending modulus and the area compressibility, and dynamic properties such as the lipid lateral diffusion coeff. and the water permeation rate. The distribution of the individual lipid components along the bilayer normal is very similar to distributions obtained from atomistic simulations. Phospholipids with different headgroup (ethanolamine) or different tail lengths (lauroyl, stearoyl) or unsatd. tails (oleoyl) can also be modeled with the CG force field. The exptl. area per headgroup can be reproduced for most lipids within 0.02 nm2. Finally, the CG model is applied to nonbilayer phases. Dodecylphosphocholine (DPC) aggregates into small micelles that are structurally very similar to ones modeled atomistically, and DOPE forms an inverted hexagonal phase with structural parameters in agreement with exptl. data.
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217Monticelli, L.; Kandasamy, S. K.; Periole, X.; Larson, R. G.; Tieleman, D. P.; Marrink, S. J. The MARTINI coarse-grained force field: Extension to proteins J. Chem. Theory Comput. 2008, 4, 819– 834 DOI: 10.1021/ct700324xGoogle Scholar217https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXks1Onsrg%253D&md5=56f4bb722f339707787e946a15dba5faThe MARTINI Coarse-Grained Force Field: Extension to ProteinsMonticelli, Luca; Kandasamy, Senthil K.; Periole, Xavier; Larson, Ronald G.; Tieleman, D. Peter; Marrink, Siewert-JanJournal of Chemical Theory and Computation (2008), 4 (5), 819-834CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Many biol. interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biol. materials. Coarse-grained (CG) mol. modeling allows computer simulations to be run on length and time scales that are 2-3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. The authors developed a new CG model for proteins as an extension of the MARTINI force field. Here, the authors validate the model for its use in peptide-bilayer systems. To validate the model, the authors calcd. the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. The authors then compared amino acid assocn. consts., the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyristoylphosphatidylcholine and dipalmitoylphosphatidylcholine (DPPC) bilayers. A comparison with results obtained from atomistic models shows good agreement in all of the tests performed. The authors also performed a systematic investigation of the partitioning of five series of polyalanine-leucine peptides (with different lengths and compns.) in DPPC bilayers. As expected, the fraction of peptides partitioned at the interface increased with decreasing peptide length and decreasing leucine content, demonstrating that the CG model is capable of discriminating partitioning behavior arising from subtle differences in the amino acid compn. Finally, the authors simulated the concn.-dependent formation of transmembrane pores by magainin, an antimicrobial peptide. In line with atomistic simulation studies, disordered toroidal pores are formed. In conclusion, the model is computationally efficient and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.
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218Marrink, S. J.; Risselada, H. J.; Yefimov, S.; Tieleman, D. P.; de Vries, A. H. The MARTINI force field: Coarse grained model for biomolecular simulations J. Phys. Chem. B 2007, 111, 7812– 7824 DOI: 10.1021/jp071097fGoogle Scholar218https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmsVKmsLc%253D&md5=428d5750b94652e4917d905a30658235The MARTINI Force Field: Coarse Grained Model for Biomolecular SimulationsMarrink, Siewert J.; Risselada, H. Jelger; Yefimov, Serge; Tieleman, D. Peter; De Vries, Alex H.Journal of Physical Chemistry B (2007), 111 (27), 7812-7824CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)We present an improved and extended version of our coarse grained lipid model. The new version, coined the MARTINI force field, is parametrized in a systematic way, based on the reprodn. of partitioning free energies between polar and apolar phases of a large no. of chem. compds. To reproduce the free energies of these chem. building blocks, the no. of possible interaction levels of the coarse-grained sites has increased compared to those of the previous model. Application of the new model to lipid bilayers shows an improved behavior in terms of the stress profile across the bilayer and the tendency to form pores. An extension of the force field now also allows the simulation of planar (ring) compds., including sterols. Application to a bilayer/cholesterol system at various concns. shows the typical cholesterol condensation effect similar to that obsd. in all atom representations.
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219Shih, A. Y.; Arkhipov, A.; Freddolino, P. L.; Schulten, K. Coarse grained protein-lipid model with application to lipoprotein particles J. Phys. Chem. B 2006, 110, 3674– 3684 DOI: 10.1021/jp0550816Google Scholar219https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtF2qsA%253D%253D&md5=e7effac4070f205380c48b5dcaf35e1eCoarse Grained Protein-Lipid Model with Application to Lipoprotein ParticlesShih, Amy Y.; Arkhipov, Anton; Freddolino, Peter L.; Schulten, KlausJournal of Physical Chemistry B (2006), 110 (8), 3674-3684CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A coarse-grained model for mol. dynamics simulations is extended from lipids to proteins. In the framework of such models pioneered by Klein, atoms are described group-wise by beads, with the interactions between beads governed by effective potentials. The extension developed here is based on a coarse-grained lipid model developed previously by Marrink et al., although future versions will reconcile the approach taken with the systematic approach of Klein and other authors. Each amino acid of the protein is represented by two coarse-grained beads, one for the backbone (identical for all residues) and one for the side-chain (which differs depending on the residue type). The coarse-graining reduces the system size about 10-fold and allows integration time steps of 25-50 fs. The model is applied to simulations of discoidal high-d. lipoprotein particles involving water, lipids, and two primarily helical proteins. These particles are an ideal test system for the extension of coarse-grained models. Our model proved to be reliable in maintaining the shape of preassembled particles and in reproducing the overall structural features of high-d. lipoproteins (HDLs) accurately. Microsecond simulations of lipoprotein assembly revealed the formation of a protein-lipid complex in which two proteins are attached to either side of a discoidal lipid bilayer.
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220Bond, P. J.; Holyoake, J.; Ivetac, A.; Khalid, S.; Sansom, M. S. Coarse-grained molecular dynamics simulations of membrane proteins and peptides J. Struct. Biol. 2007, 157, 593– 605 DOI: 10.1016/j.jsb.2006.10.004Google Scholar220https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXisVCnsrk%253D&md5=6272050e9bf882316b47fe7cfdd87cceCoarse-grained molecular dynamics simulations of membrane proteins and peptidesBond, Peter J.; Holyoake, John; Ivetac, Anthony; Khalid, Syma; Sansom, Mark S. P.Journal of Structural Biology (2007), 157 (3), 593-605CODEN: JSBIEM; ISSN:1047-8477. (Elsevier)Mol. dynamics (MD) simulations provide a valuable approach to the dynamics, structure, and stability of membrane-protein systems. Coarse-grained (CG) models, in which small groups of atoms are treated as single particles, enable extended (>100 ns) timescales to be addressed. In this study, the authors explore how CG-MD methods that were developed for detergents and lipids may be extended to membrane proteins. In particular, CG-MD simulations of a no. of membrane peptides and proteins are used to characterize their interactions with lipid bilayers. CG-MD is used to simulate the insertion of synthetic model membrane peptides (WALPs and LS3) into a lipid (PC) bilayer. WALP peptides insert in a transmembrane orientation, while the LS3 peptide adopts an interfacial location, both in agreement with exptl. biophys. data. This approach is extended to a transmembrane fragment of the Vpu protein from HIV-1, and to the coat protein from fd phage. Again, simulated protein/membrane interactions are in good agreement with solid state NMR data for these proteins. CG-MD has also been applied to an M3-M4 fragment from the CFTR protein. Simulations of CFTR M3-M4 in a detergent micelle reveal formation of an α-helical hairpin, consistent with a variety of biophys. data. In an I231D mutant, the M3-M4 hairpin is addnl. stabilized via an inter-helix Q207/D231 interaction. Finally, CG-MD simulations are extended to a more complex membrane protein, the bacterial sugar transporter LacY. Comparison of a 200 ns CG-MD simulation of LacY in a DPPC bilayer with a 50 ns atomistic simulation of the same protein in a DMPC bilayer shows that the two methods yield comparable predictions of lipid-protein interactions. Taken together, these results demonstrate the utility of CG-MD simulations for studies of membrane/protein interactions.
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221Spiga, E.; Alemani, D.; Degiacomi, M. T.; Cascella, M.; Peraro, M. D. Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins J. Chem. Theory Comput. 2013, 9, 3515– 3526 DOI: 10.1021/ct400137qGoogle Scholar221https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpslKit74%253D&md5=1573eaf62983bed6cb1b1fa99307fddeElectrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of ProteinsSpiga, Enrico; Alemani, Davide; Degiacomi, Matteo T.; Cascella, Michele; Peraro, Matteo DalJournal of Chemical Theory and Computation (2013), 9 (8), 3515-3526CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of sol. proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with resp. ref. structures and all-atom mol. dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their mol. interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resoln. An efficient and robust heuristic algorithm based on particle swarm optimization was used for the derivation of CG parameters via a force-matching procedure. The ability of this protocol to deal with high dimensional search spaces suggests that the extension of this optimization procedure to larger data sets may give a fully transferable CG force field. At the present stage, these electrostatic-consistent CG potentials are easily and efficiently parametrized, show a good degree of transferability, and can be used to simulate sol. proteins or, more interestingly, large macromol. assemblies for which long all-atom simulations may not be easily affordable.
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222Alemani, D.; Collu, F.; Cascella, M.; Dal Peraro, M. A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure Elements J. Chem. Theory Comput. 2010, 6, 315– 324 DOI: 10.1021/ct900457zGoogle Scholar222https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsF2jsrrI&md5=048bb50a976cc55a5ff792617483ab72A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure ElementsAlemani, Davide; Collu, Francesca; Cascella, Michele; Dal Peraro, MatteoJournal of Chemical Theory and Computation (2010), 6 (1), 315-324CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We introduce a nonradial potential term for coarse-grained (CG) mol. simulations of proteins. This term mimics the backbone dipole-dipole interactions and accounts for the needed directionality to form stable folded secondary structure elements. We show that α-helical and β-sheet peptide chains are correctly described in dynamics without the need for introducing any a priori bias potentials or ad hoc parameterizations, which limit broader applicability of CG simulations for proteins. Moreover, our model is able to catch the formation of supersecondary structural motifs, like transitions from long single α-helixes to helix-coil-helix or β-hairpin assemblies. This novel scheme requires the structural information of Cα beads only; it does not introduce any addnl. degrees of freedom to the system and has a general formulation, which allows it to be used in synergy with various CG protocols, leading to an improved description of the structural and dynamic properties of protein assemblies and networks.
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223Arnarez, C.; Uusitalo, J. J.; Masman, M. F.; Ingolfsson, H. I.; de Jong, D. H.; Melo, M. N.; Periole, X.; de Vries, A. H.; Marrink, S. J. Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit Solvent J. Chem. Theory Comput. 2015, 11, 260– 275 DOI: 10.1021/ct500477kGoogle Scholar223https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVWiu7nP&md5=bc78f6059a8f9eb69cbc2d8fb9210790Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit SolventArnarez, Clement; Uusitalo, Jaakko J.; Masman, Marcelo F.; Ingolfsson, Helgi I.; de Jong, Djurre H.; Melo, Manuel N.; Periole, Xavier; de Vries, Alex H.; Marrink, Siewert J.Journal of Chemical Theory and Computation (2015), 11 (1), 260-275CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grained (CG) models allow simulation of larger systems for longer times by decreasing the no. of degrees of freedom compared with all-atom models. Here we introduce an implicit-solvent version of the popular CG Martini model, nicknamed "Dry" Martini. To account for the omitted solvent degrees of freedom, the nonbonded interaction matrix underlying the Martini force field was reparametrized. The Dry Martini force field reproduces relatively well a variety of lipid membrane properties such as area per lipid, bilayer thickness, bending modulus, and coexistence of liq.-ordered and disordered domains. Furthermore, we show that the new model can be applied to study membrane fusion and tether formation, with results similar to those of the std. Martini model. Membrane proteins can also be included, but less quant. results are obtained. The absence of water in Dry Martini leads to a significant speedup for large systems, opening the way to the study of complex multicomponent membranes contg. millions of lipids.
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224Yesylevskyy, S. O.; Schafer, L. V.; Sengupta, D.; Marrink, S. J. Polarizable water model for the coarse-grained MARTINI force field PLoS Comput. Biol. 2010, 6, e1000810 DOI: 10.1371/journal.pcbi.1000810Google Scholar224https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3crgsVKisQ%253D%253D&md5=86162bc2c160c1bf7a1058eb82296455Polarizable water model for the coarse-grained MARTINI force fieldYesylevskyy Semen O; Schafer Lars V; Sengupta Durba; Marrink Siewert JPLoS computational biology (2010), 6 (6), e1000810 ISSN:.Coarse-grained (CG) simulations have become an essential tool to study a large variety of biomolecular processes, exploring temporal and spatial scales inaccessible to traditional models of atomistic resolution. One of the major simplifications of CG models is the representation of the solvent, which is either implicit or modeled explicitly as a van der Waals particle. The effect of polarization, and thus a proper screening of interactions depending on the local environment, is absent. Given the important role of water as a ubiquitous solvent in biological systems, its treatment is crucial to the properties derived from simulation studies. Here, we parameterize a polarizable coarse-grained water model to be used in combination with the CG MARTINI force field. Using a three-bead model to represent four water molecules, we show that the orientational polarizability of real water can be effectively accounted for. This has the consequence that the dielectric screening of bulk water is reproduced. At the same time, we parameterized our new water model such that bulk water density and oil/water partitioning data remain at the same level of accuracy as for the standard MARTINI force field. We apply the new model to two cases for which current CG force fields are inadequate. First, we address the transport of ions across a lipid membrane. The computed potential of mean force shows that the ions now naturally feel the change in dielectric medium when moving from the high dielectric aqueous phase toward the low dielectric membrane interior. In the second application we consider the electroporation process of both an oil slab and a lipid bilayer. The electrostatic field drives the formation of water filled pores in both cases, following a similar mechanism as seen with atomistically detailed models.
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225Marrink, S. J.; Tieleman, D. P. Perspective on the Martini model Chem. Soc. Rev. 2013, 42, 6801– 6822 DOI: 10.1039/c3cs60093aGoogle Scholar225https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFeqtrbM&md5=9bd67bdef4bf230d9a861ca3f18bf2a8Perspective on the Martini modelMarrink, Siewert J.; Tieleman, D. PeterChemical Society Reviews (2013), 42 (16), 6801-6822CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)A review. The Martini model, a coarse-grained force field for biomol. simulations, has found a broad range of applications since its release a decade ago. Based on a building block principle, the model combines speed and versatility while maintaining chem. specificity. Here we review the current state of the model. We describe recent highlights as well as shortcomings, and our ideas on the further development of the model.
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226Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. GROMACS: fast, flexible, and free J. Comput. Chem. 2005, 26, 1701– 1718 DOI: 10.1002/jcc.20291Google Scholar226https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1SlsbbO&md5=4aa71b1dc0b5b4978a88b0568245a265GROMACS: Fast, flexible, and freeVan Der Spoel, David; Lindahl, Erik; Hess, Berk; Groenhof, Gerrit; Mark, Alan E.; Berendsen, Herman J. C.Journal of Computational Chemistry (2005), 26 (16), 1701-1718CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)This article describes the software suite GROMACS (Groningen MAchine for Chem. Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for mol. dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addn., it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequil. dynamics and free energy detns. are incorporated. Interfaces with popular quantum-chem. packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and anal. programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.
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227Bowers, K. J.; Chow, E.; Xu, H.; Dror, R. O.; Eastwood, M. P.; Gregersen, B. A.; Klepeis, J. L.; Kolossváry, I.; Moraes, M. A.; Sacerdoti, F. D.Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters. Proceedings of the ACM/IEEE Conference on Supercomputing (SC06), 2006.Google ScholarThere is no corresponding record for this reference.
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228Baron, R.; Trzesniak, D.; de Vries, A. H.; Elsener, A.; Marrink, S. J.; van Gunsteren, W. F. Comparison of thermodynamic properties of coarse-grained and atomic-level simulation models ChemPhysChem 2007, 8, 452– 461 DOI: 10.1002/cphc.200600658Google Scholar228https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXis1alsr0%253D&md5=ae7ec9a5f5a0e40ffd411a79d4500225Comparison of thermodynamic properties of coarse-grained and atomic-level simulation modelsBaron, Riccardo; Trzesniak, Daniel; de Vries, Alex H.; Elsener, Andreas; Marrink, Siewert J.; van Gunsteren, Wilfred F.ChemPhysChem (2007), 8 (3), 452-461CODEN: CPCHFT; ISSN:1439-4235. (Wiley-VCH Verlag GmbH & Co. KGaA)Thermodn. data are often used to calibrate or test at.-level (AL) force fields for mol. dynamics (MD) simulations. In contrast, the majority of coarse-grained (CG) force fields do not rely extensively on thermodn. quantities. Recently, a CG force field for lipids, hydrocarbons, ions, and water, in which approx. four non-hydrogen atoms are mapped onto one interaction site, has been proposed and applied to study various aspects of lipid systems. To date, no extensive investigation of its capability to describe solvation thermodn. has been undertaken. In the present study, a detailed picture of vaporization, solvation, and phase-partitioning thermodn. for liq. hydrocarbons and water was obtained at CG and AL resolns., in order to compare the two types of models and evaluate their ability to describe thermodn. properties in the temp. range between 263 and 343 K. Both CG and AL models capture the exptl. dependence of the thermodn. properties on the temp., albeit a systematically weaker dependence is found for the CG model. Moreover, deviations are found for solvation thermodn. and for the corresponding enthalpy-entropy compensation for the CG model. Particularly water/oil repulsion seems to be overestimated. However, the results suggest that the thermodn. properties considered should be reproducible by a CG model provided it is re-parametrized on the basis of these liq.-phase properties.
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229Leaver-Fay, A.; Tyka, M.; Lewis, S.; Lange, O.; Thompson, J.; Jacak, R.; Kaufman, K.; Renfrew, D.; Smith, C.; Sheffler, W. ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules Methods Enzymol. 2011, 487, 545– 574 DOI: 10.1016/B978-0-12-381270-4.00019-6Google Scholar229https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXjtFCgtLo%253D&md5=ffd7fe5f3869975c3c0808c3cd43ace1Rosetta3: an obeject-oriented software suite for the simulation and design of macromoleculesLeaver-Fay, Andrew; Tyka, Michael; Lewis, Steven M.; Lange, Oliver F.; Thompson, James; Jacak, Ron; Kaufman, Kristian; Renfrew, P. Douglas; Smith, Colin A.; Sheffler, Will; Davis, Ian W.; Cooper, Seth; Treuille, Adrien; Mandell, Daniel J.; Richter, Florian; Ban, Yih-En Andrew; Fleishman, Sarel J.; Corn, Jacob E.; Kim, David E.; Lyskov, Sergey; Berrondo, Monica; Mentzer, Stuart; Popovic, Zoran; Havranek, James J.; Karanicolas, John; Das, Rhiju; Meiler, Jens; Kortemme, Tanja; Gray, Jeffrey J.; Kuhlman, Brian; Baker, David; Bradley, PhilipMethods in Enzymology (2011), 487 (Computer Methods, Part C), 545-574CODEN: MENZAU; ISSN:0076-6879. (Elsevier Inc.)A review. We have recently completed a full rearchitecturing of the rosetta mol. modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for mol. modeling. The source code of this rearchitecturing has been released as rosetta 3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.
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230Bradley, P.; Misura, K. M.; Baker, D. Toward high-resolution de novo structure prediction for small proteins Science 2005, 309, 1868– 1871 DOI: 10.1126/science.1113801Google Scholar230https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXpvFCisLo%253D&md5=a5f7f424c8af97c6113532cc6f102e7aToward High-Resolution de Novo Structure Prediction for Small ProteinsBradley, Philip; Misura, Kira M. S.; Baker, DavidScience (Washington, DC, United States) (2005), 309 (5742), 1868-1871CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)The prediction of protein structure from amino acid sequence is a grand challenge of computational mol. biol. By using a combination of improved low- and high-resoln. conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resoln. structure prediction (<1.5 Å) can be achieved for small protein domains (<85 residues). The primary bottleneck to consistent high-resoln. prediction appears to be conformational sampling.
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231Gront, D.; Kulp, D.; Vernon, R.; Strauss, C.; Baker, D. Generalized fragment picking in rosetta: design, protocols and applications PLoS One 2011, 6, e23294 DOI: 10.1371/journal.pone.0023294Google Scholar231https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtF2nsLzN&md5=89b6c669d014bb784b644cb3e44f60c7Generalized fragment picking in Rosetta: design, protocols and applicationsGront, Dominik; Kulp, Daniel W.; Vernon, Robert M.; Strauss, Charlie E. M.; Baker, DavidPLoS One (2011), 6 (8), e23294CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extd. from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible.
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232Smith, C.; Kortemme, T. Backrub-Like Backbone Simulation Recapitulates Natural Protein Conformational Variability and Improves Mutant Side-Chain Prediction J. Mol. Biol. 2008, 380, 742– 756 DOI: 10.1016/j.jmb.2008.05.023Google Scholar232https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnvVKgtL8%253D&md5=00a4e8cbeae56e34b083af49a138b61bBackrub-Like Backbone Simulation Recapitulates Natural Protein Conformational Variability and Improves Mutant Side-Chain PredictionSmith, Colin A.; Kortemme, TanjaJournal of Molecular Biology (2008), 380 (4), 742-756CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Incorporation of effective backbone sampling into protein simulation and design is an important step in increasing the accuracy of computational protein modeling. Recent anal. of high-resoln. crystal structures has suggested a new model, termed backrub, to describe localized, hinge-like alternative backbone and side-chain conformations obsd. in the crystal lattice. The model involves internal backbone rotations about axes between C-alpha atoms. Based on this observation, we have implemented a backrub-inspired sampling method in the Rosetta structure prediction and design program. We evaluate this model of backbone flexibility using three different tests. First, we show that Rosetta backrub simulations recapitulate the correlation between backbone and side-chain conformations in the high-resoln. crystal structures upon which the model was based. As a second test of backrub sampling, we show that backbone flexibility improves the accuracy of predicting point-mutant side-chain conformations over fixed backbone rotameric sampling alone. Finally, we show that backrub sampling of triosephosphate isomerase loop 6 can capture the millisecond/μs oscillation between the open and closed states obsd. in soln. Our results suggest that backrub sampling captures a sizable fraction of localized conformational changes that occur in natural proteins. Application of this simple model of backbone motions may significantly improve both protein design and atomistic simulations of localized protein flexibility.
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233Betancourt, M. Efficient Monte Carlo trial moves for polypeptide simulations J. Chem. Phys. 2005, 123, 174905 DOI: 10.1063/1.2102896Google ScholarThere is no corresponding record for this reference.
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234Dunbrack, Jr.; Karplus, M. Backbone-dependent Rotamer Library for Proteins Application to Side-chain Prediction J. Mol. Biol. 1993, 230, 543– 574 DOI: 10.1006/jmbi.1993.1170Google Scholar234https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3sXisFWjsL0%253D&md5=b3a7eab18a6c8c4b61e8f3e3fb4aa492Backbone-dependent rotamer library for proteins. Application to side-chain predictionDunbrack, Roland L., Jr.; Karplus, MartinJournal of Molecular Biology (1993), 230 (2), 543-74CODEN: JMOBAK; ISSN:0022-2836.A backbone-dependent rotamer library for amino acid side chains was developed and used for constructing protein side-chain conformations from the main-chain coordinates. The rotamer library was obtained from 132 protein chains in the Brookhaven Protein Database. A grid of 20° by 20° blocks for the main-chain angles .vphi., ψ was used in the rotamer library. Significant correlations were found between side-chain dihedral angle probabilities and backbone .vphi., ψ values. These probabilities were used to place the side chains on the known backbone in test applications for 6 proteins for which high-resoln. crystal structures were available. A minimization scheme was used to reorient side chains that conflict with the backbone or other side chains after the initial placement. The initial placement yields 59% of both χ1 and χ2 values in the correct position (to within 40°) for thermolysin to 81% for crambin. After refinement the values range from 61% (lysozyme) to 89% (crambin). Apparently a single protein does not adequately test a prediction scheme. The computation time required by the method scales linearly with the no. of side chains. An initial prediction from the library takes only a few seconds of computer time, while the iterative refinement takes on the order of hours. The method is automated and can easily be applied to aid exptl. side chain detns. and homol. modeling. The high degree of correlation between backbone and side chain conformations may introduce a simplification in the protein folding process by reducing the available conformational space.
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235Kuhlman, B.; Dantas, G.; Ireton, G.; Varani, G.; Stoddard, B.; Baker, D. Design of a novel globular protein fold with atomic-level accuracy Science 2003, 302, 1364– 1368 DOI: 10.1126/science.1089427Google Scholar235https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXptVCqu7o%253D&md5=2339edc7b74a403e183d3567d966b677Design of a Novel Globular Protein Fold with Atomic-Level AccuracyKuhlman, Brian; Dantas, Gautam; Ireton, Gregory C.; Varani, Gabriele; Stoddard, Barry L.; Baker, DavidScience (Washington, DC, United States) (2003), 302 (5649), 1364-1368CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue α/β protein called Top7 with a novel sequence and topol. Top7 was found exptl. to be folded and extremely stable, and the X-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet obsd. in nature.
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236Davtyan, A.; Schafer, N. P.; Zheng, W.; Clementi, C.; Wolynes, P. G.; Papoian, G. A. AWSEM-MD: protein structure prediction using coarse-grained physical potentials and bioinformatically based local structure biasing J. Phys. Chem. B 2012, 116, 8494– 8503 DOI: 10.1021/jp212541yGoogle Scholar236https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XmtlCktLc%253D&md5=d7ba0f2efa1bedd47ed22c1962f5ab72AWSEM-MD: Protein Structure Prediction Using Coarse-Grained Physical Potentials and Bioinformatically Based Local Structure BiasingDavtyan, Aram; Schafer, Nicholas P.; Zheng, Weihua; Clementi, Cecilia; Wolynes, Peter G.; Papoian, Garegin A.Journal of Physical Chemistry B (2012), 116 (29), 8494-8503CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The associative memory, water mediated, structure and energy model (AWSEM) is a coarse-grained protein force field. AWSEM contains phys. motivated terms, such as hydrogen bonding, as well as a bioinformatically-based local structure biasing term, which efficiently takes into account many-body effects that are modulated by the local sequence. When combined with appropriate local or global alignments to choose memories, AWSEM can be used to perform de novo protein structure prediction. Herein we present structure prediction results for a particular choice of local sequence alignment method based on short residue sequences called fragments. We demonstrate the model's structure prediction capabilities for three levels of global homol. between the target sequence and those proteins used for local structure biasing, all of which assume that the structure of the target sequence is not known. When there are no homologues in the database of structures used for local structure biasing, AWSEM calcns. produce structural predictions that are somewhat improved compared with prior works using related approaches. The inclusion of a small no. of structures from homologous sequences improves structure prediction only marginally, but when the fragment search is restricted to only homologous sequences, AWSEM can perform high resoln. structure prediction and can be used for kinetics and dynamics studies.
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237Zheng, W.; Schafer, N. P.; Davtyan, A.; Papoian, G. A.; Wolynes, P. G. Predictive energy landscapes for protein-protein association Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 19244– 19249 DOI: 10.1073/pnas.1216215109Google Scholar237https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVagtrnI&md5=b81d0ab4a15468258d379e2820bc13a1Predictive energy landscapes for protein-protein associationZheng, Weihua; Schafer, Nicholas P.; Davtyan, Aram; Papoian, Garegin A.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (47), 19244-19249, S19244/1-S19244/3CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We investigate protein-protein assocn. using the associative-memory, water-mediated, structure, and energy model (AWSEM), a coarse-grained protein folding model that has been optimized using energy-landscape theory. The potential was originally parameterized by enforcing a funneled nature for a database of dimeric interfaces but was later further optimized to create funneled folding landscapes for individual monomeric proteins. The ability of the model to predict interfaces was not tested previously. The present results show that simulated annealing of the model indeed is able to predict successfully the native interfaces of eight homodimers and four heterodimers, thus amounting to a flexible docking algorithm. We go on to address the relative importance of monomer geometry, flexibility, and nonnative intermonomeric contacts in the assocn. process for the homodimers. Monomer surface geometry is found to be important in detg. the binding interface, but it is insufficient. Using a uniform binding potential rather than the water-mediated potential results in sampling of misbound structures that are geometrically preferred but are nonetheless energetically disfavored by AWSEM, as well as in nature. Depending on the stability of the unbound monomers, nonnative contacts play different roles in the assocn. process. For unstable monomers, thermodn. states stabilized by nonnative interactions correspond to productive, on-pathway intermediates and can, therefore, catalyze binding through a fly-casting mechanism. For stable monomers, in contrast, states stabilized by nonnative interactions generally correspond to traps that impede binding.
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238Zheng, W.; Schafer, N. P.; Wolynes, P. G. Frustration in the energy landscapes of multidomain protein misfolding Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 1680– 1685 DOI: 10.1073/pnas.1222130110Google Scholar238https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXislChsrc%253D&md5=885d2c562c11a63cc833d95b2702e9ffFrustration in the energy landscapes of multidomain protein misfoldingZheng, Weihua; Schafer, Nicholas P.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2013), 110 (5), 1680-1685, S1680/1-S1680/4CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Frustration from strong interdomain interactions can make misfolding a more severe problem in multidomain proteins than in single-domain proteins. On the basis of bioinformatic surveys, it has been suggested that lowering the sequence identity between neighboring domains is one of nature's solns. to the multidomain misfolding problem. We investigate folding of multidomain proteins using the associative-memory, water-mediated, structure and energy model (AWSEM), a predictive coarse-grained protein force field. We find that reducing sequence identity not only decreases the formation of domain-swapped contacts but also decreases the formation of strong self-recognition contacts between p-strands with high hydrophobic content. The ensembles of misfolded structures that result from forming these amyloid-like interactions are energetically disfavored compared with the native state, but entropically favored. Therefore, these ensembles are more stable than the native ensemble under denaturing conditions, such as high temp. Domain-swapped contacts compete with self-recognition contacts in forming various trapped states, and point mutations can shift the balance between the two types of interaction. We predict that multidomain proteins that lack these specific strong interdomain interactions should fold reliably.
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239Chen, M.; Zheng, W.; Wolynes, P. G. Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memory Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 5006 DOI: 10.1073/pnas.1602702113Google Scholar239https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xmt1ShtLg%253D&md5=6912630ec15eac17aa940c8ebbfa74a5Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memoryChen, Mingchen; Zheng, Weihua; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2016), 113 (18), 5006-5011CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Aplysia cytoplasmic polyadenylation element binding (CPEB) protein, a translational regulator that recruits mRNAs and facilitates translation, has been shown to be a key component in the formation of long-term memory. Exptl. data show that CPEB exists in at least a low-mol. wt. coiled-coil oligomeric form and an amyloid fiber form involving the Q-rich domain (CPEB-Q). Using a coarse-grained energy landscape model, we predict the structures of the low-mol. wt. oligomeric form and the dynamics of their transitions to the β-form. Up to the decamer, the oligomeric structures are predicted to be coiled coils. Free energy profiles confirm that the coiled coil is the most stable form for dimers and trimers. The structural transition from α to β is shown to be concn. dependent, with the transition barrier decreasing with increased concn. We observe that a mech. pulling force can facilitate the α-helix to β-sheet (α-to-β) transition by lowering the free energy barrier between the 2 forms. Interactome anal. of the CPEB protein suggests that its interactions with the cytoskeleton could provide the necessary mech. force. We propose that, by exerting mech. forces on CPEB oligomers, an active cytoskeleton can facilitate fiber formation. This mech. catalysis makes possible a pos. feedback loop that would help localize the formation of CPEB fibers to active synapse areas and mark those synapses for forming a long-term memory after the prion form is established. The functional role of the CPEB helical oligomers in this mechanism carries with it implications for targeting such species in neurodegenerative diseases.
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240Tsai, M. Y.; Zheng, W.; Balamurugan, D.; Schafer, N. P.; Kim, B. L.; Cheung, M. S.; Wolynes, P. G. Electrostatics, structure prediction, and the energy landscapes for protein folding and binding Protein Sci. 2016, 25, 255– 269 DOI: 10.1002/pro.2751Google Scholar240https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXht12mu7%252FK&md5=5ccb38d7e17eacec13d8cfc24169ca7fElectrostatics, structure prediction, and the energy landscapes for protein folding and bindingTsai, Min-Yeh; Zheng, Weihua; Balamurugan, D.; Schafer, Nicholas P.; Kim, Bobby L.; Cheung, Margaret S.; Wolynes, Peter G.Protein Science (2016), 25 (1), 255-269CODEN: PRCIEI; ISSN:1469-896X. (Wiley-Blackwell)While being long in range and therefore weakly specific, electrostatic interactions are able to modulate the stability and folding landscapes of some proteins. The relevance of electrostatic forces for steering the docking of proteins to each other is widely acknowledged, however, the role of electrostatics in establishing specifically funneled landscapes and their relevance for protein structure prediction are still not clear. By introducing Debye-Hueckel potentials that mimic long-range electrostatic forces into the Associative memory, Water mediated, Structure, and Energy Model (AWSEM), a transferable protein model capable of predicting tertiary structures, we assess the effects of electrostatics on the landscapes of thirteen monomeric proteins and four dimers. For the monomers, we find that adding electrostatic interactions does not improve structure prediction. Simulations of ribosomal protein S6 show, however, that folding stability depends monotonically on electrostatic strength. The trend in predicted melting temps. of the S6 variants agrees with exptl. observations. Electrostatic effects can play a range of roles in binding. The binding of the protein complex KIX-pKID is largely assisted by electrostatic interactions, which provide direct charge-charge stabilization of the native state and contribute to the funneling of the binding landscape. In contrast, for several other proteins, including the DNA-binding protein FIS, electrostatics causes frustration in the DNA-binding region, which favors its binding with DNA but not with its protein partner. This study highlights the importance of long-range electrostatics in functional responses to problems where proteins interact with their charged partners, such as DNA, RNA, as well as membranes.
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241Kim, B. L.; Schafer, N. P.; Wolynes, P. G. Predictive energy landscapes for folding alpha-helical transmembrane proteins Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 11031– 11036 DOI: 10.1073/pnas.1410529111Google ScholarThere is no corresponding record for this reference.
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242Bereau, T.; Deserno, M. Generic coarse-grained model for protein folding and aggregation J. Chem. Phys. 2009, 130, 235106 DOI: 10.1063/1.3152842Google Scholar242https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnsFCktr8%253D&md5=f501aa4286a8b08d5070ac9b70670f30Generic coarse-grained model for protein folding and aggregationBereau, Tristan; Deserno, MarkusJournal of Chemical Physics (2009), 130 (23), 235106/1-235106/15CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)A generic coarse-grained (CG) protein model is presented. The intermediate level of resoln. (four beads per amino acid, implicit solvent) allows for accurate sampling of local conformations. It relies on simple interactions that emphasize structure, such as hydrogen bonds and hydrophobicity. Realistic α/β content is achieved by including an effective nearest-neighbor dipolar interaction. Parameters are tuned to reproduce both local conformations and tertiary structures. The thermodn. and kinetics of a three-helix bundle are studied. We check that the CG model is able to fold proteins with tertiary structures and amino acid sequences different from the one used for parameter tuning. By studying both helical and extended conformations, we make sure the force field is not biased toward any particular secondary structure. The accuracy involved in folding not only the test protein but also of other ones show strong evidence for amino acid cooperativity embedded in the model. Without any further adjustments or bias, a realistic oligopeptide aggregation scenario is obsd. (c) 2009 American Institute of Physics.
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243Bereau, T.; Bachmann, M.; Deserno, M. Interplay between secondary and tertiary structure formation in protein folding cooperativity J. Am. Chem. Soc. 2010, 132, 13129– 13131 DOI: 10.1021/ja105206wGoogle Scholar243https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFWru7zI&md5=3e9e4bda0651ac14195b49967a7698c6Interplay between Secondary and Tertiary Structure Formation in Protein Folding CooperativityBereau, Tristan; Bachmann, Michael; Deserno, MarkusJournal of the American Chemical Society (2010), 132 (38), 13129-13131CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Protein folding cooperativity is defined by the nature of the finite-size thermodn. transition exhibited upon folding: two-state transitions show a free-energy barrier between the folded and unfolded ensembles, while downhill folding is barrierless. A microcanonical anal., where the energy is the natural variable, has proved to be better suited than its canonical counterpart to unambiguously characterize the nature of the transition. Replica-exchange mol. dynamics simulations of a high-resoln. coarse-grained model allow for the accurate evaluation of the d. of states in order to ext. precise thermodn. information and measure its impact on structural features. The method has been applied to three helical peptides: a short helix shows sharp features of a two-state folder, while a longer helix and a three-helix bundle exhibit downhill and two-state transitions, resp. Extending the results of lattice simulations and theor. models, we have found that it is the interplay between secondary structure and the loss of non-native tertiary contacts that dets. the nature of the transition.
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244Arnold, A.; Lenz, O.; Kesselheim, S.; Weeber, R.; Fahrenberger, F.; Roehm, D.; Košovan, P.; Holm, C. In Meshfree Methods for Partial Differential Equations VI; Griebel, M.; Schweitzer, M. A., Eds.; Springer: Berlin, 2013; Vol. 89.Google ScholarThere is no corresponding record for this reference.
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245Pronk, S.; Pall, S.; Schulz, R.; Larsson, P.; Bjelkmar, P.; Apostolov, R.; Shirts, M. R.; Smith, J. C.; Kasson, P. M.; van der Spoel, D. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit Bioinformatics 2013, 29, 845– 854 DOI: 10.1093/bioinformatics/btt055Google Scholar245https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXksFWmsrg%253D&md5=4b25fd6ab4e33725ae56b5da63f4ad68GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkitPronk, Sander; Pall, Szilard; Schulz, Roland; Larsson, Per; Bjelkmar, Paer; Apostolov, Rossen; Shirts, Michael R.; Smith, Jeremy C.; Kasson, Peter M.; van der Spoel, David; Hess, Berk; Lindahl, ErikBioinformatics (2013), 29 (7), 845-854CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: Mol. simulation has historically been a low-throughput technique, but faster computers and increasing amts. of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomols. with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomol. interaction and function in a manner directly testable by expt. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomols., such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these mols. built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.
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246Sterpone, F.; Melchionna, S.; Tuffery, P.; Pasquali, S.; Mousseau, N.; Cragnolini, T.; Chebaro, Y.; St-Pierre, J. F.; Kalimeri, M.; Barducci, A. The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems Chem. Soc. Rev. 2014, 43, 4871– 4893 DOI: 10.1039/c4cs00048jGoogle ScholarThere is no corresponding record for this reference.
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247Sterpone, F.; Derreumaux, P.; Melchionna, S. Protein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with Hydrodynamics J. Chem. Theory Comput. 2015, 11, 1843– 1853 DOI: 10.1021/ct501015hGoogle Scholar247https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkvVelsrw%253D&md5=88e635a720d6431800027baed091b35cProtein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with HydrodynamicsSterpone, Fabio; Derreumaux, Philippe; Melchionna, SimoneJournal of Chemical Theory and Computation (2015), 11 (4), 1843-1853CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A novel simulation framework that integrates the OPEP coarse-grained (CG) model for proteins with the Lattice Boltzmann (LB) methodol. to account for the fluid solvent at mesoscale level is presented. OPEP is a very efficient, water-free and electrostatic-free force field that reproduces at quasi-atomistic detail processes like peptide folding, structural rearrangements, and aggregation dynamics. The LB method is based on the kinetic description of the solvent to solve the fluid mechanics under a wide range of conditions, with the further advantage of being highly scalable on parallel architectures. The capabilities of the approach are presented, and the strategy is effective in exploring the role of hydrodynamics on protein relaxation and peptide aggregation. The end result is a strategy for modeling systems of thousands of proteins, such as in the case of dense protein suspensions. The future perspectives of the multiscale approach are also discussed.
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248Barducci, A.; Bonomi, M.; Derreumaux, P. Assessing the Quality of the OPEP Coarse-Grained Force Field J. Chem. Theory Comput. 2011, 7, 1928– 1934 DOI: 10.1021/ct100646fGoogle Scholar248https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmt1Gmu7o%253D&md5=caa588d09b7421d2b9d921cbbfb96d44Assessing the Quality of the OPEP Coarse-Grained Force FieldBarducci, Alessandro; Bonomi, Massimiliano; Derreumaux, PhilippeJournal of Chemical Theory and Computation (2011), 7 (6), 1928-1934CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A coarse-grained potential that could accurately describe the overall conformational landscape of proteins would be extremely valuable not only for structure prediction but also for studying protein dynamics, large conformational motions, and intrinsically disordered systems. Here, the authors assessed the quality of the OPEP coarse-grained potential by comparing the reconstructed free-energy surfaces (FESs) of two prototypical β-hairpin and α-helix peptides to all-atom calcns. in explicit solvent. The authors found remarkable agreement between the OPEP FES and those obtained using atomistic models, despite a general overstabilization of α- and β-structures by the coarse-grained potential. The use of advanced sampling techniques based on metadynamics and parallel tempering guaranteed a thorough exploration of the conformational space accessible to the two peptides studied.
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249Chebaro, Y.; Pasquali, S.; Derreumaux, P. The coarse-grained OPEP force field for non-amyloid and amyloid proteins J. Phys. Chem. B 2012, 116, 8741– 8752 DOI: 10.1021/jp301665fGoogle Scholar249https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xpt1Cht7c%253D&md5=43469f238822babca8176b8686845671The Coarse-Grained OPEP Force Field for Non-Amyloid and Amyloid ProteinsChebaro, Yassmine; Pasquali, Samuela; Derreumaux, PhilippeJournal of Physical Chemistry B (2012), 116 (30), 8741-8752CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Coarse-grained protein models with various levels of granularity and degrees of freedom offer the possibility to explore many phenomena including folding, assembly, and recognition in terms of dynamics and thermodn. that are inaccessible to all-atom representations in explicit aq. soln. Here, we present a refined version of the coarse-grained optimized potential for efficient protein structure prediction (OPEP) based on a six-bead representation. The OPEP version 4.0 parameter set, which uses a new anal. formulation for the nonbonded interactions and adds specific side-chain-side-chain interactions for α-helix, is subjected to three tests. First, we show that mol. dynamics simulations at 300 K preserve the exptl. rigid conformations of 17 proteins with 37-152 amino acids within a root-mean-square deviation (RMSD) of 3.1 Å after 30 ns. Extending the simulation time to 100 ns for five proteins does not change the RMSDs. Second, replica exchange mol. dynamics (REMD) simulations recover the NMR structures of three prototypical β-hairpin and α-helix peptides and the NMR three-stranded β-sheet topol. of a 37-residue WW domain, starting from randomly chosen states. Third, REMD simulations on the ccβ peptide show a temp. transition from a three-stranded coiled coil to amyloid-like aggregates consistent with expts., while simulations on low mol. wt. aggregates of the prion protein helix 1 do not. Overall, these studies indicate the effectiveness of our OPEP4 coarse-grained model for protein folding and aggregation, and report two future directions for improvement.
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250Chebaro, Y.; Dong, X.; Laghaei, R.; Derreumaux, P.; Mousseau, N. Replica exchange molecular dynamics simulations of coarse-grained proteins in implicit solvent J. Phys. Chem. B 2009, 113, 267– 274 DOI: 10.1021/jp805309eGoogle ScholarThere is no corresponding record for this reference.
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251Nasica-Labouze, J.; Nguyen, P. H.; Sterpone, F.; Berthoumieu, O.; Buchete, N. V.; Cote, S.; De Simone, A.; Doig, A. J.; Faller, P.; Garcia, A. Amyloid beta Protein and Alzheimer’s Disease: When Computer Simulations Complement Experimental Studies Chem. Rev. 2015, 115, 3518– 3563 DOI: 10.1021/cr500638nGoogle Scholar251https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXksl2hurs%253D&md5=fdd061847c9171aec5d4a4b9d871768dAmyloid β Protein and Alzheimer's Disease: When Computer Simulations Complement Experimental StudiesNasica-Labouze, Jessica; Nguyen, Phuong H.; Sterpone, Fabio; Berthoumieu, Olivia; Buchete, Nicolae-Viorel; Cote, Sebastien; De Simone, Alfonso; Doig, Andrew J.; Faller, Peter; Garcia, Angel; Laio, Alessandro; Mai, Suan Li; Melchionna, Simone; Mousseau, Normand; Mu, Yuguang; Paravastu, Anant; Pasquali, Samuela; Rosenman, David J.; Strodel, Birgit; Tarus, Bogdan; Viles, John H.; Zhang, Tong; Wang, Chunyu; Derreumaux, PhilippeChemical Reviews (Washington, DC, United States) (2015), 115 (9), 3518-3563CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review, discussing the contribution of biophys. and biochem. studies and computer simulations to characterize the mol. structures of Aβ1-40/1-42 monomers, oligomers, protofibrils, and amyloid fibrils in aq. soln.
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252Nasica-Labouze, J.; Meli, M.; Derreumaux, P.; Colombo, G.; Mousseau, N. A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion sup-35 PLoS Comput. Biol. 2011, 7, e1002051 DOI: 10.1371/journal.pcbi.1002051Google Scholar252https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXms1Knt7c%253D&md5=6b95b752d59bf8a758ebff2ffb660579A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion Sup-35Nasica-Labouze, Jessica; Meli, Massimiliano; Derreumaux, Philippe; Colombo, Giorgio; Mousseau, NormandPLoS Computational Biology (2011), 7 (5), e1002051CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)The self-organization of peptides into amyloidogenic oligomers is one of the key events for a wide range of mol. and degenerative diseases. Atomic-resoln. characterization of the mechanisms responsible for the aggregation process and the resulting structures is thus a necessary step to improve our understanding of the determinants of these pathologies. To address this issue, we combine the accelerated sampling properties of replica exchange mol. dynamics simulations based on the OPEP coarse-grained potential with the at. resoln. description of interactions provided by all-atom MD simulations, and investigate the oligomerization process of the GNNQQNY for three system sizes: 3-mers, 12-mers and 20-mers. Results for our integrated simulations show a rich variety of structural arrangements for aggregates of all sizes. Elongated fibril-like structures can form transiently in the 20-mer case, but they are not stable and easily interconvert in more globular and disordered forms. Our extensive characterization of the intermediate structures and their physico-chem. determinants points to a high degree of polymorphism for the GNNQQNY sequence that can be reflected at the macroscopic scale. Detailed mechanisms and structures that underlie amyloid aggregation are also provided.
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253Maupetit, J.; Derreumaux, P.; Tuffery, P. A fast method for large-scale de novo peptide and miniprotein structure prediction J. Comput. Chem. 2010, 31, 726– 738 DOI: 10.1002/jcc.21365Google Scholar253https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlentbk%253D&md5=1be85f82df7a0ce134cc65aad8aea313A fast method for large-scale De Novo peptide and miniprotein structure predictionMaupetit, Julien; Derreumaux, Philippe; Tuffery, PierreJournal of Computational Chemistry (2010), 31 (4), 726-738CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Although peptides have many biol. and biomedical implications, an accurate method predicting their equil. structural ensembles from amino acid sequences and suitable for large-scale expts. is still missing. The authors introduce a new approach - PEP-FOLD - to the de novo prediction of peptides and miniproteins. It first predicts, in the terms of a Hidden Markov Model-derived structural alphabet, a limited no. of local conformations at each position of the structure. It then performs their assembly using a greedy procedure driven by a coarse-grained energy score. On a benchmark of 52 peptides with 9-23 amino acids, PEP-FOLD generates lowest-energy conformations within 2.8 and 2.3 Å Cα root-mean-square deviation from the full NMR structures (NMR) and the NMR rigid cores, resp., outperforming previous approaches. For 13 miniproteins with 27-49 amino acids, PEP-FOLD reaches an accuracy of 3.6 and 4.6 Å Cα root-mean-square deviation for the most-native and lowest-energy conformations, using the nonflexible regions identified by NMR. PEP-FOLD simulations are fast - a few minutes only - opening therefore, the door to in silico large-scale rational design of new bioactive peptides and miniproteins. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010.
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254Maupetit, J.; Derreumaux, P.; Tuffery, P. PEP-FOLD: an online resource for de novo peptide structure prediction Nucleic Acids Res. 2009, 37, W498– 503 DOI: 10.1093/nar/gkp323Google Scholar254https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXosFSrsb0%253D&md5=4e6ba0b1daabcd8679203bf7cc7a542cPEP-FOLD: an online resource for de novo peptide structure predictionMaupetit, Julien; Derreumaux, Philippe; Tuffery, PierreNucleic Acids Research (2009), 37 (Web Server), W498-W503CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Rational peptide design and large-scale prediction of peptide structure from sequence remain a challenge for chem. biologists. The authors present PEP-FOLD, an online service, aimed at de novo modeling of 3D conformations for peptides between 9 and 25 amino acids in aq. soln. Using a hidden Markov model-derived structural alphabet (SA) of 27 four-residue letters, PEP-FOLD first predicts the SA letter profiles from the amino acid sequence and then assembles the predicted fragments by a greedy procedure driven by a modified version of the OPEP coarse-grained force field. Starting from an amino acid sequence, PEP-FOLD performs series of 50 simulations and returns the most representative conformations identified in terms of energy and population. Using a benchmark of 25 peptides with 9-23 amino acids, and considering the reproducibility of the runs, the authors find that, on av., PEP-FOLD locates lowest energy conformations differing by 2.6 Å Cα root mean square deviation from the full NMR structures. PEP-FOLD can be accessed at http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.
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255Pasi, M.; Lavery, R.; Ceres, N. PaLaCe: A Coarse-Grain Protein Model for Studying Mechanical Properties J. Chem. Theory Comput. 2013, 9, 785– 793 DOI: 10.1021/ct3007925Google Scholar255https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1GisbrI&md5=b724c1138b60543dd3c79a864bedbdbdPaLaCe: A Coarse-Grain Protein Model for Studying Mechanical PropertiesPasi, Marco; Lavery, Richard; Ceres, NicolettaJournal of Chemical Theory and Computation (2013), 9 (1), 785-793CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present a coarse-grain protein model PaLaCe (Pasi-Lavery-Ceres) that has been developed principally to allow fast computational studies of protein mechanics and to clarify the links between mechanics and function. PaLaCe uses a two-tier protein representation with one to three pseudoatoms representing each amino acid for the main nonbonded interactions, combined with at.-scale peptide groups and some side chain atoms to allow the explicit representation of backbone hydrogen bonds and to simplify the treatment of bonded interactions. The PaLaCe force field is composed of physics-based terms, parametrized using Boltzmann inversion of conformational probability distributions derived from a protein structure data set, and iteratively refined to reproduce the exptl. distributions. PaLaCe has been implemented in the MMTK simulation package and can be used for energy minimization, normal mode calcns., and mol. or stochastic dynamics. We present simulations with PaLaCe that test its ability to maintain stable structures for folded proteins, reproduce their dynamic fluctuations, and correctly model large-scale, force-induced conformational changes.
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256Frezza, E.; Lavery, R. Internal Normal Mode Analysis (iNMA) Applied to Protein Conformational Flexibility J. Chem. Theory Comput. 2015, 11, 5503– 5512 DOI: 10.1021/acs.jctc.5b00724Google Scholar256https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsFyrur3K&md5=f83807a88396dcbd824b5b55ade713e1Internal Normal Mode Analysis (iNMA) Applied to Protein Conformational FlexibilityFrezza, Elisa; Lavery, RichardJournal of Chemical Theory and Computation (2015), 11 (11), 5503-5512CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We analyze the capacity of normal modes to predict obsd. protein conformational changes, and, notably, those induced by the formation of protein-protein complexes. We show that normal modes calcd. in internal coordinate space (ICS) provide better predictions. For a large test set, using the ICS approach describes the conformational changes more completely, and with fewer low-frequency modes than the equiv. Cartesian coordinate modes, despite the fact that the internal coordinate calcns. were restricted to torsional angles. This can be attributed to the fact that the use of ICS extends the range over which movements along the corresponding eigenvectors remain close to the true conformational energy hypersurface. We also show that the PaLaCe coarse-grain protein model performs better than a simple elastic network model. We apply ICS normal-mode anal. to protein complexes and, by extending the approach of Sunada and G‾o. We show that we can couple an accurate view of the Cartesian coordinate movements induced by ICS modes with the detection of the key residues responsible for the movements.
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257Hinsen, K. The molecular modeling toolkit: A new approach to molecular simulations J. Comput. Chem. 2000, 21, 79– 85 DOI: 10.1002/(SICI)1096-987X(20000130)21:2<79::AID-JCC1>3.0.CO;2-BGoogle Scholar257https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXkt1Shuw%253D%253D&md5=dde47349669bdfcc5ce5c83ce04cf5e0The molecular modeling toolkit: A new approach to molecular simulationsHinsen, KonradJournal of Computational Chemistry (2000), 21 (2), 79-85CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)The Mol. Modeling Toolkit is a library that implements common mol. simulation techniques, with an emphasis on biomol. simulations. It uses modern software engineering techniques (object-oriented design, a high-level language) to overcome limitations assocd. with the large monolithic simulation programs that are commonly used for biomols. Its principal advantages are (1) easy extension and combination with other libraries due to modular library design; (2) a single high-level general-purpose programming language (Python) is used for library implementation as well as for application scripts; (3) use of documented and machine-independent formats for all data files; and (4) interfaces to other simulation and visualization programs.
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258Feig, M.; Karanicolas, J.; Brooks, C. L., 3rd MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology J. Mol. Graphics Modell. 2004, 22, 377– 395 DOI: 10.1016/j.jmgm.2003.12.005Google Scholar258https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXjt1Shur4%253D&md5=071e0c32c3114c5e57239d5f800c8e34MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biologyFeig, Michael; Karanicolas, John; Brooks, Charles L.Journal of Molecular Graphics & Modelling (2004), 22 (5), 377-395CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)We describe the Multiscale Modeling Tools for Structural Biol. (MMTSB) Tool Set (http://mmtsb.scripps.edu/software/mmtsbToolSet.html), which is a novel set of utilities and programming libraries that provide new enhanced sampling and multiscale modeling techniques for the simulation of proteins and nucleic acids. The tool set interfaces with the existing mol. modeling packages CHARMM and Amber for classical all-atom simulations, and with MONSSTER for lattice-based low-resoln. conformational sampling. In addn., it adds new functionality for the integration and translation between both levels of detail. The replica exchange method is implemented to allow enhanced sampling of both the all-atom and low-resoln. models. The tool set aims at applications in structural biol. that involve protein or nucleic acid structure prediction, refinement, and/or extended conformational sampling. With structure prediction applications in mind, the tool set also implements a facility that allows the control and application of modeling tasks on a large set of conformations in what we have termed ensemble computing. Ensemble computing encompasses loosely coupled, parallel computation on high-end parallel computers, clustered computational grids and desktop grid environments. This paper describes the design and implementation of the MMTSB Tool Set and illustrates its utility with three typical examples-scoring of a set of predicted protein conformations in order to identify the most native-like structures, ab initio folding of peptides in implicit solvent with the replica exchange method, and the prediction of a missing fragment in a larger protein structure.
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259Fleishman, S. J.; Corn, J. E.; Strauch, E. M.; Whitehead, T. A.; Andre, I.; Thompson, J.; Havranek, J. J.; Das, R.; Bradley, P.; Baker, D. Rosetta in CAPRI rounds 13–19 Proteins: Struct., Funct., Genet. 2010, 78, 3212– 3218 DOI: 10.1002/prot.22784Google ScholarThere is no corresponding record for this reference.
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260Davis, I. W.; Baker, D. RosettaLigand docking with full ligand and receptor flexibility J. Mol. Biol. 2009, 385, 381– 392 DOI: 10.1016/j.jmb.2008.11.010Google Scholar260https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkt1WhsQ%253D%253D&md5=c8ff49fe105488dce94e1190346d0bb7RL Docking with Full Ligand and Receptor FlexibilityDavis, Ian W.; Baker, DavidJournal of Molecular Biology (2009), 385 (2), 381-392CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Summary: Computational docking of small-mol. ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently obsd. between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small mol. docking programs. We previously described the program RL, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RL that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the av. RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 Å RMSD for 64% (54/85) of cases overall.
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261Weitzner, B. D.; Kuroda, D.; Marze, N.; Xu, J.; Gray, J. J. Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization Proteins: Struct., Funct., Genet. 2014, 82, 1611– 1623 DOI: 10.1002/prot.24534Google ScholarThere is no corresponding record for this reference.
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262DiMaio, F.; Echols, N.; Headd, J. J.; Terwilliger, T. C.; Adams, P. D.; Baker, D. Improved low-resolution crystallographic refinement with Phenix and Rosetta Nat. Methods 2013, 10, 1102– 1104 DOI: 10.1038/nmeth.2648Google Scholar262https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2c%252FitVynsA%253D%253D&md5=57a182ff1bb5970358d27fc6bcb1e559Improved low-resolution crystallographic refinement with Phenix and RosettaDiMaio Frank; Echols Nathaniel; Headd Jeffrey J; Terwilliger Thomas C; Adams Paul D; Baker DavidNature methods (2013), 10 (11), 1102-4 ISSN:.Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.
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263Mao, B. C.; Tejero, R.; Baker, D.; Montelione, G. T. Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures J. Am. Chem. Soc. 2014, 136, 1893– 1906 DOI: 10.1021/ja409845wGoogle ScholarThere is no corresponding record for this reference.
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264London, N.; Raveh, B.; Cohen, E.; Fathi, G.; Schueler-Furman, O. Rosetta FlexPepDock web server--high resolution modeling of peptide-protein interactions Nucleic Acids Res. 2011, 39, W249– 253 DOI: 10.1093/nar/gkr431Google Scholar264https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXosVOnt7o%253D&md5=c717db75b60ad3830be39c42c90b5f0aRosetta FlexPepDock web server-high resolution modeling of peptide-protein interactionsLondon, Nir; Raveh, Barak; Cohen, Eyal; Fathi, Guy; Schueler-Furman, OraNucleic Acids Research (2011), 39 (Web Server), W249-W253CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Peptide-protein interactions are among the most prevalent and important interactions in the cell, but a large fraction of those interactions lack detailed structural characterization. The Rosetta FlexPepDock web server (http://flexpepdock.furmanlab.cs.huji.ac.il/) provides an interface to a high-resoln. peptide docking (refinement) protocol for the modeling of peptide-protein complexes, implemented within the Rosetta framework. Given a protein receptor structure and an approx., possibly inaccurate model of the peptide within the receptor binding site, the FlexPepDock server refines the peptide to high resoln., allowing full flexibility to the peptide backbone and to all side chains. This protocol was extensively tested and benchmarked on a wide array of non-redundant peptide-protein complexes, and was proven effective when applied to peptide starting conformations within 5.5 Å backbone root mean square deviation from the native conformation. FlexPepDock has been applied to several systems that are mediated and regulated by peptide-protein interactions. This easy to use and general web server interface allows non-expert users to accurately model their specific peptide-protein interaction of interest.
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265Liu, T.; Pan, X.; Chao, L.; Tan, W.; Qu, S.; Yang, L.; Wang, B.; Mei, H. Subangstrom accuracy in pHLA-I modeling by Rosetta FlexPepDock refinement protocol J. Chem. Inf. Model. 2014, 54, 2233– 2242 DOI: 10.1021/ci500393hGoogle Scholar265https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFylurjM&md5=fac070347e6405c9494b386f43f3646aSubangstrom Accuracy in pHLA-I Modeling by Rosetta FlexPepDock Refinement ProtocolLiu, Tengfei; Pan, Xianchao; Chao, Li; Tan, Wen; Qu, Sujun; Yang, Li; Wang, Bochu; Mei, HuJournal of Chemical Information and Modeling (2014), 54 (8), 2233-2242CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Flexible peptides binding to human leukocyte antigen (HLA) play a key role in mediating human immune responses and are also involved in idiosyncratic adverse drug reactions according to recent research. However, the structural detns. of pHLA complexes remain challenging under the present conditions. In this paper, the performance of a new peptide docking method, namely FlexPepDock, was systematically investigated by a benchmark of 30 crystd. structures of peptide-HLA class I complexes. The docking results showed that the near-native pHLA-I models with peptide bb-RMSD less than 2 Å were ranked in the top 1 model for 100% (70/70) docking cases, and the subangstrom models with peptide bb-RMSD less than 1 Å were ranked in the top 5 lowest-energy models for 65.7% (46/70) docking cases. Furthermore, 10 out of 70 docking cases ranked the subangstrom all-atom models in the top 5 lowest-energy models. The results showed that the FlexPepDock can generate high-quality models of pHLA-I complexes and can be widely applied to pHLA-I modeling and mechanism research of peptide-mediated immune responses.
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266Thyme, S.; Baker, D. Redesigning the specificity of protein-DNA interactions with Rosetta Methods Mol. Biol. 2014, 1123, 265– 282 DOI: 10.1007/978-1-62703-968-0_17Google Scholar266https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cvjsFCqsg%253D%253D&md5=a900d735c00fe5b35bd24d12e876fbd5Redesigning the specificity of protein-DNA interactions with RosettaThyme Summer; Baker DavidMethods in molecular biology (Clifton, N.J.) (2014), 1123 (), 265-82 ISSN:.Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.
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267Lyskov, S.; Chou, F. C.; Conchuir, S. O.; Der, B. S.; Drew, K.; Kuroda, D.; Xu, J.; Weitzner, B. D.; Renfrew, P. D.; Sripakdeevong, P. Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE) PLoS One 2013, 8, e63906 DOI: 10.1371/journal.pone.0063906Google ScholarThere is no corresponding record for this reference.
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268Basdevant, N.; Borgis, D.; Ha-Duong, T. Modeling Protein-Protein Recognition in Solution Using the Coarse-Grained Force Field SCORPION J. Chem. Theory Comput. 2013, 9, 803– 813 DOI: 10.1021/ct300943wGoogle Scholar268https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVSqtLjM&md5=8ccba3c59293c790a036e89ce29598efModeling Protein-Protein Recognition in Solution Using the Coarse-Grained Force Field SCORPIONBasdevant, Nathalie; Borgis, Daniel; Ha-Duong, TapJournal of Chemical Theory and Computation (2013), 9 (1), 803-813CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present here the SCORPION-Solvated COaRse-grained Protein interactION-force field, a physics-based simplified coarse-grained (CG) force field. It combines our previous CG protein model and a novel particle-based water model which makes it suitable for mol. dynamics (MD) simulations of protein assocn. processes. The protein model in SCORPION represents each amino acid with one to three beads, for which electrostatic and van der Waals effective interactions are fitted sep. to reproduce those of the all-atom AMBER force field. The protein internal flexibility is accounted for by an elastic network model (ENM). We now include in SCORPION a new Polarizable Coarse-Grained Solvent (PCGS) model, which is computationally efficient, consistent with the protein CG representation, and yields accurate electrostatic free energies of proteins. SCORPION is used here for the first time to perform hundreds-of-nanoseconds-long MD simulations of protein/protein recognition in water, here the case of the barnase/barstar complex. These MD simulations showed that, for five of a total of seven simulations starting from several initial conformations, and after a time going from 1 to 500 ns, the proteins bind in a conformation very close to the native bound structure and remain stable in this conformation for the rest of the simulation. An energetic anal. of these MD show that this recognition is driven both by van der Waals and electrostatic interactions between proteins. SCORPION appears therefore as a useful tool to study protein-protein recognition in a solvated environment.
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269Liwo, A.; Khalili, M.; Scheraga, H. A. Ab initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chains Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 2362– 2367 DOI: 10.1073/pnas.0408885102Google Scholar269https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhvFKit70%253D&md5=ca40abacca7b7226c7ce9aad8e186c5cAb initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chainsLiwo, Adam; Khalili, Mey; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2005), 102 (7), 2362-2367CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We report the application of Langevin dynamics to the physics-based united-residue (UNRES) force field developed in our lab. Ten trajectories were run on seven proteins [PDB ID codes 1BDD (α; 46 residues), 1GAB (α; 47 residues), 1LQ7 (α; 67 residues), 1CLB (α; 75 residues), 1E0L (β; 28 residues), and 1E0G (α+β; 48 residues), and 1IGD (α+β; 61 residues)] with the UNRES force field parameterized by using our recently developed method for obtaining a hierarchical structure of the energy landscape. All α-helical proteins and 1E0G folded to the native-like structures, whereas 1IGD and 1E0L yielded mostly nonnative α-helical folds although the native-like structures are lowest in energy for these two proteins, which can be attributed to neglecting the entropy factor in the current parameterization of UNRES. Av. folding times for successful folding simulations were of the order of nanoseconds, whereas even the ultrafast-folding proteins fold only in microseconds, which implies that the UNRES time scale is approx. three orders of magnitude larger than the exptl. time scale because the fast motions of the secondary degrees of freedom are averaged out. Folding with Langevin dynamics required 2-10 h of CPU time on av. with a single AMD Athlon MP 2800+ processor depending on the size of the protein. With the advantage of parallel processing, this process leads to the possibility to explore thousands of folding pathways and to predict not only the native structure but also the folding scenario of a protein together with its quant. kinetic and thermodn. characteristics.
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270Zhou, R.; Maisuradze, G. G.; Sunol, D.; Todorovski, T.; Macias, M. J.; Xiao, Y.; Scheraga, H. A.; Czaplewski, C.; Liwo, A. Folding kinetics of WW domains with the united residue force field for bridging microscopic motions and experimental measurements Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 18243– 18248 DOI: 10.1073/pnas.1420914111Google Scholar270https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVClu7bK&md5=9e7742558ba4d961885696b8099ad460Folding kinetics of WW domains with the united residue force field for bridging microscopic motions and experimental measurementsZhou, Rui; Maisuradze, Gia G.; Sunol, David; Todorovski, Toni; Macias, Maria J.; Xiao, Yi; Scheraga, Harold A.; Czaplewski, Cezary; Liwo, AdamProceedings of the National Academy of Sciences of the United States of America (2014), 111 (51), 18243-18248CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)To demonstrate the utility of the coarse-grained united-residue (UNRES) force field to compare exptl. and computed kinetic data for folding proteins, the authors performed long-time millisecond-timescale canonical Langevin mol. dynamics simulations of the triple β-strand from the formin-binding protein 28 (FBP28) WW domain and 6 nonnatural variants, using UNRES. The results were compared with available exptl. data in both a qual. and a quant. manner. Complexities of the folding pathways, which could not be detd. exptl., were revealed. The folding mechanisms obtained from the simulated folding kinetics were in agreement with the exptl. results, with a few discrepancies for which the authors accounted. The origins of single- and double-exponential kinetics and their correlations with 2- and 3-state folding scenarios were shown to be related to the relative barrier heights between the various states. The rate consts. obtained from time profiles of the fractions of the native, intermediate, and unfolded structures, and the kinetic equations fitted to them, correlated with the exptl. values; however, they were about 3 orders of magnitude larger than the exptl. ones for most of the systems. These differences were in agreement with the timescale extension derived by scaling down the friction of water and averaging out the fast degrees of freedom when passing from all-atom to a coarse-grained representation. These results indicate that the UNRES force field can provide accurate predictions of folding kinetics of these WW domains, often used as models for the study of the mechanisms of protein folding.
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271Maisuradze, G. G.; Senet, P.; Czaplewski, C.; Liwo, A.; Scheraga, H. A. Investigation of protein folding by coarse-grained molecular dynamics with the UNRES force field J. Phys. Chem. A 2010, 114, 4471– 4485 DOI: 10.1021/jp9117776Google Scholar271https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXitFaqu7c%253D&md5=5e091a0f996c23e80f3b3f4627a1a2b6Investigation of Protein Folding by Coarse-Grained Molecular Dynamics with the UNRES Force FieldMaisuradze, Gia G.; Senet, Patrick; Czaplewski, Cezary; Liwo, Adam; Scheraga, Harold A.Journal of Physical Chemistry A (2010), 114 (13), 4471-4485CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)Coarse-grained mol. dynamics (MD) simulations offer a dramatic extension of the time-scale of simulations compared to all-atom approaches. In this article, we describe the use of the physics-based united-residue (UNRES) force field, developed in our lab., in protein-structure simulations. We demonstrate that this force field offers about a 4000-times extension of the simulation time scale; this feature arises both from averaging out the fast-moving degrees of freedom and redn. of the cost of energy and force calcns. compared to all-atom approaches with explicit solvent. With massively parallel computers, microsecond folding simulation times of proteins contg. about 1000 residues can be obtained in days. A straightforward application of canonical UNRES/MD simulations, demonstrated with the example of the N-terminal part of the B-domain of staphylococcal protein A (PDB code: 1BDD, a three-α-helix bundle), discerns the folding mechanism and dets. kinetic parameters by parallel simulations of several hundred or more trajectories. Use of generalized-ensemble techniques, of which the multiplexed replica exchange method proved to be the most effective, enables us to compute thermodn. of folding and carry out fully physics-based prediction of protein structure, in which the predicted structure is detd. as a mean over the most populated ensemble below the folding-transition temp. By using principal component anal. of the UNRES folding trajectories of the formin-binding protein (FBP) WW domain (PDB code: 1E0L; a three-stranded antiparallel β-sheet) and 1BDD, we identified representative structures along the folding pathways and demonstrated that only a few (low-indexed) principal components can capture the main structural features of a protein-folding trajectory; the potentials of mean force calcd. along these essential modes exhibit multiple min., as opposed to those along the remaining modes that are unimodal. In addn., a comparison between the structures that are representative of the min. in the free-energy profile along the essential collective coordinates of protein folding (computed by principal component anal.) and the free-energy profile projected along the virtual-bond dihedral angles γ of the backbone revealed the key residues involved in the transitions between the different basins of the folding free-energy profile, in agreement with existing exptl. data for 1E0L.
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272Kachlishvili, K.; Maisuradze, G. G.; Martin, O. A.; Liwo, A.; Vila, J. A.; Scheraga, H. A. Accounting for a mirror-image conformation as a subtle effect in protein folding Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 8458– 8463 DOI: 10.1073/pnas.1407837111Google Scholar272https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXos1aqu70%253D&md5=903aa26bdac4da7f0b1f3c377b2bdd47Accounting for a mirror-image conformation as a subtle effect in protein foldingKachlishvili, Khatuna; Maisuradze, Gia G.; Martin, Osvaldo A.; Liwo, Adam; Vila, Jorge A.; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2014), 111 (23), 8458-8463CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)By using local (free-energy profiles along the amino acid sequence and 13Cα chem. shifts) and global (principal component) analyses to examine the mol. dynamics of protein-folding trajectories, generated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein A, we are able to (i) provide the main reason for formation of the mirror-image conformation of this protein, namely, a slow formation of the second loop and part of the third helix (Asp29-Asn35), caused by the presence of multiple local conformational states in this portion of the protein; (ii) show that formation of the mirror-image topol. is a subtle effect resulting from local interactions; (iii) provide a mechanism for how protein A overcomes the barrier between the metastable mirror-image state and the native state; and (iv) offer a plausible reason to explain why protein A does not remain in the metastable mirror-image state even though the mirror-image and native conformations are at least energetically compatible.
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273He, Y.; Mozolewska, M. A.; Krupa, P.; Sieradzan, A. K.; Wirecki, T. K.; Liwo, A.; Kachlishvili, K.; Rackovsky, S.; Jagiela, D.; Slusarz, R. Lessons from application of the UNRES force field to predictions of structures of CASP10 targets Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 14936– 14941 DOI: 10.1073/pnas.1313316110Google Scholar273https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFWrsrvO&md5=99e8f593f1e989338148ff13fda82c3cLessons from application of the UNRES force field to predictions of structures of CASP10 targetsHe, Yi; Mozolewska, Magdalena A.; Krupa, Pawel; Sieradzan, Adam K.; Wirecki, Tomasz K.; Liwo, Adam; Kachlishvili, Khatuna; Rackovsky, Shalom; Jagiela, Dawid; Slusarz, Rafal; Czaplewski, Cezary R.; Oldziej, Stanislaw; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2013), 110 (37), 14936-14941,S14936/1-S14936/2CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our lab. for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families detd. by multiplexed replica-exchange simulations, from the 10th Community Wide Expt. on the Crit. Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two α + β domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the exptl. structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain-domain orientations, which is a significant advance in the state of the art.
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274Krupa, P.; Sieradzan, A. K.; Rackovsky, S.; Baranowski, M.; Oldziej, S.; Scheraga, H. A.; Liwo, A.; Czaplewski, C. Improvement of the treatment of loop structures in the UNRES force field by inclusion of coupling between backbone- and side-chain-local conformational states. J. Chem. Theory Comput. 2013, 9, 4620 DOI: 10.1021/ct4004977Google Scholar274https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtlyjsrvO&md5=d6088df53b20d96e37e583d85d4fec76Improvement of the Treatment of Loop Structures in the UNRES Force Field by Inclusion of Coupling between Backbone- and Side-Chain-Local Conformational StatesKrupa, Pawel; Sieradzan, Adam K.; Rackovsky, S.; Baranowski, Maciej; Oldziej, Stanislaw; Scheraga, Harold A.; Liwo, Adam; Czaplewski, CezaryJournal of Chemical Theory and Computation (2013), 9 (10), 4620-4632CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The UNited RESidue (UNRES) coarse-grained model of polypeptide chains, developed in the authors' lab., enables the authors to carry out millisecond-scale mol.-dynamics simulations of large proteins effectively. It performs well in ab initio predictions of protein structure, as demonstrated in the last Community Wide Expt. on the Crit. Assessment of Techniques for Protein Structure Prediction (CASP10). However, the resoln. of the simulated structure is too coarse, esp. in loop regions, which results from insufficient specificity of the model of local interactions. To improve the representation of local interactions, the authors introduced new side-chain-backbone correlation potentials, derived from a statistical anal. of loop regions of 4585 proteins. To obtain sufficient statistics, the authors reduced the set of amino-acid-residue types to five groups, derived in the authors' earlier work on structurally optimized reduced alphabets, based on a statistical anal. of the properties of amino-acid structures. The new correlation potentials are expressed as one-dimensional Fourier series in the virtual-bond-dihedral angles involving side-chain centroids. The wt. of these new terms was detd. by a trial-and-error method, in which Multiplexed Replica Exchange Mol. Dynamics (MREMD) simulations were run on selected test proteins. The best av. root-mean-square deviations (RMSDs) of the calcd. structures from the exptl. structures below the folding-transition temps. were obtained with the wt. of the new side-chain-backbone correlation potentials equal to 0.57. The resulting conformational ensembles were analyzed in detail by using the Weighted Histogram Anal. Method (WHAM) and Ward's min.-variance clustering. This anal. showed that the RMSDs from the exptl. structures dropped by 0.5 Å on av., compared to simulations without the new terms, and the deviation of individual residues in the loop region of the computed structures from their counterparts in the exptl. structures (after optimum superposition of the calcd. and exptl. structure) decreased by up to 8 Å. Consequently, the new terms improve the representation of local structure.
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275Sieradzan, A. K.; Liwo, A.; Hansmann, U. H. Folding and self-assembly of a small protein complex J. Chem. Theory Comput. 2012, 8, 3416– 3422 DOI: 10.1021/ct300528rGoogle Scholar275https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1eksLjL&md5=93bc6e1c0bd60cfa649ad06111a02bb3Folding and self-assembly of a small protein complexSieradzan, Adam K.; Liwo, Adam; Hansmann, Ulrich H. E.Journal of Chemical Theory and Computation (2012), 8 (9), 3416-3422CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The synthetic homotetrameric ββα (BBAT1) protein possesses a stable quaternary structure with a ββα fold. Because of its small size (a total of 84 residues), the homotetramer is an excellent model system with which to study self-assembly and protein-protein interactions. The authors found from replica-exchange mol. dynamics simulations with the coarse-grain UNRES force field that the folding and assocn. pathway consisted of 3 well-sepd. steps, where assocn. to a tetramer preceded and facilitated the folding of the 4 chains. At room temp., the tetramer exists in an ensemble of diverse structures. The crystal structure became energetically favored only when the mol. was in a dense and crystal-like environment. The obsd. picture of folding promoted by assocn. may mirror the mechanism according to which intrinsically unfolded proteins assume their functional structures.
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276Rojas, A.; Liwo, A.; Browne, D.; Scheraga, H. A. Mechanism of fiber assembly: treatment of Abeta peptide aggregation with a coarse-grained united-residue force field J. Mol. Biol. 2010, 404, 537– 552 DOI: 10.1016/j.jmb.2010.09.057Google Scholar276https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVaisLzJ&md5=19246393bf0c0db34b22115bd9300d2bMechanism of Fiber Assembly: Treatment of Aβ Peptide Aggregation with a Coarse-Grained United-Residue Force FieldRojas, Ana; Liwo, Adam; Browne, Dana; Scheraga, Harold A.Journal of Molecular Biology (2010), 404 (3), 537-552CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The growth mechanism of β-amyloid (Aβ) peptide fibrils was studied by a physics-based coarse-grained united-residue model and mol. dynamics (MD) simulations. To identify the mechanism of monomer addn. to an Aβ1-40 fibril, we placed an unstructured monomer at a distance of 20 Å from a fibril template and allowed it to interact freely with the latter. The monomer was not biased towards fibril conformation by either the force field or the MD algorithm. With the use of a coarse-grained model with replica-exchange mol. dynamics, a longer timescale was accessible, making it possible to observe how the monomers probe different binding modes during their search for the fibril conformation. Although different assembly pathways were seen, they all follow a dock-lock mechanism with two distinct locking stages, consistent with exptl. data on fibril elongation. Whereas these expts. have not been able to characterize the conformations populating the different stages, we have been able to describe these different stages explicitly by following free monomers as they dock onto a fibril template and to adopt the fibril conformation (i.e., we describe fibril elongation step by step at the mol. level). During the first stage of the assembly ("docking"), the monomer tries different conformations. After docking, the monomer is locked into the fibril through two different locking stages. In the first stage, the monomer forms hydrogen bonds with the fibril template along one of the strands in a two-stranded β-hairpin; in the second stage, hydrogen bonds are formed along the second strand, locking the monomer into the fibril structure. The data reveal a free-energy barrier sepg. the two locking stages. The importance of hydrophobic interactions and hydrogen bonds in the stability of the Aβ fibril structure was examd. by carrying out addnl. canonical MD simulations of oligomers with different nos. of chains (4-16 chains), with the fibril structure as the initial conformation. The data confirm that the structures are stabilized largely by hydrophobic interactions and show that intermol. hydrogen bonds are highly stable and contribute to the stability of the oligomers as well.
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277Golas, E.; Maisuradze, G. G.; Senet, P.; Oldziej, S.; Czaplewski, C.; Scheraga, H. A.; Liwo, A. Simulation of the opening and closing of Hsp70 chaperones by coarse-grained molecular dynamics J. Chem. Theory Comput. 2012, 8, 1750– 1764 DOI: 10.1021/ct200680gGoogle Scholar277https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XjvFKks70%253D&md5=572811dcb87cc1d846be10e018e50a69Simulation of the Opening and Closing of Hsp70 Chaperones by Coarse-Grained Molecular DynamicsGolas, Ewa; Maisuradze, Gia G.; Senet, Patrick; Oldziej, Stanislaw; Czaplewski, Cezary; Scheraga, Harold A.; Liwo, AdamJournal of Chemical Theory and Computation (2012), 8 (5), 1750-1764CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Heat-shock proteins 70 (Hsp70s) are key mol. chaperones, which assist in the folding and refolding/disaggregation of proteins. Hsp70s, which consist of a nucleotide-binding domain (NBD, consisting of NBD-I and NBD-II subdomains) and a substrate-binding domain [SBD, further split into the β-sheet (SBD-β) and α-helical (SBD-α) subdomains], occur in two major conformations having (a) a closed SBD, in which the SBD and NBD domains do not interact, and (b) an open SBD, in which SBD-α interacts with NBD-I and SBD-β interacts with the top parts of NBD-I and NBD-II. In the SBD-closed conformation, SBD is bound to a substrate protein, with release occurring after transition to the open conformation. While the transition from the closed to the open conformation is triggered efficiently by binding of ATP to the NBD, it also occurs, although less frequently, in the absence of ATP. The reverse transition occurs after ATP hydrolysis. Here, we report canonical and multiplexed replica exchange simulations of the conformational dynamics of Hsp70s using a coarse-grained mol. dynamics approach with the UNRES force field. The simulations were run in the following three modes: (i) with the two halves of the NBD unrestrained relative to each other, (ii) with the two halves of the NBD restrained in an open geometry as in the SBD-closed form of DnaK (2KHO), and (iii) with the two halves of NBD restrained in a closed geometry as in known exptl. structures of ATP-bound NBD forms of Hsp70. Open conformations, in which the SBD interacted strongly with the NBD, formed spontaneously during all simulations; the no. of transitions was largest in simulations carried out with the closed NBD domain, and smallest in those carried out with the open NBD domain; this observation is in agreement with the exptl. obsd. influence of ATP-binding on the transition of Hsp70s from the SBD-closed to the SBD-open form. Two kinds of open conformations were obsd.: one in which SBD-α interacts with NBD-I and SBD-β interacts with the top parts of NBD-I and NBD-II (as obsd. in the structures of nucleotide exchange factors), and another one in which this interaction pattern is swapped. A third type of motion, in which SBD-α binds to NBD without dissocg. from SBD-β, was also obsd. It was found that the first stage of interdomain communication (approach of SBD-β, to NBD) is coupled with the rotation of the long axes of NBD-I and NBD-II toward each other. To the best of our knowledge, this is the first successful simulation of the full transition of an Hsp70 from the SBD-closed to the SBD-open conformation.
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278Boras, B. W.; Hirakis, S. P.; Votapka, L. W.; Malmstrom, R. D.; Amaro, R. E.; McCulloch, A. D. Bridging scales through multiscale modeling: a case study on protein kinase A Front. Physiol. 2015, 6, 250 DOI: 10.3389/fphys.2015.00250Google Scholar278https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC283ps1SmsQ%253D%253D&md5=42aff952a7e93e735382e39c1b39988bBridging scales through multiscale modeling: a case study on protein kinase ABoras Britton W; Hirakis Sophia P; Votapka Lane W; Malmstrom Robert D; Amaro Rommie E; McCulloch Andrew DFrontiers in physiology (2015), 6 (), 250 ISSN:.The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.
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279Ackerman, D. G.; Feigenson, G. W. Multiscale modeling of four-component lipid mixtures: domain composition, size, alignment, and properties of the phase interface J. Phys. Chem. B 2015, 119, 4240– 4250 DOI: 10.1021/jp511083zGoogle Scholar279https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXlsFGmtQ%253D%253D&md5=3c4110db7eea34ecd4811381fc1fa819Multiscale Modeling of Four-Component Lipid Mixtures: Domain Composition, Size, Alignment, and Properties of the Phase InterfaceAckerman, David G.; Feigenson, Gerald W.Journal of Physical Chemistry B (2015), 119 (11), 4240-4250CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Simplified lipid mixts. are often used to model the complex behavior of the cell plasma membrane. Indeed, as few as four components-a high-melting lipid, a nanodomain-inducing low-melting lipid, a macrodomain-inducing low-melting lipid, and cholesterol (chol)-can give rise to a wide range of domain sizes and patterns that are highly sensitive to lipid compns. Although these systems are studied extensively with expts., the mol.-level details governing their phase behavior are not yet known. We address this issue by using mol. dynamics simulations to analyze how phase sepn. evolves in a four-component system as it transitions from small domains to large domains. To do so, we fix concns. of the high-melting lipid 16:0,16:0-phosphatidylcholine (DPPC) and chol, and incrementally replace the nanodomain-inducing low-melting lipid 16:0,18:2-PC (PUPC) by the macrodomain-inducing low-melting lipid 18:2,18:2-PC (DUPC). Coarse-grained simulations of this four-component system reveal that lipid demixing increases as the amt. of DUPC increases. Addnl., we find that domain size and interleaflet alignment change sharply over a narrow range of replacement of PUPC by DUPC, indicating that intraleaflet and interleaflet behaviors are coupled. Corresponding united atom simulations show that only lipids within ∼2 nm of the phase interface are significantly perturbed regardless of domain compn. or size. Thus, whereas the fraction of interface-perturbed lipids is negligible for large domains, it is significant for smaller ones. Together, these results reveal characteristic traits of bilayer thermodn. behavior in four-component mixts., and provide a baseline for investigation of the effects of proteins and other lipids on membrane phase properties.
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280Hills, R. D., Jr.; McGlinchey, N. Model parameters for simulation of physiological lipids J. Comput. Chem. 2016, 37, 1112 DOI: 10.1002/jcc.24324Google Scholar280https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitlCqtr0%253D&md5=5a5c46ead0c4bfc00e896a66bc355280Model parameters for simulation of physiological lipidsHills, Ronald D., Jr.; McGlinchey, NicholasJournal of Computational Chemistry (2016), 37 (12), 1112-1118CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse grain simulation of proteins in their physiol. membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsatd. lipids DOPC and DOPE, mixed-chain satn. POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixts. with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid-protein interaction model, making the force field of general utility for studying membrane proteins in physiol. representative bilayers. © 2016 The Authors. Journal of Computational Chem. Published by Wiley Periodicals, Inc.
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281Bromfield, S. M.; Posocco, P.; Fermeglia, M.; Tolosa, J.; Herreros-Lopez, A.; Pricl, S.; Rodriguez-Lopez, J.; Smith, D. K. Shape-persistent and adaptive multivalency: rigid transgeden (TGD) and flexible PAMAM dendrimers for heparin binding Chem. - Eur. J. 2014, 20, 9666– 9674 DOI: 10.1002/chem.201402237Google Scholar281https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtVGqtbvK&md5=e52d5cad44dfef0a7817238f8e9e2bd1Shape-Persistent and Adaptive Multivalency: Rigid Transgeden (TGD) and Flexible PAMAM Dendrimers for Heparin BindingBromfield, Stephen M.; Posocco, Paola; Fermeglia, Maurizio; Tolosa, Juan; Herreros-Lopez, Ana; Pricl, Sabrina; Rodriguez-Lopez, Julian; Smith, David K.Chemistry - A European Journal (2014), 20 (31), 9666-9674CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)This study studies transgeden (TGD) dendrimers (polyamidoamine (PAMAM)-type dendrimers modified with rigid polyphenylenevinylene (PPV) cores) and compares their heparin-binding ability with com. available PAMAM dendrimers. Although the peripheral ligands are near-identical between the two dendrimer families, their heparin binding is very different. At low generation (G1), TGD outperforms PAMAM, but at higher generation (G2 and G3), the PAMAMs are better. Heparin binding also depends strongly on the dendrimer/heparin ratio. The authors explain these effects using multiscale modeling. TGD dendrimers exhibit "shape-persistent multivalency"; the rigidity means that small clusters of surface amines are locally well optimized for target binding, but it prevents the overall nanoscale structure from rearranging to maximize its contacts with a single heparin chain. Conversely, PAMAM dendrimers exhibit "adaptive multivalency"; the flexibility means individual surface ligands are not so well optimized locally to bind heparin chains, but the nanostructure can adapt more easily and maximize its binding contacts. As such, this study exemplifies important new paradigms in multivalent biomol. recognition.
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282Zavadlav, J.; Podgornik, R.; Praprotnik, M. Adaptive Resolution Simulation of a DNA Molecule in Salt Solution J. Chem. Theory Comput. 2015, 11, 5035– 5044 DOI: 10.1021/acs.jctc.5b00596Google Scholar282https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVyntL3I&md5=8b3e65b2088f3d1f9c4c34dc2b6fa277Adaptive resolution simulation of a DNA molecule in salt solutionZavadlav, Julija; Podgornik, Rudolf; Praprotnik, MatejJournal of Chemical Theory and Computation (2015), 11 (10), 5035-5044CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present a multiscale simulation of a DNA mol. in 1M NaCl salt soln. environment, employing the adaptive resoln. simulation approach that allows the solvent mols., i.e., water and ions, to change their resoln. from atomistic to coarse-grained and vice versa adaptively on-the-fly. The region of high resoln. moves together with the DNA center-of-mass so that the DNA itself is always modeled at high resoln. The authors show that their multiscale simulations yield a stable DNA-soln. system, with statistical properties similar to those produced by the conventional all-atom mol. dynamics simulation. Special attention is given to the collective properties, such as the dielec. const., as they provide a sensitive quality measure of this multiscale approach.
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283Panteva, M. T.; Dissanayake, T.; Chen, H.; Radak, B. K.; Kuechler, E. R.; Giambasu, G. M.; Lee, T. S.; York, D. M. Multiscale methods for computational RNA enzymology Methods Enzymol. 2015, 553, 335– 374 DOI: 10.1016/bs.mie.2014.10.064Google ScholarThere is no corresponding record for this reference.
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284Ayton, G. S.; Voth, G. A. Systematic multiscale simulation of membrane protein systems Curr. Opin. Struct. Biol. 2009, 19, 138– 144 DOI: 10.1016/j.sbi.2009.03.001Google Scholar284https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkvVSqt7s%253D&md5=6fba0da15839d8df2b3b945d6f140772Systematic multiscale simulation of membrane protein systemsAyton, Gary S.; Voth, Gregory A.Current Opinion in Structural Biology (2009), 19 (2), 138-144CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. Current multiscale simulation approaches for membrane protein systems vary depending in their degree of connection to the underlying mol. scale interactions. Various approaches have been developed that include such information into coarse-grained models of both the membrane and the proteins. By contrast, other approaches employ parameterizations obtained from exptl. data. Mesoscopic models operate at larger scales and have also been employed to examine membrane remodeling, protein inclusions, and ion channel gating. When bridged together such that mol.-level information is propagated between the different scales, a systematic multiscale methodol. for membrane protein systems can be achieved.
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285Sharma, S.; Ding, F.; Dokholyan, N. V. Multiscale modeling of nucleosome dynamics Biophys. J. 2007, 92, 1457– 1470 DOI: 10.1529/biophysj.106.094805Google ScholarThere is no corresponding record for this reference.
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286Gao, T.; Blackwell, R.; Glaser, M. A.; Betterton, M. D.; Shelley, M. J. Multiscale modeling and simulation of microtubule-motor-protein assemblies Phys. Rev. E Stat. Nonlin. Soft. Matter Phys. 2015, 92, 062709 DOI: 10.1103/PhysRevE.92.062709Google ScholarThere is no corresponding record for this reference.
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287Xie, Z. R.; Chen, J.; Wu, Y. Multiscale Model for the Assembly Kinetics of Protein Complexes J. Phys. Chem. B 2016, 120, 621 DOI: 10.1021/acs.jpcb.5b08962Google Scholar287https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XjvFajsg%253D%253D&md5=3f36a348a09539ab56be6be719f0be55Multiscale Model for the Assembly Kinetics of Protein ComplexesXie, Zhong-Ru; Chen, Jiawen; Wu, YinghaoJournal of Physical Chemistry B (2016), 120 (4), 621-632CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The assembly of proteins into high-order complexes is a general mechanism for these biomols. to implement their versatile functions in cells. Natural evolution has developed various assembling pathways for specific protein complexes to maintain their stability and proper activities. Previous studies have provided numerous examples of the misassembly of protein complexes leading to severe biol. consequences. Although the research focusing on protein complexes has started to move beyond the static representation of quaternary structures to the dynamic aspect of their assembly, the current understanding of the assembly mechanism of protein complexes is still largely limited. To tackle this problem, we developed a new multiscale modeling framework. This framework combines a lower-resoln. rigid-body-based simulation with a higher-resoln. Cα-based simulation method so that protein complexes can be assembled with both structural details and computational efficiency. We applied this model to a homotrimer and a heterotetramer as simple test systems. Consistent with exptl. observations, our simulations indicated very different kinetics between protein oligomerization and dimerization. The formation of protein oligomers is a multistep process that is much slower than dimerization but thermodynamically more stable. Moreover, we showed that even the same protein quaternary structure can have very diverse assembly pathways under different binding consts. between subunits, which is important for regulating the functions of protein complexes. Finally, we revealed that the binding between subunits in a complex can be synergistically strengthened during assembly without considering allosteric regulation or conformational changes. Therefore, our model provides a useful tool to understand the general principles of protein complex assembly.
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288Zheng, J. J.; Wang, D. Q.; Thiel, W.; Shaik, S. QM/MM study of mechanisms for compound I formation in the catalytic cycle of cytochrome P450cam J. Am. Chem. Soc. 2006, 128, 13204– 13215 DOI: 10.1021/ja063439lGoogle Scholar288https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XpsF2itLo%253D&md5=3dbc9ad468ea2b9c2e5ebbee23345460QM/MM Study of Mechanisms for Compound I Formation in the Catalytic Cycle of Cytochrome P450camZheng, Jingjing; Wang, Dongqi; Thiel, Walter; Shaik, SasonJournal of the American Chemical Society (2006), 128 (40), 13204-13215CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)In the catalytic cycle of cytochrome P450cam, after mol. oxygen binds as a ligand to the heme iron atom to yield a ferrous dioxygen complex, there are fast proton transfers that lead to the formation of the active species, Compd. I (Cpd I), which are not well understood because they occur so rapidly. In the present work, the conversion of the ferric hydroperoxo complex (Cpd 0) to Cpd I has been investigated by combined quantum-mech./mol.-mech. (QM/MM) calcns. The residues Asp251 and Glu366 are considered as proton sources. In mechanism I, a proton is transported to the distal oxygen atom of the hydroperoxo group via a hydrogen bonding network to form protonated Cpd 0 (prot-Cpd0: FeOOH2), followed by heterolytic O-O bond cleavage that generates Cpd I and water. Although a local min. is found for prot-Cpd0 in the Glu366 channel, it is very high in energy (more than 20 kcal/mol above Cpd 0) and the barriers for its decay are only 3-4 kcal/mol (both toward Cpd 0 and Cpd I). In mechanism II, an initial O-O bond cleavage followed by a concomitant proton and electron transfer yields Cpd I and water. The rate-limiting step in mechanism II is O-O cleavage with a barrier of about 13-14 kcal/mol. According to the QM/MM calcns., the favored low-energy pathway to Cpd I is provided by mechanism II in the Asp251 channel. Cpd 0 and Cpd I are of similar energies, with a slight preference for Cpd I.
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289Rothlisberger, U.; Carloni, P.; Doclo, K.; Parrinello, M. A comparative study of galactose oxidase and active site analogs based on QM/MM Car Parrinello simulations JBIC, J. Biol. Inorg. Chem. 2000, 5, 236– 250 DOI: 10.1007/s007750050368Google Scholar289https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXjtVejtLg%253D&md5=834a6a840f44d88ac34efe023cadecdcA comparative study of galactose oxidase and active site analogs based on QM/MM Car-Parrinello simulationsRothlisberger, Ursula; Carloni, Paolo; Doclo, Karel; Parrinello, MicheleJBIC, Journal of Biological Inorganic Chemistry (2000), 5 (2), 236-250CODEN: JJBCFA; ISSN:0949-8257. (Springer-Verlag)A parallel study of the radical copper enzyme galactose oxidase (GOase) and a low mol. wt. analog of the active site was performed with dynamic d. functional and mixed quantum-classical calcns. This combined approach enables a direct comparison of the properties of the biomimetic and the natural systems throughout the course of the catalytic reaction. In both cases, five essential forms of the catalytic cycle have been investigated: the resting state in its semi-reduced (catalytically inactive) and its oxidized (catalytically active) form, Asemi and Aox, resp.; a protonated intermediate B; the transition state for the rate-detg. hydrogen abstraction step C, and its product D. For A and B the electronic properties of the biomimetic compd. are qual. very similar to the ones of the natural target. However, in agreement with the exptl. obsd. difference in catalytic activity, the calcd. activation energy for the hydrogen abstraction step is distinctly lower for GOase (16 kcal/mol) than for the mimetic compd. (21 kcal/mol). The enzymic transition state is stabilized by a delocalization of the unpaired spin d. over the sulfur-modified equatorial tyrosine Tyr272, an effect that for geometric reasons is essentially absent in the biomimetic compd. Further differences between the mimic and its natural target concern the structure of the product of the abstraction step, which is characterized by a weakly coordinated aldehyde complex for the latter and a tightly bound linear complex for the former.
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290Shurki, A.; Warshel, A. Structure/function correlations of proteins using MM, QM/MM, and related approaches: Methods, concepts, pitfalls, and current progress Adv. Protein Chem. 2003, 66, 249– 313 DOI: 10.1016/S0065-3233(03)66007-9Google Scholar290https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXos1yhug%253D%253D&md5=33490555b78d1a92c4ebf9073dc3dcaeStructure/function correlations of proteins using MM, QM/MM, and related approaches: methods, concepts, pitfalls, and current progressShurki, A.; Warshel, A.Advances in Protein Chemistry (2003), 66 (Protein Simulations), 249-313CODEN: APCHA2; ISSN:0065-3233. (Elsevier Science)A review on structure-function correlations of proteins using mol. mechanics (MM), quantum mechanics (QM)/MM, and related approaches including methods, concepts, pitfalls, and current progress.
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291Roy, S.; Kastner, J. Synergistic Substrate and Oxygen Activation in Salicylate Dioxygenase Revealed by QM/MM Simulations Angew. Chem., Int. Ed. 2016, 55, 1168– 1172 DOI: 10.1002/anie.201506363Google Scholar291https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFens7bP&md5=aa56b890dc951bccb5a884ddcdd9f1fcSynergistic Substrate and Oxygen Activation in Salicylate Dioxygenase Revealed by QM/MM SimulationsRoy, Subhendu; Kaestner, JohannesAngewandte Chemie, International Edition (2016), 55 (3), 1168-1172CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)Salicylate 1,2-dioxygenase (SDO) is the first enzyme to be discovered to catalyze the oxidative cleavage of a monohydroxylated arom. compd., namely salicylate, instead of the well-known electron-rich substrates. We have investigated the mechanism of dioxygen activation in SDO by QM/MM calcns. Our study reveals that the non-heme FeII center in SDO activates salicylate and O2 synergistically through a strong covalent interaction to facilitate the reductive cleavage of O2. A covalent salicylate-FeII-O2 complex is the reactive oxygen species in this case, and its electronic structure is best described as being between the two limiting cases, FeII-O2 and FeII-O2·-, with partial electron transfer from the activated salicylate to O2 via the Fe center. Thus SDO employs a synergistic strategy of substrate and oxygen activation to carry out the catalytic reaction, which is unprecedented in the family of iron dioxygenases. Moreover, O2 activation in SDO happens without the assistance of a proton source. Our study essentially shows a new mechanistic possibility for O2 activation.
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292Raich, L.; Borodkin, V.; Fang, W.; Castro-Lopez, J.; van Aalten, D. M.; Hurtado-Guerrero, R.; Rovira, C. A trapped covalent intermediate of a glycoside hydrolase on the pathway to transglycosylation. Insights from experiments and QM/MM simulations J. Am. Chem. Soc. 2016, 138, 3325 DOI: 10.1021/jacs.5b10092Google ScholarThere is no corresponding record for this reference.
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293Kumar, R. P.; Roopa, L.; Nongthomba, U.; Sudheer Mohammed, M. M.; Kulkarni, N. Docking, molecular dynamics and QM/MM studies to delineate the mode of binding of CucurbitacinE to F-actin J. Mol. Graphics Modell. 2016, 63, 29– 37 DOI: 10.1016/j.jmgm.2015.11.007Google Scholar293https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFagtb7I&md5=dfda59d9f1031cd4b0b97d38eed1fdd5Docking, molecular dynamics and QM/MM studies to delineate the mode of binding of CucurbitacinE to F-actinKumar, R. Pravin; Roopa, L.; Nongthomba, Upendra; Sudheer Mohammed, M. M.; Kulkarni, NaveenJournal of Molecular Graphics & Modelling (2016), 63 (), 29-37CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)CucurbitacinE (CurE) has been known to bind covalently to F-actin and inhibit depolymn. However, the mode of binding of CurE to F-actin and the consequent changes in the F-actin dynamics have not been studied. Through quantum mech./mol. mech. (QM/MM) and d. function theory (DFT) simulations after the mol. dynamics (MD) simulations of the docked complex of F-actin and CurE, a detailed transition state (TS) model for the Michael reaction is proposed. The TS model shows nucleophilic attack of the sulfur of Cys257 at the β-carbon of Michael Acceptor of CurE producing an enol intermediate that forms a covalent bond with CurE. The MD results show a clear difference between the structure of the F-actin in free form and F-actin complexed with CurE. CurE affects the conformation of the nucleotide binding pocket increasing the binding affinity between F-actin and ADP, which in turn could affect the nucleotide exchange. CurE binding also limits the correlated displacement of the relatively flexible domain 1 of F-actin causing the protein to retain a flat structure and to transform into a stable "tense" state. This structural transition could inhibit depolymn. of F-actin. In conclusion, CurE allosterically modulates ADP and stabilizes F-actin structure, thereby affecting nucleotide exchange and depolymn. of F-actin.
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294Carvalho, A. T.; Barrozo, A.; Doron, D.; Kilshtain, A. V.; Major, D. T.; Kamerlin, S. C. Challenges in computational studies of enzyme structure, function and dynamics J. Mol. Graphics Modell. 2014, 54, 62– 79 DOI: 10.1016/j.jmgm.2014.09.003Google Scholar294https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Gms7nL&md5=c263bbbd97932a5d047dc6bbd2ec07c9Challenges in computational studies of enzyme structure, function and dynamicsCarvalho, Alexandra T. P.; Barrozo, Alexandre; Doron, Dvir; Kilshtain, Alexandra Vardi; Major, Dan Thomas; Kamerlin, Shina Caroline LynnJournal of Molecular Graphics & Modelling (2014), 54 (), 62-79CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)A review. In this review we give an overview of the field of Computational enzymol. We start by describing the birth of the field, with emphasis on the work of the 2013 chem. Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by expts., has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-mol. mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.
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295Duarte, F.; Amrein, B. A.; Blaha-Nelson, D.; Kamerlin, S. C. Recent advances in QM/MM free energy calculations using reference potentials Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 954– 965 DOI: 10.1016/j.bbagen.2014.07.008Google Scholar295https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVOhtrfL&md5=83b7e4fa141b1bcce3858c1d510cee08Recent advances in QM/MM free energy calculations using reference potentialsDuarte, Fernanda; Amrein, Beat A.; Blaha-Nelson, David; Kamerlin, Shina C. L.Biochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 954-965CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Recent years have seen enormous progress in the development of methods for modeling (bio)mol. systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and phys. meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biol. systems has long been shown to be an effective way to overcome some of the limitations assocd. with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chem. reactivity in biomol. systems. However, the high cost involved in performing high-level QM calcns. has limited the applicability of these approaches when calcg. free energies of chem. processes. In this review, we present some of the advances in using ref. potentials and mean field approxns. to accelerate high-level QM/MM calcns. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of phys.-based simplifications has shown to effectively reduce the cost of high-level QM/MM calcns. In particular, lower-level ref. potentials enable one to reduce the cost of expensive free energy calcns., thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of mol. dynamics.
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296Senn, H. M.; Thiel, W. QM/MM methods for biomolecular systems Angew. Chem., Int. Ed. 2009, 48, 1198– 1229 DOI: 10.1002/anie.200802019Google Scholar296https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXitFOqs7g%253D&md5=c51da58b0525651c71f9c393a79023beQM/MM methods for biomolecular systemsSenn, Hans Martin; Thiel, WalterAngewandte Chemie, International Edition (2009), 48 (7), 1198-1229CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. Combined quantum-mechanics/mol.-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomol. systems. Quantum-mech. (QM) methods are required for describing chem. reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based mol. mechanics (MM) methods. Thus to model large biomols. the logical approach is to combine the two techniques and, to use a QM method for the chem. active region (e.g., substrates and co-factors in an enzymic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomol. systems at a reasonable computational effort while providing the necessary accuracy.
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297Quesne, M. G.; Borowski, T.; de Visser, S. P. Quantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and Breakthroughs Chem. - Eur. J. 2016, 22, 2562 DOI: 10.1002/chem.201503802Google Scholar297https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVynsrrJ&md5=fd32a34ec04a5914450abd582856a88cQuantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and BreakthroughsQuesne, Matthew G.; Borowski, Tomasz; de Visser, Sam P.Chemistry - A European Journal (2016), 22 (8), 2562-2581CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. Nature has developed large groups of enzymic catalysts with the aim to transfer substrates into useful products, which enables biosystems to perform all their natural functions. As such, all biochem. processes in our body (we drink, we eat, we breath, we sleep, etc.) are governed by enzymes. One of the problems assocd. with research on biocatalysts is that they react so fast that details of their reaction mechanisms cannot be obtained with exptl. work. In recent years, major advances in computational hardware and software have been made and now large (bio)chem. systems can be studied using accurate computational techniques. One such technique is the quantum mechanics/mol. mechanics (QM/MM) technique, which has gained major momentum in recent years. Unfortunately, it is not a black-box method that is easily applied, but requires careful set-up procedures. In this work we give an overview on the tech. difficulties and caveats of QM/MM and discuss work-protocols developed in our groups for running successful QM/MM calcns.
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298Kamerlin, S. C.; Haranczyk, M.; Warshel, A. Progress in ab initio QM/MM free-energy simulations of electrostatic energies in proteins: accelerated QM/MM studies of pKa, redox reactions and solvation free energies J. Phys. Chem. B 2009, 113, 1253– 1272 DOI: 10.1021/jp8071712Google Scholar298https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVKis7%252FM&md5=8611575d4a747adad1e7e623af24a2b7Progress in Ab Initio QM/MM Free-Energy Simulations of Electrostatic Energies in Proteins: Accelerated QM/MM Studies of pKa, Redox Reactions and Solvation Free EnergiesKamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, AriehJournal of Physical Chemistry B (2009), 113 (5), 1253-1272CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A review. Hybrid quantum mech./mol. mech. (QM/MM) approaches have been used to provide a general scheme for chem. reactions in proteins. However, such approaches still present a major challenge to computational chemists, not only because of the need for very large computer time in order to evaluate the QM energy but also because of the need for proper computational sampling. This review focuses on the sampling issue in QM/MM evaluations of electrostatic energies in proteins. We chose this example since electrostatic energies play a major role in controlling the function of proteins and are key to the structure-function correlation of biol. mols. Thus, the correct treatment of electrostatics is essential for the accurate simulation of biol. systems. Although we will be presenting different types of QM/MM calcns. of electrostatic energies (and related properties) here, our focus will be on pKa calcns. This reflects the fact that pKa's of ionizable groups in proteins provide one of the most direct benchmarks for the accuracy of electrostatic models of macromols. While pKa calcns. by semimacroscopic models have given reasonable results in many cases, existing attempts to perform pKa calcns. using QM/MM-FEP have led to discrepancies between calcd. and exptl. values. In this work, we accelerate our QM/MM calcns. using an updated mean charge distribution and a classical ref. potential. We examine both a surface residue (Asp3) of the bovine pancreatic trypsin inhibitor and a residue buried in a hydrophobic pocket (Lys102) of the T4-lysozyme mutant. We demonstrate that, by using this approach, we are able to reproduce the relevant side chain pKa's with an accuracy of 3 kcal/mol. This is well within the 7 kcal/mol energy difference obsd. in studies of enzymic catalysis, and is thus sufficient accuracy to det. the main contributions to the catalytic energies of enzymes. We also provide an overall perspective of the potential of QM/MM calcns. in general evaluations of electrostatic free energies, pointing out that our approach should provide a very powerful and accurate tool to predict the electrostatics of not only soln. but also enzymic reactions, as well as the solvation free energies of even larger systems, such as nucleic acid bases incorporated into DNA.
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299Heath, A. P.; Kavraki, L. E.; Clementi, C. From coarse-grain to all-atom: toward multiscale analysis of protein landscapes Proteins: Struct., Funct., Genet. 2007, 68, 646– 661 DOI: 10.1002/prot.21371Google Scholar299https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXnvFymsbw%253D&md5=49cb2dbc1910ef4812dfdb5b0f08bf26From coarse-grain to all-atom: toward multiscale analysis of protein landscapesHeath, Allison P.; Kavraki, Lydia E.; Clementi, CeciliaProteins: Structure, Function, and Bioinformatics (2007), 68 (3), 646-661CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biol. relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolns. The authors present a method that efficiently generates realistic all-atom protein structures starting from the Cα atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calcd. using the coarse-grain structures vs. the all-atom structures shows good correspondence and little distortion in the protein folding landscape.
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300Machado, M. R.; Dans, P. D.; Pantano, S. A hybrid all-atom/coarse grain model for multiscale simulations of DNA Phys. Chem. Chem. Phys. 2011, 13, 18134– 18144 DOI: 10.1039/c1cp21248fGoogle Scholar300https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht1Gqsr%252FI&md5=e5ea22c365dad53edce51d7e06cd66ccA hybrid all-atom/coarse grain model for multiscale simulations of DNAMachado, Matias Rodrigo; Dans, Pablo Daniel; Pantano, SergioPhysical Chemistry Chemical Physics (2011), 13 (40), 18134-18144CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Hybrid simulations of mol. systems, which combine all-atom (AA) with simplified (or coarse grain, CG) representations, propose an advantageous alternative to gain atomistic details on relevant regions while getting profit from the speedup of treating a bigger part of the system at the CG level. Here we present a reduced set of parameters derived to treat a hybrid interface in DNA simulations. Our method allows us to forthrightly link a state-of-the-art force field for AA simulations of DNA with a CG representation developed by our group. We show that no modification is needed for any of the existing residues (neither AA nor CG). Only the bonding parameters at the hybrid interface are enough to produce a smooth transition of electrostatic, mechanic and dynamic features in different AA/CG systems, which are studied by mol. dynamics simulations using an implicit solvent. The simplicity of the approach potentially permits us to study the effect of mutations/modifications as well as DNA binding mols. at the atomistic level within a significantly larger DNA scaffold considered at the CG level. Since all the interactions are computed within the same classical Hamiltonian, the extension to a quantum/classical/coarse-grain multilayer approach using QM/MM modules implemented in widely used simulation packages is straightforward.
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301Michel, J.; Orsi, M.; Essex, J. W. Prediction of partition coefficients by multiscale hybrid atomic-level/coarse-grain simulations J. Phys. Chem. B 2008, 112, 657– 660 DOI: 10.1021/jp076142yGoogle Scholar301https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlslyl&md5=b9b8ac43dad39e76f8a473e7121f9096Prediction of Partition Coefficients by Multiscale Hybrid Atomic-Level/Coarse-Grain SimulationsMichel, Julien; Orsi, Mario; Essex, Jonathan W.Journal of Physical Chemistry B (2008), 112 (3), 657-660CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)Coarse-grain models are becoming an increasingly important tool in computer simulations of a wide variety of mol. processes. In many instances it is, however, desirable to describe key portions of a mol. system at the at. level. There is therefore a strong interest in the development of simulation methodologies that allow representations of matter with mixed granularities in a multiscale fashion. We report here a strategy to conduct mixed at.-level and coarse-grain simulations of mol. systems with a recently developed coarse-grain model. The methodol. is validated by computing partition coeffs. of small mols. described in at. detail and solvated by water or octane, both of which are represented by coarse-grain models. Because the present coarse-grain force field retains electrostatic interactions, the simplified solvent particles can interact realistically with the all-atom solutes. The partition coeffs. computed by this approach rival the accuracy of fully atomistic simulations and are obtained at a fraction of their computational cost. The present methodol. is simple, robust and applicable to a wide variety of mol. systems.
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302Vieth, M.; Kolinski, A.; Brooks, C. L., 3rd; Skolnick, J. Prediction of the folding pathways and structure of the GCN4 leucine zipper J. Mol. Biol. 1994, 237, 361– 367 DOI: 10.1006/jmbi.1994.1239Google Scholar302https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXivFemsLg%253D&md5=3ebe03a90938c20b2829685dde451dd5Prediction of the folding pathways and structure of the GCN4 leucine zipperVieth, Michal; Kolinski, Andrzej; Brooks, Charles L., III; Skolnick, JeffreyJournal of Molecular Biology (1994), 237 (4), 361-7CODEN: JMOBAK; ISSN:0022-2836.A hierarchical approach is described for the prediction of the three-dimensional structure and folding pathway of the GCN4 leucine zipper. Dimer assembly is simulated by Monte Carlo dynamics. The resulting lowest energy structures undergo cooperative rearrangement of their hydrophobic core leading to side-chain fixation. The coarse-grained structures are further refined using a mol. dynamics annealing protocol. This produces full atom models with a backbone root-mean-square deviation from the crystal structure of 0.81 Å. Thus, the authors demonstrate the predictive ability of the authors' approach to yield high resoln. structures of small coiled coils from their sequence.
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303Mohanty, D.; Dominy, B. N.; Kolinski, A.; Brooks, C. L., 3rd; Skolnick, J. Correlation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipper Proteins: Struct., Funct., Genet. 1999, 35, 447– 452 DOI: 10.1002/(SICI)1097-0134(19990601)35:4<447::AID-PROT8>3.0.CO;2-OGoogle Scholar303https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXjs1yqtL4%253D&md5=8044de8535422b330f19dcc823dec1eaCorrelation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipperMohanty, Debasisa; Dominy, Brian N.; Kolinski, Andrzej; Brooks, Charles L., III; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1999), 35 (4), 447-452CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)The relationship between the unfolding pseudo free energies of reduced and detailed at. models of the GCN4 leucine zipper is examd. Starting from the native crystal structure, a large no. of conformations ranging from folded to unfolded were generated by all-atom mol. dynamics unfolding simulations in an aq. environment at elevated temps. For the detailed at. model, the pseudo free energies are obtained by combining the CHARMM all-atom potential with a solvation component from the generalized Born, surface accessibility, GB/SA, model. Reduced model energies were evaluated using a knowledge-based potential. Both energies are highly correlated. In addn., both show a good correlation with the root mean square deviation, RMSD, of the backbone from native. These results suggest that knowledge-based potentials are capable of describing at least some of the properties of the folded as well as the unfolded states of proteins, even though they are derived from a database of native protein structures. Since only conformations generated from an unfolding simulation are used, we cannot assess whether these potentials can discriminate the native conformation from the manifold of alternative, low-energy misfolded states. Nevertheless, these results also have significant implications for the development of a methodol. for multiscale modeling of proteins that combines reduced and detailed at. models.
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304Fan, Z. Z.; Hwang, J. K.; Warshel, A. Using simplified protein representation as a reference potential for all-atom calculations of folding free energy Theor. Chem. Acc. 1999, 103, 77– 80 DOI: 10.1007/s002140050516Google Scholar304https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXjsV2htbk%253D&md5=9b2b5b18f1766f40ef67d2c5853c6917Using simplified protein representation as a reference potential for all-atom calculations of folding free energyFan, Z. Z.; Hwang, J.-K.; Warshel, A.Theoretical Chemistry Accounts (1999), 103 (1), 77-80CODEN: TCACFW; ISSN:1432-881X. (Springer-Verlag)An effective approach for evaluating folding free-energy surfaces of explicit all-atom models is developed and examd. This approach is based on using the potential of a simplified protein model as a ref. potential for calcg. the free energy of the corresponding explicit model. Preliminary results are presented for the folding free energy of a 12-residue helix. The potential of the method for studies of protein-folding processes is discussed, emphasizing the ability to det. the difference between the results of simplified and explicit models. This can help in establishing the validity of simplified folding models.
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305Zhang, J.; Li, W.; Wang, J.; Qin, M.; Wu, L.; Yan, Z.; Xu, W.; Zuo, G.; Wang, W. Protein folding simulations: from coarse-grained model to all-atom model IUBMB Life 2009, 61, 627– 643 DOI: 10.1002/iub.223Google Scholar305https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXmvFCmsL4%253D&md5=27c64c10758a3647b31a78d140d581e3Protein folding simulations: from coarse-grained model to all-atom modelZhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, WeiIUBMB Life (2009), 61 (6), 627-643CODEN: IULIF8; ISSN:1521-6543. (John Wiley & Sons Inc.)A review. Protein folding is an important and challenging problem in mol. biol. During the last 2 decades, mol. dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodn., and structure-stability-function relations. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal no. of amino acid or the evolution principle of protein families. Nowadays, MD simulation is still undergoing rapid developments. The 1st trend is to toward developing new coarse-grained models and studying larger and more complex mol. systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides. The 2nd trend is toward building high resoln. models and explore more detailed and accurate pictures of protein folding and the assocd. processes, such as coordination bond- or disulfide bond-involved folding, polarization, charge transfer and protonation/deprotonation processes involved in metal ion-coupled folding, and ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, the authors review several new subjects investigated by using MD simulations as well as corresponding developments of appropriate protein models. These include, but are not limited to, the attempt to go beyond the topol. based Go-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodn. and kinetics of disulfide bond-involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL, the development of discrete MD and its application in studying the α-β conformational conversion and oligomer assembly process, and the modeling of metal ion-involved protein folding.
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306Reith, D.; Putz, M.; Muller-Plathe, F. Deriving effective mesoscale potentials from atomistic simulations J. Comput. Chem. 2003, 24, 1624– 1636 DOI: 10.1002/jcc.10307Google Scholar306https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXntFentL4%253D&md5=304cc4acd956aaa71f476992e656fd13Deriving effective mesoscale potentials from atomistic simulationsReith, Dirk; Puetz, Mathias; Mueller-Plathe, FlorianJournal of Computational Chemistry (2003), 24 (13), 1624-1636CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liq. systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few interactions. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 redn. of the degrees of freedom. This procedure was performed for PI solns. as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concn. regimes.
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307Chu, J. W.; Voth, G. A. Coarse-grained modeling of the actin filament derived from atomistic-scale simulations Biophys. J. 2006, 90, 1572– 1582 DOI: 10.1529/biophysj.105.073924Google Scholar307https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XitVahtLg%253D&md5=d2b9d2bf8ace4e86de996c4c9b27f47aCoarse-grained modeling of the actin filament derived from atomistic-scale simulationsChu, Jhih-Wei; Voth, Gregory A.Biophysical Journal (2006), 90 (5), 1572-1582CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)A coarse-grained (CG) procedure that incorporates the information obtained from all-atom mol. dynamics (MD) simulations is presented and applied to actin filaments (F-actin). This procedure matches the averaged values and fluctuations of the effective internal coordinates that are used to define a CG model to the values extd. from atomistic MD simulations. The fluctuations of effective internal coordinates in a CG model are computed via normal-mode anal. (NMA), and the computed fluctuations are matched with the atomistic MD results in a self-consistent manner. Each actin monomer (G-actin) is coarse-grained into four sites, and each site corresponds to one of the subdomains of G-actin. The potential energy of a CG G-actin contains three bonds, two angles, and one dihedral angle; effective harmonic bonds are used to describe the intermonomer interactions in a CG F-actin. The persistence length of a CG F-actin was found to be sensitive to the cut-off distance of assigning intermonomer bonds. Effective harmonic bonds for a monomer with its third nearest neighboring monomers are found to be necessary to reproduce the values of persistence length obtained from all-atom MD simulations. Compared to the elastic network model, incorporating the information of internal coordinate fluctuations enhances the accuracy and robustness for a CG model to describe the shapes of low-frequency vibrational modes. Combining the fluctuation-matching CG procedure and NMA, the achievable time- and length scales of modeling actin filaments can be greatly enhanced. In particular, a method is described to compute the force-extension curve using the CG model developed in this work and NMA. It was found that F-actin is easily buckled under compressive deformation, and a writhing mode is developed as a result. In addn. to the bending and twisting modes, this novel writhing mode of F-actin could also play important roles in the interactions of F-actin with actin-binding proteins and in the force-generation process via polymn.
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308Shi, Q.; Izvekov, S.; Voth, G. A. Mixed atomistic and coarse-grained molecular dynamics: simulation of a membrane-bound ion channel J. Phys. Chem. B 2006, 110, 15045– 15048 DOI: 10.1021/jp062700hGoogle Scholar308https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XmvF2nur0%253D&md5=cfabe4f2253aab0a762d961788e34d70Mixed Atomistic and Coarse-Grained Molecular Dynamics: Simulation of a Membrane-Bound Ion ChannelShi, Qiang; Izvekov, Sergei; Voth, Gregory A.Journal of Physical Chemistry B (2006), 110 (31), 15045-15048CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The recently developed multiscale coarse-graining (MS-CG) method (Izvekov, S.; Voth, G. A. J. Phys. Chem. B 2005, 109, 2469; J. Chem. Phys. 2005, 123, 134105) is used to build a mixed all-atom and coarse-grained (AA-CG) model of the gramicidin A (gA) ion channel embedded in a dimyristoylphosphatidylcholine (DMPC) lipid bilayer and water environment. In this model, the gA peptide was described in full atomistic detail, while the lipid and water mols. were described using coarse-grained representations. The atom-CG and CG-CG interactions in the mixed AA-CG model were detd. using the MS-CG method. Mol. dynamics (MD) simulations were performed using the resulting AA-CG model. The results from simulations of the AA-CG model compare very favorably to those from all-atom MD simulations of the entire system. Since the MS-CG method employs a general and systematic approach to obtaining effective interactions from the underlying all-atom models, the present approach to rigorously developing mixed AA-CG models has the potential to be extended to many other systems.
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309Lyman, E.; Zuckerman, D. M. Resolution Exchange Simulation with Incremental Coarsening J. Chem. Theory Comput. 2006, 2, 656– 666 DOI: 10.1021/ct050337xGoogle Scholar309https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjslSlsb8%253D&md5=5edc56d3b1473383530e93a678e3e17bResolution Exchange Simulation with Incremental CoarseningLyman, Edward; Zuckerman, Daniel M.Journal of Chemical Theory and Computation (2006), 2 (3), 656-666CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors previously developed an algorithm, called "resoln. exchange", which improves canonical sampling of at. resoln. models by swapping conformations between high- and low-resoln. simulations. Here, the authors demonstrate a generally applicable incremental coarsening procedure and apply the algorithm to a larger peptide, met-enkephalin. In addn., the authors demonstrate a combination of resoln. and temp. exchange, in which the coarser simulations are also at elevated temps. Both simulations are implemented in a "top-down" mode, to allow efficient allocation of CPU time among the different replicas.
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310Villa, E.; Balaeff, A.; Schulten, K. Structural dynamics of the lac repressor-DNA complex revealed by a multiscale simulation Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 6783– 6788 DOI: 10.1073/pnas.0409387102Google ScholarThere is no corresponding record for this reference.
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311Fujisaki, H.; Shiga, M.; Moritsugu, K.; Kidera, A. Multiscale enhanced path sampling based on the Onsager-Machlup action: Application to a model polymer. J. Chem. Phys. 2013, 139, 054117 DOI: 10.1063/1.4817209Google Scholar311https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1altL3E&md5=bfc296e159da1808e2422810c5ccd9c8Multiscale enhanced path sampling based on the Onsager-Machlup action: Application to a model polymerFujisaki, Hiroshi; Shiga, Motoyuki; Moritsugu, Kei; Kidera, AkinoriJournal of Chemical Physics (2013), 139 (5), 054117/1-054117/9CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)We propose a novel path sampling method based on the Onsager-Machlup (OM) action by generalizing the multiscale enhanced sampling technique suggested by. The basic idea of this method is that the system we want to study (for example, some mol. system described by mol. mechanics) is coupled to a coarse-grained (CG) system, which can move more quickly and can be computed more efficiently than the original system. We simulate this combined system (original + CG system) using Langevin dynamics where different heat baths are coupled to the two systems. When the coupling is strong enough, the original system is guided by the CG system, and is able to sample the configuration and path space with more efficiency. We need to correct the bias caused by the coupling, however, by employing the Hamiltonian replica exchange, where we prep. many path replicas with different coupling strengths. As a result, an unbiased path ensemble for the original system can be found in the weakest coupling path ensemble. This strategy is easily implemented because a wt. for a path calcd. by the OM action is formally the same as the Boltzmann wt. if we properly define the path "Hamiltonian." We apply this method to a model polymer with Asakura-Oosawa interaction, and compare the results with the conventional transition path sampling method. (c) 2013 American Institute of Physics.
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312Orsi, M.; Sanderson, W. E.; Essex, J. W. Permeability of Small Molecules through a Lipid Bilayer: A Multiscale Simulation Study J. Phys. Chem. B 2009, 113, 12019– 12029 DOI: 10.1021/jp903248sGoogle Scholar312https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXps1KmsL8%253D&md5=a5cd73050707209be5d4b4535ccf9808Permeability of Small Molecules through a Lipid Bilayer: A Multiscale Simulation StudyOrsi, Mario; Sanderson, Wendy E.; Essex, Jonathan W.Journal of Physical Chemistry B (2009), 113 (35), 12019-12029CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The transmembrane permeation of eight small (mol. wt. <100) org. mols. across a phospholipid bilayer is investigated by multiscale mol. dynamics simulation. The bilayer and hydrating water are represented by simplified, efficient coarse-grain models, whereas the permeating mols. are described by a std. at.-level force-field. Permeability properties are obtained through a refined version of the z-constraint algorithm. By constraining each permeant at selected depths inside the bilayer, we have sampled free energy differences and diffusion coeffs. across the membrane. These data have been combined, according to the inhomogeneous soly.-diffusion model, to yield the permeability coeffs. The results are generally consistent with previous at.-level calcns. and available exptl. data. Computationally, our multiscale approach proves 2 orders of magnitude faster than traditional at.-level methods.
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313Neri, M.; Anselmi, C.; Carnevale, V.; Vargiu, A. V.; Carloni, P. Molecular dynamics simulations of outer-membrane protease T from E-coli based on a hybrid coarse-grained/atomistic potential J. Phys.: Condens. Matter 2006, 18, S347– S355 DOI: 10.1088/0953-8984/18/14/S16Google ScholarThere is no corresponding record for this reference.
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314Praprotnik, M.; Delle Site, L.; Kremer, K. Multiscale simulation of soft matter: From scale bridging to adaptive resolution Annu. Rev. Phys. Chem. 2008, 59, 545– 571 DOI: 10.1146/annurev.physchem.59.032607.093707Google Scholar314https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlvFWrtrs%253D&md5=a10479920f46503a44e1b716038bb485Multiscale simulation of soft matter: from scale bridging to adaptive resolutionPraprotnik, Matej; Delle Site, Luigi; Kremer, KurtAnnual Review of Physical Chemistry (2008), 59 (), 545-571CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)The relation between atomistic chem. structure, mol. architecture, mol. wt., and material properties is of basic concern in modern soft material science and includes std. properties of bulk materials and surface and interface aspects, as well as the relation between structure and function in nanoscopic objects and mol. assemblies of both synthetic and biol. origin. This all implies a thorough understanding on many length and correspondingly time scales, ranging from (sub)atomistic to macroscopic. Presently, computer simulations play an increasingly important, if not central, role. Some problems do not require specific atomistic details, whereas others require them only locally. However, in many cases this strict sepn. is not sufficient for a comprehensive understanding of systems, and flexible simulation schemes are required that link the different levels of resoln. We here give a general view of the problem regarding soft matter and discuss some specific examples of linked simulation techniques at different resoln. levels. We then discuss a recently developed flexible simulation scheme, the AdResS method, which allows one to adaptively change the resoln. in certain regions of space on demand.
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315Potestio, R.; Fritsch, S.; Espanol, P.; Delgado-Buscalioni, R.; Kremer, K.; Everaers, R.; Donadio, D. Hamiltonian Adaptive Resolution Simulation for Molecular Liquids Phys. Rev. Lett. 2013, 110, 110 DOI: 10.1103/PhysRevLett.110.108301Google ScholarThere is no corresponding record for this reference.
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316Heyden, A.; Lin, H.; Truhlar, D. G. Adaptive partitioning in combined quantum mechanical and molecular mechanical calculations of potential energy functions for multiscale simulations J. Phys. Chem. B 2007, 111, 2231– 2241 DOI: 10.1021/jp0673617Google Scholar316https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhsFGjur4%253D&md5=7334a09f2aac2cbc3d90f1ff0d67f977Adaptive Partitioning in Combined Quantum Mechanical and Molecular Mechanical Calculations of Potential Energy Functions for Multiscale SimulationsHeyden, Andreas; Lin, Hai; Truhlar, Donald G.Journal of Physical Chemistry B (2007), 111 (9), 2231-2241CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)In many applications of multilevel/multiscale methods, an active zone must be modeled by a high-level electronic structure method, while a larger environmental zone can be safely modeled by a lower-level electronic structure method, mol. mechanics, or an analytic potential energy function. In some cases though, the active zone must be redefined as a function of simulation time. Examples include a reactive moiety diffusing through a liq. or solid, a dislocation propagating through a material, or solvent mols. in a second coordination sphere (which is environmental) exchanging with solvent mols. in an active first coordination shell. We present a procedure for combining the levels smoothly and efficiently in such systems in which atoms or groups of atoms move between high-level and low-level zones. The method dynamically partitions the system into the high-level and low-level zones and, unlike previous algorithms, removes all discontinuities in the potential energy and force whenever atoms or groups of atoms cross boundaries and change zones. The new adaptive partitioning (AP) method is compared to Rode's "hot spot" method and Morokuma's "ONIOM-XS" method that were designed for multilevel mol. dynamics (MD) simulations. MD simulations in the microcanonical ensemble show that the AP method conserves both total energy and momentum, while the ONIOM-XS method fails to conserve total energy and the hot spot method fails to conserve both total energy and momentum. Two versions of the AP method are presented, one scaling as O(2N) and one with linear scaling in N, where N is the no. of groups in a buffer zone sepg. the active high-level zone from the environmental low-level zone. The AP method is also extended to systems with multiple high-level zones to allow, for example, the study of ions and counterions in soln. using the multilevel approach.
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317Kerdcharoen, T.; Liedl, K. R.; Rode, B. M. A QM/MM simulation method applied to the solution of Li+ in liquid ammonia Chem. Phys. 1996, 211, 313– 323 DOI: 10.1016/0301-0104(96)00152-8Google Scholar317https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmvFCqsL0%253D&md5=899733c88da0c4ab90010be751cc217bA QM/MM simulation method applied to the solution of Li+ in liquid ammoniaKerdcharoen, Teerakiat; Liedl, Klaus R.; Rode, Bernd M.Chemical Physics (1996), 211 (1,2,3), 313-323CODEN: CMPHC2; ISSN:0301-0104. (Elsevier)A mol. dynamics simulation method based on combined quantum mech. and classical potentials is proposed. This method computes the interactions between particles in a focus region, we call it "Hot Spot", at quantum chem. level within a affordable computational effort. Application to soln. chem. was examd. by simulating Li+ solvation in liq. ammonia. The new method yields a coordination no. of 4 in contrast to 6 obtained from pair-potential simulation. Dynamical properties were found in agreement with the structural change of the solvation shell. The semi-empirical MNDO method was also tested within this approach, but proved inappropriate for electrolyte solns.
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318Hofer, T. S.; Pribil, A. B.; Randolf, B. R.; Rode, B. M. Structure and dynamics of solvated Sn(II) in aqueous solution: An ab initio QM/MM MD approach J. Am. Chem. Soc. 2005, 127, 14231– 14238 DOI: 10.1021/ja052700fGoogle Scholar318https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhtVWrtrvL&md5=0d703d87a11e0790b9197cfb0eb31ab3Structure and Dynamics of Solvated Sn(II) in Aqueous Solution: An ab Initio QM/MM MD ApproachHofer, Thomas S.; Pribil, Andreas B.; Randolf, Bernhard R.; Rode, Bernd M.Journal of the American Chemical Society (2005), 127 (41), 14231-14238CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Structural and dynamical properties of the hydrated Sn(II) ion have been investigated by ab initio quantum mech./mol. mech. (QM/MM) mol. dynamics (MD) simulations at double-ζ HF quantum mech. level. The results indicate Sn(II)aq to be a rather peculiar, if not unique, case of a hydrated ion: four of its eight first-shell ligands do not take place in the otherwise frequent ligand-exchange processes, forming an approx. tetrahedral cage around the ion. The remaining ligands, however, exchange at a rate that is rather comparable to monovalent than divalent ions. This very surprising behavior of ligand exchange not yet obsd. in any previous simulation of over 30 hydrated metal ions is consistently confirmed by vibrational spectra, bond lengths, and a detailed anal. of the trajectories of the simulation.
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319Kerdcharoen, T.; Morokuma, K. ONIOM-XS: an extension of the ONIOM method for molecular simulation in condensed phase Chem. Phys. Lett. 2002, 355, 257– 262 DOI: 10.1016/S0009-2614(02)00210-5Google Scholar319https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XjslWju78%253D&md5=2f5082a7695f451a6c78f77e553bf585ONIOM-XS: an extension of the ONIOM method for molecular simulation in condensed phaseKerdcharoen, Teerakiat; Morokuma, KeijiChemical Physics Letters (2002), 355 (3,4), 257-262CODEN: CHPLBC; ISSN:0009-2614. (Elsevier Science B.V.)A new technique based on ONIOM method was implemented for simulation of liqs. and solns., in which exchange of solvents (XS) between subsystems (i.e. between QM and MM parts) is allowed. In this method, a switching layer sandwiched between "high-level" and "low-level" subsystems was introduced to help morphing of exchanging particle from one region to another. Test on ionic soln. by mol. dynamics method shows that particle exchanges across the boundary negligibly disturb the equil. conditions. A rigorous treatment of the energy expression by this method also opens new opportunities for such as Monte Carlo and free energy simulations.
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320Iwata, Y.; Kasuya, A.; Miyamoto, S. An efficient method for reconstructing protein backbones from [alpha]-carbon coordinates J. Mol. Graphics Modell. 2002, 21, 119– 128 DOI: 10.1016/S1093-3263(02)00142-0Google Scholar320https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38Xms1yks7g%253D&md5=157e7eab65fdff1a21a8f9b067b2f62cAn efficient method for reconstructing protein backbones from α-carbon coordinatesIwata, Yoriko; Kasuya, Atsushi; Miyamoto, ShuichiJournal of Molecular Graphics & Modelling (2002), 21 (2), 119-128CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)We present an approach for building protein backbones from α-carbon (Cα) coordinates. The approach is anal. and based on the information of favored regions in the Ramachandran map. The backbone construction consists of three parts: prediction of (φ, ψ) angle pairs from the Cα trace, generation of at. coordinates with these (φ, ψ) angles, and refinement by subsequent energy minimization. Tests on several known protein structures show that the root mean square deviations in reconstructed backbones are 0.25-0.48 A for coordinates and 14-34° for φ and ψ angles. The results indicate that our method is one of the best methods proposed in terms of accuracy. It has also been revealed that the approach is not only robust against errors in Cα coordinates but is also capable of providing equiv. or more reasonable models compared to other known methods. Furthermore, backbone structures were found to be built accurately by using the (φ, ψ) angles from a different structure of the same protein. This suggests that the approach could be effective and useful in homol. modeling studies.
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321Purisima, E. O.; Scheraga, H. A. Conversion from a virtual-bond chain to a complete polypeptide backbone chain Biopolymers 1984, 23, 1207– 1224 DOI: 10.1002/bip.360230706Google ScholarThere is no corresponding record for this reference.
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322Gront, D.; Kmiecik, S.; Kolinski, A. Backbone building from quadrilaterals: a fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinates J. Comput. Chem. 2007, 28, 1593– 1597 DOI: 10.1002/jcc.20624Google Scholar322https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXlslSgsLo%253D&md5=9d8e4ebf68affeefc13b11ddf0c54befBackbone Building from Quadrilaterals: a fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinatesGront, Dominik; Kmiecik, Sebastian; Kolinski, AndrzejJournal of Computational Chemistry (2007), 28 (9), 1593-1597CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)In this contribution, the authors present an algorithm for protein backbone reconstruction that comprises very high computational efficiency with high accuracy. Reconstruction of the main chain at. coordinates from the α carbon trace is a common task in protein modeling, including de novo structure prediction, comparative modeling, and processing exptl. data. The method employed follows the main idea of some earlier approaches to the problem. The details and careful design of the present approach are new and lead to the algorithm that outperforms all commonly used earlier applications. BBQ (Backbone Building from Quadrilaterals) program has been extensively tested both on native structures as well as on near-native decoy models and compared with the different available existing methods. Obtained results provide a comprehensive benchmark of existing tools and evaluate their applicability to a large scale modeling using a reduced representation of protein conformational space. The BBQ package is available for downloading from the authors' website at http://biocomp.chem.uw.edu.pl/services/BBQ/. This webpage also provides a user manual that describes BBQ functions in detail.
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323Rotkiewicz, P.; Skolnick, J. Fast procedure for reconstruction of full-atom protein models from reduced representations J. Comput. Chem. 2008, 29, 1460– 1465 DOI: 10.1002/jcc.20906Google Scholar323https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXmsFOhtrw%253D&md5=b78d84b5ffcb1b3967aab0c4c986e4c0Fast procedure for reconstruction of full-atom protein models from reduced representationsRotkiewicz, Piotr; Skolnick, JeffreyJournal of Computational Chemistry (2008), 29 (9), 1460-1465CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We introduce PULCHRA, a fast and robust method for the reconstruction of full-atom protein models starting from a reduced protein representation. The algorithm is particularly suitable as an intermediate step between coarse-grained model-based structure prediction and applications requiring an all-atom structure, such as mol. dynamics, protein-ligand docking, structure-based function prediction, or assessment of quality of the predicted structure. The accuracy of the method was tested on a set of high-resoln. crystallog. structures as well as on a set of low-resoln. protein decoys generated by a protein structure prediction algorithm TASSER.
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324Feig, M.; Rotkiewicz, P.; Kolinski, A.; Skolnick, J.; Brooks, C. L., 3rd Accurate reconstruction of all-atom protein representations from side-chain-based low-resolution models Proteins: Struct., Funct., Genet. 2000, 41, 86– 97 DOI: 10.1002/1097-0134(20001001)41:1<86::AID-PROT110>3.3.CO;2-PGoogle ScholarThere is no corresponding record for this reference.
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325Milik, M.; Kolinski, A.; Skolnick, J. Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinates J. Comput. Chem. 1997, 18, 80– 85 DOI: 10.1002/(SICI)1096-987X(19970115)18:1<80::AID-JCC8>3.0.CO;2-WGoogle Scholar325https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXhtVSksQ%253D%253D&md5=7769c831f78ee8c789b23095e1b8b185Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinatesMilik, Mariusz; Kolinski, Andrzej; Skolnick, JeffreyJournal of Computational Chemistry (1997), 18 (1), 80-85CODEN: JCCHDD; ISSN:0192-8651. (Wiley)A method for generating a full backbone protein structure from the coordinates of α-carbons, is presented. The method exts. information from known protein structures to generate positions for the reconstructed atoms. Tests on a set proteins structures show the algorithm to be of comparable accuracy to existing procedures. However, the basic advantage of the presented method is its simplicity and speed. In a test run, the present program is shown to be much faster than existing database searching algorithms, and reconstructs about 8000 residues per s. Thus, it may be included as an independent procedure in protein folding algorithms to rapidly generate approx. coordinates of backbone atoms.
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326Adcock, S. Peptide backbone reconstruction using dead-end elimination and a knowledge-based forcefield J. Comput. Chem. 2004, 25, 16– 27 DOI: 10.1002/jcc.10314Google ScholarThere is no corresponding record for this reference.
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327Claessens, M.; van Cutsem, E.; Lasters, I.; Wodak, S. Modelling the polypeptide backbone with ’spare parts’ from known protein structures Protein Eng., Des. Sel. 1989, 2, 335– 345 DOI: 10.1093/protein/2.5.335Google ScholarThere is no corresponding record for this reference.
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328Pierce, N. A.; Winfree, E. Protein design is NP-hard Protein Eng., Des. Sel. 2002, 15, 779– 782 DOI: 10.1093/protein/15.10.779Google Scholar328https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XptlOht7g%253D&md5=32a6f7e6da581d3fa92f8feeccda6bb2Protein design is NP-hardPierce, Niles A.; Winfree, ErikProtein Engineering (2002), 15 (10), 779-782CODEN: PRENE9; ISSN:0269-2139. (Oxford University Press)Biologists working in the area of computational protein design have never doubted the seriousness of the algorithmic challenges that face them in attempting in silico sequence selection. It turns out that in the language of the computer science community, this discrete optimization problem is NP-hard. The purpose of this paper is to explain the context of this observation, to provide a simple illustrative proof and to discuss the implications for future progress on algorithms for computational protein design.
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329Gordon, D. B.; Hom, G. K.; Mayo, S. L.; Pierce, N. A. Exact rotamer optimization for protein design J. Comput. Chem. 2003, 24, 232– 243 DOI: 10.1002/jcc.10121Google ScholarThere is no corresponding record for this reference.
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330Bower, M. J.; Cohen, F. E.; Dunbrack, R. L., Jr. Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool J. Mol. Biol. 1997, 267, 1268– 1282 DOI: 10.1006/jmbi.1997.0926Google Scholar330https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXjtFWhu7w%253D&md5=9bd2bdee27b12c8b6a0e6dfa8c7543b8Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling toolBower, Michael J.; Cohen, Fred E.; Dunbrack, Roland L., Jr.Journal of Molecular Biology (1997), 267 (5), 1268-1282CODEN: JMOBAK; ISSN:0022-2836. (Academic)Modeling by homol. is the most accurate computational method for translating an amino acid sequence into a protein structure. Homol. modeling can be divided into two sub-problems, placing the polypeptide backbone and adding side-chains. We present a method for rapidly predicting the conformations of protein side-chains, starting from main-chain coordinates alone. The method involves using fewer from main-chain coordinates alone. The method involves using fewer than ten rotamers per residue from a backbone-dependent rotamer library and a search to remove steric conflicts. The method is initially tested on 299 high resoln. crystal structures by rebuilding side-chains onto the exptl. detd. backbone structures. A total of 77% of χ1 and 66% of χ1+2 dihedral angles are predicted within 40° of their crystal structure values. We then tested the method on the entire database of known structures in the Protein Data Bank. The predictive accuracy of the algorithm was strongly correlated with the resoln. of the structures. In an effort to simulate a realistic homol. modeling problem, 9424 homol. models were created using three different modeling strategies. For prediction purposes, pairs of structures were identified which shared between 30% and 90% sequence identity. One strategy results in 82% of χ1+2 dihedral angles predicted within 40° of the target crystal structure values, suggesting that movements of the backbone assocd. with this degree of sequence identity are not large enough to disrupt the predictive ability of our method for non-native backbones. These results compared favorably with existing methods over a comprehensive data set.
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331Subramaniam, S.; Senes, A. Backbone dependency further improves side chain prediction efficiency in the Energy-based Conformer Library (bEBL) Proteins: Struct., Funct., Genet. 2014, 82, 3177– 3187 DOI: 10.1002/prot.24685Google ScholarThere is no corresponding record for this reference.
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332Holm, L.; Sander, C. Fast and simple Monte Carlo algorithm for side chain optimization in proteins: application to model building by homology Proteins: Struct., Funct., Genet. 1992, 14, 213– 223 DOI: 10.1002/prot.340140208Google ScholarThere is no corresponding record for this reference.
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333Liang, S.; Grishin, N. V. Side-chain modeling with an optimized scoring function Protein Sci. 2002, 11, 322– 331 DOI: 10.1110/ps.24902Google Scholar333https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XosFyksg%253D%253D&md5=08a7de597b610fddbe4d7cfe533f5be0Side-chain modeling with an optimized scoring functionLiang, Shide; Grishin, Nick V.Protein Science (2002), 11 (2), 322-331CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Modeling side-chain conformations on a fixed protein backbone has a wide application in structure prediction and mol. design. Each effort in this field requires decisions about a rotamer set, scoring function, and search strategy. We have developed a new and simple scoring function, which operates on side-chain rotamers and consists of the following energy terms: contact surface, vol. overlap, backbone dependency, electrostatic interactions, and desolvation energy. The wts. of these energy terms were optimized to achieve the minimal av. root mean square (rms) deviation between the lowest energy rotamer and real side-chain conformation on a training set of high-resoln. protein structures. In the course of optimization, for every residue, its side chain was replaced by varying rotamers, whereas conformations for all other residues were kept as they appeared in the crystal structure. We obtained prediction accuracy of 90.4% for 1, 78.3% for 1+2, and 1.18 Α overall rms deviation. Furthermore, the derived scoring function combined with a Monte Carlo search algorithm was used to place all side chains onto a protein backbone simultaneously. The av. prediction accuracy was 87.9% for 1, 73.2% for 1+2, and 1.34 rms deviation for 30 protein structures. Our approach was compared with available side-chain construction methods and showed improvement over the best among them: 4.4% for 1, 4.7% for 1+2, and 0.21 for rms deviation. We hypothesize that the scoring function instead of the search strategy is the main obstacle in side-chain modeling. Addnl., we show that a more detailed rotamer library is expected to increase 1+2 prediction accuracy but may have little effect on 1 prediction accuracy.
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334Desmet, J.; De Maeyer, M.; Hazes, B.; Lasters, I. The dead-end elimination theorem and its use in protein side-chain positioning Nature 1992, 356, 539– 542 DOI: 10.1038/356539a0Google Scholar334https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK38XisFWls7Y%253D&md5=8da83d753310c7d9881cfbc207a630deThe dead-end elimination theorem and its use in protein side-chain positioningDesmet, Johan; De Maeyer, Marc; Hazes, Bart; Lasters, IgnaceNature (London, United Kingdom) (1992), 356 (6369), 539-42CODEN: NATUAS; ISSN:0028-0836.The authors present a theorem, referred to as the dead-end elimination theorem, which imposes a suitable condition to identify rotamers that cannot be members of the global min. energy conformation. Application of this theorem effectively controls the computational explosion of the rotamer combinatorial problem, thereby allowing the detn. of the global min. energy conformation of a large collection of side chains.
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335Looger, L. L.; Hellinga, H. W. Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics J. Mol. Biol. 2001, 307, 429– 445 DOI: 10.1006/jmbi.2000.4424Google Scholar335https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXhslSns70%253D&md5=3c1cf293c6c128c571e19989e8bd6a4eGeneralized Dead-end Elimination Algorithms Make Large-scale Protein Side-chain Structure Prediction Tractable: Implications for Protein Design and Structural GenomicsLooger, Loren L.; Hellinga, Homme W.Journal of Molecular Biology (2001), 307 (1), 429-445CODEN: JMOBAK; ISSN:0022-2836. (Academic Press)The dead-end elimination (DEE) theorems are powerful tools for the combinatorial optimization of protein side-chain placement in protein design and homol. modeling. In order to reach their full potential, the theorems must be extended to handle very hard problems. We present a suite of new algorithms within the DEE paradigm that significantly extend its range of convergence and reduce run time. As a demonstration, we show that a total protein design problem of 10115 combinations, a hydrophobic core design problem of 10244 combinations, and a side-chain placement problem of 101044 combinations are solved in less than two weeks, a day and a half, and an hour of CPU time, resp. This extends the range of the method by approx. 53, 144 and 851 log-units, resp., using modest computational resources. Small to av.-sized protein domains can now be designed automatically, and side-chain placement calcns. can be solved for nearly all sizes of proteins and protein complexes in the growing field of structural genomics. (c) 2001 Academic Press.
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336de Armas, H. N.; Dewilde, M.; Verbeke, K.; De Maeyer, M.; Declerck, P. J. Study of recombinant antibody fragments and PAI-1 complexes combining protein-protein docking and results from site-directed mutagenesis (vol 15, pg 1105, 2007) Structure 2007, 15, 1339– 1339 DOI: 10.1016/j.str.2007.09.002Google ScholarThere is no corresponding record for this reference.
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337Lee, C.; Subbiah, S. Prediction of protein side-chain conformation by packing optimization J. Mol. Biol. 1991, 217, 373– 388 DOI: 10.1016/0022-2836(91)90550-PGoogle Scholar337https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3MXhtl2gt7o%253D&md5=ecba793ac8fdcc53dddd05b3a077af59Prediction of protein side-chain conformation by packing optimizationLee, Christopher; Subbiah, S.Journal of Molecular Biology (1991), 217 (2), 373-88CODEN: JMOBAK; ISSN:0022-2836.A rapid and completely automatic method was developed for prediction of protein side-chain conformation, applying the simulated annealing algorithm to optimization of side-chain packing (van der Waals) interactions. The method directly attacks the combinatorial problem of simultaneously predicting many residues' conformation, solving in 8 to 12 h problems for which the systematic search would require over 10300 central processing unit years. Over a test set of nine proteins ranging in size from 46 to 323 residues, the program's predictions for side-chain atoms had a root-mean-square (r.m.s.) deviation of 1.77Å overall vs. the native structures. More importantly, the predictions for core residues were esp. accurate, with an r.m.s. value of 1.25Å overall: 80 to 90% of the large hydrophobic side-chains dominating the internal core were correctly predicted, vs. 30 to 40% for most current methods. The predictions' main errors were in surface residues poorly constrained by packing and small residues with greater steric freedom and hydrogen bonding interactions, which were not included in the program's potential function. The van der Waals interactions appear to be the supreme determinant of the arrangement of side-chains in the core, enforcing a unique allowed packing that in every case so far examd. matches the native structure.
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338Ravindranath, P. A.; Forli, S.; Goodsell, D. S.; Olson, A. J.; Sanner, M. F. AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility PLoS Comput. Biol. 2015, 11, e1004586 DOI: 10.1371/journal.pcbi.1004586Google Scholar338https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XmtlajtLc%253D&md5=65b983947e0a16f01a5f9710120376c4AutoDockFR: advances in protein-ligand docking with explicitly specified binding site flexibilityRavindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S.; Olson, Arthur J.; Sanner, Michel F.PLoS Computational Biology (2015), 11 (12), e1004586/1-e1004586/28CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Automated docking of drug-like mols. into receptors is an essential tool in structurebased drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: (1) exponential growth of the search space, demanding more efficient search methods; and (2) increased no. of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR- AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking expts. are based on two datasets: (1) SEQ17 -a receptor diversity set contg. 17 pairs of apo-holo structures; and (2) CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solns. found for 70.6% vs. 35.3% systems on SEQ17, and 76.9%vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in no. of top ranking solns. on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on av. 79.8%of all pairwise at. interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added.
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339Pedersen, J. T.; Moult, J. Genetic algorithms for protein structure prediction Curr. Opin. Struct. Biol. 1996, 6, 227– 231 DOI: 10.1016/S0959-440X(96)80079-0Google Scholar339https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XisVOjsrY%253D&md5=f3bab9ad7238e79ceac0f666bb4c9c9eGenetic algorithms for protein structure predictionPedersen, Jan T.; Moult, JohnCurrent Opinion in Structural Biology (1996), 6 (2), 227-31CODEN: COSBEF; ISSN:0959-440X. (Current Biology)A review with refs. Genetic algorithms are a general class of search methods that mimic natural gene-based optimization mechanisms. Mutation, cross-over and replication operations are performed on strings. When applied to structure to structure prediction, each string describes a particular conformation of a protein mol. There are many ways in which such search methods may be implemented. Recently results show potential for helping with protein structure prediction, but more data are needed before a complete assessment can be made.
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340Kingsford, C. L.; Chazelle, B.; Singh, M. Solving and analyzing side-chain positioning problems using linear and integer programming Bioinformatics 2005, 21, 1028– 1036 DOI: 10.1093/bioinformatics/bti144Google Scholar340https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXis1yjs7c%253D&md5=4f73e52ac5c95f9db71516056390634fSolving and analyzing side-chain positioning problems using linear and integer programmingKingsford, Carleton L.; Chazelle, Bernard; Singh, MonaBioinformatics (2005), 21 (7), 1028-1039CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: Side-chain positioning is a central component of homol. modeling and protein design. In a common formulation of the problem, the backbone is fixed, side-chain conformations come from a rotamer library, and a pairwise energy function is optimized. It is NP-complete to find even a reasonable approx. soln. to this problem. We seek to put this hardness result into practical context. Results: We present an integer linear programming (ILP) formulation of side-chain positioning that allows us to tackle large problem sizes. We relax the integrality constraint to give a polynomial-time linear programming (LP) heuristic. We apply LP to position side chains on native and homologous backbones and to choose side chains for protein design. Surprisingly, when positioning side chains on native and homologous backbones, optimal solns. using a simple, biol. relevant energy function can usually be found using LP. On the other hand, the design problem often cannot be solved using LP directly; however, optimal solns. for large instances can still be found using the computationally more expensive ILP procedure. While different energy functions also affect the difficulty of the problem, the LP/ILP approach is able to find optimal solns. Our anal. is the first large-scale demonstration that LP-based approaches are highly effective in finding optimal (and successive near-optimal) solns. for the side-chain positioning problem.
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341Xu, J.; Jiao, F.; Berger, B. A tree-decomposition approach to protein structure prediction Proc. IEEE Comput. Syst. Bioinform. Conf. 2005, 247– 256 DOI: 10.1109/CSB.2005.9Google Scholar341https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD28%252Fms1Wltg%253D%253D&md5=c0a5e80ff2ed1b79efba6fde09fcf0a9A tree-decomposition approach to protein structure predictionXu Jinbo; Jiao Feng; Berger BonnieProceedings / IEEE Computational Systems Bioinformatics Conference, CSB. IEEE Computational Systems Bioinformatics Conference (2005), (), 247-56 ISSN:1551-7497.This paper proposes a tree decomposition of protein structures, which can be used to efficiently solve two key subproblems of protein structure prediction: protein threading for backbone prediction and protein side-chain prediction. To develop a unified tree-decomposition based approach to these two subproblems, we model them as a geometric neighborhood graph labeling problem. Theoretically, we can have a low-degree polynomial time algorithm to decompose a geometric neighborhood graph G = (V, E) into components with size O( V ((2/3))log V ). The computational complexity of the tree-decomposition based graph labeling algorithms is O( V Delta(tw+1)) where Delta is the average number of possible labels for each vertex and tw( = O( V ((2/3))log V )) the tree width of G. Empirically, tw is very small and the tree-decomposition method can solve these two problems very efficiently. This paper also compares the computational efficiency of the tree-decomposition approach with the linear programming approach to these two problems and identifies the condition under which the tree-decomposition approach is more efficient than the linear programming approach. Experimental result indicates that the tree-decomposition approach is more efficient most of the time.
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342Canutescu, A. A.; Shelenkov, A. A.; Dunbrack, R. L., Jr. A graph-theory algorithm for rapid protein side-chain prediction Protein Sci. 2003, 12, 2001– 2014 DOI: 10.1110/ps.03154503Google Scholar342https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXmvVehs7s%253D&md5=e014e2e53ed1f0a3fc6b5a14e86d2e75A graph-theory algorithm for rapid protein side-chain predictionCanutescu, Adrian A.; Shelenkov, Andrew A.; Dunbrack, Roland L., Jr.Protein Science (2003), 12 (9), 2001-2014CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Fast and accurate side-chain conformation prediction is important for homol. modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the min. energy of these small biconnected components and combining the results to identify the global min. energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34,342 side chains in <7 min of computer time. The total χ1 and χ1 + 2 dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addn. of a more complex energy function and conformational flexibility, leading to increased accuracy.
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343Nagata, K.; Randall, A.; Baldi, P. SIDEpro: a novel machine learning approach for the fast and accurate prediction of side-chain conformations Proteins: Struct., Funct., Genet. 2012, 80, 142– 153 DOI: 10.1002/prot.23170Google ScholarThere is no corresponding record for this reference.
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344Mendes, J.; Baptista, A. M.; Carrondo, M. A.; Soares, C. M. Improved modeling of side-chains in proteins with rotamer-based methods: a flexible rotamer model Proteins: Struct., Funct., Genet. 1999, 37, 530– 543 DOI: 10.1002/(SICI)1097-0134(19991201)37:4<530::AID-PROT4>3.3.CO;2-8Google ScholarThere is no corresponding record for this reference.
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345Koehl, P.; Delarue, M. Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropy J. Mol. Biol. 1994, 239, 249– 275 DOI: 10.1006/jmbi.1994.1366Google Scholar345https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXkslOks7o%253D&md5=c0a0e04d22960dbdd981e149a6b36f06Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropyKoehl, Patrice; Delarue, MarcJournal of Molecular Biology (1994), 239 (2), 249-75CODEN: JMOBAK; ISSN:0022-2836.Understanding the relations between the conformation of the side-chains and the backbone geometry is crucial for structure prediction as well as for homol. modeling. To attempt to unravel these rules, the authors have developed a method which allows them to predict the position of the side-chains from the coordinates of the main-chain atoms. This method is based on a rotamer library and refines iteratively a conformational matrix of the side-chains of a protein, CM, such that its current element at each cycle CM(ij) gives the probability that side chain i of the protein adopts the conformation of its possible rotamer j. Each residue feels the av. of all possible environments, weighted by their resp. probabilities. The method converges in only a few cycles, thereby deserving the name of self consistent mean field method. Using the rotamer with the highest probability in the optimized conformational matrix to define the conformation of the side-chain leads to the result that on av. 72% of χ1, 75% of χ2 and 62% of χ1+2 are correctly predicted for a set of 30 proteins. Tests with six pairs of homologous proteins have shown that the method is quite successful even when the protein backbone deviates from the correct conformation. The second application of the optimized conformational matrix was to provide ests. of the conformational entropy of the side-chains in the folded state of the protein. The relevance of this entropy is discussed.
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346Desmet, J.; Spriet, J.; Lasters, I. Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization Proteins: Struct., Funct., Genet. 2002, 48, 31– 43 DOI: 10.1002/prot.10131Google Scholar346https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XksFGkt7w%253D&md5=5dde851593e9a3aacf429aa82c9bc43cFast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimizationDesmet, Johan; Spriet, Jan; Lasters, IgnaceProteins: Structure, Function, and Genetics (2002), 48 (1), 31-43CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)We have developed an original method for global optimization of protein side-chain conformations, called the Fast and Accurate Side-Chain Topol. and Energy Refinement (FASTER) method. The method operates by systematically overcoming local min. of increasing order. Comparison of the FASTER results with those of the dead-end elimination (DEE) algorithm showed that both methods produce nearly identical results, but the FASTER algorithm is 100-1000 times faster than the DEE method and scales in a stable and favorable way as a function of protein size. We also show that low-order local min. may be almost as accurate as the global min. when evaluated against exptl. detd. structures. In addn., the new algorithm provides significant information about the conformational flexibility of individual side-chains. We obsd. that strictly rigid side-chains are concd. mainly in the core of the protein, whereas highly flexible side-chains are found almost exclusively among solvent-oriented residues.
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347Gront, D.; Kmiecik, S.; Blaszczyk, M.; Ekonomiuk, D.; Kolinski, A. Optimization of protein models Wires Comput. Mol. Sci. 2012, 2, 479– 493 DOI: 10.1002/wcms.1090Google ScholarThere is no corresponding record for this reference.
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348Porebski, P. J.; Cymborowski, M.; Pasenkiewicz-Gierula, M.; Minor, W. Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations Acta Crystallogr. D Struct. Biol. 2016, 72, 266– 280 DOI: 10.1107/S2059798315024730Google Scholar348https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvFymsLc%253D&md5=362cd351b9f9e6ac84c82475c98d4780Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformationsPorebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, WladekActa Crystallographica, Section D: Structural Biology (2016), 72 (2), 266-280CODEN: ACSDAD; ISSN:2059-7983. (International Union of Crystallography)Improvements in crystallog. hardware and software have allowed automated structure-soln. pipelines to approach a near-'one-click' experience for initial detn. of macromol. structures. However, in many cases the resulting initial model requires laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallog. context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from exptl. data and prior information about rotamer frequencies to find optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-d. term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of highly discriminatory nature of electron-d. maps. This method has been implemented in program Fitmunk, which uses extensive conformational sampling. This improves accuracy of modeling and makes it a versatile tool for crystallog. model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving quality of crystallog. protein models, esp. at medium and low resolns.
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349Gront, D.; Kolinski, A. BioShell--a package of tools for structural biology computations Bioinformatics 2006, 22, 621– 622 DOI: 10.1093/bioinformatics/btk037Google ScholarThere is no corresponding record for this reference.
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350Gront, D.; Kolinski, A. Utility library for structural bioinformatics Bioinformatics 2008, 24, 584– 585 DOI: 10.1093/bioinformatics/btm627Google Scholar350https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVKit7s%253D&md5=a8347823bb3c703344e98404c39ee28dUtility library for structural bioinformaticsGront, Dominik; Kolinski, AndrzejBioinformatics (2008), 24 (4), 584-585CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: In this Note we present a new software library for structural bioinformatics. The library contains programs, computing sequence- and profile-based alignments and a variety of structural calcns. with user-friendly handling of various data formats. The software organization is very flexible. Algorithms are written in Java language and may be used by Java programs. Moreover the modules can be accessed from Jython (Python scripting language implemented in Java) scripts. Finally, the new version of BioShell delivers several utility programs that can do typical bioinformatics task from a command-line level.
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351Eswar, N.; Webb, B.; Marti-Renom, M. A.; Madhusudhan, M. S.; Eramian, D.; Shen, M. Y.; Pieper, U.; Sali, A. Comparative protein structure modeling using MODELLER. Curr. Protoc. Protein Sci. 2007, Chapter 2, Unit 2 9. DOI: 10.1002/0471140864.ps0209s50Google ScholarThere is no corresponding record for this reference.
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352Webb, B.; Sali, A. Protein structure modeling with MODELLER Methods Mol. Biol. 2014, 1137, 1– 15 DOI: 10.1007/978-1-4939-0366-5_1Google Scholar352https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXns12isrc%253D&md5=19709a3ffefe33fd6e5d8506258bd6f0Protein Structure Modeling with MODELLERWebb, Benjamin; Sali, AndrejMethods in Molecular Biology (New York, NY, United States) (2014), 1137 (Protein Structure Prediction), 1-15CODEN: MMBIED; ISSN:1940-6029. (Springer)Genome sequencing projects have resulted in a rapid increase in the no. of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at at. resoln. using exptl. structure detn. methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In this chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.
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353Peterson, R. W.; Dutton, P. L.; Wand, A. J. Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer library Protein Sci. 2004, 13, 735– 751 DOI: 10.1110/ps.03250104Google Scholar353https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXhvVCmtbo%253D&md5=5ed655f76c02436e899a17b47a425d24Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer libraryPeterson, Ronald W.; Dutton, P. Leslie; Wand, A. JoshuaProtein Science (2004), 13 (3), 735-751CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Accurate prediction of the placement and conformations of protein side chains given only the backbone trace has a wide range of uses in protein design, structure prediction, and functional anal. Prediction has most often relied on discrete rotamer libraries so that rapid fitness of side-chain rotamers can be assessed against some scoring function. Scoring functions are generally based on exptl. parameters from small-mol. studies or empirical parameters based on detd. protein structures. Here, we describe the NCN algorithm for predicting the placement of side chains. A predominantly first-principles approach was taken to develop the potential energy function incorporating van der Waals and electrostatics based on the OPLS parameters, and a hydrogen bonding term. The only empirical knowledge used is the frequency of rotameric states from the PDB. The rotamer library includes nearly 50,000 rotamers, and is the most extensive discrete library used to date. Although the computational time tends to be longer than most other algorithms, the overall accuracy exceeds all algorithms in the literature when placing rotamers on an accurate backbone trace. Considering only the most buried residues, 80% of the total residues tested, the placement accuracy reaches 92% for χ1, and 83% for χ1 + 2, and an overall RMS deviation of 1 Å. Addnl., we show that if information is available to restrict χ1 to one rotamer well, then this algorithm can generate structures with an av. RMS deviation of 1.0 Å for all heavy side-chains atoms and a corresponding overall χ1 + 2 accuracy of 85.0%.
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354Lu, M.; Dousis, A. D.; Ma, J. OPUS-Rota: a fast and accurate method for side-chain modeling Protein Sci. 2008, 17, 1576– 1585 DOI: 10.1110/ps.035022.108Google Scholar354https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtV2rsb%252FL&md5=2b9192640e8c51e4bec688d5f32a19ceOPUS-Rota: a fast and accurate method for side-chain modelingLu, Mingyang; Dousis, Athanasios D.; Ma, JianpengProtein Science (2008), 17 (9), 1576-1585CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)In this paper, we introduce a fast and accurate side-chain modeling method, named OPUS-Rota. In a benchmark comparison with the methods SCWRL, NCN, LGA, SPRUCE, Rosetta, and SCAP, OPUS-Rota is shown to be much faster than all the methods except SCWRL, which is comparably fast. In terms of overall χ1 and χ1+2 accuracies, however, OPUS-Rota is 5.4 and 8.8 percentage points better, resp., than SCWRL. Compared with NCN, which has the best accuracy in the literature, OPUS-Rota is 1.6 percentage points better for overall χ1+2 but 0.3 percentage points weaker for overall χ1. Hence, our algorithm is much more accurate than SCWRL with similar execution speed, and it has accuracy comparable to or better than the most accurate methods in the literature, but with a runtime that is one or two orders of magnitude shorter. In addn., OPUS-Rota consistently outperforms SCWRL on the Wallner and Elofsson homol.-modeling benchmark set when the sequence identity is greater than 40%. We hope that OPUS-Rota will contribute to high-accuracy structure refinement, and the computer program is freely available for academic users.
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355Wallner, B.; Elofsson, A. All are not equal: a benchmark of different homology modeling programs Protein Sci. 2005, 14, 1315– 1327 DOI: 10.1110/ps.041253405Google Scholar355https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjvFSqt74%253D&md5=25e82375ff92544f4f0e4bf2141e48b9All are not equal: A benchmark of different homology modeling programsWallner, Bjoern; Elofsson, ArneProtein Science (2005), 14 (5), 1315-1327CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Modeling a protein structure based on a homologous structure is a std. method in structural biol. today. In this process an alignment of a target protein sequence onto the structure of a template(s) is used as input to a program that constructs a 3D model. It has been shown that the most important factor in this process is the correctness of the alignment and the choice of the best template structure(s), while it is generally believed that there are no major differences between the best modeling programs. Therefore, a large no. of studies to benchmark the alignment qualities and the selection process have been performed. However, to our knowledge no large-scale benchmark has been performed to evaluate the programs used to transform the alignment to a 3D model. In this study, a benchmark of six different homol. modeling programs-Modeller, SegMod/ENCAD, SWISS-MODEL, 3D-JIGSAW, nest, and Builder-is presented. The performance of these programs is evaluated using physiochem. correctness and structural similarity to the correct structure. From our anal. it can be concluded that no single modeling program outperform the others in all tests. However, it is quite clear that three modeling programs, Modeller, nest, and SegMod/ENCAD, perform better than the others. Interestingly, the fastest and oldest modeling program, SegMod/ENCAD, performs very well, although it was written more than 10 years ago and has not undergone any development since. It can also be obsd. that none of the homol. modeling programs builds side chains as well as a specialized program (SCWRL), and therefore there should be room for improvement.
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356Liang, S.; Zheng, D.; Zhang, C.; Standley, D. M. Fast and accurate prediction of protein side-chain conformations Bioinformatics 2011, 27, 2913– 2914 DOI: 10.1093/bioinformatics/btr482Google Scholar356https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsLvN&md5=1c096f7ffd16004f918039967885dbc2Fast and accurate prediction of protein side-chain conformationsLiang, Shide; Zheng, Dandan; Zhang, Chi; Standley, Daron M.Bioinformatics (2011), 27 (20), 2913-2914CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: We developed a fast and accurate side-chain modeling program [Optimized Side Chain Atomic eneRgy (OSCAR)-star] based on orientation-dependent energy functions and a rigid rotamer model. The av. computing time was 18 s per protein for 218 test proteins with higher prediction accuracy (1.1% increase for χ1 and 0.8% increase for χ1+2) than the best performing program developed by other groups. We show that the energy functions, which were calibrated to tolerate the discrete errors of rigid rotamers, are appropriate for protein loop selection, esp. for decoys without extensive structural refinement. Availability: OSCAR-star and the 218 test proteins are available for download at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
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357Moore, B. L.; Kelley, L. A.; Barber, J.; Murray, J. W.; MacDonald, J. T. High-quality protein backbone reconstruction from alpha carbons using Gaussian mixture models J. Comput. Chem. 2013, 34, 1881– 1889 DOI: 10.1002/jcc.23330Google Scholar357https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXot1Gjtr4%253D&md5=26300aac868cfdad19941fb80b34365cHigh quality protein backbone reconstruction from alpha carbons using Gaussian mixture modelsMoore, Benjamin L.; Kelley, Lawrence A.; Barber, James; Murray, James W.; MacDonald, James T.Journal of Computational Chemistry (2013), 34 (22), 1881-1889CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse-grained protein structure models offer increased efficiency in structural modeling, but these must be coupled with fast and accurate methods to revert to a full-atom structure. Here, we present a novel algorithm to reconstruct mainchain models from C traces. This has been parameterized by fitting Gaussian mixt. models (GMMs) to short backbone fragments centered on idealized peptide bonds. The method we have developed is statistically significantly more accurate than several competing methods, both in terms of RMSD values and dihedral angle differences. The method produced Ramachandran dihedral angle distributions that are closer to that obsd. in real proteins and better Phaser mol. replacement log-likelihood gains. Amino acid residue sidechain reconstruction accuracy using SCWRL4 was found to be statistically significantly correlated to backbone reconstruction accuracy. Finally, the PD2 method was found to produce significantly lower energy full-atom models using Rosetta which has implications for multiscale protein modeling using coarse-grained models. A webserver and C++ source code is freely available for noncommercial use from: http://www.sbg.bio.ic.ac.uk/phyre2/PD2_ca2main/.
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358Xiang, Z. X.; Honig, B. Extending the accuracy limits of prediction for side-chain conformations (vol 311, pg 421, 2001) J. Mol. Biol. 2001, 312, 419– 419 DOI: 10.1006/jmbi.2001.4985Google ScholarThere is no corresponding record for this reference.
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359Wang, J. M.; Wolf, R. M.; Caldwell, J. W.; Kollman, P. A.; Case, D. A. Development and testing of a general amber force field J. Comput. Chem. 2004, 25, 1157– 1174 DOI: 10.1002/jcc.20035Google Scholar359https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXksFakurc%253D&md5=2992017a8cf51f89290ae2562403b115Development and testing of a general Amber force fieldWang, Junmei; Wolf, Romain M.; Caldwell, James W.; Kollman, Peter A.; Case, David A.Journal of Computational Chemistry (2004), 25 (9), 1157-1174CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We describe here a general Amber force field (GAFF) for org. mols. GAFF is designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most org. and pharmaceutical mols. that are composed of H, C, N, O, S, P, and halogens. It uses a simple functional form and a limited no. of atom types, but incorporates both empirical and heuristic models to est. force consts. and partial at. charges. The performance of GAFF in test cases is encouraging. In test I, 74 crystallog. structures were compared to GAFF minimized structures, with a root-mean-square displacement of 0.26 Å, which is comparable to that of the Tripos 5.2 force field (0.25 Å) and better than those of MMFF 94 and CHARMm (0.47 and 0.44 Å, resp.). In test II, gas phase minimizations were performed on 22 nucleic acid base pairs, and the minimized structures and intermol. energies were compared to MP2/6-31G* results. The RMS of displacements and relative energies were 0.25 Å and 1.2 kcal/mol, resp. These data are comparable to results from Parm99/RESP (0.16 Å and 1.18 kcal/mol, resp.), which were parameterized to these base pairs. Test III looked at the relative energies of 71 conformational pairs that were used in development of the Parm99 force field. The RMS error in relative energies (compared to expt.) is about 0.5 kcal/mol. GAFF can be applied to wide range of mols. in an automatic fashion, making it suitable for rational drug design and database searching.
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360Li, Y.; Zhang, Y. REMO: A new protocol to refine full atomic protein models from C-alpha traces by optimizing hydrogen-bonding networks Proteins: Struct., Funct., Genet. 2009, 76, 665– 676 DOI: 10.1002/prot.22380Google ScholarThere is no corresponding record for this reference.
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361Maupetit, J.; Gautier, R.; Tuffery, P. SABBAC: online structural alphabet-based protein backbone reconstruction from alpha-carbon trace Nucleic Acids Res. 2006, 34, W147– W151 DOI: 10.1093/nar/gkl289Google Scholar361https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xps1yhtrk%253D&md5=ed09065314c2656171a6c7020f3c6954SABBAC: online Structural Alphabet-based protein BackBone reconstruction from Alpha-Carbon traceMaupetit, Julien; Gautier, R.; Tuffery, PierreNucleic Acids Research (2006), 34 (Web Server), W147-W151CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)SABBAC is an online service devoted to protein backbone reconstruction from alpha-carbon trace. It is based on the assembly of fragments taken from a library of reduced size, selected from the encoding of the protein trace in a hidden Markov model-derived structural alphabet. The assembly of the fragments is achieved by a greedy algorithm, using an energy-based scoring. Alpha-carbon coordinates remain unaffected. SABBAC simply positions the missing backbone atoms, no further refinement is performed. From the authors' tests, SABBAC performs equal or better than other similar online approach and is robust to deviations on the alpha-carbon coordinates. It can be accessed at http://bioserv.rpbs.jussieu.fr/SABBAC.html.
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362Xu, J. B. Rapid protein side-chain packing via tree decomposition Research in Computational Molecular Biology, Proceedings 2005, 3500, 423– 439 DOI: 10.1007/11415770_32Google ScholarThere is no corresponding record for this reference.
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363Krivov, G. G.; Shapovalov, M. V.; Dunbrack, R. L., Jr. Improved prediction of protein side-chain conformations with SCWRL4 Proteins: Struct., Funct., Genet. 2009, 77, 778– 795 DOI: 10.1002/prot.22488Google Scholar363https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlSru7nN&md5=515b93d349447312958d8d7ebfe784c7Improved prediction of protein side-chain conformations with SCWRL4Krivov, Georgii G.; Shapovalov, Maxim V.; Dunbrack, Roland L., Jr.Proteins: Structure, Function, and Bioinformatics (2009), 77 (4), 778-795CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Detn. of side-chain conformations is an important step in protein structure prediction and protein design. Many such methods have been presented, although only a small no. are in widespread use. SCWRL is one such method, and the SCWRL3 program (2003) has remained popular because of its speed, accuracy, and ease-of-use for the purpose of homol. modeling. However, higher accuracy at comparable speed is desirable. This has been achieved in a new program SCWRL4 through: (1) a new backbone-dependent rotamer library based on kernel d. ests.; (2) averaging over samples of conformations about the positions in the rotamer library; (3) a fast anisotropic hydrogen bonding function; (4) a short-range, soft van der Waals atom-atom interaction potential; (5) fast collision detection using k-discrete oriented polytopes; (6) a tree decompn. algorithm to solve the combinatorial problem; and (7) optimization of all parameters by detg. the interaction graph within the crystal environment using symmetry operators of the crystallog. space group. Accuracies as a function of electron d. of the side chains demonstrate that side chains with higher electron d. are easier to predict than those with low-electron d. and presumed conformational disorder. For a testing set of 379 proteins, 86% of χ1 angles and 75% of χ1+2 angles are predicted correctly within 40° of the X-ray positions. Among side chains with higher electron d. (25-100th percentile), these nos. rise to 89 and 80%. The new program maintains its simple command-line interface, designed for homol. modeling, and is now available as a dynamic-linked library for incorporation into other software programs. Proteins 2009. © 2009 Wiley-Liss, Inc.
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364Pearlman, D. A.; Case, D. A.; Caldwell, J. W.; Ross, W. S.; Cheatham, T. E.; Debolt, S.; Ferguson, D.; Seibel, G.; Kollman, P. Amber, a Package of Computer-Programs for Applying Molecular Mechanics, Normal-Mode Analysis, Molecular-Dynamics and Free-Energy Calculations to Simulate the Structural and Energetic Properties of Molecules Comput. Phys. Commun. 1995, 91, 1– 41 DOI: 10.1016/0010-4655(95)00041-DGoogle Scholar364https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXps1Wrtrw%253D&md5=8dc71939a46bbc17d5da08782d4e6ec8"AMBER", a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to stimulate the structural and energetic properties of moleculesPearlman, David A.; Case, David A.; Caldwell, James W.; Ross, Wilson S.; Cheatham, Thomas E. III; DeBolt, Steve; Ferguson, David; Seibel, George; Kollman, PeterComputer Physics Communications (1995), 91 (1-3), 1-42CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier)We describe the development, current features, and some directions for future development of the AMBER package of computer programs. This package has evolved from a program that was constructed to do Assisted Model Building and Energy Refinement to a group of programs embodying a no. of the powerful tools of modern computational chem.-mol. dynamics and free energy calcns.
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365Skolnick, J.; Kolinski, A.; Ortiz, A. R. MONSSTER: a method for folding globular proteins with a small number of distance restraints J. Mol. Biol. 1997, 265, 217– 241 DOI: 10.1006/jmbi.1996.0720Google Scholar365https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXpvVWjtg%253D%253D&md5=c6debfd1961a7c24893d001cc4339eacMONSSTER: a method for folding globular proteins with a small number of distance restraintsSkolnick, Jeffrey; Kolinski, Andrzej; Ortiz, Angle R.Journal of Molecular Biology (1997), 265 (2), 217-241CODEN: JMOBAK; ISSN:0022-2836. (Academic)The MONSSTER (MOdeling of New Structures from Secondary and TErtiary Restraints) method for folding of proteins using a small no. of long-distance restraints (which can be up to seven times less than the total no. of residues) and some knowledge of the secondary structure of regular fragments is described. The method employs a high-coordination lattice representation of the protein chain that incorporates a variety of potentials designed to produce protein-like behavior. These include statistical preferences for secondary structure, side-chain burial interactions, and a hydrogen-bond potential. Using this algorithm, several globular proteins (1ctf, 2gbl, 2trx, 3fxn, 1mba, 1pcy and 6pti) have been folded to moderate-resoln., native-like compact state. For example, the 68 residue 1ctf mol. having ten loosely defined, long-range restraints was reproducibly obtained with a Cα-backbone root-mean-square deviation (RMSD) from native of about 4Å. Flavodoxin with 35 restraints has been folded to structures whose av. RMSD is 4.28 Å. Furthermore, using just 20 restraints, myoglobin, which is a 146 residue helical protein, has been folded to structures whose av. RMSD from native is 5.65 Å. Plastocyanin with 25 long-range restraints adopts conformations whose av. RMSD is 5.44 Å. Possible applications of the proposed approach to the refinement of structures from NMR data, homol. model-building and the detn. of tertiary structure when the secondary structure and a small no. of restraints are predicted are briefly discussed.
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366Wan, C. K.; Han, W.; Wu, Y. D. Parameterization of PACE Force Field for Membrane Environment and Simulation of Helical Peptides and Helix-Helix Association J. Chem. Theory Comput. 2012, 8, 300– 313 DOI: 10.1021/ct2004275Google Scholar366https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVelt77O&md5=6a13f21ca23aeb96d637e36e6179b4a6Parameterization of PACE Force Field for Membrane Environment and Simulation of Helical Peptides and Helix-Helix AssociationWan, Cheuk-Kin; Han, Wei; Wu, Yun-DongJournal of Chemical Theory and Computation (2012), 8 (1), 300-313CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The recently developed PACE force field was further parametrized so that it can be applied to the studies of membrane systems. Parameters for the interactions between united-atom protein particles and lipid hydrophobic tails were developed by reproducing the solvation free energies of small org. mols. in hexadecane. Interactions between protein particles and lipid heads were parametrized by fitting the potential of mean force of the corresponding all-atom simulation. The force field was applied to the study of five helical peptides in membrane environments. The calcd. tilt angles of WALP and GWALP and their mutations are in good agreement with exptl. data. The assocn. of two glycophorin A (GpA) helixes was simulated for 6 μs. Root-mean-square-deviation of the simulated dimer from the NMR structure was found to be 0.272 nm, better than all results obtained so far. These findings demonstrate the high accuracy and applicability of the PACE force field in studying membrane proteins.
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367Han, W.; Schulten, K. Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains J. Chem. Theory Comput. 2012, 8, 4413– 4424 DOI: 10.1021/ct300696cGoogle Scholar367https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsVylu7vF&md5=7cfa25a7a8d28093a933fba246cba4caFurther Optimization of a Hybrid United-Atom and Coarse-Grained Force Field for Folding Simulations: Improved Backbone Hydration and Interactions between Charged Side ChainsHan, Wei; Schulten, KlausJournal of Chemical Theory and Computation (2012), 8 (11), 4413-4424CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)PACE, a hybrid force field that couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve its efficiency for folding simulations. Backbone hydration parameters have been reoptimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE to provide a more realistic description of interactions between charged groups. Using replica exchange mol. dynamics, ab initio folding using the new PACE has been achieved for seven small proteins (16-23 residues) with different structural motifs. Exptl. data about folded states, such as their stability at room temp., m.p., and NMR nuclear Overhauser effect constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temp. has been made with expts., through std. mol. dynamics simulations, showing that the new PACE may accelerate the actual folding kinetics 5-10-fold, permitting now the study of folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, α3D, in multiple 10-30 μs simulations, to its native states (Cα root-mean-square deviation of ∼0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.
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368Perez, A.; Marchan, I.; Svozil, D.; Sponer, J.; Cheatham, T. E., 3rd; Laughton, C. A.; Orozco, M. Refinement of the AMBER force field for nucleic acids: improving the description of alpha/gamma conformers Biophys. J. 2007, 92, 3817– 3829 DOI: 10.1529/biophysj.106.097782Google Scholar368https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXls1ygu7Y%253D&md5=e0f8d87e5fe7710e59cc41f5e8c25f7bRefinement of the AMBER force field for nucleic acids: improving the description of α/γ conformersPerez, Alberto; Marchan, Ivan; Svozil, Daniel; Sponer, Jiri; Cheatham, Thomas E., III; Laughton, Charles A.; Orozco, ModestoBiophysical Journal (2007), 92 (11), 3817-3829CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We present here the parmbsc0 force field, a refinement of the AMBER parm99 force field, where emphasis has been made on the correct representation of the α/γ concerted rotation in nucleic acids (NAs). The modified force field corrects overpopulations of the α/γ = (g+,t) backbone that were seen in long (more than 10 ns) simulations with previous AMBER parameter sets (parm94-99). The force field has been derived by fitting to high-level quantum mech. data and verified by comparison with very high-level quantum mech. calcns. and by a very extensive comparison between simulations and exptl. data. The set of validation simulations includes two of the longest trajectories published to date for the DNA duplex (200 ns each) and the largest variety of NA structures studied to date (15 different NA families and 97 individual structures). The total simulation time used to validate the force field includes near 1 μs of state-of-the-art mol. dynamics simulations in aq. soln.
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369Dans, P. D.; Zeida, A.; Machado, M. R.; Pantano, S. A Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit Electrostatics J. Chem. Theory Comput. 2010, 6, 1711– 1725 DOI: 10.1021/ct900653pGoogle Scholar369https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXkslKgsrk%253D&md5=1544bb59f4bceedf250ccc86e9b2b15fA Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit ElectrostaticsDans, Pablo D.; Zeida, Ari; Machado, Matias R.; Pantano, SergioJournal of Chemical Theory and Computation (2010), 6 (5), 1711-1725CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grain (CG) techniques allow considerable extension of the accessible size and time scales in simulations of biol. systems. Although many CG representations are available for the most common biomacromols., very few have been reported for nucleic acids. Here, the authors present a CG model for mol. dynamics simulations of DNA on the multi-microsecond time scale. The authors' model maps the complexity of each nucleotide onto six effective superatoms keeping the "chem. sense" of specific Watson-Crick recognition. Mol. interactions are evaluated using a classical Hamiltonian with explicit electrostatics calcd. under the framework of the generalized Born approach. This CG representation is able to accurately reproduce exptl. structures, breathing dynamics, and conformational transitions from the A to the B form in double helical fragments. The model achieves a good qual. reprodn. of temp.-driven melting and its dependence on size, ionic strength, and sequence specificity. Reconstruction of atomistic models from CG trajectories give remarkable agreement with structural, dynamic, and energetic features obtained from fully atomistic simulation, opening the possibility to acquire nearly at. detail data from CG trajectories.
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370Predeus, A. V.; Gul, S.; Gopal, S. M.; Feig, M. Conformational sampling of peptides in the presence of protein crowders from AA/CG-multiscale simulations J. Phys. Chem. B 2012, 116, 8610– 8620 DOI: 10.1021/jp300129uGoogle Scholar370https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktVynsb8%253D&md5=1422e75e835e493a2d9a6c2cdb266a1cConformational Sampling of Peptides in the Presence of Protein Crowders from AA/CG-Multiscale SimulationsPredeus, Alexander V.; Gul, Seref; Gopal, Srinivasa M.; Feig, MichaelJournal of Physical Chemistry B (2012), 116 (29), 8610-8620CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Macromol. crowding is recognized as an important factor influencing folding and conformational dynamics of proteins and nucleic acids. Previous views of crowding have focused on the mostly entropic vol. exclusion effect of crowding, but recent studies are indicating the importance of enthalpic effects, in particular, changes in electrostatic interactions due to crowding. Here, temp. replica exchange mol. dynamics simulations of trp-cage and melittin in the presence of explicit protein crowders are presented to further examine the effect of protein crowders on peptide dynamics. The simulations involve a three-component multiscale modeling scheme where the peptides are represented at an atomistic level, the crowder proteins at a coarse-grained level, and the surrounding aq. solvent as implicit solvent. This scheme optimally balances a phys. realistic description for the peptide with computational efficiency. The multiscale simulations were compared with simulations of the same peptides in different dielec. environments with dielec. consts. ranging from 5 to 80. It is found that the sampling in the presence of the crowders resembles sampling with reduced dielec. consts. between 10 and 40. Furthermore, diverse conformational ensembles are generated in the presence of crowders including partially unfolded states for trp-cage. These findings emphasize the importance of enthalpic interactions over vol. exclusion effects in describing the effects of cellular crowding.
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371Zacharias, M. Protein-protein docking with a reduced protein model accounting for side-chain flexibility Protein Sci. 2003, 12, 1271– 1282 DOI: 10.1110/ps.0239303Google Scholar371https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXktV2lsL4%253D&md5=c96e82d1896942dc8bcc137e3ee87238Protein-protein docking with a reduced protein model accounting for side-chain flexibilityZacharias, MartinProtein Science (2003), 12 (6), 1271-1282CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking min. on the protein surfaces. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chem. character. Energy minimization of protein test complexes in the reduced representation results in geometries close to expt. with backbone root mean square deviations (RMSDs) of ∼1 to 3 Å for the mobile protein partner from the exptl. geometry. For most test cases, the energy-minimized exptl. structure scores among the top five energy min. in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a soln. within ∼2 to 3.5 Å RMSD of the full mobile partner from the exptl. geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.
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372Lin, Z. X.; Gunsteren, W. F. Refinement of the Application of the GROMOS 54A7 Force Field to beta-Peptides J. Comput. Chem. 2013, 34, 2796– 2805 DOI: 10.1002/jcc.23459Google ScholarThere is no corresponding record for this reference.
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373Fiorucci, S.; Zacharias, M. Binding site prediction and improved scoring during flexible protein-protein docking with ATTRACT Proteins: Struct., Funct., Genet. 2010, 78, 3131– 3139 DOI: 10.1002/prot.22808Google Scholar373https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVSqsbrN&md5=26aaea3a7c1144176e7ebcf855b89ce8Binding site prediction and improved scoring during flexible protein-protein docking with ATTRACTFiorucci, Sebastien; Zacharias, MartinProteins: Structure, Function, and Bioinformatics (2010), 78 (15), 3131-3139CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)The ATTRACT protein-protein docking program combined with a coarse-grained protein model has been used to predict protein-protein complex structures in CAPRI rounds 13-19. For six targets acceptable or better quality solns. have been submitted (high quality predictions for targets 32, 40, 41, and 42). The improved performance compared to previous rounds can be attributed in part to the inclusion of conformational flexibility during systematic searches and an optimized scoring function. In addn., a recently developed method for the prediction of putative protein binding sites based on the electrostatic penalty to place neutral low dielec. probes on the protein surface was applied to the most recent targets. The approach resulted in useful predictions of putative binding sites that can help to limit the systematic docking searches. Possible improvements of the docking approach in particular at the scoring and refinement steps are discussed.
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374Maupetit, J.; Tuffery, P.; Derreumaux, P. A coarse-grained protein force field for folding and structure prediction Proteins: Struct., Funct., Genet. 2007, 69, 394– 408 DOI: 10.1002/prot.21505Google Scholar374https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtVykt7vL&md5=e6769e5f853e816fe0eafa13e9e4fed2A coarse-grained protein force field for folding and structure predictionMaupetit, Julien; Tuffery, P.; Derreumaux, PhilippeProteins: Structure, Function, and Bioinformatics (2007), 69 (2), 394-408CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)We have revisited the protein coarse-grained optimized potential for efficient structure prediction (OPEP). The training and validation sets consist of 13 and 16 protein targets. Because optimization depends on details of how the ensemble of decoys is sampled, trial conformations are generated by mol. dynamics, threading, greedy, and Monte Carlo simulations, or taken from publicly available databases. The OPEP parameters are varied by a genetic algorithm using a scoring function which requires that the native structure has the lowest energy, and the native-like structures have energy higher than the native structure but lower than the remote conformations. Overall, we find that OPEP correctly identifies 24 native or native-like states for 29 targets and has very similar capability to the all-atom discrete optimized protein energy model (DOPE), found recently to outperform five currently used energy models.
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375Goga, N.; Melo, M. N.; Rzepiela, A. J.; de Vries, A. H.; Hadar, A.; Marrink, S. J.; Berendsen, H. J. Benchmark of Schemes for Multiscale Molecular Dynamics Simulations J. Chem. Theory Comput. 2015, 11, 1389– 1398 DOI: 10.1021/ct501102bGoogle Scholar375https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkt1Oit7Y%253D&md5=89403c635fecbbd481ab6be9fb96b691Benchmark of Schemes for Multiscale Molecular Dynamics SimulationsGoga, N.; Melo, M. N.; Rzepiela, A. J.; de Vries, A. H.; Hadar, A.; Marrink, S. J.; Berendsen, H. J. C.Journal of Chemical Theory and Computation (2015), 11 (4), 1389-1398CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)In multiscale mol. dynamics simulations the accuracy of detailed models is combined with the efficiency of a reduced representation. For several applications - namely those of sampling enhancement - it is desirable to combine fine-grained (FG) and coarse-grained (CG) approaches into a single hybrid approach with an adjustable mixing parameter. We present a benchmark of three algorithms that use a mixing of the two representation layers using a Lagrangian formalism. The three algorithms use three different approaches for keeping the particles at the FG level of representation together: (1) addn. of forces, (2) mass scaling, and (3) temp. scaling. The benchmark is applied to liq. hexadecane and includes an evaluation of the av. configurational entropy of the FG and CG subsystems. The temp.-scaling scheme achieved a 3-fold sampling speedup with little deviation of FG properties. The addn.-of-forces scheme kept FG properties the best but provided little sampling speedup. The mass-scaling scheme yielded a 5-fold speedup but deviated the most from FG properties.
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376Nielsen, S. O.; Bulo, R. E.; Moore, P. B.; Ensing, B. Recent progress in adaptive multiscale molecular dynamics simulations of soft matter Phys. Chem. Chem. Phys. 2010, 12, 12401– 12414 DOI: 10.1039/c004111dGoogle Scholar376https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1OgtrbL&md5=6484a83415e3732fb9cd89b039aa06d8Recent progress in adaptive multiscale molecular dynamics simulations of soft matterNielsen, Steven O.; Bulo, Rosa E.; Moore, Preston B.; Ensing, BerndPhysical Chemistry Chemical Physics (2010), 12 (39), 12401-12414CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)A review. Understanding mesoscopic phenomena in terms of the fundamental motions of atoms and electrons poses a severe challenge for mol. simulation. This challenge is being met by multiscale modeling techniques that aim to bridge between the microscopic and mesoscopic time and length scales. In such techniques different levels of theory are combined to describe a system at a no. of scales or resolns. Here we review recent advancements in adaptive hybrid simulations, in which the different levels are used in sep. spatial domains and matter can diffuse from one region to another with an accompanying resoln. change. We discuss what it means to simulate such a system, and how to enact the resoln. changes. We show how to construct efficient adaptive hybrid quantum mechanics/mol. mechanics (QM/MM) and atomistic/coarse grain (AA/CG) mol. dynamics methods that use an intermediate healing region to smoothly couple the regions together. This coupling is formulated to use only the native forces inherent to each region. The total energy is conserved through the use of auxiliary bookkeeping terms. Error control, and the choice of time step and healing region width, is obtained by careful anal. of the energy flow between the different representations. We emphasize the CG AA reverse mapping problem and show how this problem is resolved through the use of rigid atomistic fragments located within each CG particle whose orientation is preconditioned for a possible resoln. change through a rotational dynamics scheme. These advancements are shown to enable the adaptive hybrid multiscale mol. dynamics simulation of macromol. soft matter systems.
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377Zhang, Y. Template-based modeling and free modeling by I-TASSER in CASP7 Proteins: Struct., Funct., Genet. 2007, 69, 108– 117 DOI: 10.1002/prot.21702Google ScholarThere is no corresponding record for this reference.
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378Kim, D. E.; Chivian, D.; Baker, D. Protein structure prediction and analysis using the Robetta server Nucleic Acids Res. 2004, 32, W526– 531 DOI: 10.1093/nar/gkh468Google Scholar378https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXlvFKmsrY%253D&md5=198eb7740579b1da7ad0b15616aae22dProtein structure prediction and analysis using the Robetta serverKim, David E.; Chivian, Dylan; Baker, DavidNucleic Acids Research (2004), 32 (Web Server), W526-W531CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and anal. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Exptl. NMR constraints data can also be submitted with a query sequence for RosettaNMR de novo structure detn. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.
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379Kelley, L. A.; Mezulis, S.; Yates, C. M.; Wass, M. N.; Sternberg, M. J. The Phyre2 web portal for protein modeling, prediction and analysis Nat. Protoc. 2015, 10, 845– 858 DOI: 10.1038/nprot.2015.053Google Scholar379https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnvFSqurs%253D&md5=e69b1b5c799cc3b8e3a562c90299a813The Phyre2 web portal for protein modeling, prediction and analysisKelley, Lawrence A.; Mezulis, Stefans; Yates, Christopher M.; Wass, Mark N.; Sternberg, Michael J. E.Nature Protocols (2015), 10 (6), 845-858CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which the authors previously published a paper in Nature Protocols. In this updated protocol, the authors describe Phyre2, which uses advanced remote homol. detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they det. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain compn. and model quality. A range of addnl. available tools is described to find a protein structure in a genome, to submit large no. of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.
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380Jefferys, B. R.; Kelley, L. A.; Sternberg, M. J. Protein folding requires crowd control in a simulated cell J. Mol. Biol. 2010, 397, 1329– 1338 DOI: 10.1016/j.jmb.2010.01.074Google ScholarThere is no corresponding record for this reference.
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381Schindler, C. E.; de Vries, S. J.; Zacharias, M. Fully Blind Peptide-Protein Docking with pepATTRACT Structure 2015, 23, 1507– 1515 DOI: 10.1016/j.str.2015.05.021Google Scholar381https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFaiu7fE&md5=4fe4ebb645e424f4f00b4f7918cab5dcFully Blind Peptide-Protein Docking with pepATTRACTSchindler, Christina E. M.; de Vries, Sjoerd J.; Zacharias, MartinStructure (Oxford, United Kingdom) (2015), 23 (8), 1507-1515CODEN: STRUE6; ISSN:0969-2126. (Elsevier Ltd.)Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement exptl. characterization of these complexes, but current protocols are not applicable on the proteome scale. Here, we present a new fully blind flexible peptide-protein docking protocol, pepATTRACT, which combines a rapid coarse-grained global peptide docking search of the entire protein surface with a two-stage atomistic flexible refinement. Global unbound-unbound docking yielded near-native models for 70% of the docking cases when testing the protocol on the largest benchmark of peptide-protein complexes available to date. This performance is similar to that of state-of-the-art local docking protocols that rely on information about the binding site. Upon restricting the search to the peptide binding region, the resulting pepATTRACT-local approach outperformed existing methods. Docking scripts for pepATTRACT and pepATTRACT-local can be generated via a web interface at www.attract.ph.tum.de/peptide.html.
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382Schindler, C. E.; de Vries, S. J.; Zacharias, M. iATTRACT: simultaneous global and local interface optimization for protein-protein docking refinement Proteins: Struct., Funct., Genet. 2015, 83, 248– 258 DOI: 10.1002/prot.24728Google ScholarThere is no corresponding record for this reference.
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383Raveh, B.; London, N.; Zimmerman, L.; Schueler-Furman, O. Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors PLoS One 2011, 6, e18934 DOI: 10.1371/journal.pone.0018934Google Scholar383https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXls1Kksb0%253D&md5=ac5099b6dfa6d7a3b8e45d8c8c45a816Rosetta FlexPepDockab-initio: simultaneous folding, docking and refinement of peptides onto their receptorsRaveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, OraPLoS One (2011), 6 (4), e18934CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)Flexible peptides that fold upon binding to another protein mol. mediate a large no. of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDockab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approx. specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDockab-initio samples efficiently and simultaneously sampled the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resoln. models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resoln. peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions.
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384Jamroz, M.; Kolinski, A.; Kmiecik, S. CABS-flex predictions of protein flexibility compared with NMR ensembles Bioinformatics 2014, 30, 2150– 2154 DOI: 10.1093/bioinformatics/btu184Google Scholar384https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht1SqtL7N&md5=3771bee8bed66b23da3a9dee99309f33CABS-flex predictions of protein flexibility compared with NMR ensemblesJamroz, Michal; Kolinski, Andrzej; Kmiecik, SebastianBioinformatics (2014), 30 (15), 2150-2154CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)A review. Motivation: Identification of flexible regions of protein structures is important for understanding of their biol. functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom mol. dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Results: Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On av., this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting protein regions that undergo conformational changes as well as the extent of such changes.
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385Kruger, D. M.; Ahmed, A.; Gohlke, H. NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins Nucleic Acids Res. 2012, 40, W310– 316 DOI: 10.1093/nar/gks478Google ScholarThere is no corresponding record for this reference.
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386Camps, J.; Carrillo, O.; Emperador, A.; Orellana, L.; Hospital, A.; Rueda, M.; Cicin-Sain, D.; D’Abramo, M.; Gelpi, J. L.; Orozco, M. FlexServ: an integrated tool for the analysis of protein flexibility Bioinformatics 2009, 25, 1709– 1710 DOI: 10.1093/bioinformatics/btp304Google Scholar386https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnsFygtLo%253D&md5=27989bd30d186c47a4bb567af66a5bb8FlexServ: an integrated tool for the analysis of protein flexibilityCamps, Jordi; Carrillo, Oliver; Emperador, Agusti; Orellana, Laura; Hospital, Adam; Rueda, Manuel; Cicin-Sain, Damjan; D'Abramo, Marco; Gelpi, Josep Lluis; Orozco, ModestoBioinformatics (2009), 25 (13), 1709-1710CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: FlexServ is a web-based tool for the anal. of protein flexibility. The server incorporates powerful protocols for the coarse-grained detn. of protein dynamics using different versions of Normal Mode Anal. (NMA), Brownian dynamics (BD) and Discrete Dynamics (DMD). It can also analyze user provided trajectories. The server allows a complete anal. of flexibility using a large variety of metrics, including basic geometrical anal., B-factors, essential dynamics, stiffness anal., collectivity measures, Lindemann's indexes, residue correlation, chain-correlations, dynamic domain detn., hinge point detections, etc. Data is presented through a web interface as plain text, 2D and 3D graphics.
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387de Vries, S. J.; Schindler, C. E.; Chauvot de Beauchene, I.; Zacharias, M. A web interface for easy flexible protein-protein docking with ATTRACT Biophys. J. 2015, 108, 462– 465 DOI: 10.1016/j.bpj.2014.12.015Google Scholar387https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntVWjsQ%253D%253D&md5=a5ed83a84633c95201596986df45f460A Web Interface for Easy Flexible Protein-Protein Docking with ATTRACTde Vries, Sjoerd J.; Schindler, Christina E. M.; Chauvot de Beauchene, Isaure; Zacharias, MartinBiophysical Journal (2015), 108 (3), 462-465CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Protein-protein docking programs can give valuable insights into the structure of protein complexes in the absence of an exptl. complex structure. Web interfaces can facilitate the use of docking programs by structural biologists. Here, we present an easy web interface for protein-protein docking with the ATTRACT program. While aimed at nonexpert users, the web interface still covers a considerable range of docking applications. The web interface supports systematic rigid-body protein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibility. The execution of a docking protocol takes up to a few hours on a std. desktop computer.
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388May, A.; Zacharias, M. Protein-protein docking in CAPRI using ATTRACT to account for global and local flexibility Proteins: Struct., Funct., Genet. 2007, 69, 774– 780 DOI: 10.1002/prot.21735Google ScholarThere is no corresponding record for this reference.
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389Zacharias, M. ATTRACT: protein-protein docking in CAPRI using a reduced protein model Proteins: Struct., Funct., Genet. 2005, 60, 252– 256 DOI: 10.1002/prot.20566Google ScholarThere is no corresponding record for this reference.
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390de Vries, S.; Zacharias, M. Flexible docking and refinement with a coarse-grained protein model using ATTRACT Proteins: Struct., Funct., Genet. 2013, 81, 2167– 2174 DOI: 10.1002/prot.24400Google ScholarThere is no corresponding record for this reference.
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391Dehouck, Y.; Kwasigroch, J. M.; Rooman, M.; Gilis, D. BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations Nucleic Acids Res. 2013, 41, W333– 339 DOI: 10.1093/nar/gkt450Google ScholarThere is no corresponding record for this reference.
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392Dehouck, Y.; Gilis, D.; Rooman, M. A new generation of statistical potentials for proteins Biophys. J. 2006, 90, 4010– 4017 DOI: 10.1529/biophysj.105.079434Google Scholar392https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XltF2mt7s%253D&md5=9e0b446c406d4d388bb2a4ad0ef271e4A new generation of statistical potentials for proteinsDehouck, Y.; Gilis, D.; Rooman, M.Biophysical Journal (2006), 90 (11), 4010-4017CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We propose a novel and flexible derivation scheme of statistical, database-derived, potentials, which allows one to take simultaneously into account specific correlations between several sequence and structure descriptors. This scheme leads to the decompn. of the total folding free energy of a protein into a sum of lower order terms, thereby giving the possibility to analyze independently each contribution and clarify its significance and importance, to avoid overcounting certain contributions, and to deal more efficiently with the limited size of the database. In addn., this derivation scheme appears as quite general, for many previously developed potentials can be expressed as particular cases of our formalism. We use this formalism as a framework to generate different residue-based energy functions, whose performances are assessed on the basis of their ability to discriminate genuine proteins from decoy models. The optimal potential is generated as a combination of several coupling terms, measuring correlations between residue types, backbone torsion angles, solvent accessibilities, relative positions along the sequence, and interresidue distances. This potential outperforms all tested residue-based potentials, and even several atom-based potentials. Its incorporation in algorithms aiming at predicting protein structure and stability should therefore substantially improve their performances.
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393Dehouck, Y.; Grosfils, A.; Folch, B.; Gilis, D.; Bogaerts, P.; Rooman, M. Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0 Bioinformatics 2009, 25, 2537– 2543 DOI: 10.1093/bioinformatics/btp445Google Scholar393https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtFyhtbbF&md5=59f9acfcafd822a7f3a27eb3cf3538cdFast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0Dehouck, Yves; Grosfils, Aline; Folch, Benjamin; Gilis, Dimitri; Bogaerts, Philippe; Rooman, MarianneBioinformatics (2009), 25 (19), 2537-2543CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)The rational design of proteins with modified properties, through amino acid substitutions, is of crucial importance in a large variety of applications. Given the huge no. of possible substitutions, every protein engineering project would benefit strongly from the guidance of in silico methods able to predict rapidly, and with reasonable accuracy, the stability changes resulting from all possible mutations in a protein. The authors exploit newly developed statistical potentials, based on a formalism that highlights the coupling between 4 protein sequence and structure descriptors, and take into account the amino acid vol. variation upon mutation. The stability change is expressed as a linear combination of these energy functions, whose proportionality coeffs. vary with the solvent accessibility of the mutated residue and are identified with the help of a neural network. A correlation coeff. of R = 0.63 and a root mean square error of σc = 1.15 kcal/mol between measured and predicted stability changes are obtained upon cross-validation. These scores reach R = 0.79, and σc = 0.86 kcal/mol after exclusion of 10% outliers. The predictive power of the authors' method is shown to be significantly higher than that of other programs described in the literature.
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394Viswanath, S.; Ravikant, D. V.; Elber, R. DOCK/PIERR: web server for structure prediction of protein-protein complexes Methods Mol. Biol. 2014, 1137, 199– 207 DOI: 10.1007/978-1-4939-0366-5_14Google Scholar394https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXns12is7w%253D&md5=a3b91ed176c57f88ba7c9e580a48421bDOCK/PIERR: Web Server for Structure Prediction of Protein-Protein ComplexesViswanath, Shruthi; Ravikant, D. V. S.; Elber, RonMethods in Molecular Biology (New York, NY, United States) (2014), 1137 (Protein Structure Prediction), 199-207CODEN: MMBIED; ISSN:1940-6029. (Springer)In protein docking we aim to find the structure of the complex formed when two proteins interact. Protein-protein interactions are crucial for cell function. Here we discuss the usage of DOCK/PIERR. In DOCK/PIERR, a uniformly discrete sampling of orientations of one protein with respect to the other, are scored, followed by clustering, refinement, and reranking of structures. The novelty of this method lies in the scoring functions used. These are obtained by examg. hundreds of millions of correctly and incorrectly docked structures, using an algorithm based on math. programming, with provable convergence properties.
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395Ravikant, D. V.; Elber, R. PIE-efficient filters and coarse grained potentials for unbound protein-protein docking Proteins: Struct., Funct., Genet. 2010, 78, 400– 419 DOI: 10.1002/prot.22550Google ScholarThere is no corresponding record for this reference.
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396Viswanath, S.; Ravikant, D. V.; Elber, R. Improving ranking of models for protein complexes with side chain modeling and atomic potentials Proteins: Struct., Funct., Genet. 2013, 81, 592– 606 DOI: 10.1002/prot.24214Google ScholarThere is no corresponding record for this reference.
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397Frappier, V.; Chartier, M.; Najmanovich, R. J. ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability Nucleic Acids Res. 2015, 43, W395– 400 DOI: 10.1093/nar/gkv343Google ScholarThere is no corresponding record for this reference.
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398Lyskov, S.; Gray, J. J. The RosettaDock server for local protein-protein docking Nucleic Acids Res. 2008, 36, W233– 238 DOI: 10.1093/nar/gkn216Google Scholar398https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXptlKkurs%253D&md5=689113abd16fae2d161cf812b4fb720bThe RosettaDock server for local protein-protein dockingLyskov, Sergey; Gray, Jeffrey J.Nucleic Acids Research (2008), 36 (Web Server), W233-W238CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The RosettaDock server (http://rosettadock.graylab.jhu.edu) identifies low-energy conformations of a protein-protein interaction near a given starting configuration by optimizing rigid-body orientation and side-chain conformations. The server requires two protein structures as inputs and a starting location for the search. RosettaDock generates 1000 independent structures, and the server returns pictures, coordinate files and detailed scoring information for the 10 top-scoring models. A plot of the total energy of each of the 1000 models created shows the presence or absence of an energetic binding funnel. RosettaDock has been validated on the docking benchmark set and through the Crit. Assessment of PRedicted Interactions blind prediction challenge.
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399London, N.; Schueler-Furman, O. FunHunt: model selection based on energy landscape characteristics Biochem. Soc. Trans. 2008, 36, 1418– 1421 DOI: 10.1042/BST0361418Google Scholar399https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVCgsb3I&md5=3a0c9e7496f43424ac9ff149bda47f32FunHunt: model selection based on energy landscape characteristicsLondon, Nir; Schueler-Furman, OraBiochemical Society Transactions (2008), 36 (6), 1418-1421CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)Protein folding and binding is commonly depicted as a search for the min. energy conformation in a vast energy landscape. Indeed, modeling of protein complex structures by RosettaDock often results in a set of low-energy conformations near the native structure. Ensembles of low-energy conformations can appear, however, in other regions of the energy landscape, esp. when backbone movements occur upon binding. What then characterizes the energy landscape near the correct orientation. The authors have applied a machine learning algorithm to distinguish ensembles of low-energy conformations around the native conformation from other low-energy ensembles. FunHunt, the resulting classifier, identified the native orientation for 50/52 protein complexes in a test set, and for all of 12 recent CAPRI targets. FunHunt is also able to choose the near-native orientation among models created by algorithms other than RosettaDock, demonstrating its general applicability for model selection. The features used by FunHunt teach us about the nature of native interfaces. Remarkably, the energy decrease of trajectories toward near-native orientations is significantly larger than for other orientations. This provides a possible explanation for the stability of assocn. in the native orientation. The FunHunt approach, discriminating models based on ensembles of structures that map the nearby energy landscape, can be adapted and extended to addnl. tasks, such as ab initio model selection, protein interface design and specificity predictions.
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400Sircar, A.; Kim, E. T.; Gray, J. J. RosettaAntibody: antibody variable region homology modeling server Nucleic Acids Res. 2009, 37, W474– 479 DOI: 10.1093/nar/gkp387Google Scholar400https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXosFSktLw%253D&md5=a997ea013edd9949901aacddbe8247b1RosettaAntibody: antibody variable region homology modeling serverSircar, Aroop; Kim, Eric T.; Gray, Jeffrey J.Nucleic Acids Research (2009), 37 (Web Server), W474-W479CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The RosettaAntibody server (http://antibody.graylab.jhu.edu) predicts the structure of an antibody variable region given the amino-acid sequences of the resp. light and heavy chains. In an initial stage, the server identifies and displays the most sequence homologous template structures for the light and heavy framework regions and each of the complementarity detg. region (CDR) loops. Subsequently, the most homologous templates are assembled into a side-chain optimized crude model, and the server returns a picture and coordinate file. For users requesting a high-resoln. model, the server executes the full RosettaAntibody protocol which addnl. models the hyper-variable CDR H3 loop. The high-resoln. protocol also relieves steric clashes by optimizing the CDR backbone torsion angles and by simultaneously perturbing the relative orientation of the light and heavy chains. RosettaAntibody generates 2000 independent structures, and the server returns pictures, coordinate files, and detailed scoring information for the 10 top-scoring models. The 10 models enable users to use rational judgment in choosing the best model or to use the set as an ensemble for further studies such as docking. The high-resoln. models generated by RosettaAntibody have been used for the successful prediction of antibody-antigen complex structures.
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401Shaw, D. E.; Maragakis, P.; Lindorff-Larsen, K.; Piana, S.; Dror, R. O.; Eastwood, M. P.; Bank, J. A.; Jumper, J. M.; Salmon, J. K.; Shan, Y. Atomic-level characterization of the structural dynamics of proteins Science 2010, 330, 341– 346 DOI: 10.1126/science.1187409Google Scholar401https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1OisL%252FN&md5=85c9d897881e8684fc39d69b2b6b2fadAtomic-Level Characterization of the Structural Dynamics of ProteinsShaw, David E.; Maragakis, Paul; Lindorff-Larsen, Kresten; Piana, Stefano; Dror, Ron O.; Eastwood, Michael P.; Bank, Joseph A.; Jumper, John M.; Salmon, John K.; Shan, Yibing; Wriggers, WillyScience (Washington, DC, United States) (2010), 330 (6002), 341-346CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)Mol. dynamics (MD) simulations are widely used to study protein motions at an at. level of detail, but they have been limited to time scales shorter than those of many biol. crit. conformational changes. We examd. two fundamental processes in protein dynamics-protein folding and conformational change within the folded state-by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equil. simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; sep. simulations of the protein's constituent substructures shed light on possible determinants of this pathway. A 1-ms simulation of the folded protein BPTI reveals a small no. of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.
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402Freddolino, P. L.; Liu, F.; Gruebele, M.; Schulten, K. Ten-microsecond molecular dynamics simulation of a fast-folding WW domain Biophys. J. 2008, 94, L75– 77 DOI: 10.1529/biophysj.108.131565Google Scholar402https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlsF2htL0%253D&md5=f443f76d09c6f846d9df6c5cc0988c22Ten-microsecond molecular dynamics simulation of a fast-folding WW domainFreddolino, Peter L.; Liu, Feng; Gruebele, Martin; Schulten, KlausBiophysical Journal (2008), 94 (10), L75-L77CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)All-atom mol. dynamics (MD) simulations of protein folding allow anal. of the folding process at an unprecedented level of detail. Unfortunately, such simulations have not yet reached their full potential both due to difficulties in sufficiently sampling the microsecond timescales needed for folding, and because the force field used may yield neither the correct dynamical sequence of events nor the folded structure. The ongoing study of protein folding through computational methods thus requires both improvements in the performance of MD programs to make longer timescales accessible, and testing of force fields in the context of folding simulations. Here, the authors report a 10-μs simulation of an incipient downhill-folding peptidylprolyl isomerase Pin1 WW domain mutant along with measurement of a mol. time and activated folding time of 1.5 and 13.3 μs, resp. The protein simulated in explicit solvent exhibited several metastable states with incorrect topol. and did not assume the native state during the present simulations.
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403Fersht, A. R. From the first protein structures to our current knowledge of protein folding: delights and scepticisms Nat. Rev. Mol. Cell Biol. 2008, 9, 650– 654 DOI: 10.1038/nrm2446Google Scholar403https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXosl2rsLg%253D&md5=bdc2c8fe953a92119410aa1354e3bd44From the first protein structures to our current knowledge of protein folding: Delights and scepticismsFersht, Alan R.Nature Reviews Molecular Cell Biology (2008), 9 (8), 650-654CODEN: NRMCBP; ISSN:1471-0072. (Nature Publishing Group)A review. Every breakthrough that opens new vistas also removes the ground from under the feet of other scientists. The scientific joy of those who have seen the new light is accompanied by the dismay of those whose way of life has been changed forever. The publication of the first structures of proteins at at. resoln. 50 years ago astounded and inspired scientists in every field but caused others to flee or scoff. That advance and every subsequent paradigm-shifting breakthrough in protein science have met with some resistance before universal acceptance. I relate these events and their impact on the field of protein folding.
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404Schaeffer, R. D.; Fersht, A.; Daggett, V. Combining experiment and simulation in protein folding: closing the gap for small model systems Curr. Opin. Struct. Biol. 2008, 18, 4– 9 DOI: 10.1016/j.sbi.2007.11.007Google Scholar404https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVGit74%253D&md5=404efb9a9af6c1b1b59f9abe09f0d919Combining experiment and simulation in protein folding: closing the gap for small model systemsSchaeffer, R. Dustin; Fersht, Alan; Daggett, ValerieCurrent Opinion in Structural Biology (2008), 18 (1), 4-9CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. All-atom mol. dynamics (MD) simulations on increasingly powerful computers have been combined with expts. to characterize protein folding in detail over wider time ranges. The folding of small ultrafast folding proteins is being simulated on μs timescales, leading to improved structural predictions and folding rates. To what extent is closing the gap' between simulation and expt. for such systems providing insights into general mechanisms of protein folding.
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405Sułkowska, J. I.; Cieplak, M. Selection of Optimal Variants of Go̅-Like Models of Proteins through Studies of Stretching Biophys. J. 2008, 95, 3174– 3191 DOI: 10.1529/biophysj.107.127233Google Scholar405https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1Srs7nP&md5=bd53abc8f364c55d61481dce316f5c7aSelection of optimal variants of G‾o-like models of proteins through studies of stretchingSulkowska, Joanna I.; Cieplak, MarekBiophysical Journal (2008), 95 (7), 3174-3191CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The G‾o-like models of proteins are constructed based on the knowledge of the native conformation. However, there are many possible choices of a Hamiltonian for which the ground state coincides with the native state. Here, we propose to use exptl. data on protein stretching to det. what choices are most adequate phys. This criterion is motivated by the fact that stretching processes usually start with the native structure, in the vicinity of which the G‾o-like models should work the best. Our selection procedure is applied to 62 different versions of the G‾o model and is based on 28 proteins. We consider different potentials, contact maps, local stiffness energies, and energy scales-uniform and nonuniform. In the latter case, the strength of the nonuniformity was governed either by specificity or by properties related to positioning of the side groups. Among them is the simplest variant: uniform couplings with no i, i + 2 contacts. This choice also leads to good folding properties in most cases. We elucidate relationship between the local stiffness described by a potential which involves local chirality and the one which involves dihedral and bond angles. The latter stiffness improves folding but there is little difference between them when it comes to stretching.
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406Prieto, L.; Rey, A. Topology-based potentials and the study of the competition between protein folding and aggregation J. Chem. Phys. 2009, 130, 115101 DOI: 10.1063/1.3089708Google ScholarThere is no corresponding record for this reference.
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407Takada, S.; Kanada, R.; Tan, C.; Terakawa, T.; Li, W.; Kenzaki, H. Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations Acc. Chem. Res. 2015, 48, 3026– 3035 DOI: 10.1021/acs.accounts.5b00338Google Scholar407https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFyjsr7O&md5=99733b902bdbf0e19e835d73c44772f9Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular SimulationsTakada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, HirooAccounts of Chemical Research (2015), 48 (12), 3026-3035CODEN: ACHRE4; ISSN:0001-4842. (American Chemical Society)A review. Due to hierarchic nature of biomol. systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations were used to address long-time dynamics of large systems. Here, the authors review recent developments and applications of CG modeling methods, focusing on the authors' methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomol. simulator, CafeMol. The authors' CG model has resoln. such that ∼10 non-hydrogen atoms are grouped into one CG particle on av. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. The authors first describe two representative minimal models of proteins, called the elastic network model and the classic G‾o model. The authors then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, the authors describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodn. exptl. data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded vol. terms for nonspecific cases. The authors also discuss the time scale mapping in CG mol. dynamics simulations. While the apparent single time step of the authors' CGMD is ∼10 times larger than that in the fully atomistic mol. dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude using CG model and a low friction const. in Langevin dynamics. Next, the authors present four examples of applications. First, the classic G‾o model was used to emulate one ATP cycle of a mol. motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, the authors simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concn.-dependent compaction. Finally, many of limitations in the current approaches and future directions are discussed. Esp., more accurate electrostatic treatment and a phospholipid model that matches the authors' CG resolns. are of immediate importance.
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408Zhang, Z.; Chan, H. S. Competition between native topology and nonnative interactions in simple and complex folding kinetics of natural and designed proteins Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 2920– 2925 DOI: 10.1073/pnas.0911844107Google Scholar408https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXis1Clt7c%253D&md5=bdb9b4ee6b45aadbbf1b0d05e93cc7ecCompetition between native topology and nonnative interactions in simple and complex folding kinetics of natural and designed proteinsZhang, Zhuqing; Chan, Hue SunProceedings of the National Academy of Sciences of the United States of America (2010), 107 (7), 2920-2925, S2920/1-S2920/7CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We compared folding properties of designed protein Top7 and natural protein S6 by using coarse-grained chain models with a mainly native-centric construct that accounted also for nonnative hydrophobic interactions and desolvation barriers. Top7 and S6 have similar secondary structure elements and are approx. equal in length and hydrophobic compn. Yet their exptl. folding kinetics were drastically different. Consistent with expt., our simulated folding chevron arm for Top7 exhibited a severe rollover, whereas that for S6 was essentially linear, and Top7 model kinetic relaxation was multiphasic under strongly folding conditions. The peculiar behavior of Top7 was assocd. with several classes of kinetic traps in our model. Significantly, the amino acid residues participating in nonnative interactions in trapped conformations in our Top7 model overlapped with those deduced exptl. These affirmations suggest that the simple ingredients of native topol. plus sequence-dependent nonnative interactions are sufficient to account for some key features of protein folding kinetics. Notably, when nonnative interactions were absent in the model, Top7 chevron rollover was not correctly predicted. In contrast, nonnative interactions had little effect on the quasi linearity of the model folding chevron arm for S6. This intriguing distinction indicates that folding cooperativity is governed by a subtle interplay between the sequence-dependent driving forces for native topol. and the locations of favorable nonnative interactions entailed by the same sequence. Constructed with a capability to mimic this interplay, our simple modeling approach should be useful in general for assessing a designed sequence's potential to fold cooperatively.
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409Shan, B.; Eliezer, D.; Raleigh, D. P. The unfolded state of the C-terminal domain of the ribosomal protein L9 contains both native and non-native structure Biochemistry 2009, 48, 4707– 4719 DOI: 10.1021/bi802299jGoogle Scholar409https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXlvFWnsbc%253D&md5=3481c5177f3bd7b35d56e5109234c9fbThe unfolded state of the C-terminal domain of the ribosomal protein L9 contains both native and non-native structureShan, Bing; Eliezer, David; Raleigh, Daniel P.Biochemistry (2009), 48 (22), 4707-4719CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)Interest in the structural and dynamic properties of unfolded proteins has increased in recent years owing to continued interest in protein folding and misfolding. Knowledge of the unfolded state under native conditions is particularly important for obtaining a complete picture of the protein folding process. The C-terminal domain of ribosomal protein L9 (CTL9) is a globular α,β protein with an unusual mixed parallel and antiparallel β-strand structure. The folding kinetics and equil. unfolding of CTL9 strongly depended on pH, and followed a simple 2-state model. Both the native and the unfolded state could be significantly populated at pH 3.8 in the absence of denaturant, allowing the native state and the unfolded state to be characterized under identical conditions. Backbone 15N, 13C, 1H and side-chain 13Cβ, 1Hβ chem. shifts, amide proton NOEs, and 15N R2 relaxation rates were obtained for the 2 conformational states at pH 3.8. All of the data indicated that the pH 3.8 native state was well folded and was similar to the native state at neutral pH. There was significant residual structure in the pH 3.8 unfolded state. The regions corresponding to the 2 native state α-helixes showed strong preference to populate helical φ and ψ angles. The segment that connects α-helix 2 and β-strand 2 had a significant tendency to form non-native α-helical structure. Comparison with the pH 2.0 unfolded state and the urea unfolded state indicated that the tendency to adopt both native and non-native helical structure was stronger at pH 3.8, demonstrating that the unfolded state of CTL9 under native-like conditions was more structured. The implications for the folding of CTL9 are discussed.
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410Rothwarf, D. M.; Scheraga, H. A. Role of non-native aromatic and hydrophobic interactions in the folding of hen egg white lysozyme Biochemistry 1996, 35, 13797– 13807 DOI: 10.1021/bi9608119Google Scholar410https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmtVOmurg%253D&md5=32f25454758763f7ddadb0ed769b4851Role of non-native aromatic and hydrophobic interactions in the folding of hen egg white lysozymeRothwarf, David M.; Scheraga, Harold A.Biochemistry (1996), 35 (43), 13797-13807CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)The folding kinetics were detd. for hen egg white lysozyme and 2 mutants in which Trp-62 and Trp-108 were individually replaced by tyrosine (Tyr-62-lysozyme and Tyr-108-lysozyme, resp.). An earlier study of wild-type lysozyme had indicated that 2 transient intermediates were formed during the early stages of refolding. Both intermediates were characterized by substantial quenching of tryptophan fluorescence which suggested that, during the refolding process, Trp-62 and/or Trp-108 was involved in a non-native tertiary interaction(s). Both Tyr-108- and Tyr-62-lysozyme fold significantly faster than wild-type lysozyme (7- and 13-fold, resp.). These results indicate that the rate-limiting step in the folding of lysozyme arises not from any inherent slowness in the formation of the native structure but rather as a consequence of the formation of a highly stable intermediate which contains significant non-native structure which must be disrupted prior to, or in concert with, subsequent folding. The data suggest that arom. and hydrophobic interactions play a pivotal role in the formation of the non-native intermediate. The general role that non-native interactions play in the folding process is discussed.
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411Jana, B.; Morcos, F.; Onuchic, J. N. From structure to function: the convergence of structure based models and co-evolutionary information Phys. Chem. Chem. Phys. 2014, 16, 6496– 6507 DOI: 10.1039/c3cp55275fGoogle ScholarThere is no corresponding record for this reference.
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412Okazaki, K.; Koga, N.; Takada, S.; Onuchic, J. N.; Wolynes, P. G. Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 11844– 11849 DOI: 10.1073/pnas.0604375103Google Scholar412https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XosVSgs7k%253D&md5=341dd37d5e9528521eec63bbcacb5190Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: structure-based molecular dynamics simulationsOkazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2006), 103 (32), 11844-11849CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Biomols. often undergo large-amplitude motions when they bind or release other mols. Unlike macroscopic machines, these biomol. machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the multiple-basin model, that can directly be used for mol. dynamics simulation of even very large biomol. systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temp. near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition.
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413Li, W.; Wang, W.; Takada, S. Energy landscape views for interplays among folding, binding, and allostery of calmodulin domains Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 10550– 10555 DOI: 10.1073/pnas.1402768111Google Scholar413https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFCnsrfM&md5=92ebcafe17e570c174fc20b8bf250f4dEnergy landscape views for interplays among folding, binding, and allostery of calmodulin domainsLi, Wenfei; Wang, Wei; Takada, ShojiProceedings of the National Academy of Sciences of the United States of America (2014), 111 (29), 10550-10555CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Ligand binding modulates the energy landscape of proteins, thus altering their folding and allosteric conformational dynamics. To investigate such interplay, calmodulin (CaM) has been a model protein. Despite much attention, fully resolved mechanisms of CaM folding/binding have not been elucidated. Here, by constructing a computational model that can integrate folding, binding, and allosteric motions, the authors studied the in-depth folding of isolated CaM domains coupled with binding of 2 Ca2+ ions and assocd. allosteric conformational changes. First, mech. pulled simulations revealed the coexistence of 3 distinct conformational states: the unfolded, the closed, and the open states, which was in accord with and augmented the structural understanding of recent single-mol. expts. Second, near the denaturation temp., the authors found the same 3 conformational states as well as 3 distinct binding states: 0, 1, and 2 Ca2+ ion-bound states, leading to as many as 9 states. Third, in terms of the 9-state representation, the authors found multi-route folding/binding pathways and shifts in their probabilities with the Ca2+ concn. At a lower Ca2+ concns., "combined spontaneous folding and induced fit" occurred, whereas at a higher concns., "binding-induced folding" dominated. Even without Ca2+ binding, the authors obsd. that the folding pathway of CaM domains could be modulated by the presence of metastable states. Finally, full-length CaM also exhibited an intriguing coupling between 2 domains when applying tension.
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414Koga, N.; Takada, S. Folding-based molecular simulations reveal mechanisms of the rotary motor F1-ATPase Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 5367– 5372 DOI: 10.1073/pnas.0509642103Google Scholar414https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjslaqurY%253D&md5=758f7e9f4187b943136f0b1e72f85af3Folding-based molecular simulations reveal mechanisms of the rotary motor F1-ATPaseKoga, Nobuyasu; Takada, ShojiProceedings of the National Academy of Sciences of the United States of America (2006), 103 (14), 5367-5372CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Biomol. machines fulfill their function through large conformational changes that typically occur on the millisecond time scale or longer. Conventional atomistic simulations can only reach microseconds at the moment. Here, extending the minimalist model developed for protein folding, we propose the "switching G‾o model" and use it to simulate the rotary motion of the ATP-driven mol. motor F1-ATPase. The simulation recovers the unidirectional 120° rotation of the γ-subunit, the rotor. The rotation was induced solely by steric repulsion from the α3β3 subunits, the stator, which undergo conformational changes during ATP hydrolysis. In silico alanine mutagenesis further elucidated which residues play specific roles in the rotation. Finally, regarding the mechanochem. coupling scheme, we found that the tri-site model does not lead to successful rotation but that the always-bi-site model produces ≈30° and ≈90° substeps, perfectly in accord with expts. In the always-bi-site model, the no. of sites occupied by nucleotides is always two during the hydrolysis cycle. This study opens up an avenue of simulating functional dynamics of huge biomols. that occur on the millisecond time scales involving large-amplitude conformational change.
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415Han, W.; Schulten, K. Characterization of folding mechanisms of Trp-cage and WW-domain by network analysis of simulations with a hybrid-resolution model J. Phys. Chem. B 2013, 117, 13367– 13377 DOI: 10.1021/jp404331dGoogle Scholar415https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1Wlt7vE&md5=ae252e12cd28f5b4d75b143b7f21988cCharacterization of Folding Mechanisms of Trp-Cage and WW-Domain by Network Analysis of Simulations with a Hybrid-Resolution ModelHan, Wei; Schulten, KlausJournal of Physical Chemistry B (2013), 117 (42), 13367-13377CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)In this study, we apply a hybrid-resoln. model, namely, PACE, to characterize the free energy surfaces (FESs) of Trp-cage and a WW-domain variant along with the resp. folding mechanisms. Unbiased, independent simulations with PACE are found to achieve together multiple folding and unfolding events for both proteins, allowing us to perform network anal. of the FESs to identify folding pathways. PACE reproduces for both proteins expected complexity hidden in the folding FESs, in particular metastable non-native intermediates. Pathway anal. shows that some of these intermediates are, actually, on-pathway folding intermediates and that intermediates kinetically closest to the native states can be either crit. on-pathway or off-pathway intermediates, depending on the protein. Apart from general insights into folding, specific folding mechanisms of the proteins are resolved. We find that Trp-cage folds via a dominant pathway in which hydrophobic collapse occurs before the N-terminal helix forms; full incorporation of Trp6 into the hydrophobic core takes place as the last step of folding, which, however, may not be the rate-limiting step. For the WW-domain variant studied, we observe two main folding pathways with opposite orders of formation of the two hairpins involved in the structure; for either pathway, formation of hairpin 1 is more likely to be the rate-limiting step. Altogether, our results suggest that PACE combined with network anal. is a computationally efficient and valuable tool for the study of protein folding.
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416Han, W.; Wan, C. K.; Jiang, F.; Wu, Y. D. PACE Force Field for Protein Simulations. 1. Full Parameterization of Version 1 and Verification J. Chem. Theory Comput. 2010, 6, 3373– 3389 DOI: 10.1021/ct1003127Google Scholar416https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtleiurzK&md5=22cf63c37da26e873bd06048150ce14bPACE Force Field for Protein Simulations. 1. Full Parameterization of Version 1 and VerificationHan, Wei; Wan, Cheuk-Kin; Jiang, Fan; Wu, Yun-DongJournal of Chemical Theory and Computation (2010), 6 (11), 3373-3389CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A further parametrization of a united-atom protein model coupled with coarse-grained water has been carried out to cover all amino acids (AAs). The local conformational features of each AA have been fitted on the basis of restricted coil-library statistics of high-resoln. X-ray crystal structures of proteins. Potential functions were developed on the basis of combined backbone and side chain rotamer conformational preferences, or rotamer Ramachandran plots (.vphi., Ψ, χ1). Side chain-side chain and side chain-backbone interaction potentials were parametrized to fit the potential mean forces of corresponding all-atom simulations. The force field has been applied in mol. dynamics simulations of several proteins of 56-108 AA residues whose X-ray crystal and/or NMR structures are available. Starting from the crystal structures, each protein was simulated for about 100 ns. The Cα RMSDs of the calcd. structures are 2.4-4.2 Å with respect to the crystal and/or NMR structures, which are still larger than but close to those of all-atom simulations (1.1-3.6 Å). Starting from the PDB structure of malate synthase G of 723 AA residues, the wall-clock time of a 30 ns simulation is about three days on a 2.65 GHz dual-core CPU. The RMSD to the exptl. structure is about 4.3 Å. These results implicate the applicability of the force field in the study of protein structures.
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417Thorpe, I. F.; Zhou, J.; Voth, G. A. Peptide folding using multiscale coarse-grained models J. Phys. Chem. B 2008, 112, 13079– 13090 DOI: 10.1021/jp8015968Google Scholar417https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFelt7fM&md5=e7e6883526fac062d9c7be8d108f9df8Peptide Folding Using Multiscale Coarse-Grained ModelsThorpe, Ian F.; Zhou, Jian; Voth, Gregory A.Journal of Physical Chemistry B (2008), 112 (41), 13079-13090CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The multiscale coarse-graining (MS-CG) method has been previously used to describe the equil. properties of peptides. The present study reveals that MS-CG models of α-helical polyalanine and the β-hairpin V5PGV5 possess the capacity to efficiently refold in simulations initiated from unfolded configurations. The MS-CG peptides exhibit free energy landscapes that are funneled toward folded configurations and two-state folding behavior, consistent with the known characteristics of small, rapidly folding peptides. Moreover, the models demonstrate enhanced sampling capabilities when compared to systems with full at. detail. The significance of these observations with respect to the theor. basis of the MS-CG approach is discussed. The MS-CG peptides were used to reconstruct atomically detailed configurations in order to evaluate the extent to which MS-CG ensembles embody all-atom peptide free energy landscapes. Ensembles obtained from these reconstructed configurations display good agreement with the all-atom simulation data used to generate the MS-CG models and also corroborate the presence of features obsd. in the MS-CG peptide free energy landscapes. These findings suggest that MS-CG models may be of significant utility in the study of peptide folding.
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418Hills, R. D., Jr.; Lu, L.; Voth, G. A. Multiscale coarse-graining of the protein energy landscape PLoS Comput. Biol. 2010, 6, e1000827 DOI: 10.1371/journal.pcbi.1000827Google ScholarThere is no corresponding record for this reference.
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419Adhikari, A. N.; Freed, K. F.; Sosnick, T. R. De novo prediction of protein folding pathways and structure using the principle of sequential stabilization Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 17442– 17447 DOI: 10.1073/pnas.1209000109Google Scholar419https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVSltLrK&md5=f6a8bda849c6adf37982a28401b72eaaDe novo prediction of protein folding pathways and structure using the principle of sequential stabilizationAdhikari, Aashish N.; Freed, Karl F.; Sosnick, Tobin R.Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (43), 17442-17447, S17442/1-S17442/10CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Motivated by the relation between the folding mechanism and the native structure, the authors develop a unified approach for predicting folding pathways and tertiary structure using only the primary sequence as input. Simulations begin from a realistic unfolded state devoid of secondary structure and use a chain representation lacking explicit side-chains, rendering the simulations many orders of magnitude faster than mol. dynamics simulations. The multiple round nature of the algorithm mimics the authentic folding process and tests the effectiveness of sequential stabilization (SS) as a search strategy wherein 2° structural elements add onto existing structures in a process of progressive learning and stabilization of structure found in prior rounds of folding. Because no a priori knowledge is used, the authors can identify kinetically significant non-native interactions and intermediates, sometimes generated by only 2 mutations, while the evolution of contact matrixes is often consistent with expts. Moreover, structure prediction improves substantially by incorporating information from prior rounds. The success of this simple, homol.-free approach affirms the validity of the description of the primary determinants of folding pathways and structure, and the effectiveness of SS as a search strategy.
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420Adhikari, A. N.; Freed, K. F.; Sosnick, T. R. Simplified protein models: predicting folding pathways and structure using amino acid sequences Phys. Rev. Lett. 2013, 111, 028103 DOI: 10.1103/PhysRevLett.111.028103Google ScholarThere is no corresponding record for this reference.
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421Rodrigues, J. P.; Levitt, M.; Chopra, G. KoBaMIN: a knowledge-based minimization web server for protein structure refinement Nucleic Acids Res. 2012, 40, W323– 328 DOI: 10.1093/nar/gks376Google Scholar421https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjtVCru7Y%253D&md5=a55ebd0571d0f1c268d9e6016aaa0ccfKoBaMIN: a knowledge-based minimization web server for protein structure refinementRodrigues, Joao P. G. L. M.; Levitt, Michael; Chopra, GauravNucleic Acids Research (2012), 40 (W1), W323-W328CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The KoBaMIN web server provides an online interface to a simple, consistent and computationally efficient protein structure refinement protocol based on minimization of a knowledge-based potential of mean force. The server can be used to refine either a single protein structure or an ensemble of proteins starting from their unrefined coordinates in PDB format. The refinement method is particularly fast and accurate due to the underlying knowledge-based potential derived from structures deposited in the PDB; as such, the energy function implicitly includes the effects of solvent and the crystal environment. Our server allows for an optional but recommended step that optimizes stereochem. using the MESHI software. The KoBaMIN server also allows comparison of the refined structures with a provided ref. structure to assess the changes brought about by the refinement protocol. The performance of KoBaMIN has been benchmarked widely on a large set of decoys, all models generated at the seventh worldwide expts. on crit. assessment of techniques for protein structure prediction (CASP7) and it was also shown to produce top-ranking predictions in the refinement category at both CASP8 and CASP9, yielding consistently good results across a broad range of model quality values. The web server is fully functional and freely available at http://csb.stanford.edu/kobamin.
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422Zhou, H. X.; Rivas, G.; Minton, A. P. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences Annu. Rev. Biophys. 2008, 37, 375– 397 DOI: 10.1146/annurev.biophys.37.032807.125817Google Scholar422https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnsVGlurg%253D&md5=2e1fe7edb342b273b68868b02a8d137bMacromolecular crowding and confinement: Biochemical, biophysical, and potential physiological consequencesZhou, Huan-Xiang; Rivas, German; Minton, Allen P.Annual Review of Biophysics (2008), 37 (), 375-397CODEN: ARBNCV ISSN:. (Annual Reviews Inc.)A review. Expected and obsd. effects of vol. exclusion on the free energy of rigid and flexible macromols. in crowded and confined systems, and consequent effects of crowding and confinement on macromol. reaction rates and equil. are summarized. Findings from relevant theor./simulation and exptl. literature published from 2004 onward are reviewed. Addnl. complexity arising from the heterogeneity of local environments in biol. media, and the presence of nonspecific interactions between macromols. over and above steric repulsion, are discussed. Theor. and exptl. approaches to the characterization of crowding- and confinement-induced effects in systems approaching the complexity of living organisms are suggested.
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423Feig, M.; Sugita, Y. Reaching new levels of realism in modeling biological macromolecules in cellular environments J. Mol. Graphics Modell. 2013, 45, 144– 156 DOI: 10.1016/j.jmgm.2013.08.017Google Scholar423https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1Wksr%252FE&md5=c56d5feaa6f0d3fde059ee3a3998a4e6Reaching new levels of realism in modeling biological macromolecules in cellular environmentsFeig, Michael; Sugita, YujiJournal of Molecular Graphics & Modelling (2013), 45 (), 144-156CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)A review. An increasing no. of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are addnl. challenges in integrating different aspects ranging from questions about biomol. stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomols. in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomols., as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.
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424Derreumaux, P. Coarse-grained models for protein folding and aggregation Methods Mol. Biol. 2013, 924, 585– 600 DOI: 10.1007/978-1-62703-017-5_22Google Scholar424https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXit1Gnurc%253D&md5=359fa9262e07fe6c98105e484be8e4acCoarse-grained models for protein folding and aggregationDerreumaux, PhilippeMethods in Molecular Biology (New York, NY, United States) (2013), 924 (Biomolecular Simulations), 585-600CODEN: MMBIED; ISSN:1064-3745. (Springer)A review. Coarse-grained models for protein folding and aggregation are used to explore large dimension scales and timescales that are inaccessible to all-atom models in explicit aq. soln. Combined with enhanced configuration search methods, these simplified models with various levels of granularity offer the possibility to det. equil. structures, compare folding kinetics and thermodn. with expts. for single proteins and understand the dynamic assembly of amyloid proteins leading to neurodegenerative diseases. I shall describe recent progress in developing such models, and discuss their potentials and limitations in probing the folding and misfolding of proteins with computer simulations.
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425Borgia, M. B.; Borgia, A.; Best, R. B.; Steward, A.; Nettels, D.; Wunderlich, B.; Schuler, B.; Clarke, J. Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins Nature 2011, 474, 662– 665 DOI: 10.1038/nature10099Google Scholar425https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmslSrs7w%253D&md5=18747a3a3792b08e7004677b6be7d29bSingle-molecule fluorescence reveals sequence-specific misfolding in multidomain proteinsBorgia, Madeleine B.; Borgia, Alessandro; Best, Robert B.; Steward, Annette; Nettels, Daniel; Wunderlich, Bengt; Schuler, Benjamin; Clarke, JaneNature (London, United Kingdom) (2011), 474 (7353), 662-665CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)A large range of debilitating medical conditions is linked to protein misfolding, which may compete with productive folding particularly in proteins contg. multiple domains. Of the eukaryotic proteome, 75% consists of multidomain proteins; yet it is not understood how interdomain misfolding is avoided. It has been proposed that maintaining low sequence identity between covalently linked domains is a mechanism to avoid misfolding. Here, the authors used single-mol. FRET to detect and quantify rare misfolding events in tandem Ig domains from the I band of titin under native conditions. About 5.5% of mols. with identical domains misfolded during refolding in vitro and formed an unexpectedly stable state with an unfolding half-time of several days. Tandem arrays of Ig-like domains in humans showed significantly lower sequence identity between neighboring domains than between non-adjacent domains. In particular, the sequence identity of neighboring domains was found to be preferentially below 40%. The authors obsd. no misfolding for a tandem of naturally neighboring domains with low sequence identity (24%), whereas misfolding occurred between domains that were 42% identical. Coarse-grained mol. simulations predicted the formation of domain-swapped structures that were in excellent agreement with the obsd. transfer efficiency of the misfolded species. The authors infer that the interactions underlying misfolding are very specific and result in a sequence-specific domain-swapping mechanism. Diversifying the sequence between neighboring domains seems to be a successful evolutionary strategy to avoid misfolding in multidomain proteins.
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426Morriss-Andrews, A.; Shea, J. E. Computational studies of protein aggregation: methods and applications Annu. Rev. Phys. Chem. 2015, 66, 643– 666 DOI: 10.1146/annurev-physchem-040513-103738Google Scholar426https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnvFartL4%253D&md5=8f49c01fff7cdd66562ee8820ff9a48fComputational studies of protein aggregation: methods and applicationsMorriss-Andrews, Alex; Shea, Joan-EmmaAnnual Review of Physical Chemistry (2015), 66 (), 643-666CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews)A review. Protein aggregation involves the self-assembly of normally sol. proteins into large supramol. assemblies. The typical end product of aggregation is the amyloid fibril, an extended structure enriched in β-sheet content. The aggregation process has been linked to a no. of diseases, most notably Alzheimer's disease, but fibril formation can also play a functional role in certain organisms. This review focuses on theor. studies of the process of fibril formation, with an emphasis on the computational models and methods commonly used to tackle this problem.
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427Shental-Bechor, D.; Smith, M. T.; Mackenzie, D.; Broom, A.; Marcovitz, A.; Ghashut, F.; Go, C.; Bralha, F.; Meiering, E. M.; Levy, Y. Nonnative interactions regulate folding and switching of myristoylated protein Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 17839– 17844 DOI: 10.1073/pnas.1201803109Google Scholar427https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhsl2ktbzJ&md5=4b8ca8d0e384730e60914b2a1a1b2fbaNonnative interactions regulate folding and switching of myristoylated proteinShental-Bechor, Dalit; Smith, Martin T. J.; MacKenzie, Duncan; Broom, Aron; Marcovitz, Amir; Ghashut, Fadila; Go, Chris; Bralha, Fernando; Meiering, Elizabeth M.; Levy, YaakovProceedings of the National Academy of Sciences of the United States of America (2012), 109 (44), 17839-17844, S17839/1-S17839/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The authors present an integrated exptl. and computational study of the mol. mechanisms by which myristoylation affects protein folding and function, which has been little characterized to date. Myristoylation, the covalent linkage of a hydrophobic C14 fatty acyl chain to the N-terminal Gly residue in a protein, is a common modification that plays a crit. role in vital regulated cellular processes by undergoing reversible energetic and conformational switching. Coarse-grained folding simulations for the model pH-dependent actin- and membrane-binding protein hisactophilin (I) revealed that non-native hydrophobic interactions of the myristoyl group with the protein as well as non-native electrostatic interactions had a pronounced effect on folding rates and thermodn. stability. Folding measurements for hydrophobic residue mutations of I and atomistic simulations indicated that the non-native interactions of the myristoyl group in the folding transition state were nonspecific and robust, and thus smoothed the energy landscape for folding. In contrast, myristoyl interactions in the native state were highly specific and tuned for sensitive control of switching functionality. Simulations and amide H-exchange measurements provided evidence for increases as well as decreases in stability localized on one side of the myristoyl binding pocket in the protein, implicating strain and altered dynamics in switching. The effects of folding and function arising from myristoylation were profoundly different from the effects of other post-translational modifications.
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428Lu, D.; Yang, C.; Liu, Z. How hydrophobicity and the glycosylation site of glycans affect protein folding and stability: a molecular dynamics simulation J. Phys. Chem. B 2012, 116, 390– 400 DOI: 10.1021/jp203926rGoogle Scholar428https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsFansb7E&md5=838b7a9371ce78243d32176fb0d3876eHow hydrophobicity and the glycosylation site of glycans affect protein folding and stability: A molecular dynamics simulationLu, Diannan; Yang, Cheng; Liu, ZhengJournal of Physical Chemistry B (2012), 116 (1), 390-400CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Glycosylation is one of the most common post-translational modifications in the biosynthesis of protein, but its effect on the protein conformational transitions underpinning folding and stabilization is poorly understood. Here, the authors present a coarse-grained off-lattice 46-β barrel model protein glycosylated by glycans with different hydrophobicity and glycosylation sites to examine the effect of glycans on protein folding and stabilization using a Langevin dynamics simulation, in which an H term was proposed as the index of the hydrophobicity of glycan. Compared with its native counterpart, introducing glycans of suitable hydrophobicity (0.1 < H < 0.4) at flexible peptide residues of this model protein not only facilitated folding of the protein but also increased its conformation stability significantly. On the contrary, when glycans were introduced at the restricted peptide residues of the protein, only those hydrophilic (H = 0) or very weak hydrophobic (H < 0.2) ones contributed slightly to protein stability but hindered protein folding due to increased free energy barriers. The glycosylated protein retained the 2-step folding mechanism in terms of hydrophobic collapse and structural rearrangement. Glycan chains located in a suitable site with an appropriate hydrophobicity facilitated both collapse and rearrangement, whereas others, although accelerating collapse, hindered rearrangement. In addn. to entropy effects, i.e., narrowing the space of the conformations of the unfolded state, the presence of glycans with suitable hydrophobicity at suitable glycosylation site strengthened the folded state via hydrophobic interaction, i.e., the enthalpy effect. The simulations showed both the stabilization and the destabilization effects of glycosylation, as exptl. reported in the literature, and provided mol. insight into glycosylated proteins. The understanding of the effects of glycans with different hydrophobicities on the folding and stability of proteins, as attempted by the present work, is helpful not only to explain the stabilization and destabilization effect of real glycoproteins but also to design protein-polymer conjugates for biotechnol. purposes.
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429Chan, H. S.; Zhang, Z.; Wallin, S.; Liu, Z. Cooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained models Annu. Rev. Phys. Chem. 2011, 62, 301– 326 DOI: 10.1146/annurev-physchem-032210-103405Google Scholar429https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVWmt74%253D&md5=f32eb4a2142f630a149077d93afffb4aCooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained modelsChan, Hue Sun; Zhang, Zhuqing; Wallin, Stefan; Liu, ZhirongAnnual Review of Physical Chemistry (2011), 62 (), 301-326CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Coarse-grained, self-contained polymer models are powerful tools in the study of protein folding. They are also essential to assess predictions from less rigorous theor. approaches that lack an explicit-chain representation. Here we review advances in coarse-grained modeling of cooperative protein folding, noting in particular that the Levinthal paradox was raised in response to the exptl. discovery of two-state-like folding in the late 1960s, rather than to the problem of conformational search per se. Comparisons between theory and expt. indicate a prominent role of desolvation barriers in cooperative folding, which likely emerges generally from a coupling between local conformational preferences and nonlocal packing interactions. Many of these principles have been elucidated by native-centric models, wherein nonnative interactions may be treated perturbatively. We discuss these developments as well as recent applications of coarse-grained chain modeling to knotted proteins and to intrinsically disordered proteins.
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430Qin, M.; Wang, W.; Thirumalai, D. Protein folding guides disulfide bond formation Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 11241– 11246 DOI: 10.1073/pnas.1503909112Google Scholar430https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlyjt73M&md5=bc556b6cf6d4142ac1ef749ddf7836f9Protein folding guides disulfide bond formationQin, Meng; Wang, Wei; Thirumalai, D.Proceedings of the National Academy of Sciences of the United States of America (2015), 112 (36), 11241-11246CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The Anfinsen principle that the protein sequence uniquely dets. its structure is based on expts. on oxidative refolding of a protein with disulfide bonds. The problem of how protein folding drives disulfide bond formation is poorly understood. Here, we have solved this long-standing problem by creating a general method for implementing the chem. of disulfide bond formation and rupture in coarse-grained mol. simulations. As a case study, we investigate the oxidative folding of bovine pancreatic trypsin inhibitor (BPTI). After confirming the exptl. findings that the multiple routes to the folded state contain a network of states dominated by native disulfides, we show that the entropically unfavorable native single disulfide [14-38] between Cys14 and Cys38 forms only after polypeptide chain collapse and complete structuring of the central core of the protein contg. an antiparallel β-sheet. Subsequent assembly, resulting in native two-disulfide bonds and the folded state, involves substantial unfolding of the protein and transient population of nonnative structures. The rate of [14-38] formation increases as the β-sheet stability increases. The flux to the native state, through a network of kinetically connected native-like intermediates, changes dramatically by altering the redox conditions. Disulfide bond formation between Cys residues not present in the native state are relevant only on the time scale of collapse of BPTI. The finding that formation of specific collapsed native-like structures guides efficient folding is applicable to a broad class of single-domain proteins, including enzyme-catalyzed disulfide proteins.
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431Jewett, A. I.; Shea, J. E. Reconciling theories of chaperonin accelerated folding with experimental evidence Cell. Mol. Life Sci. 2010, 67, 255– 276 DOI: 10.1007/s00018-009-0164-6Google Scholar431https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXis1ejsQ%253D%253D&md5=6afcd22f8a0e21189a778281cb7e3dafReconciling theories of chaperonin accelerated folding with experimental evidenceJewett, Andrew I.; Shea, Joan-EmmaCellular and Molecular Life Sciences (2010), 67 (2), 255-276CODEN: CMLSFI; ISSN:1420-682X. (Birkhaeuser Verlag)A review. For the last 20 yr, a large vol. of exptl. and theor. work has been undertaken to understand how chaperones like GroEL can assist protein folding in the cell. The most accepted explanation appears to be the simplest: GroEL, like most other chaperones, helps proteins fold by preventing aggregation. However, evidence suggests that, under some conditions, GroEL can play a more active role by accelerating protein folding. A large no. of models have been proposed to explain how this could occur. Focused expts. have been designed and carried out using different protein substrates with conclusions that support many different mechanisms. Here, the authors attempt to see the forest through the trees. The authors review all suggested mechanisms for chaperonin-mediated folding and weigh the plausibility of each in light of what is now known about the most stringent, essential, GroEL-dependent protein substrates.
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432Lucent, D.; England, J.; Pande, V. Inside the chaperonin toolbox: theoretical and computational models for chaperonin mechanism Phys. Biol. 2009, 6, 015003 DOI: 10.1088/1478-3975/6/1/015003Google ScholarThere is no corresponding record for this reference.
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433Stan, G.; Lorimer, G. H.; Thirumalai, D.; Brooks, B. R. Coupling between allosteric transitions in GroEL and assisted folding of a substrate protein Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 8803– 8808 DOI: 10.1073/pnas.0700607104Google ScholarThere is no corresponding record for this reference.
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434Orozco, M.; Orellana, L.; Hospital, A.; Naganathan, A. N.; Emperador, A.; Carrillo, O.; Gelpi, J. L. Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomings Adv. Protein Chem. Struct. Biol. 2011, 85, 183– 215 DOI: 10.1016/B978-0-12-386485-7.00005-3Google Scholar434https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVKhs7bN&md5=a6e041025028248e487fd3f29c6a2466Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomingsOrozco, Modesto; Orellana, Laura; Hospital, Adam; Naganathan, Athi N.; Emperador, Agusti; Carrillo, Oliver; Gelpi, J. L.Advances in Protein Chemistry and Structural Biology (2011), 85 (Computational Chemistry Methods in Structural Biology), 183-215CODEN: APCSG7; ISSN:1876-1623. (Elsevier Ltd.)A review. Flexibility is the key magnitude to understand the variety of functions of proteins. Unfortunately, its exptl. study is quite difficult, and in fact, most exptl. procedures are designed to reduce flexibility and allow a better definition of the structure. Theor. approaches have become then the alternative but face serious timescale problems, since many biol. relevant deformation movements happen in a timescale that is far beyond the possibility of current atomistic models. In this complex scenario, coarse-grained simulation methods have emerged as a powerful and inexpensive alternative. Along this chapter, we will review these coarse-grained methods, and explain their phys. foundations and their range of applicability.
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435Piana, S.; Lindorff-Larsen, K.; Shaw, D. E. How Robust Are Protein Folding Simulations with Respect to Force Field Parameterization? Biophys. J. 2011, 100, L47– L49 DOI: 10.1016/j.bpj.2011.03.051Google Scholar435https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXlsFagsr8%253D&md5=e861a2c068b5044251664c17552da5b8How Robust Are Protein Folding Simulations with Respect to Force Field Parameterization?Piana, Stefano; Lindorff-Larsen, Kresten; Shaw, David E.Biophysical Journal (2011), 100 (9), L47-L49CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Mol. dynamics simulations hold the promise of providing an at.-level description of protein folding that cannot easily be obtained from expts. Here, we examine the extent to which the mol. mechanics force field used in such simulations might influence the obsd. folding pathways. To that end, we performed equil. simulations of a fast-folding variant of the villin headpiece using four different force fields. In each simulation, we obsd. a large no. of transitions between the unfolded and folded states, and in all four cases, both the rate of folding and the structure of the native state were in good agreement with expts. We found, however, that the folding mechanism and the properties of the unfolded state depend substantially on the choice of force field. We thus conclude that although it is important to match a single, exptl. detd. structure and folding rate, this does not ensure that a given simulation will provide a unique and correct description of the full free-energy surface and the mechanism of folding.
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436Martin-Garcia, F.; Papaleo, E.; Gomez-Puertas, P.; Boomsma, W.; Lindorff-Larsen, K. Comparing Molecular Dynamics Force Fields in the Essential Subspace. PLoS One 2015, 10, e0121114 DOI: 10.1371/journal.pone.0121114Google ScholarThere is no corresponding record for this reference.
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437Palazzesi, F.; Prakash, M. K.; Bonomi, M.; Barducci, A. Accuracy of current all-atom force-fields in modeling protein disordered states J. Chem. Theory Comput. 2015, 11, 2– 7 DOI: 10.1021/ct500718sGoogle Scholar437https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFeit7bO&md5=997c50dda2779cd92286484bd4d3b951Accuracy of Current All-Atom Force-Fields in Modeling Protein Disordered StatesPalazzesi, Ferruccio; Prakash, Meher K.; Bonomi, Massimiliano; Barducci, AlessandroJournal of Chemical Theory and Computation (2015), 11 (1), 2-7CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. Dynamics (MD) plays a fundamental role in characterizing protein disordered states that are emerging as crucial actors in many biol. processes. Here the authors assess the accuracy of three current force-fields in modeling disordered peptides by combining enhanced-sampling MD simulations with NMR data. These force-fields generate significantly different conformational ensembles, and AMBER03w provides the best agreement with expts., which is further improved by adding the ILDN corrections.
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438Rueda, M.; Ferrer-Costa, C.; Meyer, T.; Perez, A.; Camps, J.; Hospital, A.; Gelpi, J. L.; Orozco, M. A consensus view of protein dynamics Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 796– 801 DOI: 10.1073/pnas.0605534104Google Scholar438https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtVegsbY%253D&md5=13f810bed01cd1a3f40f21268fe6a75bA consensus view of protein dynamicsRueda, Manuel; Ferrer-Costa, Carles; Meyer, Tim; Perez, Alberto; Camps, Jordi; Hospital, Adam; Gelpi, Josep Lluis; Orozco, ModestoProceedings of the National Academy of Sciences of the United States of America (2007), 104 (3), 796-801CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The dynamics of proteins in aq. soln. has been investigated through a massive approach based on "state of the art" mol. dynamics simulations performed for all protein metafolds using the four most popular force fields (OPLS, CHARMM, AMBER, and GROMOS). A detailed anal. of the massive database of trajectories (>1.5 terabytes of data obtained using ≈50 years of CPU) allowed us to obtain a robust-consensus picture of protein dynamics in aq. soln.
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439Emperador, A.; Carrillo, O.; Rueda, M.; Orozco, M. Exploring the suitability of coarse-grained techniques for the representation of protein dynamics Biophys. J. 2008, 95, 2127– 2138 DOI: 10.1529/biophysj.107.119115Google ScholarThere is no corresponding record for this reference.
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440Emperador, A.; Meyer, T.; Orozco, M. United-Atom Discrete Molecular Dynamics of Proteins Using Physics-Based Potentials J. Chem. Theory Comput. 2008, 4, 2001– 2010 DOI: 10.1021/ct8003832Google Scholar440https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlGrsrnI&md5=d242feabd72c9be192436614ff2b1cc8United-Atom Discrete Molecular Dynamics of Proteins Using Physics-Based PotentialsEmperador, Agusti; Meyer, Tim; Orozco, ModestoJournal of Chemical Theory and Computation (2008), 4 (12), 2001-2010CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present a method for the efficient simulation of the equil. dynamics of proteins based on the well established discrete mol. dynamics algorithm, which avoids integration of Newton equations of motion at short time steps, allowing then the derivation of very large trajectories for proteins with a reduced computational cost. In the presented implementation we used an all heavy-atoms description of proteins, with simple potentials describing the conformational region around the exptl. structure based on local phys. interactions (covalent structure, hydrogen bonds, hydrophobic contacts, solvation, steric hindrance, and bulk dispersion interactions). The method shows a good ability to describe the flexibility of 33 diverse proteins in water as detd. by atomistic mol. dynamics simulation and can be useful for massive simulation of proteins in crowded environments or for refinement of protein structure in large complexes.
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441Bowman, G. R. Accurately modeling nanosecond protein dynamics requires at least microseconds of simulation J. Comput. Chem. 2016, 37, 558– 566 DOI: 10.1002/jcc.23973Google Scholar441https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXpvFWnt7s%253D&md5=658f38891f310f844edc4cd5377eb453Accurately modeling nanosecond protein dynamics requires at least microseconds of simulationBowman, Gregory R.Journal of Computational Chemistry (2016), 37 (6), 558-566CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Advances in hardware and algorithms have greatly extended the timescales accessible to mol. simulation. This article assesses whether such long timescale simulations improve our ability to calc. order parameters that describe conformational heterogeneity on ps-ns timescales or if force fields are now a limiting factor. Order parameters from expt. are compared with order parameters calcd. in three different ways from simulations ranging from 10 ns to 100 μs in length. Importantly, bootstrapping is employed to assess the variability in results for each simulation length. The results of 10-100 ns timescale simulations are highly variable, possibly explaining the variation in levels of agreement between simulation and expt. in published works examg. different proteins. Fortunately, microsecond timescale simulations improve both the accuracy and precision of calcd. order parameters, at least so long as the full exponential fit or truncated av. approxn. is used instead of the common long-time limit approxn. The improved precision of these long timescale simulations allows a statistically sound comparison of a no. of modern force fields, such as Amber03, Amber99sb-ILDN, and Charmm27. While there is some variation between these force fields, they generally give very similar results for sufficiently long simulations. The fact that so much simulation is required to precisely capture ps-ns timescale processes suggests that extremely extensive simulations are required for slower processes. Advanced sampling techniques could aid greatly, however, such methods will need to maintain accurate kinetics if they are to be of value for calcg. dynamical properties like order parameters. © 2015 Wiley Periodicals, Inc.
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442Bahar, I.; Rader, A. J. Coarse-grained normal mode analysis in structural biology Curr. Opin. Struct. Biol. 2005, 15, 586– 592 DOI: 10.1016/j.sbi.2005.08.007Google Scholar442https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhtVKjsLzE&md5=2bb5bbf564b14a0977452a28e28b8374Coarse-grained normal mode analysis in structural biologyBahar, Ivet; Rader, A. J.Current Opinion in Structural Biology (2005), 15 (5), 586-592CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The realization that exptl. obsd. functional motions of proteins can be predicted by coarse-grained normal mode anal. has renewed interest in applications to structural biol. Notable applications include the prediction of biol. relevant motions of proteins and supramol. structures driven by their structure-encoded collective dynamics; the refinement of low-resoln. structures, including those detd. by cryo-electron microscopy; and the identification of conserved dynamic patterns and mech. key regions within protein families. Addnl., hybrid methods that couple at. simulations with deformations derived from coarse-grained normal mode anal. are able to sample collective motions beyond the range of conventional mol. dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.
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443Ma, J. Usefulness and limitations of normal mode analysis in modeling dynamics of biomolecular complexes Structure 2005, 13, 373– 380 DOI: 10.1016/j.str.2005.02.002Google Scholar443https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXit1Chsbs%253D&md5=820348ab7b6039233f65129dcbf67db5Usefulness and Limitations of Normal Mode Analysis in Modeling Dynamics of Biomolecular ComplexesMa, JianpengStructure (Cambridge, MA, United States) (2005), 13 (3), 373-380CODEN: STRUE6; ISSN:0969-2126. (Cell Press)A review. Various types of large-amplitude mol. deformation are ubiquitously involved in the functions of biol. macromols., esp. supramol. complexes. They can be very effectively analyzed by normal mode anal. with well-established procedures. However, despite its enormous success in numerous applications, certain issues related to the applications of normal mode anal. require further discussion. In this review, the author addresses some common issues so as to raise the awareness of the usefulness and limitations of the method in the general community of structural biol.
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444Lexa, K. W.; Carlson, H. A. Full protein flexibility is essential for proper hot-spot mapping J. Am. Chem. Soc. 2011, 133, 200– 202 DOI: 10.1021/ja1079332Google Scholar444https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFKjtbbJ&md5=e534a799461ee66ddf75c6a0571ca983Full Protein Flexibility is Essential for Proper Hot-Spot MappingLexa, Katrina W.; Carlson, Heather A.Journal of the American Chemical Society (2011), 133 (2), 200-202CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)A traditional technique for structure-based drug design (SBDD) is mapping of protein surfaces with probe mols. to identify "hot spots" where key functional groups can best complement the receptor. Common methods, such as minimization of probes or calcn. of grids, use a fixed protein structure in the gas phase, ignoring both protein flexibility and proper competition between the probes and water. As a result, the potential surface is quite rugged, and many spurious local min. are identified. In this work, the authors compared rigid and fully flexible proteins in mixed-solvent mol. dynamics, which allows for flexibility and full solvent effects. The authors were surprised to find that the large no. of local min. are still found when a protein's conformational sampling is restricted; the dynamic averaging of probes and competition with water do not smooth the potential surface as one might expect. Only when a protein is allowed to be fully flexible in the simulation are the proper min. located and the spurious ones eliminated. The authors' results indicate that inclusion of full protein flexibility is crit. to accurate hot-spot mapping for SBDD.
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445Antunes, D. A.; Devaurs, D.; Kavraki, L. E. Understanding the challenges of protein flexibility in drug design Expert Opin. Drug Discovery 2015, 10, 1301– 1313 DOI: 10.1517/17460441.2015.1094458Google Scholar445https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFOmt7fL&md5=20d2e716785ecac65a223c7954ef0b16Understanding the challenges of protein flexibility in drug designAntunes, Dinler A.; Devaurs, Didier; Kavraki, Lydia E.Expert Opinion on Drug Discovery (2015), 10 (12), 1301-1313CODEN: EODDBX; ISSN:1746-0441. (Taylor & Francis Ltd.)Protein-ligand interactions play key roles in various metabolic pathways, and the proteins involved in these interactions represent major targets for drug discovery. Mol. docking is widely used to predict the structure of protein-ligand complexes, and protein flexibility stands out as one of the most important and challenging issues for binding mode prediction. Various docking methods accounting for protein flexibility have been proposed, tackling problems of ever-increasing dimensionality. This paper presents an overview of conformational sampling methods treating target flexibility during mol. docking. Special attention is given to approaches considering full protein flexibility. Contrary to what is frequently done, this review does not rely on classical biomol. recognition models to classify existing docking methods. Instead, it applies algorithmic considerations, focusing on the level of flexibility accounted for. This review also discusses the diversity of docking applications, from virtual screening (VS) of small drug-like compds. to geometry prediction (GP) of protein-peptide complexes. Considering the diversity of docking methods presented here, deciding which one is the best at treating protein flexibility depends on the system under study and the research application. In VS expts., ensemble docking can be used to implicitly account for large-scale conformational changes, and selective docking can addnl. consider local binding-site rearrangements. In other cases, on-the-fly exploration of the whole protein-ligand complex might be needed for accurate GP of the binding mode. Among other things, future methods are expected to provide alternative binding modes, which will better reflect the dynamic nature of protein-ligand interactions.
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446Alvarez-Garcia, D.; Barril, X. Relationship between Protein Flexibility and Binding: Lessons for Structure-Based Drug Design J. Chem. Theory Comput. 2014, 10, 2608– 2614 DOI: 10.1021/ct500182zGoogle Scholar446https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotlWjtLs%253D&md5=53099fb844bc5037d5ed9689f74497b2Relationship between protein flexibility and binding: Lessons for structure-based drug designAlvarez-Garcia, Daniel; Barril, XavierJournal of Chemical Theory and Computation (2014), 10 (6), 2608-2614CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Conceptually, the simplistic lock and key model has been superseded by more realistic views of mol. recognition that take into account the intrinsic dynamics of biol. macromols. However, it is still common for structure-based drug discovery methods to represent the receptor as static structures. The practical advantages of this approxn., the notable success attained over the past few decades with such simple models, and the absence of clear guidelines for weighing the pros and cons of accounting for flexibility may prompt some investigators to stretch the rigid model beyond its scope. Here, the authors investigated the relation between protein flexibility and binding free energy and present some useful hints for understanding when, and to what extent, flexibility should be considered. Using mol. dynamics simulations of hen egg-white lysozyme (HEWL) with explicit aq./org. solvent mixts. and a range of restraint conditions, the authors found out how artificially restricted mobility affects binding hot spots. Barring sampling errors or an inappropriate choice of ref. structure, it was found that decreased mobility (measured as B-factors) leads to artifactually more neg. binding free energies, but a logarithmic relation between both terms attenuates the errors. Consequently, ignoring flexibility may be an acceptable approxn. for intrinsically rigid regions (such as the active site of enzymes), but may lead to larger errors elsewhere. For the same reason, local conformational sampling yields very accurate predictions and, owing to its practical advantages, may be preferable to full conformational sampling for many applications.
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447Zhang, J.; Minary, P.; Levitt, M. Multiscale natural moves refine macromolecules using single-particle electron microscopy projection images Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 9845– 9850 DOI: 10.1073/pnas.1205945109Google Scholar447https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKksLjE&md5=301bdc0f581d6fd3d497e7150cf6b589Multiscale natural moves refine macromolecules using single-particle electron microscopy projection imagesZhang, Junjie; Minary, Peter; Levitt, MichaelProceedings of the National Academy of Sciences of the United States of America (2012), 109 (25), 9845-9850, S9845/1-S9845/10CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The method presented here refines mol. conformations directly against projections of single particles measured by electron microscopy. By optimizing the orientation of the projection at the same time as the conformation, the method is well-suited to two-dimensional class avs. from cryoelectron microscopy. Such direct use of two-dimensional images circumvents the need for a three-dimensional d. map, which may be difficult to reconstruct from projections due to structural heterogeneity or preferred orientations of the sample on the grid. Our refinement protocol exploits Natural Move Monte Carlo to model a macromol. as a small no. of segments connected by flexible loops, on multiple scales. After tests on artificial data from lysozyme, we applied the method to the Methonococcus maripaludis chaperonin. We successfully refined its conformation from a closed-state initial model to an open-state final model using just one class-averaged projection. We also used Natural Moves to iteratively refine against heterogeneous projection images of Methonococcus maripaludis chaperonin in a mix of open and closed states. Our results suggest a general method for electron microscopy refinement specially suited to macromols. with significant conformational flexibility. The algorithm is available in the program Methodologies for Optimization and Sampling In Computational Studies.
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448Consortium, T. U. UniProt: a hub for protein information. Nucleic Acids Res. 2014.Google ScholarThere is no corresponding record for this reference.
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449Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235– 242 DOI: 10.1093/nar/28.1.235Google Scholar449https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXhvVKjt7w%253D&md5=227fb393f754be2be375ab727bfd05dcThe Protein Data BankBerman, Helen M.; Westbrook, John; Feng, Zukang; Gilliland, Gary; Bhat, T. N.; Weissig, Helge; Shindyalov, Ilya N.; Bourne, Philip E.Nucleic Acids Research (2000), 28 (1), 235-242CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The Protein Data Bank (PDB; http://www.rcsb.org/pdb/)is the single worldwide archive of structural data of biol. macromols. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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450Rost, B. Twilight zone of protein sequence alignments Protein Eng., Des. Sel. 1999, 12, 85– 94 DOI: 10.1093/protein/12.2.85Google ScholarThere is no corresponding record for this reference.
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451Liang, S.; Zhang, C.; Zhou, Y. LEAP: highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains J. Comput. Chem. 2014, 35, 335– 341 DOI: 10.1002/jcc.23509Google Scholar451https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFSktLzM&md5=22748e325288183d4e908476f37fbd1bLEAP: Highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chainsLiang, Shide; Zhang, Chi; Zhou, YaoqiJournal of Computational Chemistry (2014), 35 (4), 335-341CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Prediction of protein loop conformations without any prior knowledge (ab initio prediction) is an unsolved problem. Its soln. will significantly impact protein homol. and template-based modeling as well as ab initio protein-structure prediction. Here, we developed a coarse-grained, optimized scoring function for initial sampling and ranking of loop decoys. The resulting decoys are then further optimized in backbone and side-chain conformations and ranked by all-atom energy scoring functions. The final integrated technique called loop prediction by energy-assisted protocol achieved a median value of 2.1 Å root mean square deviation (RMSD) for 325 12-residue test loops and 2.0 Å RMSD for 45 12-residue loops from crit. assessment of structure-prediction techniques (CASP) 10 target proteins with native core structures (backbone and side chains). If all side-chain conformations in protein cores were predicted in the absence of the target loop, loop-prediction accuracy only reduces slightly (0.2 Å difference in RMSD for 12-residue loops in the CASP target proteins). The accuracy obtained is about 1 Å RMSD or more improvement over other methods we tested. The executable file for a Linux system is freely available for academic users at http://sparks-lab.org.
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452Kmiecik, S.; Jamroz, M.; Kolinski, M. Structure prediction of the second extracellular loop in G-protein-coupled receptors Biophys. J. 2014, 106, 2408– 2416 DOI: 10.1016/j.bpj.2014.04.022Google Scholar452https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpvVahtbo%253D&md5=e1e5e9ff7ba2fbd508fa4b20a52139b0Structure prediction of the second extracellular loop in G-protein-coupled receptorsKmiecik, Sebastian; Jamroz, Michal; Kolinski, MichalBiophysical Journal (2014), 106 (11), 2408-2416CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to det. their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theor. predictions of ECL2 secondary structure and exptl. constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystd. GPCRs.
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453Goldfeld, D. A.; Zhu, K.; Beuming, T.; Friesner, R. A. Loop prediction for a GPCR homology model: algorithms and results Proteins: Struct., Funct., Genet. 2013, 81, 214– 228 DOI: 10.1002/prot.24178Google ScholarThere is no corresponding record for this reference.
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454Kolinski, M.; Filipek, S. Study of a structurally similar kappa opioid receptor agonist and antagonist pair by molecular dynamics simulations J. Mol. Model. 2010, 16, 1567– 1576 DOI: 10.1007/s00894-010-0678-8Google Scholar454https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1Kjt7rN&md5=1350be2c7b8c77acaebb26ea3676bca6Study of a structurally similar kappa opioid receptor agonist and antagonist pair by molecular dynamics simulationsKolinski, Michal; Filipek, SlawomirJournal of Molecular Modeling (2010), 16 (10), 1567-1576CODEN: JMMOFK; ISSN:0948-5023. (Springer GmbH)Among the structurally similar guanidinonaltrindole (GNTI) compds., 5'-GNTI is an antagonist while 6'-GNTI is an agonist of the κOR opioid receptor. To explore how a subtle alteration of the ligand structure influences the receptor activity, we investigated two concurrent processes: the final steps of ligand binding at the receptor binding site and the initial steps of receptor activation. To trace these early activation steps, the membranous part of the receptor was built on an inactive receptor template while the extracellular loops were built using the ab initio CABS method. We used the simulated annealing procedure for ligand docking and all-atom mol. dynamics simulations to det. the immediate changes in the structure of the ligand-receptor complex. The binding of an agonist, in contrast to an antagonist, induced the breakage of the "3-7 lock" between helixes TM3 and TM7. We also obsd. an action of the extended rotamer toggle switch which suggests that those two switches are interdependent.
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455Zhang, Y. Interplay of I-TASSER and QUARK for template-based and ab initio protein structure prediction in CASP10 Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 175– 187 DOI: 10.1002/prot.24341Google ScholarThere is no corresponding record for this reference.
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456Szilagyi, A.; Zhang, Y. Template-based structure modeling of protein-protein interactions Curr. Opin. Struct. Biol. 2014, 24, 10– 23 DOI: 10.1016/j.sbi.2013.11.005Google Scholar456https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtVamsr8%253D&md5=4d1e5e76bae7ce18946b7ddab49158f9Template-based structure modeling of protein-protein interactionsSzilagyi, Andras; Zhang, YangCurrent Opinion in Structural Biology (2014), 24 (), 10-23CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homol.-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Crit. improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput exptl. data. Nevertheless, bottlenecks exist due to the incompleteness of the protein-protein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement.
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457Iacoangeli, A.; Marcatili, P.; Tramontano, A. Exploiting homology information in nontemplate based prediction of protein structures J. Chem. Theory Comput. 2015, 11, 5045– 5051 DOI: 10.1021/acs.jctc.5b00371Google Scholar457https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsFWhs7nI&md5=6e331ada2054a825678e3a21a11cfc56Exploiting Homology Information in Nontemplate Based Prediction of Protein StructuresIacoangeli, Alfredo; Marcatili, Paolo; Tramontano, AnnaJournal of Chemical Theory and Computation (2015), 11 (10), 5045-5051CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors describe a novel strategy for exploring the conformational space of proteins and show that this leads to better models for proteins the structure of which is not amenable to template based methods. The authors' strategy is based on the assumption that the energy global min. of homologous proteins must correspond to similar conformations, while the precise profiles of their energy landscape, and consequently the positions of the local min., are likely to be different. In line with this hypothesis, the authors apply a replica exchange Monte Carlo simulation protocol that, rather than using different parameters for each parallel simulation, uses the sequences of homologous proteins. The authors' results are competitive with respect to alternative methods, including those producing the best model for each of the analyzed targets in the CASP10 (10th Crit. Assessment of techniques for protein Structure Prediction) expt. free modeling category.
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458Zhang, W.; Yang, J.; He, B.; Walker, S. E.; Zhang, H.; Govindarajoo, B.; Virtanen, J.; Xue, Z.; Shen, H. B.; Zhang, Y. Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11 Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24930Google ScholarThere is no corresponding record for this reference.
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459Xu, D.; Zhang, Y. Ab Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignment Sci. Rep. 2013, 3, 1895 DOI: 10.1038/srep01895Google Scholar459https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3snotVOntQ%253D%253D&md5=b735f3b8756f7f75c23137f4efa4cb7aAb Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignmentXu Dong; Zhang YangScientific reports (2013), 3 (), 1895 ISSN:.Genome-wide protein structure prediction and structure-based function annotation have been a long-term goal in molecular biology but not yet become possible due to difficulties in modeling distant-homology targets. We developed a hybrid pipeline combining ab initio folding and template-based modeling for genome-wide structure prediction applied to the Escherichia coli genome. The pipeline was tested on 43 known sequences, where QUARK-based ab initio folding simulation generated models with TM-score 17% higher than that by traditional comparative modeling methods. For 495 unknown hard sequences, 72 are predicted to have a correct fold (TM-score > 0.5) and 321 have a substantial portion of structure correctly modeled (TM-score > 0.35). 317 sequences can be reliably assigned to a SCOP fold family based on structural analogy to existing proteins in PDB. The presented results, as a case study of E. coli, represent promising progress towards genome-wide structure modeling and fold family assignment using state-of-the-art ab initio folding algorithms.
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460Thevenet, P.; Shen, Y.; Maupetit, J.; Guyon, F.; Derreumaux, P.; Tuffery, P. PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides Nucleic Acids Res. 2012, 40, W288– 293 DOI: 10.1093/nar/gks419Google Scholar460https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjtVCkurs%253D&md5=ba2fc12d7a8d5067fa975a085a98f244PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptidesThevenet, Pierre; Shen, Yimin; Maupetit, Julien; Guyon, Frederic; Derreumaux, Philippe; Tuffery, PierreNucleic Acids Research (2012), 40 (W1), W288-W293CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)In the context of the renewed interest of peptides as therapeutics, it is important to have an online resource for 3D structure prediction of peptides with well-defined structures in aq. soln. We present an updated version of PEP-FOLD allowing the treatment of both linear and disulfide bonded cyclic peptides with 9-36 amino acids. The server makes possible to define disulfide bonds and any residue-residue proximity under the guidance of the biologists. Using a benchmark of 34 cyclic peptides with one, two and three disulfide bonds, the best PEP-FOLD models deviate by an av. RMS of 2.75 Å from the full NMR structures. Using a benchmark of 37 linear peptides, PEP-FOLD locates lowest-energy conformations deviating by 3 Å RMS from the NMR rigid cores. The evolution of PEP-FOLD comes as a new online service to supersede the previous server. The server is available at: http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.
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461Thévenet, P.; Rey, J.; Moroy, G.; Tuffery, P. In Computational Peptidology; Zhou, P.; Huang, J., Eds.; Springer: New York, 2015; Vol. 1268.Google ScholarThere is no corresponding record for this reference.
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462Samudrala, R.; Xia, Y.; Huang, E.; Levitt, M. Ab initio protein structure prediction using a combined hierarchical approach Proteins: Struct., Funct., Genet. 1999, 37 (Suppl 3) 194– 198 DOI: 10.1002/(SICI)1097-0134(1999)37:3+<194::AID-PROT24>3.0.CO;2-FGoogle ScholarThere is no corresponding record for this reference.
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463Kolinski, A.; Skolnick, J. Monte Carlo simulations of protein folding. II. Application to protein A, ROP, and crambin Proteins: Struct., Funct., Genet. 1994, 18, 353– 366 DOI: 10.1002/prot.340180406Google Scholar463https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXktlSnsr8%253D&md5=07940835aa95056f96420f05052cd5a6Monte Carlo simulations of protein folding. II. Application to protein A, ROP, and CrambinKolinski, Andrzej; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1994), 18 (4), 353-66CODEN: PSFGEY; ISSN:0887-3585.The hierarchy of lattice Monte Carlo models is applied to the simulation of protein folding and the prediction of 3-dimensional structure. Using sequence information alone, 3 proteins have been successfully folded: the B domain of staphylococcal protein A, a 120 residue, monomeric version of ROP dimer, and crambin. Starting from a random expanded conformation, the model proteins fold along relatively well-defined folding pathways. These involve a collection of early intermediates, which are followed by the final (and rate-detg.) transition from compact intermediates closely resembling the molten globule state to the native-like state. The predicted structures are rather unique, with native-like packing of the side chains. The accuracy of the predicted native conformations is better than those obtained in previous folding simulations. The best fold of protein A have a coordinate rms of 2.25 Å from the native Cαs trace, and the best coordinate rms from crambin is 3.18 Å. For ROP monomer, the lowest coordinate rms from equiv. Cαs of ROP dimer is 3.65 Å. Thus, for two simple helical proteins and a small α/β protein, the ability to predict protein structure from sequence has been demonstrated.
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464Kolinski, A.; Skolnick, J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme Proteins: Struct., Funct., Genet. 1994, 18, 338– 352 DOI: 10.1002/prot.340180405Google Scholar464https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXktlSnsr4%253D&md5=2d1c1da84b7574a5b401686f3dfc26c4Monte Carlo simulations of protein folding. I. Lattice model and interaction schemeKolinski, Andrzej; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1994), 18 (4), 338-52CODEN: PSFGEY; ISSN:0887-3585.A new hierarchical method for the simulation of the protein folding process and the de novo prediction of protein three-dimensional structure is proposed. The reduced representation of the protein α-carbon backbone employs lattice discretizations of increasing geometrical resoln. and a single ball representation of side chain rotamers. In particular, coarser and finer lattice backbone descriptions are used. The coarser (finer) lattice represents Cα traces of native proteins with an accuracy of 1.0 (0.7) Å rms. Folding is simulated by means of very fast Monte Carlo lattice dynamics. The potential of mean force, predominantly of statistical origin, contains several novel terms that facilitate the cooperative assembly of secondary structure elements and the cooperative packing of the side chains. Particular contributions to the interaction scheme are discussed in detail.
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465Tai, C. H.; Bai, H.; Taylor, T. J.; Lee, B. Assessment of template-free modeling in CASP10 and ROLL Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 57– 83 DOI: 10.1002/prot.24470Google Scholar465https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFentLbP&md5=40ee48832f8e2baa18d63815e9511141Assessment of template-free modeling in CASP10 and ROLLTai, Chin-Hsien; Bai, Hongjun; Taylor, Todd J.; Lee, ByungkookProteins: Structure, Function, and Bioinformatics (2014), 82 (S2), 57-83CODEN: PSFBAF ISSN:. (Wiley-Blackwell)We present the assessment of predictions for Template-Free Modeling in CASP10 and a report on the first ROLL expt. wherein predictions are collected year round for review at the regular CASP season. Models were first clustered so that duplicated or very similar ones were grouped together and represented by one model in the cluster. The representatives were then compared with targets using GDT_TS, QCS, and three addnl. superposition-independent score functions newly developed for CASP10. For each target, the top 15 representatives by each score were pooled to form the Top15Union set. All models in this set were visually inspected by four of us independently using the new plugin, EvalScore, which we developed with the UCSF Chimera group. The best models were selected for each target after extensive debate among the four examiners. Groups were ranked by the no. of targets (hits) for which a group's model was selected as one of the best models. The Keasar group had most hits in both categories, with four of 19 FM and eight of 36 ROLL targets. The most successful prediction servers were QUARK from Zhang's group for FM category with three hits and Zhang-server for the ROLL category with seven hits. As obsd. in CASP9, many successful groups were not true "template-free" modelers but used remote templates and/or server models to obtain their winning models. The results of the first ROLL expt. were broadly similar to those of the CASP10 FM exercise. Proteins 2013. © 2013 Wiley Periodicals, Inc.
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466Kinch, L.; Yong Shi, S.; Cong, Q.; Cheng, H.; Liao, Y.; Grishin, N. V. CASP9 assessment of free modeling target predictions Proteins: Struct., Funct., Genet. 2011, 79 (Suppl 10) 59– 73 DOI: 10.1002/prot.23181Google ScholarThere is no corresponding record for this reference.
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467Ben-David, M.; Noivirt-Brik, O.; Paz, A.; Prilusky, J.; Sussman, J. L.; Levy, Y. Assessment of CASP8 structure predictions for template free targets Proteins: Struct., Funct., Genet. 2009, 77 (59) 50– 65 DOI: 10.1002/prot.22591Google ScholarThere is no corresponding record for this reference.
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468Xu, D.; Zhang, Y. Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field Proteins: Struct., Funct., Genet. 2012, 80, 1715– 1735 DOI: 10.1002/prot.24065Google Scholar468https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XlsFyitLY%253D&md5=756720149740253705d28afc82234207Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force fieldXu, Dong; Zhang, YangProteins: Structure, Function, and Bioinformatics (2012), 80 (7), 1715-1735CODEN: PSFBAF ISSN:. (Wiley-Blackwell)Ab initio protein folding is one of the major unsolved problems in computational biol. owing to the difficulties in force field design and conformational search. The authors developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1-20 residues where multiple fragment structures are retrieved at each position from unrelated exptl. structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A no. of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed. QUARK prediction procedure is depicted and tested on the structure modeling of 145 nonhomologous proteins. Although no global templates were used and all fragments from exptl. structures with template modeling score >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in one-third cases of short proteins up to 100 residues. In the ninth community-wide Crit. Assessment of protein Structure Prediction expt., QUARK server outperformed the second and third best servers by 18 and 47% based on the cumulative Z-score of global distance test-total scores in the FM category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress toward the soln. of the most important problem in the field. Proteins 2012; © 2012 Wiley Periodicals, Inc.
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469Moult, J.; Fidelis, K.; Kryshtafovych, A.; Schwede, T.; Tramontano, A. Critical assessment of methods of protein structure prediction (CASP)--round x Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 1– 6 DOI: 10.1002/prot.24452Google ScholarThere is no corresponding record for this reference.
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470Kinch, L. N.; Li, W.; Monastyrskyy, B.; Kryshtafovych, A.; Grishin, N. V. Evaluation of free modeling targets in CASP11 and ROLL Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24973Google ScholarThere is no corresponding record for this reference.
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471Kim, H.; Kihara, D. Protein structure prediction using residue- and fragment-environment potentials in CASP11 Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24920Google ScholarThere is no corresponding record for this reference.
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472Feig, M.; Mirjalili, V. Protein structure refinement via molecular-dynamics simulations: What works and what does not? Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24871Google ScholarThere is no corresponding record for this reference.
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473Berggard, T.; Linse, S.; James, P. Methods for the detection and analysis of protein-protein interactions Proteomics 2007, 7, 2833– 2842 DOI: 10.1002/pmic.200700131Google Scholar473https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2svpsVWksA%253D%253D&md5=7b359c9eaecb7b91b6c1aa3dc1807f4aMethods for the detection and analysis of protein-protein interactionsBerggard Tord; Linse Sara; James PeterProteomics (2007), 7 (16), 2833-42 ISSN:1615-9853.A large number of methods have been developed over the years to study protein-protein interactions. Many of these techniques are now available to the nonspecialist researcher thanks to new affordable instruments and/or resource centres. A typical protein-protein interaction study usually starts with an initial screen for novel binding partners. We start this review by describing three techniques that can be used for this purpose: (i) affinity-tagged proteins (ii) the two-hybrid system and (iii) some quantitative proteomic techniques that can be used in combination with, e.g., affinity chromatography and coimmunoprecipitation for screening of protein-protein interactions. We then describe some public protein-protein interaction databases that can be searched to identify previously reported interactions for a given bait protein. Four strategies for validation of protein-protein interactions are presented: confocal microscopy for intracellular colocalization of proteins, coimmunoprecipitation, surface plasmon resonance (SPR) and spectroscopic studies. Throughout the review we focus particularly on the advantages and limitations of each method.
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474Setny, P.; Bahadur, R. P.; Zacharias, M. Protein-DNA docking with a coarse-grained force field BMC Bioinf. 2012, 13, 228 DOI: 10.1186/1471-2105-13-228Google Scholar474https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpvFalsQ%253D%253D&md5=974e69804e1f5eb13ebae186f43b887dProtein-DNA docking with a coarse-grained force fieldSetny, Piotr; Bahadur, Ranjit Prasad; Zacharias, MartinBMC Bioinformatics (2012), 13 (), 228CODEN: BBMIC4; ISSN:1471-2105. (BioMed Central Ltd.)Background: Protein-DNA interactions are important for many cellular processes, however structural knowledge for a large fraction of known and putative complexes is still lacking. Computational docking methods aim at the prediction of complex architecture given detailed structures of its constituents. They are becoming an increasingly important tool in the field of macromol. assemblies, complementing particularly demanding protein-nucleic acids X ray crystallog. and providing means for the refinement and integration of low resoln. data coming from rapidly advancing methods such as cryoelectron microscopy. Results: We present a new coarse-grained force field suitable for protein-DNA docking. The force field is an extension of previously developed parameter sets for protein-RNA and protein-protein interactions. The docking is based on potential energy minimization in translational and orientational degrees of freedom of the binding partners. It allows for fast and efficient systematic search for native-like complex geometry without any prior knowledge regarding binding site location. Conclusions: We find that the force field gives very good results for bound docking. The quality of predictions in the case of unbound docking varies, depending on the level of structural deviation from bound geometries. We analyze the role of specific protein-DNA interactions on force field performance, both with respect to complex structure prediction, and the reprodn. of exptl. binding affinities. We find that such direct, specific interactions only partially contribute to protein-DNA recognition, indicating an important role of shape complementarity and sequence-dependent DNA internal energy, in line with the concept of indirect protein-DNA readout mechanism.
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475Uusitalo, J. J.; Ingolfsson, H. I.; Akhshi, P.; Tieleman, D. P.; Marrink, S. J. Martini Coarse-Grained Force Field: Extension to DNA J. Chem. Theory Comput. 2015, 11, 3932– 3945 DOI: 10.1021/acs.jctc.5b00286Google Scholar475https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFGiur7I&md5=f66edb14d055b00005a6bf140fbfc602Martini Coarse-Grained Force Field: Extension to DNAUusitalo, Jaakko J.; Ingolfsson, Helgi I.; Akhshi, Parisa; Tieleman, D. Peter; Marrink, Siewert J.Journal of Chemical Theory and Computation (2015), 11 (8), 3932-3945CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors systematically parameterized a coarse-grained (CG) model for DNA that is compatible with the Martini force field. The model maps each nucleotide into six to seven CG beads and is parameterized following the Martini philosophy. The CG nonbonded interactions are based on partitioning of the nucleobases between polar and nonpolar solvents as well as base-base potential of mean force calcns. The bonded interactions are fit to single-stranded DNA (ssDNA) atomistic simulations and an elastic network was used to retain double-stranded DNA (dsDNA) and other specific DNA conformations. The authors present the implementation of the Martini DNA model and demonstrate the properties of individual bases, ssDNA as well as dsDNA, and DNA-protein complexes. The model opens up large-scale simulations of DNA interacting with a wide range of other (bio)mols. that are available within the Martini framework.
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476Hori, N.; Takada, S. Coarse-Grained Structure-Based Model for RNA-Protein Complexes Developed by Fluctuation Matching J. Chem. Theory Comput. 2012, 8, 3384– 3394 DOI: 10.1021/ct300361jGoogle Scholar476https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtV2gtrzN&md5=39feafbb08d9681d6b532c2dbeba6a9eCoarse-Grained Structure-Based Model for RNA-Protein Complexes Developed by Fluctuation MatchingHori, Naoto; Takada, ShojiJournal of Chemical Theory and Computation (2012), 8 (9), 3384-3394CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)RNA and RNA-protein complexes have recently been intensively studied in expts., but the corresponding mol. simulation work is much less abundant, primarily due to its large system size and the long time scale involved. Here, to overcome these bottlenecks, the authors develop a coarse-grained (CG) structure-based simulation model for RNA and RNA-protein complexes and test it for several mol. systems. The CG model for RNA contains three particles per nucleotide, each for phosphate, sugar, and a base. Focusing on RNA mols. that fold to well-defined native structures, the authors employed a structure-based potential, which is similar to the Go-like potential successfully used in CG modeling of proteins. In addn., the authors tested three means to approx. electrostatic interactions. Many parameters involved in the CG potential were detd. via a multiscale method: the authors matched the native fluctuation of the CG model with that by all-atom simulations for 16 RNA mols. and 10 RNA-protein complexes, from which the authors derived a generic set of CG parameters. The derived parameters can reproduce native fluctuations well for four RNA and two RNA-protein complexes. For tRNA, the native fluctuation in soln. includes large-amplitude motions that reach conformations nearly corresponding to the hybrid state P/E and EF-Tu-bound state A/T seen in the complexes with ribosome. Finally, large-amplitude modes of ribosome are briefly described.
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477Setny, P.; Zacharias, M. A coarse-grained force field for Protein-RNA docking Nucleic Acids Res. 2011, 39, 9118– 9129 DOI: 10.1093/nar/gkr636Google Scholar477https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsFCisLnJ&md5=2ccae666029f2c4bc9e1046d9ce18db7A coarse-grained force field for Protein-RNA dockingSetny, Piotr; Zacharias, MartinNucleic Acids Research (2011), 39 (21), 9118-9129CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The awareness of important biol. role played by functional, non coding (nc) RNA has grown tremendously in recent years. To perform their tasks, ncRNA mols. typically unite with protein partners, forming ribonucleoprotein complexes. Structural insight into their architectures can be greatly supplemented by computational docking techniques, as they provide means for the integration and refinement of exptl. data that is often limited to fragments of larger assemblies or represents multiple levels of spatial resoln. Here, we present a coarse-grained force field for protein-RNA docking, implemented within the framework of the ATTRACT program. Complex structure prediction is based on energy minimization in rotational and translational degrees of freedom of binding partners, with possible extension to include structural flexibility. The coarse-grained representation allows for fast and efficient systematic docking search without any prior knowledge about complex geometry.
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478Negami, T.; Shimizu, K.; Terada, T. Coarse-Grained Molecular Dynamics Simulations of Protein-Ligand Binding J. Comput. Chem. 2014, 35, 1835– 1845 DOI: 10.1002/jcc.23693Google Scholar478https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFyqt7jE&md5=8b2fdf3912387ac20c2c32f8092a553aCoarse-grained molecular dynamics simulations of protein-ligand bindingNegami, Tatsuki; Shimizu, Kentaro; Terada, TohruJournal of Computational Chemistry (2014), 35 (25), 1835-1845CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse-grained mol. dynamics (CGMD) simulations with the MARTINI force field were performed to reproduce the protein-ligand binding processes. The authors chose two protein-ligand systems, the levansucrase-sugar (glucose or sucrose), and LinB-1,2-dichloroethane systems, as target systems that differ in terms of the size and shape of the ligand-binding pocket and the physicochem. properties of the pocket and the ligand. Spatial distributions of the Coarse-grained (CG) ligand mols. revealed potential ligand-binding sites on the protein surfaces other than the real ligand-binding sites. The ligands bound most strongly to the real ligand-binding sites. The binding and unbinding rate consts. obtained from the CGMD simulation of the levansucrase-sucrose system were ∼10 times greater than the exptl. values; this is mainly due to faster diffusion of the CG ligand in the CG water model. The authors could obtain dissocn. consts. close to the exptl. values for both systems. Anal. of the ligand fluxes demonstrated that the CG ligand mols. entered the ligand-binding pockets through specific pathways. The ligands tended to move through grooves on the protein surface. Thus, the CGMD simulations produced reasonable results for the two different systems overall and are useful for studying the protein-ligand binding processes.
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479Li, D.; Liu, M. S.; Ji, B.; Hwang, K.; Huang, Y. Coarse-grained molecular dynamics of ligands binding into protein: The case of HIV-1 protease inhibitors J. Chem. Phys. 2009, 130, 215102 DOI: 10.1063/1.3148022Google ScholarThere is no corresponding record for this reference.
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480Prasanna, X.; Chattopadhyay, A.; Sengupta, D. Cholesterol modulates the dimer interface of the beta(2)-adrenergic receptor via cholesterol occupancy sites Biophys. J. 2014, 106, 1290– 1300 DOI: 10.1016/j.bpj.2014.02.002Google Scholar480https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXks1Wntro%253D&md5=7e1fcfd905abd3f6cb3ab9182a006129Cholesterol Modulates the Dimer Interface of the β2-Adrenergic Receptor via Cholesterol Occupancy SitesPrasanna, Xavier; Chattopadhyay, Amitabha; Sengupta, DurbaBiophysical Journal (2014), 106 (6), 1290-1300CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The β2-adrenergic receptor is an important member of the G-protein-coupled receptor (GPCR) superfamily, whose stability and function are modulated by membrane cholesterol. The recent high-resoln. crystal structure of the β2-adrenergic receptor revealed the presence of possible cholesterol-binding sites in the receptor. However, the functional relevance of cholesterol binding to the receptor remains unexplored. The authors used MARTINI coarse-grained mol.-dynamics simulations to explore dimerization of the β2-adrenergic receptor in lipid bilayers contg. cholesterol. A novel (to the authors' knowledge) aspect of the authors' results is that receptor dimerization is modulated by membrane cholesterol. The authors show that cholesterol binds to transmembrane helix IV, and cholesterol occupancy at this site restricts its involvement at the dimer interface. With increasing cholesterol concn., an increased presence of transmembrane helixes I and II, but a reduced presence of transmembrane helix IV, is obsd. at the dimer interface. To the authors' knowledge, this study is one of the first to explore the correlation between cholesterol occupancy and GPCR organization. The authors' results indicate that dimer plasticity is relevant not just as an organizational principle but also as a subtle regulatory principle for GPCR function. The authors believe these results constitute an important step toward designing better drugs for GPCR dimer targets.
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481Zacharias, M. Combining coarse-grained nonbonded and atomistic bonded interactions for protein modeling Proteins: Struct., Funct., Genet. 2013, 81, 81– 92 DOI: 10.1002/prot.24164Google ScholarThere is no corresponding record for this reference.
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482Solernou, A.; Fernandez-Recio, J. pyDockCG: new coarse-grained potential for protein-protein docking J. Phys. Chem. B 2011, 115, 6032– 6039 DOI: 10.1021/jp112292bGoogle ScholarThere is no corresponding record for this reference.
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483de Vries, S. J.; Zacharias, M. ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM maps PLoS One 2012, 7, e49733 DOI: 10.1371/journal.pone.0049733Google Scholar483https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXksV2l&md5=1e5df4fa9d20ac1c6bcb7dde33fc2f54ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM mapsde Vries, Sjoerd J.; Zacharias, MartinPLoS One (2012), 7 (12), e49733CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)Many of the most important functions in the cell are carried out by proteins organized in large mol. machines. Cryo-electron microscopy (cryo-EM) is increasingly being used to obtain low resoln. d. maps of these large assemblies. A new method, ATTRACT-EM, for the computational assembly of mol. assemblies from their components has been developed. Based on concepts from the protein-protein docking field, it utilizes cryo-EM d. maps to assemble mol. subunits at near at. detail, starting from millions of initial subunit configurations. The search efficiency was further enhanced by recombining partial solns., the inclusion of symmetry information, and refinement using a mol. force field. The approach was tested on the GroES-GroEL system, using an exptl. cryo-EM map at 23.5 Å resoln., and on several smaller complexes. Inclusion of exptl. information on the symmetry of the systems and the application of a new gradient vector matching algorithm allowed the efficient identification of docked assemblies in close agreement with expt. Application to the GroES-GroEL complex resulted in a top ranked model with a deviation of 4.6 Å (and a 2.8 Å model within the top 10) from the GroES-GroEL crystal structure, a significant improvement over existing methods.
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484Periole, X.; Knepp, A. M.; Sakmar, T. P.; Marrink, S. J.; Huber, T. Structural determinants of the supramolecular organization of G protein-coupled receptors in bilayers J. Am. Chem. Soc. 2012, 134, 10959– 10965 DOI: 10.1021/ja303286eGoogle Scholar484https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xot1anurg%253D&md5=54e1d9387db3ea3debfad724d5db8a7aStructural Determinants of the Supramolecular Organization of G Protein-Coupled Receptors in BilayersPeriole, Xavier; Knepp, Adam M.; Sakmar, Thomas P.; Marrink, Siewert J.; Huber, ThomasJournal of the American Chemical Society (2012), 134 (26), 10959-10965CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The G protein-coupled receptor (GPCR) rhodopsin self-assembles into supramol. structures in native bilayers, but the structural determinants of receptor oligomerization are not known. We carried out multiple self-assembly coarse-grained mol. dynamics (CGMD) simulations of model membranes contg. up to 64 mols. of the visual receptor rhodopsin over time scales reaching 100 μs. The simulations show strong preferential interaction modes between receptors. Two primary modes of receptor-receptor interactions are consistent with umbrella sampling/potential of mean force (PMF) calcns. as a function of the distance between a pair of receptors. The preferential interfaces, involving helixes (H) 1/8, 4/5 and 5, present no energy barrier to forming a very stable receptor dimer. Most notably, the PMFs show that the preferred rhodopsin dimer exists in a tail-to-tail conformation, with the interface comprising transmembrane H1/H2 and amphipathic H8 at the extracellular and cytoplasmic surfaces, resp. This dimer orientation is in line with earlier electron microscopy, x-ray, and crosslinking expts. of rhodopsin and other GPCRs. Less stable interfaces, involving H4 and H6, have a free energy barrier for desolvation (delipidation) of the interfaces and appear to be designed to stabilize 'lubricated' (i.e., lipid-coated) dimers. The overall CGMD strategy used here is general and can be applied to study the homo- and heterodimerization of GPCRs and other transmembrane proteins. Systematic extension of the work will deepen our understanding of the forces involved in the membrane organization of integral membrane proteins.
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485Steczkiewicz, K.; Zimmermann, M. T.; Kurcinski, M.; Lewis, B. A.; Dobbs, D.; Kloczkowski, A.; Jernigan, R. L.; Kolinski, A.; Ginalski, K. Human telomerase model shows the role of the TEN domain in advancing the double helix for the next polymerization step Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 9443– 9448 DOI: 10.1073/pnas.1015399108Google ScholarThere is no corresponding record for this reference.
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486Liu, S.; Vakser, I. A. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking BMC Bioinf. 2011, 12, 280 DOI: 10.1186/1471-2105-12-280Google Scholar486https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3MjitVajtQ%253D%253D&md5=3c0322a42123dad1b6c68d0c33d1d733DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein dockingLiu Shiyong; Vakser Ilya ABMC bioinformatics (2011), 12 (), 280 ISSN:.BACKGROUND: Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom) pairs in the non-interaction state. RESULTS: The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK) potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. CONCLUSIONS: A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of the potentials.
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487Ghoorah, A. W.; Devignes, M. D.; Smail-Tabbone, M.; Ritchie, D. W. Spatial clustering of protein binding sites for template based protein docking Bioinformatics 2011, 27, 2820– 2827 DOI: 10.1093/bioinformatics/btr493Google Scholar487https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsL3E&md5=d1d7c3abfd064fdb629ff482bb73758cSpatial clustering of protein binding sites for template based protein dockingGhoorah, Anisah W.; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Ritchie, David W.Bioinformatics (2011), 27 (20), 2820-2827CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homol. to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes.
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488Andreani, J.; Faure, G.; Guerois, R. InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution Bioinformatics 2013, 29, 1742– 1749 DOI: 10.1093/bioinformatics/btt260Google ScholarThere is no corresponding record for this reference.
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489Solernou, A.; Fernandez-Recio, J. pyDockCG: new coarse-grained potential for protein-protein docking J. Phys. Chem. B 2011, 115, 6032– 6039 DOI: 10.1021/jp112292bGoogle ScholarThere is no corresponding record for this reference.
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490Frembgen-Kesner, T.; Elcock, A. H. Absolute protein-protein association rate constants from flexible, coarse-grained Brownian dynamics simulations: the role of intermolecular hydrodynamic interactions in barnase-barstar association Biophys. J. 2010, 99, L75– 77 DOI: 10.1016/j.bpj.2010.09.006Google Scholar490https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlKkur3I&md5=157dd5f426bcafbe782bca9210a6fec0Absolute Protein-Protein Association Rate Constants from Flexible, Coarse-Grained Brownian Dynamics Simulations: The Role of Intermolecular Hydrodynamic Interactions in Barnase-Barstar AssociationFrembgen-Kesner, Tamara; Elcock, Adrian H.Biophysical Journal (2010), 99 (9), L75-L77CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Theory and computation have long been used to rationalize the exptl. assocn. rate consts. of protein-protein complexes, and Brownian dynamics (BD) simulations in particular have been successful in reproducing the relative rate consts. of wild-type and mutant protein pairs. Missing from previous BD studies of assocn. kinetics, however, has been the description of hydrodynamic interactions (HIs) between and within the diffusing proteins. Here we address this issue by rigorously including HIs in BD simulations of the barnase-barstar assocn. reaction. We first show that even very simplified representations of the proteins - involving approx. one pseudoatom for every three residues in the protein - can provide excellent reprodn. of the abs. assocn. rate consts. of wild-type and mutant protein pairs. We then show that simulations that include intermol. HIs also produce excellent ests. of assocn. rate consts., but for a given reaction criterion, yield values that are decreased by ∼35-80% relative to those obtained in the absence of intermol. HIs. Therefore, the neglect of intermol. HIs in previous BD simulation studies is likely to have contributed to the somewhat overestimated abs. rate consts. previously obtained. Consequently, intermol. HIs could be an important component to include in accurate modeling of the kinetics of macromol. assocn. events.
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491Emperador, A.; Sfriso, P.; Villarreal, M. A.; Gelpi, J. L.; Orozco, M. PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein Systems J. Chem. Theory Comput. 2015, 11, 5929– 5938 DOI: 10.1021/acs.jctc.5b00660Google Scholar491https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVSls7rK&md5=888a24ebc16fb2203176c246a8764d23PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein SystemsEmperador, Agusti; Sfriso, Pedro; Villarreal, Marcos Ariel; Gelpi, Josep Lluis; Orozco, ModestoJournal of Chemical Theory and Computation (2015), 11 (12), 5929-5938CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. dynamics simulations of proteins are usually performed on a single mol., and coarse-grained protein models are calibrated using single-mol. simulations, therefore ignoring intermol. interactions. The authors present here a new coarse-grained force field for the study of many protein systems. The force field, which is implemented in the context of the discrete mol. dynamics algorithm, is able to reproduce the properties of folded and unfolded proteins, in both isolation, complexed forming well-defined quaternary structures, or aggregated, thanks to its proper evaluation of protein-protein interactions. The accuracy and computational efficiency of the method makes it a universal tool for the study of the structure, dynamics, and assocn./dissocn. of proteins.
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492May, A.; Pool, R.; van Dijk, E.; Bijlard, J.; Abeln, S.; Heringa, J.; Feenstra, K. A. Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins Bioinformatics 2014, 30, 326– 334 DOI: 10.1093/bioinformatics/btt675Google Scholar492https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Cjt70%253D&md5=61540a9ae1e44fa047e85d7fb0d9892fCoarse-grained versus atomistic simulations: realistic interaction free energies for real proteinsMay, Ali; Pool, Rene; van Dijk, Erik; Bijlard, Jochem; Abeln, Sanne; Heringa, Jaap; Feenstra, K. AntonBioinformatics (2014), 30 (3), 326-334CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: To assess whether two proteins will interact under physiol. conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quant. est. binding free energies. Full atomistic mol. simulation methods do have this potential, but are completely unfeasible for large-scale applications in terms of computational cost required. Here we investigate whether applying coarse-grained (CG) mol. dynamics simulations is a viable alternative for complexes of known structure. Results: We calc. the free energy barrier with respect to the bound state based on mol. dynamics simulations using both a full atomistic and a CG force field for the TCR-pMHC complex and the MP1-p14 scaffolding complex. We find that the free energy barriers from the CG simulations are of similar accuracy as those from the full atomistic ones, while achieving a speedup of >500-fold. We also observe that extensive sampling is extremely important to obtain accurate free energy barriers, which is only within reach for the CG models. Finally, we show that the CG model preserves biol. relevance of the interactions: (i) we observe a strong correlation between evolutionary likelihood of mutations and the impact on the free energy barrier with respect to the bound state; and (ii) we confirm the dominant role of the interface core in these interactions. Therefore, our results suggest that CG mol. simulations can realistically be used for the accurate prediction of protein-protein interaction strength.
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493Bastard, K.; Prevost, C.; Zacharias, M. Accounting for loop flexibility during protein-protein docking Proteins: Struct., Funct., Genet. 2006, 62, 956– 969 DOI: 10.1002/prot.20770Google ScholarThere is no corresponding record for this reference.
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494Schneider, S.; Saladin, A.; Fiorucci, S.; Prevost, C.; Zacharias, M. ATTRACT and PTools: open source programs for protein-protein docking Methods Mol. Biol. 2012, 819, 221– 232 DOI: 10.1007/978-1-61779-465-0_15Google Scholar494https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFSjur7E&md5=94914ba8090379fd3b3f82587e70175cATTRACT and PTOOLS: open source programs for protein-protein dockingSchneider, Sebastian; Saladin, Adrien; Fiorucci, Sebastien; Prevost, Chantal; Zacharias, MartinMethods in Molecular Biology (New York, NY, United States) (2012), 819 (Computational Drug Discovery and Design), 221-232CODEN: MMBIED; ISSN:1064-3745. (Springer)The prediction of the structure of protein-protein complexes based on structures or structural models of isolated partners is of increasing importance for structural biol. and bioinformatics. The ATTRACT program can be used to perform systematic docking searches based on docking energy minimization. It is part of the object-oriented PTools library written in Python and C++. The library contains various routines to manipulate protein structures, to prep. and perform docking searches as well as analyzing docking results. It also intended to facilitate further methodol. developments in the area of macromol. docking that can be easily integrated. Here, we describe the application of PTools to perform systematic docking searches and to analyze the results. In addn., the possibility to perform multicomponent docking will also be presented.
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495Sacquin-Mora, S.; Laforet, E.; Lavery, R. Locating the active sites of enzymes using mechanical properties Proteins: Struct., Funct., Genet. 2007, 67, 350– 359 DOI: 10.1002/prot.21353Google ScholarThere is no corresponding record for this reference.
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496Poulain, P.; Saladin, A.; Hartmann, B.; Prevost, C. Insights on protein-DNA recognition by coarse grain modelling J. Comput. Chem. 2008, 29, 2582– 2592 DOI: 10.1002/jcc.21014Google ScholarThere is no corresponding record for this reference.
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497Saladin, A.; Amourda, C.; Poulain, P.; Ferey, N.; Baaden, M.; Zacharias, M.; Delalande, O.; Prevost, C. Modeling the early stage of DNA sequence recognition within RecA nucleoprotein filaments Nucleic Acids Res. 2010, 38, 6313– 6323 DOI: 10.1093/nar/gkq459Google ScholarThere is no corresponding record for this reference.
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498Molza, A. E.; Ferey, N.; Czjzek, M.; Le Rumeur, E.; Hubert, J. F.; Tek, A.; Laurent, B.; Baaden, M.; Delalande, O. Innovative interactive flexible docking method for multi-scale reconstruction elucidates dystrophin molecular assembly Faraday Discuss. 2014, 169, 45– 62 DOI: 10.1039/C3FD00134BGoogle ScholarThere is no corresponding record for this reference.
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499Lensink, M. F.; Wodak, S. J. Docking, scoring, and affinity prediction in CAPRI Proteins: Struct., Funct., Genet. 2013, 81, 2082– 2095 DOI: 10.1002/prot.24428Google Scholar499https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1agurvL&md5=fd76a3201716b47f338ee29507d92ab5Docking, scoring, and affinity prediction in CAPRILensink, Marc F.; Wodak, Shoshana J.Proteins: Structure, Function, and Bioinformatics (2013), 81 (12), 2082-2095CODEN: PSFBAF ISSN:. (Wiley-Blackwell)We present the fifth evaluation of docking and related scoring methods used in the community-wide expt. on the Crit. Assessment of Predicted Interactions (CAPRI). The evaluation examd. predictions submitted for a total of 15 targets in eight CAPRI rounds held during the years 2010-2012. The targets represented one the most diverse set tackled by the CAPRI community so far. They included only 10 "classical" docking and scoring problems. In one of the classical targets, the new challenge was to predict the position of water mols. in the protein-protein interface. The remaining five targets represented other new challenges that involved estg. the relative binding affinity and the effect of point mutations on the stability of designed and natural protein-protein complexes. Although the 10 classical CAPRI targets included two difficult multicomponent systems, and a protein-oligosaccharide complex with which CAPRI participants had little experience, this evaluation indicates that the performance of docking and scoring methods has remained quite robust. More remarkably, we find that automatic docking servers exhibit a significantly improved performance, with some servers now performing on par with predictions done by humans. The performance of CAPRI participants in the new challenges, briefly reviewed here, was mediocre overall, but some groups did relatively well and their approaches suggested ways of improving methods for designing binders and for estg. the free energies of protein assemblies, which should impact the field of protein modeling and design as a whole.
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500Kozakov, D.; Beglov, D.; Bohnuud, T.; Mottarella, S. E.; Xia, B.; Hall, D. R.; Vajda, S. How good is automated protein docking? Proteins: Struct., Funct., Genet. 2013, 81, 2159– 2166 DOI: 10.1002/prot.24403Google Scholar500https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1agtrzJ&md5=b82ba81c585b0b514c4a94eb361cd962How good is automated protein docking?Kozakov, Dima; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E.; Xia, Bing; Hall, David R.; Vajda, SandorProteins: Structure, Function, and Bioinformatics (2013), 81 (12), 2159-2166CODEN: PSFBAF ISSN:. (Wiley-Blackwell)The protein docking server ClusPro has been participating in crit. assessment of prediction of interactions (CAPRI) since its introduction in 2004. This article evaluates the performance of ClusPro 2.0 for targets 46-58 in Rounds 22-27 of CAPRI. The anal. leads to a no. of important observations. First, ClusPro reliably yields acceptable or medium accuracy models for targets of moderate difficulty that have also been successfully predicted by other groups, and fails only for targets that have few acceptable models submitted. Second, the quality of automated docking by ClusPro is very close to that of the best human predictor groups, including our own submissions. This is very important, because servers have to submit results within 48 h and the predictions should be reproducible, whereas human predictors have several weeks and can use any type of information. Third, while we refined the ClusPro results for manual submission by running computationally costly Monte Carlo minimization simulations, we obsd. significant improvement in accuracy only for two of the six complexes correctly predicted by ClusPro. Fourth, new developments, not seen in previous rounds of CAPRI, are that the top ranked model provided by ClusPro was acceptable or better quality for all these six targets, and that the top ranked model was also the highest quality for five of the six, confirming that ranking models based on cluster size can reliably identify the best near-native conformations.
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501Vajda, S.; Kozakov, D. Convergence and combination of methods in protein-protein docking Curr. Opin. Struct. Biol. 2009, 19, 164– 170 DOI: 10.1016/j.sbi.2009.02.008Google Scholar501https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkvVSqt7Y%253D&md5=412d42d11d31d7e656d0834405b4d2e6Convergence and combination of methods in protein-protein dockingVajda, Sandor; Kozakov, DimaCurrent Opinion in Structural Biology (2009), 19 (2), 164-170CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. The anal. of results from Crit. Assessment of Predicted Interactions (CAPRI), the first community-wide expt. devoted to protein docking, shows that all successful methods consist of multiple stages. The methods belong to 3 classes: global methods based on fast Fourier transforms (FFTs) or geometric matching, medium-range Monte Carlo methods, and the restraint-guided High Ambiguity Driven biomol. DOCKing (HADDOCK) program. Although these classes of methods require very different amts. of information in addn. to the structures of component proteins, they all share the same 4 computational steps: (1) simplified and/or rigid body search; (2) selecting the region(s) of interest; (3) refinement of docked structures; and (4) selecting the best models. Although each method is optimal for a specific class of docking problems, combining computational steps from different methods can improve the reliability and accuracy of results.
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502Huang, S. Y. Search strategies and evaluation in protein-protein docking: principles, advances and challenges Drug Discovery Today 2014, 19, 1081– 1096 DOI: 10.1016/j.drudis.2014.02.005Google Scholar502https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotFyhsb8%253D&md5=28d301e8e996ca34314ede2661938798Search strategies and evaluation in protein-protein docking: principles, advances and challengesHuang, Sheng-YouDrug Discovery Today (2014), 19 (8), 1081-1096CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)A review. Protein-protein docking is attracting increasing attention in drug discovery research targeting protein-protein interactions, owing to its potential in predicting protein-protein interactions and identifying 'hot spot' residues at the protein-protein interface. Given the relative lack of information about binding sites and the fact that proteins are generally larger than ligand, the search algorithms and evaluation methods for protein-protein docking differ somewhat from those for protein-ligand docking and, hence, require different research strategies. Here, we review the basic concepts, principles and advances of current search strategies and evaluation methods for protein-protein docking. We also discuss the current challenges and limitations, as well as future directions, of established approaches.
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503Huang, S. Y. Exploring the potential of global protein-protein docking: an overview and critical assessment of current programs for automatic ab initio docking Drug Discovery Today 2015, 20, 969– 977 DOI: 10.1016/j.drudis.2015.03.007Google Scholar503https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXltFCht70%253D&md5=b7924b6b5f797685bab4f077ec294acbExploring the potential of global protein-protein docking: an overview and critical assessment of current programs for automatic ab initio dockingHuang, Sheng-YouDrug Discovery Today (2015), 20 (8), 969-977CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)Protein-protein docking is an important computational tool for studying protein-protein interactions. A variety of docking programs with different sampling algorithms and scoring functions as well as computational efficiencies have been subsequently developed over the last decades. Here, we have reviewed the trend and performance of current global docking programs through a comprehensive assessment of the 18 docking/scoring protocols of 14 global docking programs on the latest protein docking benchmark 4.0. The effects of docking algorithms, interaction types, and conformational changes on the docking performance were investigated and discussed. The findings are expected to provide a general guideline for the choice of an appropriate docking protocol and offer insights into the optimization and development of docking and scoring algorithms.
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504Tuffery, P.; Derreumaux, P. Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches J. R. Soc., Interface 2012, 9, 20– 33 DOI: 10.1098/rsif.2011.0584Google Scholar504https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktFCns7w%253D&md5=559359a4fd0c00b6b6f2c825dc455540Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approachesTuffery, Pierre; Derreumaux, PhilippeJournal of the Royal Society, Interface (2012), 9 (66), 20-33CODEN: JRSICU; ISSN:1742-5689. (Royal Society)A review. The recognition process between a protein and a partner represents a significant theor. challenge. In silico structure-based drug design carried out with nothing more than the three-dimensional structure of the protein has led to the introduction of many compds. into clin. trials and numerous drug approvals. Central to guiding the discovery process is to recognize active among non-active compds. While large-scale computer simulations of compds. taken from a library (virtual screening) or designed de novo are highly desirable in the post-genomic area, many tech. problems remain to be adequately addressed. This article presents an overview and discusses the limits of current computational methods for predicting the correct binding pose and accurate binding affinity. It also presents the performances of the most popular algorithms for exploring binary and multi-body protein interactions.
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505Li, H.; Lu, L.; Chen, R.; Quan, L.; Xia, X.; Lu, Q. PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta PLoS One 2014, 9, e94769 DOI: 10.1371/journal.pone.0094769Google ScholarThere is no corresponding record for this reference.
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506Wabik, J.; Kurcinski, M.; Kolinski, A. Coarse-Grained Modeling of Peptide Docking Associated with Large Conformation Transitions of the Binding Protein: Troponin I Fragment-Troponin C System Molecules 2015, 20, 10763– 10780 DOI: 10.3390/molecules200610763Google ScholarThere is no corresponding record for this reference.
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507Ravikumar, K. M.; Huang, W.; Yang, S. Coarse-grained simulations of protein-protein association: an energy landscape perspective Biophys. J. 2012, 103, 837– 845 DOI: 10.1016/j.bpj.2012.07.013Google Scholar507https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1eku7nM&md5=8e27e21327fd69539751cf9911318937Coarse-Grained Simulations of Protein-Protein Association: An Energy Landscape PerspectiveRavikumar, Krishnakumar M.; Huang, Wei; Yang, SichunBiophysical Journal (2012), 103 (4), 837-845CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Understanding protein-protein assocn. is crucial in revealing the mol. basis of many biol. processes. Here, we describe a theor. simulation pipeline to study protein-protein assocn. from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via mol. dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examn. on mol. forces shows that the formation of assocd. protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein assocn. occurring in functional biomol. complexes.
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508Irback, A.; Jonsson, S. A. E.; Linnemann, N.; Linse, B.; Wallin, S. Aggregate geometry in amyloid fibril nucleation Phys. Rev. Lett. 2013, 110, 058101 DOI: 10.1103/PhysRevLett.110.058101Google ScholarThere is no corresponding record for this reference.
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509Bieler, N. S.; Knowles, T. P.; Frenkel, D.; Vacha, R. Connecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulations PLoS Comput. Biol. 2012, 8, e1002692 DOI: 10.1371/journal.pcbi.1002692Google Scholar509https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFOrsLnM&md5=f1f53532587dfa379c6ec4ffecd895bbConnecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulationsBieler, Noah S.; Knowles, Tuomas P. J.; Frenkel, Daan; Vacha, RobertPLoS Computational Biology (2012), 8 (10), e1002692CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)The pre-fibrillar stages of amyloid formation have been implicated in cellular toxicity, but have proved to be challenging to study directly in expts. and simulations. Rational strategies to suppress the formation of toxic amyloid oligomers require a better understanding of the mechanisms by which they are generated. We report Dynamical Monte Carlo simulations that allow us to study the early stages of amyloid formation. We use a generic, coarse-grained model of an amyloidogenic peptide that has two internal states: the first one representing the sol. random coil structure and the second one the β-sheet conformation. We find that this system exhibits a propensity towards fibrillar self-assembly following the formation of a crit. nucleus. Our calcns. establish connections between the early nucleation events and the kinetic information available in the later stages of the aggregation process that are commonly probed in expts. We analyze the kinetic behavior in our simulations within the framework of the theory of classical nucleated polymn. and are able to connect the structural events at the early stages in amyloid growth with the resulting macroscopic observables such as the effective nucleus size. Furthermore, the free-energy landscapes that emerge from these simulations allow us to identify pertinent properties of the monomeric state that could be targeted to suppress oligomer formation.
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510Li, M. S.; Klimov, D. K.; Straub, J. E.; Thirumalai, D. Probing the mechanisms of fibril formation using lattice models J. Chem. Phys. 2008, 129, 175101 DOI: 10.1063/1.2989981Google Scholar510https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlCksL%252FO&md5=6bc2eeaa868b4ddf622c34bffdf2cd8bProbing the mechanisms of fibril formation using lattice modelsLi, Mai Suan; Klimov, D. K.; Straub, J. E.; Thirumalai, D.Journal of Chemical Physics (2008), 129 (17), 175101/1-175101/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Using exhaustive Monte Carlo simulations we study the kinetics and mechanism of fibril formation using lattice models as a function of temp. (T) and the no. of chains (M). While these models are at best caricatures of peptides, we show that a no. of generic features thought to govern fibril assembly are captured by the toy model. The monomer, which contains eight beads made from three letters (hydrophobic, polar, and charged), adopts a compact conformation in the native state. In both the single-layered protofilament (seen for M≤10) and the two-layer fibril (M°10) structures, the monomers are arranged in an antiparallel fashion with the "strandlike" conformation that is perpendicular to the fibril axis. Partial unfolding of the folded monomer that populates an aggregation-prone conformation (N*) is required for ordered assembly. The contacts in the N* conformation, which is one of the four structures in the first "excited" state of the monomer, are also present in the native conformation. The time scale for fibril formation is a min. in the T-range when the conformation N* is substantially populated. The kinetics of fibril assembly occurs in three distinct stages. In each stage there is a cascade of events that transforms the monomers and oligomers to ordered structures. In the first "burst" stage, highly mobile oligomers of varying sizes form. The conversion to the N* conformation occurs within the oligomers during the second stage in which a vast no. of interchain contacts are established. As time progresses, a dominant cluster emerges that contains a majority of the chains. In the final stage, the aggregation of N* particles serve as a template onto which smaller oligomers or monomers can dock and undergo conversion to fibril structures. The overall time for growth in the latter stages is well described by the Lifshitz-Slyazov growth kinetics for crystn. from supersatd. solns. The detailed anal. shows that elements of the three popular models, namely, nucleation-growth (NG), templated assembly (TA), and nucleated conformational conversion (NCC) are present at various stages of fibril assembly. (c) 2008 American Institute of Physics.
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511Friedman, R.; Caflisch, A. Surfactant effects on amyloid aggregation kinetics J. Mol. Biol. 2011, 414, 303– 312 DOI: 10.1016/j.jmb.2011.10.011Google ScholarThere is no corresponding record for this reference.
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512Bellesia, G.; Shea, J. E. Self-assembly of beta-sheet forming peptides into chiral fibrillar aggregates J. Chem. Phys. 2007, 126, 245104 DOI: 10.1063/1.2739547Google Scholar512https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXnsVOmsr4%253D&md5=368f791d0be49393a342fcbcbfc887b8Self-assembly of β-sheet forming peptides into chiral fibrillar aggregatesBellesia, Giovanni; Shea, Joan-EmmaJournal of Chemical Physics (2007), 126 (24), 245104/1-245104/11CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The authors introduce a novel mid-resoln. off-lattice coarse-grained model to investigate the self-assembly of β-sheet-forming peptides. The model retains most of the peptide backbone degrees of freedom as well as one interaction center describing the side chains. The peptide consists of a core of alternating hydrophobic and hydrophilic residues, capped by two oppositely charged residues. Nonbonded interactions are described by Lennard-Jones and Coulombic terms. The influence of different levels of "hydrophobic" and "steric" forces between the side chains of the peptides on the thermodn. and kinetics of aggregation was investigated using Langevin dynamics. The model is simple enough to allow the simulation of systems consisting of hundreds of peptides, while remaining realistic enough to successfully lead to the formation of chiral, ordered β tapes, ribbons, and higher order fibrillar aggregates.
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513Carmichael, S. P.; Shell, M. S. A new multiscale algorithm and its application to coarse-grained peptide models for self-assembly J. Phys. Chem. B 2012, 116, 8383– 8393 DOI: 10.1021/jp2114994Google Scholar513https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1Oms7k%253D&md5=8a51350f45b075ad2d14609713917654A New Multiscale Algorithm and Its Application to Coarse-Grained Peptide Models for Self-AssemblyCarmichael, Scott P.; Shell, M. ScottJournal of Physical Chemistry B (2012), 116 (29), 8383-8393CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Peptide self-assembly plays a role in a no. of diseases, in pharmaceutical degrdn., and in emerging biomaterials. Here, we aim to develop an accurate mol.-scale picture of this process using a multiscale computational approach. We have reformulated this methodol. using a trajectory-reweighting and perturbation strategy that enables complex coarse-grained models with at least hundreds of parameters to be optimized efficiently. This new algorithm allows for complex peptide systems to be coarse-grained into much simpler models that nonetheless recapitulate many correct features of detailed all-atom ones. In particular, we present results for a polyalanine case study, with attention to both individual peptide folding and large-scale fibril assembly.
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514Cheon, M.; Chang, I.; Hall, C. K. Extending the PRIME model for protein aggregation to all 20 amino acids Proteins: Struct., Funct., Genet. 2010, 78, 2950– 2960 DOI: 10.1002/prot.22817Google Scholar514https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFCrtrnL&md5=797a5b4c26ba155c516c0e689f306df8Extending the PRIME model for protein aggregation to all 20 amino acidsCheon, Mookyung; Chang, Iksoo; Hall, Carol K.Proteins: Structure, Function, and Bioinformatics (2010), 78 (14), 2950-2960CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)We extend PRIME, an intermediate-resoln. protein model previously used in simulations of the aggregation of polyalanine and polyglutamine, to the description of the geometry and energetics of peptides contg. all 20 amino acid residues. The 20 amino acid side chains are classified into 14 groups according to their hydrophobicity, polarity, size, charge, and potential for side chain hydrogen bonding. The parameters for extended PRIME, called PRIME 20, include hydrogen-bonding energies, side chain interaction range and energy, and excluded vol. The parameters are obtained by applying a perceptron-learning algorithm and a modified stochastic learning algorithm that optimizes the energy gap between 711 known native states from the PDB and decoy structures generated by gapless threading. The no. of independent pair interaction parameters is chosen to be small enough to be phys. meaningful yet large enough to give reasonably accurate results in discriminating decoys from native structures. The most phys. meaningful results are obtained with 19 energy parameters. Proteins 2010. © 2010 Wiley-Liss, Inc.
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515Uversky, V. N. Introduction to intrinsically disordered proteins (IDPs) Chem. Rev. 2014, 114, 6557– 6560 DOI: 10.1021/cr500288yGoogle Scholar515https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtV2js7zP&md5=9aa8ac1269cf374cd6447ae02dd63804Introduction to Intrinsically Disordered Proteins (IDPs)Uversky, Vladimir N.Chemical Reviews (Washington, DC, United States) (2014), 114 (13), 6557-6560CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review on proteins with intrinsically disordered structure, interest to which grows rapidly in recent years, their interaction with various biomols. and thermodn. aspects of the interactions.
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516Habchi, J.; Tompa, P.; Longhi, S.; Uversky, V. N. Introducing protein intrinsic disorder Chem. Rev. 2014, 114, 6561– 6588 DOI: 10.1021/cr400514hGoogle Scholar516https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtlygt7Y%253D&md5=56ee20777b53dabddad9fc22ddb2aed5Introducing protein intrinsic disorderHabchi, Johnny; Tompa, Peter; Longhi, Sonia; Uversky, Vladimir N.Chemical Reviews (Washington, DC, United States) (2014), 114 (13), 6561-6588CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review. This paper is intended as a general introduction to a series of thematic reviews on intrinsically disordered proteins (IDPs). Although IDPs possess no well-defined 3-dimensional structure but rather adapt an ensemble of conformations in soln., they are still functional. A literature review is provided by summarizing the main aspects of IDPs that have led to an exponential increase of interest in these proteins. Moreover, through the different parts of this review, biochem. and biophys. approaches that are frequently used to assess intrinsic disorder are detailed.
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517Mittag, T.; Kay, L. E.; Forman-Kay, J. D. Protein dynamics and conformational disorder in molecular recognition J. Mol. Recognit. 2009, 23, 105– 116 DOI: 10.1002/jmr.961Google ScholarThere is no corresponding record for this reference.
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518Uversky, V. N.; Gillespie, J. R.; Fink, A. L. Why are “natively unfolded” proteins unstructured under physiologic conditions? Proteins: Struct., Funct., Genet. 2000, 41, 415– 427 DOI: 10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.3.CO;2-ZGoogle ScholarThere is no corresponding record for this reference.
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519Wright, P. E.; Dyson, H. J. Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm J. Mol. Biol. 1999, 293, 321– 331 DOI: 10.1006/jmbi.1999.3110Google Scholar519https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXms12rtbw%253D&md5=bf38ba52223ec01ee473b2891a713893Intrinsically Unstructured Proteins: Re-assessing the Protein Structure-Function ParadigmWright, Peter E.; Dyson, H. JaneJournal of Molecular Biology (1999), 293 (2), 321-331CODEN: JMOBAK; ISSN:0022-2836. (Academic Press)A review with 93 refs. A major challenge in the post-genome era will be detn. of the functions of the encoded protein sequences. Since it is generally assumed that the function of a protein is closely linked to its three-dimensional structure, prediction or exptl. detn. of the library of protein structures is a matter of high priority. However, a large proportion of gene sequences appear to code not for folded, globular proteins, but for long stretches of amino acids that are likely to be either unfolded in soln. or adopt non-globular structures of unknown conformation. Characterization of the conformational propensities and function of the non-globular protein sequences represents a major challenge. The high proportion of these sequences in the genomes of all organisms studied to date argues for important, as yet unknown functions, since there could be no other reason for their persistence throughout evolution. Clearly the assumption that a folded three-dimensional structure is necessary for function needs to be re-examd. Although the functions of many proteins are directly related to their three-dimensional structures, numerous proteins that lack intrinsic globular structure under physiol. conditions have now been recognized. Such proteins are frequently involved in some of the most important regulatory functions in the cell, and the lack of intrinsic structure in many cases is relieved when the protein binds to its target mol. The intrinsic lack of structure can confer functional advantages on a protein, including the ability to bind to several different targets. It also allows precise control over the thermodn. of the binding process and provides a simple mechanism for inducibility by phosphorylation or through interaction with other components of the cellular machinery. Numerous examples of domains that are unstructured in soln. but which become structured upon binding to the target have been noted in the areas of cell cycle control and both transcriptional and translational regulation, and unstructured domains are present in proteins that are targeted for rapid destruction. Since such proteins participate in crit. cellular control mechanisms, it appears likely that their rapid turnover, aided by their unstructured nature in the unbound state, provides a level of control that allows rapid and accurate responses of the cell to changing environmental conditions. (c) 1999 Academic Press.
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520Zhang, Y.; Stec, B.; Godzik, A. Between order and disorder in protein structures: analysis of ″dual personality″ fragments in proteins Structure 2007, 15, 1141– 1147 DOI: 10.1016/j.str.2007.07.012Google ScholarThere is no corresponding record for this reference.
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521Eliezer, D. Biophysical characterization of intrinsically disordered proteins Curr. Opin. Struct. Biol. 2009, 19, 23– 30 DOI: 10.1016/j.sbi.2008.12.004Google Scholar521https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXit1OmsLs%253D&md5=4f813b15e8bae72fbde66ec7120a32b1Biophysical characterization of intrinsically disordered proteinsEliezer, DavidCurrent Opinion in Structural Biology (2009), 19 (1), 23-30CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. The challenges assocd. with the structural characterization of disordered proteins have resulted in the application of a host of biophys. methods to such systems. NMR spectroscopy is perhaps the most readily suited technique for providing high-resoln. structural information on disordered protein states in soln. Optical methods, solid state NMR, ESR and X-ray scattering can also provide valuable information regarding the ensemble of conformations sampled by disordered states. Finally, computational studies have begun to assume an increasingly important role in interpreting and extending the impact of exptl. data obtained for such systems. This article discusses recent advances in the applications of these methods to intrinsically disordered proteins.
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522Rauscher, S.; Pomès, R. Molecular simulations of protein disorderThis paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular & Cellular Biology 52nd Annual Meeting — Protein Folding: Principles and Diseases” and has undergone the Journal’s usual peer review process Biochem. Cell Biol. 2010, 88, 269– 290 DOI: 10.1139/O09-169Google Scholar522https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXjs1egsbw%253D&md5=9be380bd6b6d5acde1ae415dc1331694Molecular simulations of protein disorderRauscher, Sarah; Pomes, RegisBiochemistry and Cell Biology (2010), 88 (2), 269-290CODEN: BCBIEQ; ISSN:0829-8211. (National Research Council of Canada)A review. Protein disorder is abundant in proteomes throughout all kingdoms of life and serves many biol. important roles. Disordered states of proteins are challenging to study exptl. due to their structural heterogeneity and tendency to aggregate. Computer simulations, which are not impeded by these properties, have recently emerged as a useful tool to characterize the conformational ensembles of intrinsically disordered proteins. In this review, we provide a survey of computational studies of protein disorder with an emphasis on the interdisciplinary nature of these studies. The application of simulation techniques to the study of disordered states is described in the context of exptl. and bioinformatics approaches. Exptl. data can be incorporated into simulations, and simulations can provide predictions for expt. In this way, simulations have been integrated into the existing methodologies for the study of disordered state ensembles. We provide recent examples of simulations of disordered states from the literature and our own work. Throughout the review, we emphasize important predictions and biophys. understanding made possible through the use of simulations. This review is intended as both an overview and a guide for structural biologists and theor. biophysicists seeking accurate, at.-level descriptions of disordered state ensembles.
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523Baker, C. M.; Best, R. B. Insights into the binding of intrinsically disordered proteins from molecular dynamics simulation Wires Comput. Mol. Sci. 2014, 4, 182– 198 DOI: 10.1002/wcms.1167Google Scholar523https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtl2ju7w%253D&md5=0c269fbf7ac5d527d416a842dccbc0a3Insights into the binding of intrinsically disordered proteins from molecular dynamics simulationBaker, Christopher M.; Best, Robert B.Wiley Interdisciplinary Reviews: Computational Molecular Science (2014), 4 (3), 182-198CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)A review. Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no well-defined secondary or tertiary structure, existing instead as dynamic ensembles of conformations. They are biol. important, with approx. 20% of all eukaryotic proteins disordered, and found at the heart of many biochem. networks. To fulfil their biol. roles, many IDPs need to bind to proteins and/or nucleic acids. And although unstructured in soln., IDPs typically fold into a well-defined three-dimensional structure upon interaction with a binding partner. The flexibility and structural diversity inherent to IDPs makes this coupled folding and binding difficult to study at at. resoln. by expt. alone, and computer simulation currently offers perhaps the best opportunity to understand this process. But simulation of coupled folding and binding is itself extremely challenging; these mols. are large and highly flexible, and their binding partners, such as DNA or cyclins, are also often large. Therefore, their study requires either simplified representations, advanced enhanced sampling schemes, or both. It is not always clear that existing simulation techniques, optimized for studying folded proteins, are well suited to IDPs. In this article, we examine the progress that has been made in the study of coupled folding and binding using mol. dynamics simulation. We summarize what has been learnt, and examine the state of the art in terms of both methodologies and models. We also consider the lessons to be learnt from advances in other areas of simulation and highlight the issues that remain of be addressed.
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524David de, S.; Christopher, M. B.; Robert, B. B. In Computational Approaches to Protein Dynamics; CRC Press: Boca Raton, FL, 2014.Google ScholarThere is no corresponding record for this reference.
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525Rauscher, S.; Gapsys, V.; Gajda, M. J.; Zweckstetter, M.; de Groot, B. L.; Grubmuller, H. Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment J. Chem. Theory Comput. 2015, 11, 5513– 5524 DOI: 10.1021/acs.jctc.5b00736Google Scholar525https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhs1ChsbvM&md5=0c38ce869b7b2bb569f59f9a77c19bedStructural ensembles of intrinsically disordered proteins depend strongly on force field: A comparison to experimentRauscher, Sarah; Gapsys, Vytautas; Gajda, Michal J.; Zweckstetter, Markus; de Groot, Bert L.; Grubmueller, HelmutJournal of Chemical Theory and Computation (2015), 11 (11), 5513-5524CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Intrinsically disordered proteins (IDPs) are notoriously challenging to study both exptl. and computationally. The structure of IDPs cannot be described by a single conformation but must instead be described as an ensemble of interconverting conformations. Atomistic simulations are increasingly used to obtain such IDP conformational ensembles. Here, the authors compared the IDP ensembles generated by 8 all-atom empirical force fields against primary SAXS and NMR data. Ensembles obtained with different force fields exhibited marked differences in chain dimensions, H-bonding, and secondary structure content. These differences were unexpectedly large: changing the force field was found to have a stronger effect on secondary structure content than changing the entire peptide sequence. The CHARMM 22* ensemble performed best in this force field comparison: it had the lowest error in chem. shifts and J-couplings and agreed well with the SAXS data. A high population of left-handed α-helix was present in the CHARMM 36 ensemble, which was inconsistent with measured scalar couplings. To eliminate inadequate sampling as a reason for differences between force fields, extensive simulations were carried out (0.964 ms in total); the remaining small sampling uncertainty was shown to be much smaller than the obsd. differences. The findings highlighted how IDPs, with their rugged energy landscapes, are highly sensitive test systems that are capable of revealing force field deficiencies and, therefore, contributing to force field development.
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526Sugase, K.; Dyson, H. J.; Wright, P. E. Mechanism of coupled folding and binding of an intrinsically disordered protein Nature 2007, 447, 1021– 1025 DOI: 10.1038/nature05858Google Scholar526https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXms1yqu7Y%253D&md5=e9be89311be0350df15c5dcfe6f86db7Mechanism of coupled folding and binding of an intrinsically disordered proteinSugase, Kenji; Dyson, H. Jane; Wright, Peter E.Nature (London, United Kingdom) (2007), 447 (7147), 1021-1025CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Protein folding and binding are analogous processes, in which the protein 'searches' for favorable intramol. or intermol. interactions on a funnelled energy landscape. Many eukaryotic proteins are disordered under physiol. conditions, and fold into ordered structures only on binding to their cellular targets. The mechanism by which folding is coupled to binding is poorly understood, but it has been hypothesized on theor. grounds that the binding kinetics may be enhanced by a 'fly-casting' effect, where the disordered protein binds weakly and non-specifically to its target and folds as it approaches the cognate binding site. Here we show, using NMR titrns. and 15N relaxation dispersion, that the phosphorylated kinase inducible activation domain (pKID) of the transcription factor CREB forms an ensemble of transient encounter complexes on binding to the KIX domain of the CREB binding protein. The encounter complexes are stabilized primarily by non-specific hydrophobic contacts, and evolve by way of an intermediate to the fully bound state without dissocn. from KIX. The carboxy-terminal helix of pKID is only partially folded in the intermediate, and becomes stabilized by intermol. interactions formed in the final bound state. Future applications of our method will provide new understanding of the mol. mechanisms by which intrinsically disordered proteins perform their diverse biol. functions.
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527Chen, H. F. Molecular dynamics simulation of phosphorylated KID post-translational modification. PLoS One 2009, 4, e6516 DOI: 10.1371/journal.pone.0006516Google Scholar527https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1MrjsFCktg%253D%253D&md5=aa0841aa09440c955cad15f190744a8aMolecular dynamics simulation of phosphorylated KID post-translational modificationChen Hai-FengPloS one (2009), 4 (8), e6516 ISSN:.BACKGROUND: Kinase-inducible domain (KID) as transcriptional activator can stimulate target gene expression in signal transduction by associating with KID interacting domain (KIX). NMR spectra suggest that apo-KID is an unstructured protein. After post-translational modification by phosphorylation, KID undergoes a transition from disordered to well folded protein upon binding to KIX. However, the mechanism of folding coupled to binding is poorly understood. METHODOLOGY: To get an insight into the mechanism, we have performed ten trajectories of explicit-solvent molecular dynamics (MD) for both bound and apo phosphorylated KID (pKID). Ten MD simulations are sufficient to capture the average properties in the protein folding and unfolding. CONCLUSIONS: Room-temperature MD simulations suggest that pKID becomes more rigid and stable upon the KIX-binding. Kinetic analysis of high-temperature MD simulations shows that bound pKID and apo-pKID unfold via a three-state and a two-state process, respectively. Both kinetics and free energy landscape analyses indicate that bound pKID folds in the order of KIX access, initiation of pKID tertiary folding, folding of helix alpha(B), folding of helix alpha(A), completion of pKID tertiary folding, and finalization of pKID-KIX binding. Our data show that the folding pathways of apo-pKID are different from the bound state: the foldings of helices alpha(A) and alpha(B) are swapped. Here we also show that Asn139, Asp140 and Leu141 with large Phi-values are key residues in the folding of bound pKID. Our results are in good agreement with NMR experimental observations and provide significant insight into the general mechanisms of binding induced protein folding and other conformational adjustment in post-translational modification.
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528Huang, Y.; Liu, Z. Kinetic Advantage of Intrinsically Disordered Proteins in Coupled Folding–Binding Process: A Critical Assessment of the “Fly-Casting” Mechanism J. Mol. Biol. 2009, 393, 1143– 1159 DOI: 10.1016/j.jmb.2009.09.010Google Scholar528https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlWhu7nJ&md5=cd30aaa9817e1fa8d28917a0e50e1c1bKinetic Advantage of Intrinsically Disordered Proteins in Coupled Folding-Binding Process: A Critical Assessment of the "Fly-Casting" MechanismHuang, Yongqi; Liu, ZhirongJournal of Molecular Biology (2009), 393 (5), 1143-1159CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Intrinsically disordered proteins (IDPs) are recognized to play important roles in many biol. functions such as transcriptional and translational regulation, cellular signal transduction, protein phosphorylation, and mol. assemblies. The coupling of folding with binding through a "fly-casting" mechanism has been proposed to account for the fast binding kinetics of IDPs. In this article, exptl. data from the literature were collated to verify the kinetic advantages of IDPs, while mol. simulations were performed to clarify the origin of the kinetic advantages. The phosphorylated KID-kinase-inducible domain interacting domain (KIX) complex was used as an example in the simulations. By modifying a coarse-grained model with a native-centric Go-like potential, we were able to continuously tune the degree of disorder of the phosphorylated KID domain and thus investigate the intrinsic role of chain flexibility in binding kinetics. The simulations show that the "fly-casting" effect is not only due to the greater capture radii of IDPs. The coupling of folding with binding of IDPs leads to a significant redn. in binding free-energy barrier. Such a redn. accelerates the binding process. Although the greater capture radius has been regarded as the main factor in promoting the binding rate of IDPs, we found that this parameter will also lead to the slower translational diffusion of IDPs when compared with ordered proteins. As a result, the capture rate of IDPs was found to be slower than that of ordered proteins. The main origin of the faster binding for IDPs are the fewer encounter times required before the formation of the final binding complex. The roles of the interchain native contacts fraction (Qb) and the mass-center distance (ΔR) as reaction coordinates are also discussed.
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529Ganguly, D.; Chen, J. Topology-based modeling of intrinsically disordered proteins: Balancing intrinsic folding and intermolecular interactions Proteins: Struct., Funct., Genet. 2011, 79, 1251– 1266 DOI: 10.1002/prot.22960Google Scholar529https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvVWrsbc%253D&md5=c41eca538845eb9fddbf2b03ffa10a65Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactionsGanguly, Debabani; Chen, JianhanProteins: Structure, Function, and Bioinformatics (2011), 79 (4), 1251-1266CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topol.-based Go-like modeling as an effective tool for the mechanism of IDP recognition within the theor. framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Go-like models designed for folded proteins tend to over-est. the level of residual structures in unbound IDPs, whereas under-estg. the strength of intermol. interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topol.-derived models to balance intrinsic folding propensities and intermol. interactions, based on exptl. knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Go-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titrn. and relaxation dispersion study and provides a mol.-level interpretation of kinetic rates derived from dispersion curve anal. These case studies provide important insight into the applicability and potential pitfalls of topol.-based modeling for studying IDP folding and interaction in general.
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530Huang, Y.; Liu, Z. Nonnative interactions in coupled folding and binding processes of intrinsically disordered proteins PLoS One 2010, 5, e15375 DOI: 10.1371/journal.pone.0015375Google ScholarThere is no corresponding record for this reference.
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531Turjanski, A. G.; Gutkind, J. S.; Best, R. B.; Hummer, G. Binding-induced folding of a natively unstructured transcription factor PLoS Comput. Biol. 2008, 4, e1000060 DOI: 10.1371/journal.pcbi.1000060Google Scholar531https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1c3ktlOksQ%253D%253D&md5=89af13cd7f9ef49b9a38a0887fd3dbdbBinding-induced folding of a natively unstructured transcription factorTurjanski Adrian Gustavo; Gutkind J Silvio; Best Robert B; Hummer GerhardPLoS computational biology (2008), 4 (4), e1000060 ISSN:.Transcription factors are central components of the intracellular regulatory networks that control gene expression. An increasingly recognized phenomenon among human transcription factors is the formation of structure upon target binding. Here, we study the folding and binding of the pKID domain of CREB to the KIX domain of the co-activator CBP. Our simulations of a topology-based Go-type model predict a coupled folding and binding mechanism, and the existence of partially bound intermediates. From transition-path and Phi-value analyses, we find that the binding transition state resembles the unstructured state in solution, implying that CREB becomes structured only after committing to binding. A change of structure following binding is reminiscent of an induced-fit mechanism and contrasts with models in which binding occurs to pre-structured conformations that exist in the unbound state at equilibrium. Interestingly, increasing the amount of structure in the unbound pKID reduces the rate of binding, suggesting a "fly-casting"-like process. We find that the inclusion of attractive non-native interactions results in the formation of non-specific encounter complexes that enhance the on-rate of binding, but do not significantly change the binding mechanism. Our study helps explain how being unstructured can confer an advantage in protein target recognition. The simulations are in general agreement with the results of a recently reported nuclear magnetic resonance study, and aid in the interpretation of the experimental binding kinetics.
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532Huang, Y.; Liu, Z. Smoothing molecular interactions: the ″kinetic buffer″ effect of intrinsically disordered proteins Proteins: Struct., Funct., Genet. 2010, 78, 3251– 3259 DOI: 10.1002/prot.22820Google ScholarThere is no corresponding record for this reference.
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533Law, S. M.; Ahlstrom, L. S.; Panahi, A.; Brooks, C. L. Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins J. Phys. Chem. Lett. 2014, 5, 3441– 3444 DOI: 10.1021/jz501811kGoogle Scholar533https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsFOrtbfL&md5=7616e3be2deaf12bee951123850034a8Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered ProteinsLaw, Sean M.; Ahlstrom, Logan S.; Panahi, Afra; Brooks, Charles L.Journal of Physical Chemistry Letters (2014), 5 (19), 3441-3444CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)Mol. recognition by intrinsically disordered proteins (IDPs) plays a central role in many crit. cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here the authors employ the "Hamiltonian mapping" methodol., which is rooted in the weighted histogram anal. method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing ref. simulations on a given Hamiltonian, the authors illustrate for two model IDPs how this method can extrapolate thermodn. behavior under a range of modified Hamiltonians, in this case representing changes in the binding affinity (Kd) of the system. Given sufficient conformational sampling in a single trajectory, Hamiltonian mapping accurately reproduces Kd values from direct simulation. This method may be generally applied to systems beyond IDPs in force field optimization and in describing changes in thermodn. behavior as a function of external conditions for connection with expt.
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534Knott, M.; Best, R. B. Discriminating binding mechanisms of an intrinsically disordered protein via a multi-state coarse-grained model J. Chem. Phys. 2014, 140, 175102 DOI: 10.1063/1.4873710Google Scholar534https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXnsVertLk%253D&md5=a5d43d30da1f44ffad2a1a0384857247Discriminating binding mechanisms of an intrinsically disordered protein via a multi-state coarse-grained modelKnott, Michael; Best, Robert B.Journal of Chemical Physics (2014), 140 (17), 175102/1-175102/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Many proteins undergo a conformational transition upon binding to their cognate binding partner, with intrinsically disordered proteins (IDPs) providing an extreme example in which a folding transition occurs. However, it is often not clear whether this occurs via an "induced fit" or "conformational selection" mechanism, or via some intermediate scenario. In the first case, transient encounters with the binding partner favor transitions to the bound structure before the two proteins dissoc., while in the second the bound structure must be selected from a subset of unbound structures which are in the correct state for binding, because transient encounters of the incorrect conformation with the binding partner are most likely to result in dissocn. A particularly interesting situation involves those intrinsically disordered proteins which can bind to different binding partners in different conformations. We have devised a multi-state coarse-grained simulation model which is able to capture the binding of IDPs in alternate conformations, and by applying it to the binding of nuclear coactivator binding domain (NCBD) to either ACTR or IRF-3 we are able to det. the binding mechanism. By all measures, the binding of NCBD to either binding partner appears to occur via an induced fit mechanism. Nonetheless, we also show how a scenario closer to conformational selection could arise by choosing an alternative non-binding structure for NCBD. (c) 2014 American Institute of Physics.
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535Rutter, G. O.; Brown, A. H.; Quigley, D.; Walsh, T. R.; Allen, M. P. Testing the transferability of a coarse-grained model to intrinsically disordered proteins Phys. Chem. Chem. Phys. 2015, 17, 31741– 31749 DOI: 10.1039/C5CP05652GGoogle ScholarThere is no corresponding record for this reference.
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536Terakawa, T.; Higo, J.; Takada, S. Multi-scale ensemble modeling of modular proteins with intrinsically disordered linker regions: application to p53 Biophys. J. 2014, 107, 721– 729 DOI: 10.1016/j.bpj.2014.06.026Google Scholar536https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht12msrvP&md5=71999cdececfdc0716bf8799bcb71b6bMulti-scale Ensemble Modeling of Modular Proteins with Intrinsically Disordered Linker Regions: Application to p53Terakawa, Tsuyoshi; Higo, Junichi; Takada, ShojiBiophysical Journal (2014), 107 (3), 721-729CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)In eukaryotic proteins, intrinsically disordered regions (IDRs) are ubiquitous and often exist in linker regions that flank the functional domains of modular proteins, regulating their functions. For detailed structural ensemble modeling of IDRs, we propose a multiscale method for IDRs that possess significant long-range order in modular proteins and apply it to the eukaryotic transcription factor p53 as an example. First, we performed all-atom (AA) mol. dynamics (MD) simulations of the explicitly solvated p53 linker region, without exptl. restraint terms, finding fractional long-range contacts within the linker. Second, we fed this AA MD ensemble into a coarse-grained (CG) model, finding an optimal set of contact potentials. The optimized CG MD simulations reproduced the contact probability map from the AA MD simulations. Finally, we performed the CG MD simulation of the tetrameric p53 fragments including the core domains, the linker, and the tetramerization domain. Using the obtained ensemble, we theor. calcd. the small angle x-ray scattering (SAXS) profile of this fragment. The obtained SAXS profile agrees well with the expt. We also found that the long-range contacts in the p53 linker region are required to reproduce the exptl. SAXS profile. The developed framework in which we calc. the long-range contact probability map from the AA MD simulation and incorporate it to the CG model can be applied to broad range of IDRs.
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537Norgaard, A. B.; Ferkinghoff-Borg, J.; Lindorff-Larsen, K. Experimental Parameterization of an Energy Function for the Simulation of Unfolded Proteins Biophys. J. 2008, 94, 182– 192 DOI: 10.1529/biophysj.107.108241Google Scholar537https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXkvFY%253D&md5=1a76ebf781f80aada40e86d42a4cc6b1Experimental parameterization of an energy function for the simulation of unfolded proteinsNorgaard, Anders B.; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, KrestenBiophysical Journal (2008), 94 (1), 182-192CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The detn. of conformational preferences in unfolded and disordered proteins is an important challenge in structural biol. The authors here describe an algorithm to optimize energy functions for the simulation of unfolded proteins. The procedure is based on the max. likelihood principle and employs a fast and efficient gradient descent method to find the set of parameters of the energy function that best explain the exptl. data. The authors first validate the method by using synthetic ref. data, and subsequently apply the algorithms to data from NMR spin-labeling expts. on the Δ131Δ fragment of Staphylococcal nuclease. A significant strength of the procedure that the authors present is that it directly uses exptl. data to optimize the energy parameters, without relying on the availability of high resoln. structures. The procedure is fully general and can be applied to a range of exptl. data and energy functions including the force fields used in mol. dynamics simulations.
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538Amorós, D.; Ortega, A.; García de la Torre, J. Prediction of Hydrodynamic and Other Solution Properties of Partially Disordered Proteins with a Simple, Coarse-Grained Model J. Chem. Theory Comput. 2013, 9, 1678– 1685 DOI: 10.1021/ct300948uGoogle Scholar538https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXnvVGrsw%253D%253D&md5=5c4629fe843769e938d5a4b60328d09ePrediction of Hydrodynamic and Other Solution Properties of Partially Disordered Proteins with a Simple, Coarse-Grained ModelAmoros, D.; Ortega, A.; Garcia de la Torre, J.Journal of Chemical Theory and Computation (2013), 9 (3), 1678-1685CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The possibility of validating structures of intrinsically disordered proteins against soln. properties is a goal that would be most helpful in the understanding of their function. The authors have devised a scheme for the prediction of soln. properties of partially disordered proteins that comprise one or more ordered domains, along with flexible tails or linkers. A very simple, coarse-grained, residue-level model, which is easily parametrized using available structural information, along with previously developed tools for the simulation of soln. conformation and dynamics, allows the prediction of properties like sedimentation coeffs., relaxation times, and x-ray or neutron scattering. This is demonstrated for a variety of partially disordered proteins, for which well-characterized soln. properties are very accurately evaluated, with predictions falling in most cases within exptl. errors.
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539Qin, S.; Zhou, H.-X. Effects of Macromolecular Crowding on the Conformational Ensembles of Disordered Proteins J. Phys. Chem. Lett. 2013, 4, 3429– 3434 DOI: 10.1021/jz401817xGoogle Scholar539https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFWlurbL&md5=32eb5f746de4d8b82f3df03c4b94e202Effects of Macromolecular Crowding on the Conformational Ensembles of Disordered ProteinsQin, Sanbo; Zhou, Huan-XiangJournal of Physical Chemistry Letters (2013), 4 (20), 3429-3434CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)Due to their conformational malleability, intrinsically disordered proteins (IDPs) are particularly susceptible to influences of crowded cellular environments. Here we report a computational study of the effects of macromol. crowding on the conformational ensemble of a coarse-grained IDP model, by using two approaches. In one, the IDP is simulated along with the crowders; in the other, crowder-free simulations are postprocessed to predict the conformational ensembles under crowding. We found significant decreases in the radius of gyration of the IDP under crowding, and suggest repulsive interactions with crowders as a common cause for chain compaction in a no. of exptl. studies. The postprocessing approach accurately reproduced the conformational ensembles of the IDP in the direct simulations here, and holds enormous potential for realistic modeling of IDPs under crowding, by permitting thorough conformation sampling for the proteins even when they and the crowders are both represented at the all-atom level.
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540Wang, J.; Wang, Y.; Chu, X.; Hagen, S. J.; Han, W.; Wang, E. Multi-Scaled Explorations of Binding-Induced Folding of Intrinsically Disordered Protein Inhibitor IA3 to its Target Enzyme PLoS Comput. Biol. 2011, 7, e1001118 DOI: 10.1371/journal.pcbi.1001118Google Scholar540https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXltVWltLw%253D&md5=eb9f2910bd98103e585d1cd36bd97da1Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzymeWang, Jin; Wang, Yong; Chu, Xiakun; Hagen, Stephen J.; Han, Wei; Wang, ErkangPLoS Computational Biology (2011), 7 (4), e1001118CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Biomol. function is realized by recognition, and increasing evidence shows that recognition is detd. not only by structure but also by flexibility and dynamics. The authors explored a biomol. recognition process that involves a major conformational change - protein folding. In particular, the authors explore the binding-induced folding of IA3, an intrinsically disordered protein that blocks the active site cleft of the yeast aspartic proteinase saccharopepsin (YPrA) by folding its own N-terminal residues into an amphipathic alpha helix. The authors developed a multi-scaled approach that explores the underlying mechanism by combining structure-based mol. dynamics simulations at the residue level with a stochastic path method at the at. level. Both the free energy profile and the assocd. kinetic paths reveal a common scheme whereby IA3 binds to its target enzyme prior to folding itself into a helix. This theor. result is consistent with recent time-resolved expts. Furthermore, exploration of the detailed trajectories reveals the important roles of non-native interactions in the initial binding that occurs prior to IA3 folding. In contrast to the common view that non-native interactions contribute only to the roughness of landscapes and impede binding, the non-native interactions here facilitate binding by reducing significantly the entropic search space in the landscape. The information gained from multi-scaled simulations of the folding of this intrinsically disordered protein in the presence of its binding target may prove useful in the design of novel inhibitors of aspartic proteinases.
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541Stadler, A. M.; Stingaciu, L.; Radulescu, A.; Holderer, O.; Monkenbusch, M.; Biehl, R.; Richter, D. Internal Nanosecond Dynamics in the Intrinsically Disordered Myelin Basic Protein J. Am. Chem. Soc. 2014, 136, 6987– 6994 DOI: 10.1021/ja502343bGoogle Scholar541https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmslSqsr4%253D&md5=0e3b54caec9499f890643f5c62085046Internal nanosecond dynamics in the intrinsically disordered myelin basic proteinStadler, Andreas M.; Stingaciu, Laura; Radulescu, Aurel; Holderer, Olaf; Monkenbusch, Michael; Biehl, Ralf; Richter, DieterJournal of the American Chemical Society (2014), 136 (19), 6987-6994CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Intrinsically disordered proteins lack a well-defined folded structure and contain a high degree of structural freedom and conformational flexibility, which is expected to enhance binding to their physiol. targets. In soln. and in the lipid-free state, myelin basic protein (MBP) belongs to this class of proteins. Here, Using small-angle scattering, MBP was found to be structurally disordered similar to Gaussian chains. The combination of structural and hydrodynamic information revealed an intermediary compactness of the protein between globular proteins and random coil polymers. Modeling by a coarse-grained structural ensemble gave indications for a compact core with flexible ends. Neutron spin-echo (NSE) spectroscopy measurements revealed a large contribution of internal dynamics to the overall diffusion. The exptl. results showed a high flexibility of the structural ensemble. Displacement patterns along the 1st 2 normal modes demonstrated that collective stretching and bending motions dominated the internal modes. The obsd. dynamics represented nanosecond conformational fluctuations within the reconstructed coarse-grained structural ensemble, allowing the exploration of a large configurational space. In an alternative approach, the authors investigated if models from polymer theory, recently used for the interpretation of fluorescence spectroscopy expts. on disordered proteins, were suitable for the interpretation of the obsd. motions. Within the framework of the Zimm model with internal friction (ZIF), a large offset of 81.6 ns was needed as an addn. to all relaxation times due to intrachain friction sources. The ZIF model, however, showed small but systematic deviations from the measured data. The large value of the internal friction led to the breakdown of the Zimm model.
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542Yu, H.; Han, W.; Ma, W.; Schulten, K. Transient beta-hairpin formation in alpha-synuclein monomer revealed by coarse-grained molecular dynamics simulation J. Chem. Phys. 2015, 143, 243142 DOI: 10.1063/1.4936910Google ScholarThere is no corresponding record for this reference.
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543Ghavami, A.; Veenhoff, L. M.; van der Giessen, E.; Onck, P. R. Probing the disordered domain of the nuclear pore complex through coarse-grained molecular dynamics simulations Biophys. J. 2014, 107, 1393– 1402 DOI: 10.1016/j.bpj.2014.07.060Google Scholar543https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsFags73O&md5=65a8bee4d1b11608c44609721832fba7Probing the Disordered Domain of the Nuclear Pore Complex through Coarse-Grained Molecular Dynamics SimulationsGhavami, Ali; Veenhoff, Liesbeth M.; van der Giessen, Erik; Onck, Patrick R.Biophysical Journal (2014), 107 (6), 1393-1402CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The distribution of disordered proteins (FG-nups) that line the transport channel of the nuclear pore complex (NPC) is investigated by means of coarse-grained mol. dynamics simulations. A one-bead-per-amino-acid model is presented that accounts for the hydrophobic/hydrophilic and electrostatic interactions between different amino acids, polarity of the solvent, and screening of free ions. The results indicate that the interaction of the FG-nups forms a high-d., doughnut-like distribution inside the NPC, which is rich in FG-repeats. We show that the obtained distribution is encoded in the amino-acid sequence of the FG-nups and is driven by both electrostatic and hydrophobic interactions. To explore the relation between structure and function, we have systematically removed different combinations of FG-nups from the pore to simulate inviable and viable NPCs that were previously studied exptl. The obtained d. distributions show that the max. d. of the FG-nups inside the pore does not exceed 185 mg/mL in the nonviable NPCs, whereas for the wild-type and viable NPCs, this value increases to 300 mg/mL. Interestingly, this max. d. is not correlated to the total mass of the FG-nups, but depends sensitively on the specific combination of essential Nups located in the central plane of the NPC.
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544Ahlstrom, L. S.; Law, S. M.; Dickson, A.; Brooks, C. L. Multiscale Modeling of a Conditionally Disordered pH-Sensing Chaperone J. Mol. Biol. 2015, 427, 1670– 1680 DOI: 10.1016/j.jmb.2015.01.002Google Scholar544https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtF2gs74%253D&md5=492c3d19e063027187c0edab01d4c76dMultiscale Modeling of a Conditionally Disordered pH-Sensing ChaperoneAhlstrom, Logan S.; Law, Sean M.; Dickson, Alex; Brooks, Charles L.Journal of Molecular Biology (2015), 427 (8), 1670-1680CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The pH-sensing chaperone HdeA promotes the survival of enteropathogenic bacteria during transit through the harshly acidic environment of the mammalian stomach. At low pH, HdeA transitions from an inactive, folded, dimer to chaperone-active, disordered, monomers to protect against the acid-induced aggregation of periplasmic proteins. Toward achieving a detailed mechanistic understanding of the pH response of HdeA, we develop a multiscale modeling approach to capture its pH-dependent thermodn. Our approach combines pKa (logarithmic acid dissocn. const.) calcns. from all-atom const. pH mol. dynamics simulations with coarse-grained modeling and yields new, at.-level, insights into HdeA chaperone function that can be directly tested by expt. "pH triggers" that significantly destabilize the dimer are each located near the N-terminus of a helix, suggesting that their neutralization at low pH destabilizes the helix macrodipole as a mechanism of monomer disordering. Moreover, we observe a non-monotonic change in the pH-dependent stability of HdeA, with maximal stability of the dimer near pH 5. This affect is attributed to the protonation Glu37, which exhibits an anomalously high pKa value and is located within the hydrophobic dimer interface. Finally, the pH-dependent binding pathway of HdeA comprises a partially unfolded, dimeric intermediate that becomes increasingly stable relative to the native dimer at lower pH values and displays key structural features for chaperone-substrate interaction. We anticipate that the insights from our model will help inform ongoing NMR and biochem. investigations.
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545Koehler Leman, J.; Ulmschneider, M. B.; Gray, J. J. Computational modeling of membrane proteins Proteins: Struct., Funct., Genet. 2015, 83, 1– 24 DOI: 10.1002/prot.24703Google Scholar545https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFeitrvO&md5=b1dc8d57d59832241025d99a9ba93855Computational modeling of membrane proteinsKoehler Leman, Julia; Ulmschneider, Martin B.; Gray, Jeffrey J.Proteins: Structure, Function, and Bioinformatics (2015), 83 (1), 1-24CODEN: PSFBAF ISSN:. (Wiley-Blackwell)A review. The detn. of membrane protein (MP) structures has always trailed that of sol. proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure detn. The percentage of MP structures in the protein databank (PDB) has been at a const. 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was exptl. elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topol. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and mol. dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.
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546Baker, M. Making membrane proteins for structures: a trillion tiny tweaks Nat. Methods 2010, 7, 429– 434 DOI: 10.1038/nmeth0610-429Google Scholar546https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsF2it7o%253D&md5=45cec959130da53eaf570f3767dd9087Making membrane proteins for structures: a trillion tiny tweaksBaker, MonyaNature Methods (2010), 7 (6), 429-434CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)A review on multiple means to get high-quality membrane proteins for x-ray crystallog. and NMR spectroscopy studies.
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547Marrink, S. J.; Mark, A. E. Molecular dynamics simulation of the formation, structure, and dynamics of small phospholipid vesicles J. Am. Chem. Soc. 2003, 125, 15233– 15242 DOI: 10.1021/ja0352092Google Scholar547https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXovVOhsbc%253D&md5=75693a417eba874efe843800d7a28069Molecular Dynamics Simulation of the Formation, Structure, and Dynamics of Small Phospholipid VesiclesMarrink, Siewert J.; Mark, Alan E.Journal of the American Chemical Society (2003), 125 (49), 15233-15242CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Here, we use coarse grained mol. dynamics (MD) simulations to study the spontaneous aggregation of dipalmitoylphosphatidylcholine (DPPC) lipids into small unilamellar vesicles. We show that the aggregation process occurs on a nanosecond time scale, with bicelles and cuplike vesicles formed at intermediate stages. Formation of hemifused vesicles is also obsd. at higher lipid concn. With either 25% dipalmitoylphosphatidylethanolamine (DPPE) or lysoPC mixed into the system, the final stages of the aggregation process occur significantly faster. The structure of the spontaneously formed vesicles is analyzed in detail. Microsecond simulations of isolated vesicles reveal significant differences in the packing of the lipids between the inner and outer monolayers, and between PC, PE, and lysoPC. Due to the small size of the vesicles they remain almost perfectly spherical, undergoing very limited shape fluctuations or bilayer undulations. The lipid lateral diffusion rate is found to be faster in the outer than in the inner monolayer. The water permeability coeff. of the pure DPPC vesicles is of the order of 10-3 cm s-1, in agreement with exptl. measurements.
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548Knecht, V.; Marrink, S. J. Molecular dynamics simulations of lipid vesicle fusion in atomic detail Biophys. J. 2007, 92, 4254– 4261 DOI: 10.1529/biophysj.106.103572Google Scholar548https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmsFeksb4%253D&md5=996b9ea4dc0571b488541c38374f2acfMolecular dynamics simulations of lipid vesicle fusion in atomic detailKnecht, Volker; Marrink, Siewert-JanBiophysical Journal (2007), 92 (12), 4254-4261CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The fusion of a membrane-bonded vesicle with a target membrane is a key step in intracellular trafficking, exocytosis, and drug delivery. Mol. dynamics simulations have been used to study the fusion of small unilamellar vesicles composed of a dipalmitoyl-phosphatidylcholine (DPPC)/palmitic acid 1:2 mixt. in at. detail. The simulations were performed at 350-370 K and mimicked the temp.- and pH-induced fusion of DPPC/palmitic acid vesicles from expts. by others. To make the calcns. computationally feasible, a vesicle simulated at periodic boundary conditions was fused with its periodic image. Starting from a performed stalk between the outer leaflets of the vesicle and its periodic image, a hemifused state formed within 2 ns. In one out of six simulations, a transient pore formed close to the stalk, resulting in the mixing of DPPC lipids between the outer and the inner leaflet. The hemifused state was (meta)stable on a timescale of up to 11 ns. Forcing a single lipid into the interior of the hemifusion diaphragm induced the formation and expansion of a fusion pore on a nanosecond timescale. This work opens the perspective to study a wide variety of mesoscopic biol. processes in at. detail.
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549Bennett, W. F.; MacCallum, J. L.; Hinner, M. J.; Marrink, S. J.; Tieleman, D. P. Molecular view of cholesterol flip-flop and chemical potential in different membrane environments J. Am. Chem. Soc. 2009, 131, 12714– 12720 DOI: 10.1021/ja903529fGoogle Scholar549https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXpslahtb8%253D&md5=0ac4464b09d393f9a4d377c9cc2f2470Molecular View of Cholesterol Flip-Flop and Chemical Potential in Different Membrane EnvironmentsBennett, W. F. Drew; MacCallum, Justin L.; Hinner, Marlon J.; Marrink, Siewert J.; Tieleman, D. PeterJournal of the American Chemical Society (2009), 131 (35), 12714-12720CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The relative stability of cholesterol in cellular membranes and the thermodn. of fluctuations from equil. have important consequences for sterol trafficking and lateral domain formation. We used mol. dynamics computer simulations to investigate the partitioning of cholesterol in a systematic set of lipid bilayers. In addn. to atomistic simulations, we undertook a large set of coarse grained simulations, which allowed longer time and length scales to be sampled. Our results agree with recent expts. that the rate of cholesterol flip-flop can be fast on physiol. time scales, while extending our understanding of this process to a range of lipids. We predicted that the rate of flip-flop is strongly dependent on the compn. of the bilayer. In polyunsatd. bilayers, cholesterol undergoes flip-flop on a submicrosecond time scale, while flip-flop occurs in the second range in satd. bilayers with high cholesterol content. We also calcd. the free energy of cholesterol desorption, which can be equated to the excess chem. potential of cholesterol in the bilayer compared to water. The free energy of cholesterol desorption from a DPPC bilayer is 80 kJ/mol, compared to 67 kJ/mol for a DAPC bilayer. In general, cholesterol prefers more ordered and rigid bilayers and has the lowest affinity for bilayers with two polyunsatd. chains. Overall, the simulations provide a detailed mol. level thermodn. description of cholesterol interactions with lipid bilayers, of fundamental importance to eukaryotic life.
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550Ogushi, F.; Ishitsuka, R.; Kobayashi, T.; Sugita, Y. Rapid flip-flop motions of diacylglycerol and ceramide in phospholipid bilayers Chem. Phys. Lett. 2012, 522, 96 DOI: 10.1016/j.cplett.2011.11.057Google Scholar550https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktFCjsQ%253D%253D&md5=ea07a981543f0037e086dff6c46f84e0Rapid flip-flop motions of diacylglycerol and ceramide in phospholipid bilayersOgushi, Fumiko; Ishitsuka, Reiko; Kobayashi, Toshihide; Sugita, YujiChemical Physics Letters (2012), 522 (), 96-102CODEN: CHPLBC; ISSN:0009-2614. (Elsevier B.V.)The authors investigated flip-flop motions of diacylglycerol and ceramide in phospholipid bilayers using coarse-grained mol. dynamics simulations. In the simulations, flip-flop motions of diacylglycerol and ceramide in the DAPC membrane were slower than cholesterol. The rates correlated with the no. of unsatd. bonds in the membrane phospholipids and hence with fluidity of membranes. These findings qual. agreed with corresponding exptl. data. Statistical anal. of the trajectories suggests that flip-flop could be approximated as a Poisson process. The rate of the transverse movement was influenced by depth of the polar head group in the membrane and extent of interaction with water.
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551Esteban-Martin, S.; Risselada, H. J.; Salgado, J.; Marrink, S. J. Stability of asymmetric lipid bilayers assessed by molecular dynamics simulations J. Am. Chem. Soc. 2009, 131, 15194– 15202 DOI: 10.1021/ja904450tGoogle Scholar551https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht1Sqt7%252FJ&md5=4b1f14269207a499e35e3c9766156ebfStability of Asymmetric Lipid Bilayers Assessed by Molecular Dynamics SimulationsEsteban-Martin, Santi; Risselada, H. Jelger; Salgado, Jesus; Marrink, Siewert J.Journal of the American Chemical Society (2009), 131 (42), 15194-15202CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The asym. insertion of amphiphiles into biol. membranes compromises the balance between the inner and outer monolayers. As a result, area expansion of the receiving leaflet and curvature strain may lead to membrane permeation, shape changes, or membrane fusion events. Both atomistic and coarse-grained mol. dynamics simulations of dipalmitoyl-phosphatidylcholine (DPPC) bilayers were conducted to study the effect of an asym. distribution of lipids between the two monolayers on membrane stability. Highly asym. lipid bilayers were found to be surprisingly stable within the sub-microsecond time span of the simulations. Even the limiting case of a monolayer immersed in water ruptured spontaneously only after at least 20 ns simulation. A thermal shock could destabilize these kinetically trapped states. Mixed systems composed of DPPC and short tail diC8PC lipids were also studied, showing that the presence of the cone-shaped short tail lipid facilitates the release of tension in the asym. systems via formation of a transmembrane pore. Thus, asym. area expansion and curvature stress cooperate to yield bilayer disruption. It appears that, although asym. area expansion destabilizes the bilayer structure, the activation energy for trans-monolayer lipid re-equilibration is increased. Such a large kinetic barrier can be reduced by lipids with pos. spontaneous curvature. These effects are important at the onset of bilayer destabilization phenomena, such as lipid pore formation and membrane fusion, and should be considered for the mechanism of induction of such processes by peptides and proteins.
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552Kasson, P. M.; Lindahl, E.; Pande, V. S. Atomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tails PLoS Comput. Biol. 2010, 6, e1000829 DOI: 10.1371/journal.pcbi.1000829Google Scholar552https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cnivVahtg%253D%253D&md5=fc4db798ffdd01d9c65400061156a2aaAtomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tailsKasson Peter M; Lindahl Erik; Pande Vijay SPLoS computational biology (2010), 6 (6), e1000829 ISSN:.Membrane fusion is essential to both cellular vesicle trafficking and infection by enveloped viruses. While the fusion protein assemblies that catalyze fusion are readily identifiable, the specific activities of the proteins involved and nature of the membrane changes they induce remain unknown. Here, we use many atomic-resolution simulations of vesicle fusion to examine the molecular mechanisms for fusion in detail. We employ committor analysis for these million-atom vesicle fusion simulations to identify a transition state for fusion stalk formation. In our simulations, this transition state occurs when the bulk properties of each lipid bilayer remain in a lamellar state but a few hydrophobic tails bulge into the hydrophilic interface layer and make contact to nucleate a stalk. Additional simulations of influenza fusion peptides in lipid bilayers show that the peptides promote similar local protrusion of lipid tails. Comparing these two sets of simulations, we obtain a common set of structural changes between the transition state for stalk formation and the local environment of peptides known to catalyze fusion. Our results thus suggest that the specific molecular properties of individual lipids are highly important to vesicle fusion and yield an explicit structural model that could help explain the mechanism of catalysis by fusion proteins.
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553Laganowsky, A.; Reading, E.; Allison, T. M.; Ulmschneider, M. B.; Degiacomi, M. T.; Baldwin, A. J.; Robinson, C. V. Membrane proteins bind lipids selectively to modulate their structure and function Nature 2014, 510, 172 DOI: 10.1038/nature13419Google Scholar553https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFygs7%252FF&md5=02119c92280671a8dea0e7b76ea0f857Membrane proteins bind lipids selectively to modulate their structure and functionLaganowsky, Arthur; Reading, Eamonn; Allison, Timothy M.; Ulmschneider, Martin B.; Degiacomi, Matteo T.; Baldwin, Andrew J.; Robinson, Carol V.Nature (London, United Kingdom) (2014), 510 (7503), 172-175CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to det. the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate (PI), in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin (CDL) imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar expts. identify AmtB as being highly selective for phosphatidylglycerol (PG), prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resoln. structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane protein structure and/or function. We anticipate that these findings will be important not only for defining the selectivity of membrane proteins towards lipids, but also for understanding the role of lipids in modulating protein function or drug binding.
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554Bond, P. J.; Sansom, M. S. Insertion and assembly of membrane proteins via simulation J. Am. Chem. Soc. 2006, 128, 2697– 2704 DOI: 10.1021/ja0569104Google Scholar554https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtVKjsr4%253D&md5=9c915e74b4a1223b9dd0183bdd2bee73Insertion and Assembly of Membrane Proteins via SimulationBond, Peter J.; Sansom, Mark S. P.Journal of the American Chemical Society (2006), 128 (8), 2697-2704CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Interactions of lipids are central to the folding and stability of membrane proteins. Coarse-grained mol. dynamics simulations have been used to reveal the mechanisms of self-assembly of protein/membrane and protein/detergent complexes for representatives of two classes of membrane protein, namely, glycophorin (a simple α-helical bundle) and OmpA (a β-barrel). The accuracy of the coarse-grained simulations is established via comparison with the equiv. atomistic simulations of self-assembly of protein/detergent micelles. The simulation of OmpA/bilayer self-assembly reveals how a folded outer membrane protein can be inserted in a bilayer. The glycophorin/bilayer simulation supports the two-state model of membrane folding, in which transmembrane helix insertion precedes dimer self-assembly within a bilayer. The simulations also suggest that a dynamic equil. exists between the glycophorin helix monomer and dimer within a bilayer. The simulated glycophorin helix dimer is remarkably close in structure to that revealed by NMR. Thus, coarse-grained methods may help to define mechanisms of membrane protein (re)folding and will prove suitable for simulation of larger scale dynamic rearrangements of biol. membranes.
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555Hall, B. A.; Chetwynd, A. P.; Sansom, M. S. Exploring peptide-membrane interactions with coarse-grained MD simulations Biophys. J. 2011, 100, 1940– 1948 DOI: 10.1016/j.bpj.2011.02.041Google Scholar555https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvVKhsrc%253D&md5=d0d0312559a1a2da28a1b6b7e931bd35Exploring Peptide-Membrane Interactions with Coarse-Grained MD SimulationsHall, Benjamin A.; Chetwynd, Alan P.; Sansom, Mark S. P.Biophysical Journal (2011), 100 (8), 1940-1948CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The interaction of α-helical peptides with lipid bilayers is central to our understanding of the physicochem. principles of biol. membrane organization and stability. Mutations that alter the position or orientation of an α-helix within a membrane, or that change the probability that the α-helix will insert into the membrane, can alter a range of membrane protein functions. We describe a comparative coarse-grained mol. dynamics simulation methodol., based on self-assembly of a lipid bilayer in the presence of an α-helical peptide, which allows us to model membrane transmembrane helix insertion. We validate this methodol. against available exptl. data for synthetic model peptides (WALP23 and LS3). Simulation-based ests. of apparent free energies of insertion into a bilayer of cystic fibrosis transmembrane regulator-derived helixes correlate well with published data for translocon-mediated insertion. Comparison of values of the apparent free energy of insertion from self-assembly simulations with those from coarse-grained mol. dynamics potentials of mean force for model peptides, and with translocon-mediated insertion of cystic fibrosis transmembrane regulator-derived peptides suggests a nonequil. model of helix insertion into bilayers.
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556Sobhanifar, S.; Schneider, B.; Lohr, F.; Gottstein, D.; Ikeya, T.; Mlynarczyk, K.; Pulawski, W.; Ghoshdastider, U.; Kolinski, M.; Filipek, S. Structural investigation of the C-terminal catalytic fragment of presenilin 1 Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 9644– 9649 DOI: 10.1073/pnas.1000778107Google ScholarThere is no corresponding record for this reference.
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557Klingelhoefer, J. W.; Carpenter, T.; Sansom, M. S. Peptide nanopores and lipid bilayers: interactions by coarse-grained molecular-dynamics simulations Biophys. J. 2009, 96, 3519– 3528 DOI: 10.1016/j.bpj.2009.01.046Google Scholar557https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnvVert74%253D&md5=10b6f8c757b2f4ed7bbdc8d380a98a1cPeptide nanopores and lipid bilayers: interactions by coarse-grained molecular-dynamics simulationsKlingelhoefer, Jochen W.; Carpenter, Timothy; Sansom, Mark S. P.Biophysical Journal (2009), 96 (9), 3519-3528CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)A set of 49 protein nanopore-lipid bilayer systems was explored by means of coarse-grained mol.-dynamics simulations to study the interactions between nanopores and the lipid bilayers in which they are embedded. The seven nanopore species investigated represent the two main structural classes of membrane proteins (α-helical and β-barrel), and the seven different bilayer systems range in thickness from ∼28 to ∼43 Å. The study focuses on the local effects of hydrophobic mismatch between the nanopore and the lipid bilayer. The effects of nanopore insertion on lipid bilayer thickness, the dependence between hydrophobic thickness and the obsd. nanopore tilt angle, and the local distribution of lipid types around a nanopore in mixed-lipid bilayers are all analyzed. Different behavior for nanopores of similar hydrophobic length but different geometry is obsd. The local lipid bilayer perturbation caused by the inserted nanopores suggests possible mechanisms for both lipid bilayer-induced protein sorting and protein-induced lipid sorting. A correlation between smaller lipid bilayer thickness (larger hydrophobic mismatch) and larger nanopore tilt angle is obsd. and, in the case of larger hydrophobic mismatches, the simulated tilt angle distribution seems to broaden. Furthermore, both nanopore size and key residue types (e.g., tryptophan) seem to influence the level of protein tilt, emphasizing the reciprocal nature of nanopore-lipid bilayer interactions.
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558Balali-Mood, K.; Bond, P. J.; Sansom, M. S. Interaction of monotopic membrane enzymes with a lipid bilayer: a coarse-grained MD simulation study Biochemistry 2009, 48, 2135– 2145 DOI: 10.1021/bi8017398Google Scholar558https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXit1Wgtbw%253D&md5=7d24e712ae6651696a102ae60cd9eb2dInteraction of Monotopic Membrane Enzymes with a Lipid Bilayer: A Coarse-Grained MD Simulation StudyBalali-Mood, Kia; Bond, Peter J.; Sansom, Mark S. P.Biochemistry (2009), 48 (10), 2135-2145CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)Monotopic membrane proteins bind tightly to cell membranes but do not generally span the lipid bilayer. Their interactions with lipid bilayers may be studied via coarse-grained mol. dynamics (CG-MD) simulations. Understanding such interactions is important as monotopic enzymes frequently act on hydrophobic substrates, while x-ray structures rarely provide direct information about their interactions with membranes. CG-MD self-assembly simulations enable prediction of the orientation and depth of insertion into a lipid bilayer of a monotopic protein, and also of the interactions of individual protein residues with lipid mols. The CG-MD method has been evaluated via comparison with extended (>30 ns) atomistic simulations of monoamine oxidase, revealing good agreement between the results of coarse-grained and atomistic simulations. CG-MD simulations have been applied to a set of 11 monotopic proteins for which three-dimensional structures are available. These proteins may be divided into two groups on the basis of the results of the simulations. One group consists of those proteins which are inserted into the lipid bilayer to a limited extent, interacting mainly at the phospholipid-water interface. The second group consists of those which are inserted more deeply into the bilayer. Those monotopic proteins which are inserted more deeply cause significant local perturbation of bilayer properties such as bilayer thickness. Deeper insertion seems to correlate with a greater no. of basic residues in the "foot" whereby a monotopic protein interacts with the membrane.
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559Sansom, M. S.; Scott, K. A.; Bond, P. J. Coarse-grained simulation: a high-throughput computational approach to membrane proteins Biochem. Soc. Trans. 2008, 36, 27– 32 DOI: 10.1042/BST0360027Google Scholar559https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1ajtb0%253D&md5=424f251326616431102765093ba07a84Coarse-grained simulation: a high-throughput computational approach to membrane proteinsSansom, Mark S. P.; Scott, Kathryn A.; Bond, Peter J.Biochemical Society Transactions (2008), 36 (1), 27-32CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)A review. An understanding of the interactions of membrane proteins with a lipid bilayer environment is central to relating their structure to their function and stability. A high-throughput approach to prediction of membrane protein interactions with a lipid bilayer based on coarse-grained Mol. Dynamics simulations is described. This method has been used to develop a database of CG simulations (coarse-grained simulations) of membrane proteins. Comparison of CG simulations and AT simulations (atomistic simulations) of lactose permease reveals good agreement between the two methods in terms of predicted lipid headgroup contacts. Both CG and AT simulations predict considerable local bilayer deformation by the voltage sensor domain of the potassium channel KvAP.
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560Dominguez, L.; Meredith, S. C.; Straub, J. E.; Thirumalai, D. Transmembrane fragment structures of amyloid precursor protein depend on membrane surface curvature J. Am. Chem. Soc. 2014, 136, 854– 857 DOI: 10.1021/ja410958jGoogle Scholar560https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFOnsbjP&md5=9f9a6c85d62696895fdedb7da53492f4Transmembrane Fragment Structures of Amyloid Precursor Protein Depend on Membrane Surface CurvatureDominguez, Laura; Meredith, Stephen C.; Straub, John E.; Thirumalai, DavidJournal of the American Chemical Society (2014), 136 (3), 854-857CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The amyloid β (Aβ) peptide assocd. with Alzheimer's disease results from processing of the amyloid precursor protein (APP) by secretases. Cleavage of APP by β-secretase produces a 99 amino acid C-terminal fragment of APP (C99) consisting of a single transmembrane (TM) helix. Simulations of C99 congeners and structural studies of C99 in surfactant micelles and lipid vesicles have shown that a key peptide structural motif is a prominent "GG-kink," centered at two glycines dividing the TM helix. The flexibility of the GG-kink is important in the processing of C99 by γ-secretase. We performed multiscale simulations of C9915-55 in a DPC surfactant micelle and POPC lipid bilayer in order to elucidate the role of membrane surface curvature in modulating the peptide structure. C9915-55 in a DPC surfactant micelle possesses a "GG-kink," in the TM domain near the dynamic hinge located at G37/G38. Such a kink is not obsd. in C9915-55 in a POPC lipid bilayer. Intramol. interaction between the extracellular and TM domains of C9915-55 is enhanced in the micelle environment, influencing helical stability, TM helix extension, exposure to water, and depth of insertion in the lipophilic region. Our results show that the fluctuations of the structural ensemble of APP are strongly influenced by membrane surface curvature.
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561Long, S. B.; Tao, X.; Campbell, E. B.; MacKinnon, R. Atomic structure of a voltage-dependent K+ channel in a lipid membrane-like environment Nature 2007, 450, 376– U373 DOI: 10.1038/nature06265Google Scholar561https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtlajs7%252FN&md5=45593aca2f588a16cc49bbddcc20a4e3Atomic structure of a voltage-dependent K+ channel in a lipid membrane-like environmentLong, Stephen B.; Tao, Xiao; Campbell, Ernest B.; MacKinnon, RoderickNature (London, United Kingdom) (2007), 450 (7168), 376-382CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Voltage-dependent K+ (Kv) channels repolarize the action potential in neurons and muscle. This type of channel is gated directly by membrane voltage through protein domains known as voltage sensors, which are mol. voltmeters that read the membrane voltage and regulate the pore. Here we describe the structure of a chimeric voltage-dependent K+ channel, which we call the 'paddle-chimera channel', in which the voltage-sensor paddle has been transferred from Kv2.1 to Kv1.2. Crystd. in complex with lipids, the complete structure at 2.4 angstroem resoln. reveals the pore and voltage sensors embedded in a membrane-like arrangement of lipid mols. The detailed structure, which can be compared directly to a large body of functional data, explains charge stabilization within the membrane and suggests a mechanism for voltage-sensor movements and pore gating.
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562Sengupta, D.; Chattopadhyay, A. Identification of cholesterol binding sites in the serotonin1A receptor J. Phys. Chem. B 2012, 116, 12991– 12996 DOI: 10.1021/jp309888uGoogle Scholar562https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFWks77O&md5=7d6baa0a1397fc7d0ad6119d4865295bIdentification of cholesterol binding sites in the serotonin1A receptorSengupta, Durba; Chattopadhyay, AmitabhaJournal of Physical Chemistry B (2012), 116 (43), 12991-12996CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The serotonin1A receptor is a representative member of the G protein-coupled receptor (GPCR) superfamily and serves as an important drug target in the development of therapeutic agents for neuropsychiatric disorders. Previous work has shown the requirement of membrane cholesterol in the organization, dynamics, and function of the serotonin1A receptor. Here, the authors show that membrane cholesterol binds preferentially to certain sites on the serotonin1A receptor by performing multiple, long time scale MARTINI coarse-grain mol. dynamics simulations. Interestingly, these results identified the highly conserved cholesterol recognition/interaction amino acid consensus (CRAC) motif on transmembrane helix V as one of the sites with high cholesterol occupancy, thereby confirming its role as a putative cholesterol binding motif. These results represent the 1st direct evidence for membrane cholesterol binding to specific sites on the serotonin1A receptor and represent an important step in the overall understanding of GPCR function in health and disease.
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563Koivuniemi, A.; Vuorela, T.; Kovanen, P. T.; Vattulainen, I.; Hyvonen, M. T. Lipid exchange mechanism of the cholesteryl ester transfer protein clarified by atomistic and coarse-grained simulations PLoS Comput. Biol. 2012, 8, e1002299 DOI: 10.1371/journal.pcbi.1002299Google Scholar563https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFSqu7k%253D&md5=13185165cb3d37e76faacc2d8a7cd895Lipid exchange mechanism of the cholesteryl ester transfer protein clarified by atomistic and coarse-grained simulationsKoivuniemi, Artturi; Vuorela, Timo; Kovanen, Petri T.; Vattulainen, Ilpo; Hyvonen, Marja T.PLoS Computational Biology (2012), 8 (1), e1002299CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Cholesteryl ester transfer protein (CETP) transports cholesteryl esters, triglycerides, and phospholipids between different lipoprotein fractions in blood plasma. The inhibition of CETP has been shown to be a sound strategy to prevent and treat the development of coronary heart disease. We employed mol. dynamics simulations to unravel the mechanisms assocd. with the CETP-mediated lipid exchange. To this end we used both atomistic and coarse-grained models whose results were consistent with each other. We found CETP to bind to the surface of high d. lipoprotein (HDL)-like lipid droplets through its charged and tryptophan residues. Upon binding, CETP rapidly (in about 10 ns) induced the formation of a small hydrophobic patch to the phospholipid surface of the droplet, opening a route from the core of the lipid droplet to the binding pocket of CETP. This was followed by a conformational change of helix X of CETP to an open state, in which we found the accessibility of cholesteryl esters to the C-terminal tunnel opening of CETP to increase. Furthermore, in the absence of helix X, cholesteryl esters rapidly diffused into CETP through the C-terminal opening. The results provide compelling evidence that helix X acts as a lid which conducts lipid exchange by alternating the open and closed states. The findings have potential for the design of novel mol. agents to inhibit the activity of CETP.
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564Pleskot, R.; Pejchar, P.; Zarsky, V.; Staiger, C. J.; Potocky, M. Structural insights into the inhibition of actin-capping protein by interactions with phosphatidic acid and phosphatidylinositol (4,5)-bisphosphate PLoS Comput. Biol. 2012, 8, e1002765 DOI: 10.1371/journal.pcbi.1002765Google ScholarThere is no corresponding record for this reference.
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565Stansfeld, P. J.; Hopkinson, R.; Ashcroft, F. M.; Sansom, M. S. PIP(2)-binding site in Kir channels: definition by multiscale biomolecular simulations Biochemistry 2009, 48, 10926– 10933 DOI: 10.1021/bi9013193Google ScholarThere is no corresponding record for this reference.
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566Yin, F.; Kindt, J. T. Hydrophobic mismatch and lipid sorting near OmpA in mixed bilayers: atomistic and coarse-grained simulations Biophys. J. 2012, 102, 2279– 2287 DOI: 10.1016/j.bpj.2012.04.005Google ScholarThere is no corresponding record for this reference.
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567Arnarez, C.; Mazat, J. P.; Elezgaray, J.; Marrink, S. J.; Periole, X. Evidence for cardiolipin binding sites on the membrane-exposed surface of the cytochrome bc1 J. Am. Chem. Soc. 2013, 135, 3112– 3120 DOI: 10.1021/ja310577uGoogle Scholar567https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVCjt7o%253D&md5=8b88191b2e174b337c8efdffca93b008Evidence for Cardiolipin Binding Sites on the Membrane-Exposed Surface of the Cytochrome bc1Arnarez, Clement; Mazat, Jean-Pierre; Elezgaray, Juan; Marrink, Siewert-J.; Periole, XavierJournal of the American Chemical Society (2013), 135 (8), 3112-3120CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The respiratory chain is located in the inner membrane of mitochondria and produces the major part of the ATP used by a cell. Cardiolipin (CL), a doubly-charged phospholipid composing ∼10-20% of the mitochondrial membrane, plays an important role in the function and supramol. organization of the respiratory chain complexes. We present an extensive set of coarse-grain mol. dynamics (CGMD) simulations aiming at the detn. of the preferential interfaces of CLs on the respiratory chain complex III (cytochrome bc1, CIII). Six CL binding sites are identified, including the CL binding sites known from earlier structural studies and buried in protein cavities. The simulations revealed the importance of two subunits of CIII (G and K in bovine heart) for the structural integrity of these internal CL binding sites. In addn., new binding sites are found on the membrane-exposed protein surface. The reproducibility of these binding sites over two species (bovine heart and yeast mitochondria) points to an important role for the function of the respiratory chain. Interestingly, the membrane-exposed CL binding sites are located on the matrix side of CIII in the inner membrane, and thus may provide localized sources of protons ready for uptake by CIII. Furthermore, we found that CLs bound to those membrane-exposed sites bridge the proteins during their assembly into supercomplexes by sharing the binding sites.
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568Weingarth, M.; Prokofyev, A.; van der Cruijsen, E. A.; Nand, D.; Bonvin, A. M.; Pongs, O.; Baldus, M. Structural determinants of specific lipid binding to potassium channels J. Am. Chem. Soc. 2013, 135, 3983– 3988 DOI: 10.1021/ja3119114Google Scholar568https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXivVyjtbs%253D&md5=8c667335f5f765a293dec730163cf341Structural Determinants of Specific Lipid Binding to Potassium ChannelsWeingarth, Markus; Prokofyev, Alexander; van der Cruijsen, Elwin A. W.; Nand, Deepak; Bonvin, Alexandre M. J. J.; Pongs, Olaf; Baldus, MarcJournal of the American Chemical Society (2013), 135 (10), 3983-3988CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)We have investigated specific lipid binding to the pore domain of potassium channels KcsA and chimeric KcsA-Kv1.3 on the structural and functional level using extensive coarse-grained and atomistic mol. dynamics (MD) simulations, solid-state NMR, and single channel measurements. We show that while KcsA activity is critically modulated by the specific and cooperative binding of anionic nonannular lipids close to the channel's selectivity filter, the influence of nonannular lipid binding on KcsA-Kv1.3 is much reduced. The diminished impact of specific lipid binding on KcsA-Kv1.3 results from a point-mutation at the corresponding nonannular lipid binding site leading to a salt-bridge between adjacent KcsA-Kv1.3 subunits, which is conserved in many voltage-gated potassium channels and prevents strong nonannular lipid binding to the pore domain. Our findings elucidate how protein-lipid and protein-protein interactions modulate K+ channel activity. The combination of MD, NMR, and functional studies as shown here may help to dissect the structural and dynamical processes that are crit. for the functioning of larger membrane proteins, including Kv channels in a membrane setting.
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569Sharma, S.; Juffer, A. H. An atomistic model for assembly of transmembrane domain of T cell receptor complex J. Am. Chem. Soc. 2013, 135, 2188– 2197 DOI: 10.1021/ja308413eGoogle ScholarThere is no corresponding record for this reference.
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570Dominguez, L.; Foster, L.; Meredith, S. C.; Straub, J. E.; Thirumalai, D. Structural heterogeneity in transmembrane amyloid precursor protein homodimer is a consequence of environmental selection J. Am. Chem. Soc. 2014, 136, 9619– 9626 DOI: 10.1021/ja503150xGoogle Scholar570https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpslegt74%253D&md5=34f02544624e8b0be212ab89c2cda440Structural heterogeneity in transmembrane amyloid precursor protein homodimer is a consequence of environmental selectionDominguez, Laura; Foster, Leigh; Meredith, Stephen C.; Straub, John E.; Thirumalai, D.Journal of the American Chemical Society (2014), 136 (27), 9619-9626CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The 99-residue C-terminal fragment of amyloid precursor protein (C99), consisting of a single transmembrane (TM) helix, is known to form homodimers. Homodimers can be processed by γ-secretase to produce amyloid-β (Aβ) protein, which is implicated in Alzheimer's disease (AD). While knowledge of the structure of C99 homodimers is of great importance, exptl. NMR studies and simulations have produced varying structural models, including right-handed and left-handed coiled-coils. In order to investigate the structure of this crit. protein complex, simulations of the C9915-55 homodimer in POPC membrane bilayer and dodecylphosphocholine (DPC) surfactant micelle environments were performed using a multiscale approach that blends atomistic and coarse-grained models. The C9915-55 homodimer adopted a dominant right-handed coiled-coil topol. consisting of 3 characteristic structural states in a bilayer, only one of which was dominant in the micelle. This structural study, which provides a self-consistent framework for understanding a no. of expts., showed that the energy landscape of the C99 homodimer supported a variety of slowly interconverting structural states. The relative importance of any given state could be modulated through environmental selection realized by altering the membrane or micelle characteristics.
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571Carpenter, T.; Bond, P. J.; Khalid, S.; Sansom, M. S. Self-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channel Biophys. J. 2008, 95, 3790– 3801 DOI: 10.1529/biophysj.108.131078Google Scholar571https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1eksr3L&md5=ae97377b16d555433a7de894577a910aSelf-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channelCarpenter, Timothy; Bond, Peter J.; Khalid, Syma; Sansom, Mark S. P.Biophysical Journal (2008), 95 (8), 3790-3801CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of α-helixes and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained mol. dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helixes during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helixes. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 × 5 μs) were used to study the tetramerization of inserted M2 helixes. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This anal. reveals that the M2 tetramer has 2 × rotationally sym. packing of the helixes. The helixes form a left-handed bundle, with a helix tilt angle of ∼16°. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundle's stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.
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572Provasi, D.; Boz, M. B.; Johnston, J. M.; Filizola, M. Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-association PLoS Comput. Biol. 2015, 11, e1004148 DOI: 10.1371/journal.pcbi.1004148Google Scholar572https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xpt12msLk%253D&md5=42f9876cca764097f69ea7ba9c4b6a37Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-associationProvasi, Davide; Boz, Mustafa Burak; Johnston, Jennifer M.; Filizola, MartaPLoS Computational Biology (2015), 11 (3), e1004148/1-e1004148/21CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Substantial evidence in support of the formation of opioid receptor (OR) di-/oligomers suggests previously unknown mechanisms used by these proteins to exert their biol. functions. In an attempt to guide exptl. assessment of the identity of the minimal signaling unit for ORs, we conducted extensive coarse-grained (CG) mol. dynamics (MD) simulations of different combinations of the three major OR subtypes, i.e., μ-OR, δ-OR, and κ-OR, in an explicit lipid bilayer. Specifically, we ran multiple, independent MD simulations of each homomeric μ-OR/μ-OR, δ-OR/δ-OR, and κ-OR/κ-OR complex, as well as two of the most studied heteromeric complexes, i.e., δ-OR/μ-OR and δ-OR/κ-OR, to derive the preferred supramol. organization and dimer interfaces of ORs in a cell membrane model. These simulations yielded over 250 μs of accumulated data, which correspond to approx. 1 ms of effective simulated dynamics according to established scaling factors of the CG model we employed. Anal. of these data indicates similar preferred supramol. organization and dimer interfaces of ORs across the different receptor subtypes, but also important differences in the kinetics of receptor assocn. at specific dimer interfaces. We also investigated the kinetic properties of interfacial lipids, and explored their possible role in modulating the rate of receptor assocn. and in promoting the formation of filiform aggregates, thus supporting a distinctive role of the membrane in OR oligomerization and, possibly, signaling.
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573Johnston, J. M.; Wang, H.; Provasi, D.; Filizola, M. Assessing the relative stability of dimer interfaces in g protein-coupled receptors PLoS Comput. Biol. 2012, 8, e1002649 DOI: 10.1371/journal.pcbi.1002649Google Scholar573https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1CnsLjE&md5=c28c9e997026a1f11fef3a717e94e167Assessing the relative stability of dimer interfaces in G protein-coupled receptorsJohnston, Jennifer M.; Wang, Hao; Provasi, Davide; Filizola, MartaPLoS Computational Biology (2012), 8 (8), e1002649CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Considerable evidence has accumulated in recent years suggesting that G protein-coupled receptors (GPCRs) assoc. in the plasma membrane to form homo- and/or heteromers. Nevertheless, the stoichiometry, fraction and lifetime of such receptor complexes in living cells remain topics of intense debate. Motivated by exptl. data suggesting differing stabilities for homomers of the cognate human β1- and β2-adrenergic receptors, we have carried out approx. 160 μs of biased mol. dynamics simulations to calc. the dimerization free energy of crystal structure-based models of these receptors, interacting at two interfaces that have often been implicated in GPCR assocn. under physiol. conditions. Specifically, results are presented for simulations of coarse-grained (MARTINI-based) and atomistic representations of each receptor, in homodimeric configurations with either transmembrane helixes TM1/H8 or TM4/3 at the interface, in an explicit lipid bilayer. Our results support a definite contribution to the relative stability of GPCR dimers from both interface sequence and configuration. We conclude that β1- and β2-adrenergic receptor homodimers with TM1/H8 at the interface are more stable than those involving TM4/3 and that this might be reconciled with exptl. studies by considering a model of oligomerization in which more stable TM1 homodimers diffuse through the membrane, transiently interacting with other protomers at interfaces involving other TM helixes.
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574Ayton, G. S.; Voth, G. A. Multiscale simulation of protein mediated membrane remodeling Semin. Cell Dev. Biol. 2010, 21, 357– 362 DOI: 10.1016/j.semcdb.2009.11.011Google Scholar574https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXkvFKrt78%253D&md5=278f7c0439def895bf49a1fcf6d6f018Multiscale simulation of protein mediated membrane remodelingAyton, Gary S.; Voth, Gregory A.Seminars in Cell & Developmental Biology (2010), 21 (4), 357-362CODEN: SCDBFX; ISSN:1084-9521. (Elsevier Ltd.)A review. Proteins interacting with membranes can result in substantial membrane deformations and curvatures. This effect is known in its broadest terms as membrane remodeling. This review article will survey current multiscale simulation methodologies that have been employed to examine protein mediated membrane remodeling.
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575Genheden, S.; Essex, J. W. A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes J. Chem. Theory Comput. 2015, 11, 4749– 4759 DOI: 10.1021/acs.jctc.5b00469Google Scholar575https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlymsbvL&md5=bbe0cddc06d9c83f0007e997029c871fA Simple and Transferable All-Atom/Coarse-Grained Hybrid Model to Study Membrane ProcessesGenheden, Samuel; Essex, Jonathan W.Journal of Chemical Theory and Computation (2015), 11 (10), 4749-4759CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)An efficient all-atom/coarse-grained hybrid model is presented and applied to study membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, the efficiency is improved by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different time steps. Furthermore, the interaction between the atoms and the coarse-grained beads is fine-tuned by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calcn. of small-mol. partition coeffs. Finally, the model is applied to membrane peptides. The tilt angle is studied of the Walp23 and Kalp23 helixes in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent mols. or tabulated potentials, thus offering a novel, simple approach to study membrane processes.
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576Vorobyov, I.; Kim, I.; Chu, Z. T.; Warshel, A. Refining the treatment of membrane proteins by coarse-grained models Proteins: Struct., Funct., Genet. 2016, 84, 92– 117 DOI: 10.1002/prot.24958Google ScholarThere is no corresponding record for this reference.
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577Kessel, A.; Shental-Bechor, D.; Haliloglu, T.; Ben-Tal, N. Interactions of hydrophobic peptides with lipid bilayers: Monte Carlo simulations with M2delta Biophys. J. 2003, 85, 3431– 3444 DOI: 10.1016/S0006-3495(03)74765-1Google ScholarThere is no corresponding record for this reference.
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578Maddox, M. W.; Longo, M. L. A Monte Carlo study of peptide insertion into lipid bilayers: equilibrium conformations and insertion mechanisms Biophys. J. 2002, 82, 244– 263 DOI: 10.1016/S0006-3495(02)75391-5Google ScholarThere is no corresponding record for this reference.
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579Milik, M.; Skolnick, J. Insertion of peptide chains into lipid membranes: an off-lattice Monte Carlo dynamics model Proteins: Struct., Funct., Genet. 1993, 15, 10– 25 DOI: 10.1002/prot.340150104Google ScholarThere is no corresponding record for this reference.
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580Baumgartner, A. Insertion and hairpin formation of membrane proteins: a Monte Carlo study Biophys. J. 1996, 71, 1248– 1255 DOI: 10.1016/S0006-3495(96)79324-4Google ScholarThere is no corresponding record for this reference.
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581Lopez, C. F.; Nielsen, S. O.; Srinivas, G.; Degrado, W. F.; Klein, M. L. Probing Membrane Insertion Activity of Antimicrobial Polymers via Coarse-grain Molecular Dynamics J. Chem. Theory Comput. 2006, 2, 649– 655 DOI: 10.1021/ct050298pGoogle Scholar581https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XislCjt70%253D&md5=b8298b5565fe9160a797c73d67ed383fProbing Membrane Insertion Activity of Antimicrobial Polymers via Coarse-Grain Molecular DynamicsLopez, Carlos F.; Nielsen, Steven O.; Srinivas, Goundla; DeGrado, William F.; Klein, Michael L.Journal of Chemical Theory and Computation (2006), 2 (3), 649-655CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Knowledge of the mechanism of action of antimicrobial agents is crucial for the development of new compds. to combat microbial pathogens. To this end, computational studies on the interaction of known membrane-active antimicrobial polymers with phospholipid bilayers reveal spontaneous membrane insertion and cooperative action at low and high concns., resp. In late-stage attack, antimicrobials cross the membrane core and occasionally align to provide a stepping-stone pathway for water permeation; this suggests a possible new mode of action that does not depend on pore formation for transport to and across the inner leaflet. The computations rationalize the obsd. activity of a new class of antimicrobial compds.
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582Dryga, A.; Chakrabarty, S.; Vicatos, S.; Warshel, A. Realistic simulation of the activation of voltage-gated ion channels Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 3335– 3340 DOI: 10.1073/pnas.1121094109Google ScholarThere is no corresponding record for this reference.
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583Kim, I.; Warshel, A. Coarse-grained simulations of the gating current in the voltage-activated Kv1.2 channel Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 2128– 2133 DOI: 10.1073/pnas.1324014111Google Scholar583https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXisFyis7Y%253D&md5=310e4cde327b90015d5a87e2a69714f1Coarse-grained simulations of the gating current in the voltage-activated Kv1.2 channelKim, Ilsoo; Warshel, AriehProceedings of the National Academy of Sciences of the United States of America (2014), 111 (6), 2128-2133CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Quant. structure-based modeling of voltage activation of ion channels is very challenging. For example, it is very hard to reach converging results, by microscopic simulations while macroscopic treatments involve major uncertainties regarding key features. The current work overcomes some of the above challenges by using our recently developed coarse-grained (CG) model in simulating the activation of the Kv1.2 channel. The CG model has allowed us to explore problems that cannot be fully addressed at present by microscopic simulations, while providing insights on some features that are not usually considered in continuum models, including the distribution of the electrolytes between the membrane and the electrodes during the activation process and thus the phys. nature of the gating current. Here, we demonstrate that the CG model yields realistic gating charges and free energy landscapes that allow us to simulate the fluctuating gating current in the activation processes. Our ability to simulate the time dependence of the fast gating current allows us to reproduce the obsd. trend and provides a clear description of its relationship to the landscape involved in the activation process.
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584Rychkova, A.; Vicatos, S.; Warshel, A. On the energetics of translocon-assisted insertion of charged transmembrane helices into membranes Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 17598– 17603 DOI: 10.1073/pnas.1012207107Google Scholar584https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlartbrL&md5=8138efcd04f563ae9dbe13388e271ba2On the energetics of translocon-assisted insertion of charged transmembrane helices into membranesRychkova, Anna; Vicatos, Spyridon; Warshel, AriehProceedings of the National Academy of Sciences of the United States of America (2010), 107 (41), 17598-17603, S17598/1-S17598/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The understanding of the mechanism of insertion of transmembrane (TM) helixes through the translocon presents a major open challenge. Although the exptl. information about the partition of the inserted helixes between the membrane and the soln. contains crucial information about this process, it is not clear how to ext. this information. In particular, it is not clear how to rationalize the small apparent insertion energy, ΔGapp, of an ionized residue in the center of a TM helix. Here we explore the nature of the insertion energies, asking what should be the value of these parameters if their measurements represent equil. conditions. This is done using a coarse-grained model with advanced electrostatic treatment. Estg. the energetics of ionized arginine of a TM helix in the presence of neighboring helixes or the translocon provides a rationale for the obsd. ΔGapp of ionized residues. It is concluded that the apparent insertion free energy of TM with charged residues reflects probably more than just the free energy of moving the isolate single helix from water into the membrane. The present approach should be effective not only in exploring the mechanism of the operation of the translocon but also for studies of other membrane proteins.
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585Alford, R. F.; Koehler Leman, J.; Weitzner, B. D.; Duran, A. M.; Tilley, D. C.; Elazar, A.; Gray, J. J. An Integrated Framework Advancing Membrane Protein Modeling and Design PLoS Comput. Biol. 2015, 11, e1004398 DOI: 10.1371/journal.pcbi.1004398Google Scholar585https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XkvVKit7o%253D&md5=4618d6db56c18c04a5dd63dd694241b9An integrated framework advancing membrane protein modeling and designAlford, Rebecca F.; Leman, Julia Koehler; Weitzner, Brian D.; Duran, Amanda M.; Tgilley, Drew C.; Elazar, Assaf; Gray, Jeffrey J.PLoS Computational Biology (2015), 11 (9), e1004398/1-e1004398/23CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Membrane proteins are crit. functional mols. in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to det. their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resoln. structural refinement; (3) protein-protein docking; and (4) assembly of sym. protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.
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586Xu, X.; Yan, C.; Wohlhueter, R.; Ivanov, I. Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic Resolution Comput. Struct. Biotechnol. J. 2015, 13, 492– 503 DOI: 10.1016/j.csbj.2015.08.005Google Scholar586https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFOlsbvK&md5=e7eeba75dfdaf67a6e41ea26cd3c8f19Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic ResolutionXu, Xiaojun; Yan, Chunli; Wohlhueter, Robert; Ivanov, IvayloComputational and Structural Biotechnology Journal (2015), 13 (), 492-503CODEN: CSBJAC; ISSN:2001-0370. (Elsevier B.V.)While conventional high-resoln. techniques in structural biol. are challenged by the size and flexibility of many biol. assemblies, recent advances in low-resoln. techniques such as cryo-electron microscopy (cryo-EM) and small angle X-ray scattering (SAXS) have opened up new avenues to define the structures of such assemblies. By systematically combining various sources of structural, biochem. and biophys. information, integrative modeling approaches aim to provide a unified structural description of such assemblies, starting from high-resoln. structures of the individual components and integrating all available information from low-resoln. exptl. methods. In this review, we describe integrative modeling approaches, which use complementary data from either cryo-EM or SAXS. Specifically, we focus on the popular mol. dynamics flexible fitting (MDFF) method, which has been widely used for flexible fitting into cryo-EM maps. Second, we describe hybrid mol. dynamics, Rosetta Monte-Carlo and min. ensemble search (MES) methods that can be used to incorporate SAXS into pseudoat. structural models. We present concise descriptions of the two methods and their most popular alternatives, along with select illustrative applications to protein/nucleic acid assemblies involved in DNA replication and repair.
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587Latek, D.; Kolinski, A. CABS-NMR--De novo tool for rapid global fold determination from chemical shifts, residual dipolar couplings and sparse methyl-methyl NOEs J. Comput. Chem. 2011, 32, 536– 544 DOI: 10.1002/jcc.21640Google ScholarThere is no corresponding record for this reference.
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588van der Schot, G.; Bonvin, A. M. Performance of the WeNMR CS-Rosetta3 web server in CASD-NMR J. Biomol. NMR 2015, 62, 497– 502 DOI: 10.1007/s10858-015-9942-7Google ScholarThere is no corresponding record for this reference.
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589Rossi, P.; Shi, L.; Liu, G.; Barbieri, C. M.; Lee, H. W.; Grant, T. D.; Luft, J. R.; Xiao, R.; Acton, T. B.; Snell, E. H. A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta Proteins: Struct., Funct., Genet. 2015, 83, 309– 317 DOI: 10.1002/prot.24719Google ScholarThere is no corresponding record for this reference.
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590Jang, R.; Wang, Y.; Xue, Z. D.; Zhang, Y. NMR data-driven structure determination using NMR-I-TASSER in the CASD-NMR experiment J. Biomol. NMR 2015, 62, 511– 525 DOI: 10.1007/s10858-015-9914-yGoogle ScholarThere is no corresponding record for this reference.
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591Zheng, W. Accurate flexible fitting of high-resolution protein structures into cryo-electron microscopy maps using coarse-grained pseudo-energy minimization Biophys. J. 2011, 100, 478– 488 DOI: 10.1016/j.bpj.2010.12.3680Google Scholar591https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVGmtQ%253D%253D&md5=5ea50acf9c5eaeca1b8ee88e629333d9Accurate Flexible Fitting of High-Resolution Protein Structures into Cryo-Electron Microscopy Maps Using Coarse-Grained Pseudo-Energy MinimizationZheng, WenjunBiophysical Journal (2011), 100 (2), 478-488CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Cryo-electron microscopy (cryo-EM) has been widely used to explore conformational states of large biomol. assemblies. The detailed interpretation of cryo-EM data requires the flexible fitting of a known high-resoln. protein structure into a low-resoln. cryo-EM map. To this end, we have developed what we believe is a new method based on a two-bead-per-residue protein representation, and a modified form of the elastic network model that allows large-scale conformational changes while maintaining pseudobonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified elastic network model energy with a cryo-EM-fitting score and a collision energy that penalizes steric collisions. Unlike previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled. We have validated our method for a diverse set of 10 pairs of protein structures using simulated cryo-EM maps with a range of resolns. and in the absence/presence of random noise. We have shown that our method is both accurate and efficient compared with alternative techniques, and its performance is robust to the addn. of random noise. Our method is also shown to be useful for the flexible fitting of three exptl. cryo-EM maps.
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592Grubisic, I.; Shokhirev, M. N.; Orzechowski, M.; Miyashita, O.; Tama, F. Biased coarse-grained molecular dynamics simulation approach for flexible fitting of X-ray structure into cryo electron microscopy maps J. Struct. Biol. 2010, 169, 95– 105 DOI: 10.1016/j.jsb.2009.09.010Google ScholarThere is no corresponding record for this reference.
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593Zhang, J.; Baker, M. L.; Schroder, G. F.; Douglas, N. R.; Reissmann, S.; Jakana, J.; Dougherty, M.; Fu, C. J.; Levitt, M.; Ludtke, S. J. Mechanism of folding chamber closure in a group II chaperonin Nature 2010, 463, 379– 383 DOI: 10.1038/nature08701Google Scholar593https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXovVGgtQ%253D%253D&md5=ac6c036c116db4a4b4abdefceb2ed091Mechanism of folding chamber closure in a group II chaperoninZhang, Junjie; Baker, Matthew L.; Schroeder, Gunnar F.; Douglas, Nicholai R.; Reissmann, Stefanie; Jakana, Joanita; Dougherty, Matthew; Fu, Caroline J.; Levitt, Michael; Ludtke, Steven J.; Frydman, Judith; Chiu, WahNature (London, United Kingdom) (2010), 463 (7279), 379-383CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Group II chaperonins are essential mediators of cellular protein folding in eukaryotes and archaea. These oligomeric protein machines, ∼1 megadalton, consist of two back-to-back rings encompassing a central cavity that accommodates polypeptide substrates. Chaperonin-mediated protein folding is critically dependent on the closure of a built-in lid, which is triggered by ATP hydrolysis. The structural rearrangements and mol. events leading to lid closure are still unknown. Here we report four single particle cryo-electron microscopy (cryo-EM) structures of Mm-cpn, an archaeal group II chaperonin, in the nucleotide-free (open) and nucleotide-induced (closed) states. The 4.3 Å resoln. of the closed conformation allowed construction of the first ever at. model directly from the single particle cryo-EM d. map, in which we were able to visualize the nucleotide and more than 70% of the side chains. The model of the open conformation was obtained by using the deformable elastic network modeling with the 8 Å resoln. open-state cryo-EM d. restraints. Together, the open and closed structures show how local conformational changes triggered by ATP hydrolysis lead to an alteration of intersubunit contacts within and across the rings, ultimately causing a rocking motion that closes the ring. Our analyses show that there is an intricate and unforeseen set of interactions controlling allosteric communication and inter-ring signaling, driving the conformational cycle of group II chaperonins. Beyond this, we anticipate that our methodol. of combining single particle cryo-EM and computational modeling will become a powerful tool in the detn. of at. details involved in the dynamic processes of macromol. machines in soln.
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594DiMaio, F.; Song, Y.; Li, X.; Brunner, M. J.; Xu, C.; Conticello, V.; Egelman, E.; Marlovits, T. C.; Cheng, Y.; Baker, D. Atomic-accuracy models from 4.5-A cryo-electron microscopy data with density-guided iterative local refinement Nat. Methods 2015, 12, 361– 365 DOI: 10.1038/nmeth.3286Google Scholar594https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MrnslOksA%253D%253D&md5=a019ca4dd689f2321c103867d74db255Atomic-accuracy models from 4.5-ÅA cryo-electron microscopy data with density-guided iterative local refinementDiMaio Frank; Song Yifan; Baker David; Song Yifan; Li Xueming; Cheng Yifan; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Xu Chunfu; Conticello Vincent; Egelman Edward; Baker DavidNature methods (2015), 12 (4), 361-365 ISSN:.We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-ÅA resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.
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595Demers, J. P.; Habenstein, B.; Loquet, A.; Kumar Vasa, S.; Giller, K.; Becker, S.; Baker, D.; Lange, A.; Sgourakis, N. G. High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy Nat. Commun. 2014, 5, 4976 DOI: 10.1038/ncomms5976Google Scholar595https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXksVeqsr8%253D&md5=6a65afb2807b2b58e2eb04b3780cae35High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopyDemers, Jean-Philippe; Habenstein, Birgit; Loquet, Antoine; Kumar Vasa, Suresh; Giller, Karin; Becker, Stefan; Baker, David; Lange, Adam; Sgourakis, Nikolaos G.Nature Communications (2014), 5 (), 4976CODEN: NCAOBW; ISSN:2041-1723. (Nature Publishing Group)We introduce a general hybrid approach for detg. the structures of supramol. assemblies. Cryo-electron microscopy (cryo-EM) data define the overall envelope of the assembly and rigid-body orientation of the subunits while solid-state NMR (ssNMR) chem. shifts and distance constraints define the local secondary structure, protein fold and inter-subunit interactions. Finally, Rosetta structure calcns. provide a general framework to integrate the different sources of structural information. Combining a 7.7-Å cryo-EM d. map and 996 ssNMR distance constraints, the structure of the type-III secretion system needle of Shigella flexneri is detd. to a precision of 0.4 Å. The calcd. structures are cross-validated using an independent data set of 691 ssNMR constraints and scanning transmission electron microscopy measurements. The hybrid model resolves the conformation of the non-conserved N terminus, which occupies a protrusion in the cryo-EM d., and reveals conserved pore residues forming a continuous pattern of electrostatic interactions, thereby suggesting a mechanism for effector protein translocation.
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596Esquivel-Rodriguez, J.; Kihara, D. Computational methods for constructing protein structure models from 3D electron microscopy maps J. Struct. Biol. 2013, 184, 93– 102 DOI: 10.1016/j.jsb.2013.06.008Google ScholarThere is no corresponding record for this reference.
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597Shrestha, R.; Berenger, F.; Zhang, K. Y. Accelerating ab initio phasing with de novo models Acta Crystallogr., Sect. D: Biol. Crystallogr. 2011, 67, 804– 812 DOI: 10.1107/S090744491102779XGoogle ScholarThere is no corresponding record for this reference.
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598Shrestha, R.; Simoncini, D.; Zhang, K. Y. Error-estimation-guided rebuilding of de novo models increases the success rate of ab initio phasing Acta Crystallogr., Sect. D: Biol. Crystallogr. 2012, 68, 1522– 1534 DOI: 10.1107/S0907444912037961Google ScholarThere is no corresponding record for this reference.
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599Yang, S.; Park, S.; Makowski, L.; Roux, B. A rapid coarse residue-based computational method for x-ray solution scattering characterization of protein folds and multiple conformational states of large protein complexes Biophys. J. 2009, 96, 4449– 4463 DOI: 10.1016/j.bpj.2009.03.036Google Scholar599https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXpsFOrtrg%253D&md5=a84231b3eabd6b83a079a492099ecf81A rapid coarse residue-based computational method for X-ray solution scattering characterization of protein folds and multiple conformational states of large protein complexesYang, Sichun; Park, Sanghyun; Makowski, Lee; Roux, BenoitBiophysical Journal (2009), 96 (11), 4449-4463CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)We present a coarse residue-based computational method to rapidly compute the soln. scattering profile from a protein with dynamical fluctuations. The method is built upon a coarse-grained (CG) representation of the protein. This CG representation takes advantage of the intrinsic low-resoln. and CG nature of soln. scattering data. It allows rapid scattering detn. from a large no. of conformations that can be extd. from CG simulations to obtain scattering characterization of protein conformations. The method includes several important elements, effective residue structure factors derived from the Protein Data Bank, explicit treatment of water mols. in the hydration layer at the surface of the protein, and an ensemble av. of scattering from a variety of appropriate conformations to account for macromol. flexibility. This simplified method is calibrated and illustrated to accurately reproduce the exptl. scattering curve of Hen egg white lysozyme. We then illustrated the applications of this CG method by computing the soln. scattering patterns of several representative protein folds and multiple conformational states. The results suggest that soln. scattering data, when combined with the reliable computational method that we developed, show great potential for a better structural description of multidomain complexes in different functional states, and for recognizing structural folds when sequence similarity to a protein of known structure is low.
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600Stovgaard, K.; Andreetta, C.; Ferkinghoff-Borg, J.; Hamelryck, T. Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models BMC Bioinf. 2010, 11, 429 DOI: 10.1186/1471-2105-11-429Google Scholar600https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cjosl2rsQ%253D%253D&md5=ef71c9a203195bb3ce614b39e7cb55f3Calculation of accurate small angle X-ray scattering curves from coarse-grained protein modelsStovgaard Kasper; Andreetta Christian; Ferkinghoff-Borg Jesper; Hamelryck ThomasBMC bioinformatics (2010), 11 (), 429 ISSN:.BACKGROUND: Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS) is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. RESULTS: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. CONCLUSION: We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data.
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601Hagita, K.; McGreevy, R. L.; Arai, T.; Inui, M.; Matsuda, K.; Tamura, K. First example of multi-scale reverse Monte Carlo modeling for small-angle scattering experimental data using reverse mapping from coarse-grained particles to atoms J. Phys.: Condens. Matter 2010, 22, 404215 DOI: 10.1088/0953-8984/22/40/404215Google Scholar601https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlGls7vP&md5=9188c5d853dba7a768075eced225957dFirst example of multi-scale reverse Monte Carlo modeling for small-angle scattering experimental data using reverse mapping from coarse-grained particles to atomsHagita, K.; McGreevy, R. L.; Arai, T.; Inui, M.; Matsuda, K.; Tamura, K.Journal of Physics: Condensed Matter (2010), 22 (40), 404215/1-404215/11CODEN: JCOMEL; ISSN:0953-8984. (Institute of Physics Publishing)We propose a new method for multi-scale reverse Monte Carlo (RMC) modeling of small-angle scattering data using reverse mapping from coarse-grained particles to atoms in cases where scale sepn. cannot be assumed. For efficient RMC anal. for small-angle scattering data, it is important to det. a large scale structure with the lowest possible computing cost. In order to find this large scale structure, a method using coarse-grained particles instead of atoms is suitable. As our first example, we examine the structure of expanded fluid Hg near the crit. point. For this system, small-angle x-ray scattering (SAXS) data and wide-angle x-ray diffraction data (XRD) are obsd. in the same thermodn. state. First, RMC anal. using coarse-grained particles for SAXS data is performed. Second, RMC anal. for SAXS and XRD data is performed with the replacement of a coarse-grained particle by an ad hoc cluster of several Hg atoms. In the present study, we have detd. that the size of one coarse-grained particle corresponds to ten Hg atoms. The no. d. for the coarse-grained particles is set to one-tenth the actual no. d. of atoms and the cutoff length is three times (6.9 Å) that of Hg atoms (2.3 Å). As a result, this approach is found to be successful and the computing cost of RMC anal. can be reduced.
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602Haxton, T. K. High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained Sites J. Chem. Theory Comput. 2015, 11, 1244– 1254 DOI: 10.1021/ct500881xGoogle Scholar602https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitlKksbw%253D&md5=be0d6906322d0c0dc6ab026ab5e8d8f2High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained SitesHaxton, Thomas K.Journal of Chemical Theory and Computation (2015), 11 (3), 1244-1254CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We introduce a method to bring nearly atomistic resoln. to coarse-grained models, and we apply the method to proteins. Using a small no. of coarse-grained sites (about one per eight atoms) but assigning an independent three-dimensional orientation to each site, we preferentially integrate out stiff degrees of freedom (bond lengths and angles, as well as dihedral angles in rings) that are accurately approximated by their av. values, while retaining soft degrees of freedom (unconstrained dihedral angles) mostly responsible for conformational variability. We demonstrate that our scheme retains nearly atomistic resoln. by mapping all exptl. protein configurations in the Protein Data Bank onto coarse-grained configurations and then anal. backmapping those configurations back to all-atom configurations. This roundtrip mapping throws away all information assocd. with the eliminated (stiff) degrees of freedom except for their av. values, which we use to construct optimal backmapping functions. Despite the 4:1 redn. in the no. of degrees of freedom, we find that heavy atoms move only 0.051 Å on av. during the roundtrip mapping, while hydrogens move 0.179 Å on av., an unprecedented combination of efficiency and accuracy among coarse-grained protein models. We discuss the advantages of such a high-resoln. model for parametrizing effective interactions and accurately calcg. observables through direct or multiscale simulations.
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603Kang, M.; Roberts, C.; Cheng, Y.; Chang, C. E. Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 Protease J. Chem. Theory Comput. 2011, 7, 3438– 3446 DOI: 10.1021/ct2004885Google Scholar603https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFOitLfE&md5=38bd8818a7ec33b4fbb6ff9f86018972Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 ProteaseKang, Myungshim; Roberts, Christopher; Cheng, Yuhui; Chang, Chia-en A.Journal of Chemical Theory and Computation (2011), 7 (10), 3438-3446CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Most biol. processes are initiated or mediated by the assocn. of ligands and proteins. This work studies multistep, ligand-protein assocn. processes by Brownian dynamics simulations with coarse-grained models for HIV-1 protease (HIVp) and its neutral ligands. We report the av. assocn. times when the ligand concn. is 100 μM. The influence of crowding on the simulated binding time was also studied. HIVp has flexible loops that serve as a gate during the ligand binding processes. It is believed that the flaps are partially closed most of the time in its free state. To accelerate our simulations, we fixed a part of the HIVp and reparameterized our coarse-grained model, using atomistic mol. dynamics simulations, to reproduce the "gating" motions of HIVp. HIVp-ligand interactions changed the gating behavior of HIVp and helped ligands diffuse on HIVp surface to accelerate binding. The structural adjustment of the ligand toward its final stable state was the limiting step in the binding processes, which is highly system dependent. The intermol. attraction between the ligands and crowder proteins contributes the most to the crowding effects. The results highlight broader implications in recognition pathways under more complex environment that considers mol. dynamics and conformational changes. This work brings insights into ligand-protein assocns. and is helpful in the design of targeted ligands.
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604Negami, T.; Shimizu, K.; Terada, T. Protein-Ligand Binding Simulation with the Martini Coarse-Grained Force Field. Biophys. J. 2014, 106, 609a. DOI: 10.1016/j.bpj.2013.11.3370Google ScholarThere is no corresponding record for this reference.
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605Ruiz-Herrero, T.; Estrada, J.; Guantes, R.; Miguez, D. G. A tunable coarse-grained model for ligand-receptor interaction PLoS Comput. Biol. 2013, 9, e1003274 DOI: 10.1371/journal.pcbi.1003274Google ScholarThere is no corresponding record for this reference.
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606de Jong, D. H.; Baoukina, S.; Ingolfsson, H. I.; Marrink, S. J. Martini straight: Boosting performance using a shorter cutoff and GPUs Comput. Phys. Commun. 2016, 199, 1– 7 DOI: 10.1016/j.cpc.2015.09.014Google Scholar606https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhs1Krtb%252FJ&md5=9bb06db6dbe3171eb07bf7509105fc67Martini straight: Boosting performance using a shorter cutoff and GPUsde Jong, Djurre H.; Baoukina, Svetlana; Ingolfsson, Helgi I.; Marrink, Siewert J.Computer Physics Communications (2016), 199 (), 1-7CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier B.V.)In mol. dynamics simulations, sufficient sampling is of key importance and a continuous challenge in the field. The coarse grain Martini force field has been widely used to enhance sampling. In its original implementation, this force field applied a shifted Lennard-Jones potential for the non-bonded van der Waals interactions, to avoid problems related to a relatively short cutoff. Here we investigate the use of a straight cutoff Lennard-Jones potential with potential modifiers. Together with a Verlet neighbor search algorithm, the modified potential allows the use of GPUs to accelerate the computations in Gromacs. We find that this alternative potential has little influence on most of the properties studied, including partitioning free energies, bulk liq. properties and bilayer properties. At the same time, energy conservation is kept within reasonable bounds. We conclude that the newly proposed straight cutoff approach is a viable alternative to the std. shifted potentials used in Martini, offering significant speedup even in the absence of GPUs.
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607Lettieri, S.; Zuckerman, D. M. Accelerating molecular Monte Carlo simulations using distance and orientation-dependent energy tables: tuning from atomistic accuracy to smoothed ″coarse-grained″ models J. Comput. Chem. 2012, 33, 268– 275 DOI: 10.1002/jcc.21970Google ScholarThere is no corresponding record for this reference.
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608Tunbridge, I.; Best, R. B.; Gain, J.; Kuttel, M. M. Simulation of Coarse-Grained Protein-Protein Interactions with Graphics Processing Units J. Chem. Theory Comput. 2010, 6, 3588– 3600 DOI: 10.1021/ct1003884Google Scholar608https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1CmtLnE&md5=25836ea416b8414aab7135646358e849Simulation of Coarse-Grained Protein-Protein Interactions with Graphics Processing UnitsTunbridge, Ian; Best, Robert B.; Gain, James; Kuttel, Michelle M.Journal of Chemical Theory and Computation (2010), 6 (11), 3588-3600CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors report a hybrid parallel central and graphics processing units (CPU-GPU) implementation of a coarse-grained model for replica exchange Monte Carlo (REMC) simulations of protein assemblies. The authors describe the design, optimization, validation, and benchmarking of their algorithms, particularly the parallelization strategy, which is specific to the requirements of GPU hardware. Performance evaluation of the authors' hybrid implementation shows scaled speedup as compared to a single-core CPU; ref. simulations of small 100 residue proteins have a modest speedup of 4, while large simulations with thousands of residues are up to 1400 times faster. Importantly, the combination of coarse-grained models with highly parallel GPU hardware vastly increases the length- and time-scales accessible for protein simulation, making it possible to simulate much larger systems of interacting proteins than have previously been attempted. As a first step toward the simulation of the assembly of an entire viral capsid, the authors have demonstrated that the chosen coarse-grained model, together with REMC sampling, is capable of identifying the correctly bound structure, for a pair of fragments from the human hepatitis B virus capsid. The authors' parallel soln. can easily be generalized to other interaction functions and other types of macromols. and has implications for the parallelization of similar N-body problems that require random access lookups.
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609Czaplewski, C.; Liwo, A.; Makowski, M.; Oldziej, S.; Scheraga, H. A. Coarse-Grained Models of Proteins: Theory and Applications Multiscale Approaches to Protein Modeling 2011, 35– 83 DOI: 10.1007/978-1-4419-6889-0_3Google ScholarThere is no corresponding record for this reference.
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610Thorpe, I. F.; Goldenberg, D. P.; Voth, G. A. Exploration of transferability in multiscale coarse-grained peptide models J. Phys. Chem. B 2011, 115, 11911– 11926 DOI: 10.1021/jp204455gGoogle ScholarThere is no corresponding record for this reference.
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611Potoyan, D. A.; Savelyev, A.; Papoian, G. A. Recent successes in coarse-grained modeling of DNA Wires Comput. Mol. Sci. 2013, 3, 69– 83 DOI: 10.1002/wcms.1114Google ScholarThere is no corresponding record for this reference.
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612Boniecki, M. J.; Lach, G.; Dawson, W. K.; Tomala, K.; Lukasz, P.; Soltysinski, T.; Rother, K. M.; Bujnicki, J. M. SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction Nucleic Acids Res. 2016, 44, e63 DOI: 10.1093/nar/gkv1479Google Scholar612https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhs12qt73P&md5=f791ee4418e04676d97866fae0e6214aSimRNA: a coarse-grained method for RNA folding simulations and 3D structure predictionBoniecki, Michal J.; Lach, Grzegorz; Dawson, Wayne K.; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M.; Bujnicki, Janusz M.Nucleic Acids Research (2016), 44 (7), e63/1-e63/12CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)RNA mols. play fundamental roles in cellular processes. Their function and interactions with other biomols. are dependent on the ability to form complex three-dimensional (3D) structures. However, exptl. detn. of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approx. the energy and identify conformations that correspond to biol. relevant structures. SimRNA can fold RNA mols. using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use addnl. restraints, derived from exptl. or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures.
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613Hyeon, C.; Denesyuk, N. A.; Thirumalai, D. Development and Applications of Coarse-Grained Models for RNA Isr. J. Chem. 2014, 54, 1358– 1373 DOI: 10.1002/ijch.201400029Google Scholar613https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVSnurrN&md5=ffd7c390b827112b614cfb1dad168c05Development and Applications of Coarse-Grained Models for RNAHyeon, Changbong; Denesyuk, Natalia A.; Thirumalai, D.Israel Journal of Chemistry (2014), 54 (8-9), 1358-1373CODEN: ISJCAT; ISSN:0021-2148. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. In contrast to proteins, much less attention has been focused on the development of computational models for describing RNA mols., which are being recognized as playing key roles in many cellular functions. Current atomically detailed force fields are not accurate enough to capture the properties of even simple nucleic acid constructs. In this article, we review our efforts to develop coarse-grained (CG) models that capture the underlying physics for the particular length scale of interest. Two models are discussed. One of them is the three interaction site (TIS) model, in which each nucleotide is represented by three beads corresponding to sugar, phosphate, and base. The other is the self-organized polymer (SOP) model, in which each nucleotide is represented as a single interaction center. Applications of the TIS model to study the complexity of hairpin formation and the effects of crowding in a shifting equil. between two conformations in human telomerase pseudoknot are described. The work on crowding illustrates a direct link to the activity of telomerase. We use the SOP model to describe the response of the Tetrahymena ribozyme to force. The simulated unfolding pathways agree well with single mol. pulling expts. We also review predictions for the unfolding pathways for the Azoarcus ribozyme. The success of the CG applications to describe dynamics in RNA gives hope that more complex processes involving RNA-protein interactions can be tackled using variants of the proposed models.
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614Lopez, C. A.; Rzepiela, A. J.; de Vries, A. H.; Dijkhuizen, L.; Hunenberger, P. H.; Marrink, S. J.; Martini Coarse-Grained Force Field: Extension to Carbohydrates J. Chem. Theory Comput. 2009, 5, 3195– 3210 DOI: 10.1021/ct900313wGoogle Scholar614https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlChur%252FF&md5=e358a3bd8f010d95846c94836af9cc54Martini Coarse-Grained Force Field: Extension to CarbohydratesLopez, Cesar A.; Rzepiela, Andrzej J.; de Vries, Alex H.; Dijkhuizen, Lubbert; Hunenberger, Philippe H.; Marrink, Siewert J.Journal of Chemical Theory and Computation (2009), 5 (12), 3195-3210CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present an extension of the Martini coarse-grained force field to carbohydrates. The parametrization follows the same philosophy as was used previously for lipids and proteins, focusing on the reprodn. of partitioning free energies of small compds. between polar and nonpolar phases. The carbohydrate building blocks considered are the monosaccharides glucose and fructose and the disaccharides sucrose, trehalose, maltose, cellobiose, nigerose, laminarabiose, kojibiose, and sophorose. Bonded parameters for these saccharides are optimized by comparison to conformations sampled with an atomistic force field, in particular with respect to the representation of the most populated rotameric state for the glycosidic bond. Application of the new coarse-grained carbohydrate model to the oligosaccharides amylose and Curdlan shows a preservation of the main structural properties with 3 orders of magnitude more efficient sampling than the atomistic counterpart. Finally, the authors investigate the cryo- and anhydro-protective effect of glucose and trehalose on a lipid bilayer and find a strong decrease of the melting temp., in good agreement with both exptl. findings and atomistic simulation studies.
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615Lopez, C. A.; Bellesia, G.; Redondo, A.; Langan, P.; Chundawat, S. P. S.; Dale, B. E.; Marrink, S. J.; Gnanakaran, S. MARTINI Coarse-Grained Model for Crystalline Cellulose Microfibers J. Phys. Chem. B 2015, 119, 465– 473 DOI: 10.1021/jp5105938Google Scholar615https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFOjs7bI&md5=4cbec8abad57d8fe1ac7db96a932d50aMARTINI Coarse-Grained Model for Crystalline Cellulose MicrofibersLopez, Cesar A.; Bellesia, Giovanni; Redondo, Antonio; Langan, Paul; Chundawat, Shishir P. S.; Dale, Bruce E.; Marrink, Siewert J.; Gnanakaran, S.Journal of Physical Chemistry B (2015), 119 (2), 465-473CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Com.-scale biofuel prodn. requires a deep understanding of the structure and dynamics of its principal target: cellulose. However, an accurate description and modeling of this carbohydrate structure at the mesoscale remains elusive, particularly because of its overwhelming length scale and configurational complexity. We have derived a set of MARTINI coarse-grained force field parameters for the simulation of cryst. cellulose fibers. The model is adapted to reproduce different physicochem. and mech. properties of native cellulose Iβ. The model is able not only to handle a transition from cellulose Iβ to another cellulose allomorph, cellulose IIII, but also to capture the phys. response to temp. and mech. bending of longer cellulose nanofibers. By developing the MARTINI model of a solid cellulose cryst. fiber from the building blocks of a sol. cellobiose coarse-grained model, we have provided a systematic way to build MARTINI models for other cryst. biopolymers.
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Abstract
Figure 1
Figure 1. Application ranges for molecular modeling at different resolutions: quantum, all-atom, coarse-grained, and mesoscale. The plot shows approximate ranges of time scales and system sizes (lengths). The presented application ranges can be expanded by merging tools of different resolution into multiscale schemes.
Figure 2
Figure 2. All-atom representation of a tripeptide and the corresponding coarse-grained models. Various coarse-grained models are presented: Rosetta centroid mode (CEN) representation, (71)CABS, (72) UNRES, (73) SICHO, (74) and Levitt and Warshel model. (34) United side chain atoms are colored in orange. Pseudobonds of fluctuating length are shown as springs and lattice models are shown on the underlying lattice slide.
Figure 3
Figure 3. All-atom versus coarse-grained energy landscape. The figure illustrates the effect of the smoothening of the energy landscape in a coarse-grained model as compared to an all-atom model. The flattening enables efficient exploration of the energy landscape in search for the global minima, while avoiding traps in the local minima.
Figure 4
Figure 4. Example moves of a protein chain used for MC dynamics in the CABS model. (72) The upper panel shows local small-scale moves: two-bond and three-bond. The middle panel presents a large-scale move: small distance displacement of a chain fragment. The lower panel shows a “reptation” move in which a “bubble” on a protein chain is removed in one spot and randomly created somewhere else along the chain. A long random sequence of all moves provides an MC dynamics trajectory of the modeled protein chain. Large-scale and reptation moves are attempted less frequently than local moves. For clarity, the upper panel moves are shown with side chains (colored in orange), while the remaining panels without side chains. Positions of the alpha carbons are restricted to the underlying cubic lattice.
Figure 5
Figure 5. All-atom versus coarse-grained representation in the MARTINI model. (225) All-atom representation is shown in balls and sticks, while coarse-grained representation in large spheres. The figure shows an example lipid molecule, fragment of a protein chain, and water representations.
Figure 6
Figure 6. Typical multiscale modeling scheme that merges coarse-grained and all-atom modeling. In specific tasks, the resulting all-atom structures could be used as an input for the next stage of coarse-grained simulations. Other multiscale schemes are briefly discussed in the text.
Figure 7
Figure 7. Folding pathways obtained in ab initio simulations using the UNRES coarse-grained model and Langevin dynamics. (269) The pathways are presented for two proteins 1CLB and 1E0G. The protein models are marked with the RMSD values (root-mean-square deviation from the corresponding experimental structures, in Ångstroms) and simulation time. The simulations took a few hours of a single CPU time; therefore, the UNRES model provided a three to four-order-of-magnitude speed-up relative to all-atom MD simulations.
Figure 8
Figure 8. Protein-peptide docking with full flexibility of a protein loop region close to the binding site. The upper panel shows protein receptor flexibility during docking simulation. The starting protein structure (experimental structure in an unbound form) is shown in green. Simulated protein models are presented in blue while the flexible loop region in orange. The lower panel presents comparison of the predicted protein-peptide complex (blue) with the experimental structure of the complex (red) and the starting structure (green). Docking was performed using a coarse-grained CABS-dock method with no knowledge about the binding site or peptide conformation. During docking simulation the peptide was allowed to be fully mobile and flexible. The RMSD between the predicted and experimental peptide structure (after the best superposition of the receptor structure) was 2.03 Å. The example is described in detail elsewhere. (214)
Figure 9
Figure 9. Comparison of all-atom and coarse-grained modeling capabilities applied in simulations of the aggregation processes. The upper panel emphasizes the ability of coarse-grained models to model a full spectrum of aggregates that occur on different aggregation pathways, from a single monomer to a highly ordered fibril, including: (1) elongation by prestructured monomer addition, (2) lateral growth by templated protofilament assembly, (3) elongation by dock-lock monomer addition, and (4) growth by dock-lock oligomer addition. The lower panel highlights the capabilities of all-atom approaches limited to the forming of small oligomers or the short-scale dynamics of formed aggregates. The “Under Construction” sign emphasize the inaccessibility of the intermediate aggregation stages to all-atom modeling. Adapted from ref. (31) Copyright 2014 American Chemical Society.
Figure 10
Figure 10. Mechanism of coupled folding and binding of the pKID/KIX complex as revealed by coarse-grained modeling. (212) Docking simulations allowed full flexibility of the disordered pKID during a blind search for the binding site onto the KIX surface. During docking, the movement of the KIX backbone was limited to near-native fluctuations.
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16Lindorff-Larsen, K.; Piana, S.; Dror, R. O.; Shaw, D. E. How fast-folding proteins fold Science 2011, 334, 517– 520 DOI: 10.1126/science.120835116https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtlKjtrnL&md5=5a4eefa5b9d07b03819c491c105de75cHow fast-folding proteins foldLindorff-Larsen, Kresten; Piana, Stefano; Dror, Ron O.; Shaw, David E.Science (Washington, DC, United States) (2011), 334 (6055), 517-520CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)An outstanding challenge in the field of mol. biol. has been to understand the process by which proteins fold into their characteristic three-dimensional structures. Here, we report the results of at.-level mol. dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set of common principles underlying the folding of 12 structurally diverse proteins. In simulations conducted with a single physics-based energy function, the proteins, representing all three major structural classes, spontaneously and repeatedly fold to their exptl. detd. native structures. Early in the folding process, the protein backbone adopts a native-like topol. while certain secondary structure elements and a small no. of nonlocal contacts form. In most cases, folding follows a single dominant route in which elements of the native structure appear in an order highly correlated with their propensity to form in the unfolded state.
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17Piana, S.; Klepeis, J. L.; Shaw, D. E. Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations Curr. Opin. Struct. Biol. 2014, 24, 98– 105 DOI: 10.1016/j.sbi.2013.12.00617https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtVahurg%253D&md5=b15e49d29a51a4715d4e442d8e59d8e9Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulationsPiana, Stefano; Klepeis, John L.; Shaw, David E.Current Opinion in Structural Biology (2014), 24 (), 98-105CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Advances in computer hardware, software and algorithms have now made it possible to run atomistically detailed, physics-based mol. dynamics simulations of sufficient length to observe multiple instances of protein folding and unfolding within a single equil. trajectory. Although such studies have already begun to provide new insights into the process of protein folding, realizing the full potential of this approach will depend not only on simulation speed, but on the accuracy of the phys. models ('force fields') on which such simulations are based. While exptl. data are not available for comparison with all of the salient characteristics observable in long protein-folding simulations, we examine here the extent to which current force fields reproduce (and fail to reproduce) certain relevant properties for which such comparisons are possible.
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18Piana, S.; Lindorff-Larsen, K.; Shaw, D. E. Atomistic description of the folding of a dimeric protein J. Phys. Chem. B 2013, 117, 12935– 12942 DOI: 10.1021/jp402099318https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFKrs7bJ&md5=ea6e10e1468aba7a4675dc309c613aa9Atomistic Description of the Folding of a Dimeric ProteinPiana, Stefano; Lindorff-Larsen, Kresten; Shaw, David E.Journal of Physical Chemistry B (2013), 117 (42), 12935-12942CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Equil. mol. dynamics simulations are increasingly being used to describe the folding of individual proteins and protein domains at an at. level of detail. Isolated protein domains, however, are rarely obsd. in vivo, where multidomain proteins and multimeric assemblies are far more common. It is clear that the folding of such proteins is often inextricably coupled with the process of dimerization; indeed, many protein monomers and protein domains are not stable in isolation, and fold to their native structures only when stabilized by interactions with other members of a protein complex. Here, we use equil. mol. dynamics simulations with an aggregate simulation length of 4 ms to elucidate key aspects of the folding mechanism, and of the assocd. free-energy surface, of the Top7-CFr dimer, a 114-amino-acid protein homodimer with a mixed α/β structure. In these simulations, we obsd. a no. of folding and unfolding events. Each folding event was characterized by the assembly of two unfolded Top7-CFr monomers to form a stable, folded dimer. We found that the isolated monomer is unstable but that, early in the folding pathway, nascent native structure is stabilized by contacts between the two monomer subunits. These contacts are in some cases native, as in an induced-folding model, and in other cases non-native, as in a fly-casting mechanism. Occasionally, folding by conformational selection, in which both subunits form independently before dimerization, was also obsd. Folding then proceeds through the sequential addn. of strands to the protein β sheet. Although the long-time-scale relaxation of the folding process can be well described by a single exponential, these simulations reveal the presence of a no. of kinetic traps, characterized by structures in which individual strands are added in an incorrect order.
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19Kolinski, A.; Skolnick, J. Reduced models of proteins and their applications Polymer 2004, 45, 511– 524 DOI: 10.1016/j.polymer.2003.10.06419https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXpvFGiur4%253D&md5=09479fe5bfdf8d30f3b849bbc876e3b0Reduced models of proteins and their applicationsKolinski, Andrzej; Skolnick, JeffreyPolymer (2004), 45 (2), 511-524CODEN: POLMAG; ISSN:0032-3861. (Elsevier Science Ltd.)A review. Reduced computer modeling of proteins now has a history of about 30 yr. In spite of the enormous increase in computing abilities, reduced models are still very important tools for theor. studies of protein structure, dynamics and thermodn. Very simple, highly idealized lattice (and recently also off-lattice) models could be studied in great detail, providing valuable insight into the most general factors governing structure stability, folding kinetics and interactions responsible for characteristic two-state behavior near the folding temp. More complex models now enable modeling of real proteins on the level of low to moderate resoln., allowing the authors to address more detailed questions. Ab initio protein structure predictions, still being far from a routine task, have become feasible. When supported by evolutionary information from multiple sequence alignments and potential local and/or global structural similarity to known structures, reduced modeling opens up new areas of comparative modeling, thereby complementing contemporary structural genomics.
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20Tozzini, V. Coarse-grained models for proteins Curr. Opin. Struct. Biol. 2005, 15, 144– 150 DOI: 10.1016/j.sbi.2005.02.00520https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjtlaltLk%253D&md5=edd46ef4ea767f1084991e8062dd4043Coarse-grained models for proteinsTozzini, ValentinaCurrent Opinion in Structural Biology (2005), 15 (2), 144-150CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Coarse-grained models for proteins and biomol. aggregates have recently enjoyed renewed interest. Coarse-grained representations combined with enhanced computer power currently allow the simulation of systems of biol. relevant size (submicrometric) and timescale (microsecond or millisecond). Although these techniques still cannot be considered as predictive as all-atom simulations, noticeable advances have recently been achieved, mainly concerning the use of more rigorous parameterization techniques and novel algorithms for sampling configurational space. Moreover, the simulation size scales and timescales coincide with those that can be reached with the most advanced spectroscopic techniques, making it possible to directly compare simulation and expt.
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21Scheraga, H. A.; Khalili, M.; Liwo, A. Protein-folding dynamics: overview of molecular simulation techniques Annu. Rev. Phys. Chem. 2007, 58, 57– 83 DOI: 10.1146/annurev.physchem.58.032806.10461421https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXlslSisbc%253D&md5=22f6b8a0c6be71dbc5235e9aa9af9919Protein-folding dynamics: Overview of molecular simulation techniquesScheraga, Harold A.; Khalili, Mey; Liwo, AdamAnnual Review of Physical Chemistry (2007), 58 (), 57-83CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Mol. dynamics (MD) simulation is an invaluable tool with which to study protein folding in silico. Although just a few years ago the dynamic behavior of a protein mol. could be simulated only in the neighborhood of the exptl. conformation (or protein unfolding could be simulated at high temp.), the advent of distributed computing, new techniques such as replica-exchange MD, new approaches (based on, e.g., the stochastic difference equation), and physics-based reduced models of proteins now make it possible to study protein folding pathways from completely unfolded structures. Here, the authors present algorithms for MD simulations and their extensions and applications to protein folding studies, using all-atom models with explicit and implicit solvent as well as reduced models of polypeptide chains.
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22Clementi, C. Coarse-grained models of protein folding: toy models or predictive tools? Curr. Opin. Struct. Biol. 2008, 18, 10– 15 DOI: 10.1016/j.sbi.2007.10.00522https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVGitr0%253D&md5=477bb414c5c4e5409ce7c1d67b6a9a2bCoarse-grained models of protein folding: toy models or predictive tools?Clementi, CeciliaCurrent Opinion in Structural Biology (2008), 18 (1), 10-15CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. Coarse-grained models are emerging as a practical alternative to all-atom simulations for the characterization of protein folding mechanisms over long time scales. While a decade ago minimalist toy models were mainly designed to test general hypotheses on the principles regulating protein folding, the latest coarse-grained models are increasingly realistic and can be used to characterize quant. the detailed folding mechanism of specific proteins. The ability of such models to reproduce the essential features of folding dynamics suggests that each single at. degree of freedom is not by itself particularly relevant to folding and supports a statistical mech. approach to characterize folding transitions. When combined with more refined models and with exptl. studies, the systematic investigation of protein systems and complexes using coarse-grained models can advance our theor. understanding of the actual organizing principles that emerge from the complex network of interactions among protein at. constituents.
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23Espinoza-Fonseca, L. M. Thermodynamic aspects of coupled binding and folding of an intrinsically disordered protein: a computational alanine scanning study Biochemistry 2009, 48, 11332– 11334 DOI: 10.1021/bi901705zThere is no corresponding record for this reference.
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24Rader, A. J. Coarse-grained models: getting more with less Curr. Opin. Pharmacol. 2010, 10, 753– 759 DOI: 10.1016/j.coph.2010.09.00324https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVals7vO&md5=b28f9aad085e660ba636f6026cfc8e18Coarse-grained models: getting more with lessRader, A. J.Current Opinion in Pharmacology (2010), 10 (6), 753-759CODEN: COPUBK; ISSN:1471-4892. (Elsevier Ltd.)A review. There has recently been a proliferation of simplified, coarse-grained models to study aspects of biomol. dynamics, binding, assembly and folding. Despite differences in construction these various coarse-grained models share a common underlying desire to identify the minimal set of variables required to realistically describe the essence of these mols. Recent results emphasizing common and distinctive features are highlighted. For someone not involved in developing such models it is a daunting task to decide which, if any, coarse-grained model would be appropriate for a given system. Although this decision ultimately depends upon what kinds of questions one is probing, suggestions about reaching a conclusion are provided.
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25Kamerlin, S. C.; Vicatos, S.; Dryga, A.; Warshel, A. Coarse-grained (multiscale) simulations in studies of biophysical and chemical systems Annu. Rev. Phys. Chem. 2011, 62, 41– 64 DOI: 10.1146/annurev-physchem-032210-10333525https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVWmsbY%253D&md5=b209237e5d504e7ed1dfd820fc410615Coarse-grained (multiscale) simulations in studies of biophysical and chemical systemsKamerlin, Shina C. L.; Vicatos, Spyridon; Dryga, Anatoly; Warshel, AriehAnnual Review of Physical Chemistry (2011), 62 (), 41-64CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Recent years have witnessed an explosion in computational power, leading to attempts to model ever more complex systems. Nevertheless, there remain cases for which the use of brute-force computer simulations is clearly not the soln. In such cases, great benefit can be obtained from the use of phys. sound simplifications. The introduction of such coarse graining can be traced back to the early usage of a simplified model in studies of proteins. Since then, the field has progressed tremendously. In this review, we cover both key developments in the field and potential future directions. Addnl., particular emphasis is given to two general approaches, namely the renormalization and ref. potential approaches, which allow one to move back and forth between the coarse-grained (CG) and full models, as these approaches provide the foundation for CG modeling of complex systems.
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26Wu, C.; Shea, J. E. Coarse-grained models for protein aggregation Curr. Opin. Struct. Biol. 2011, 21, 209– 220 DOI: 10.1016/j.sbi.2011.02.00226https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkt1Kis7o%253D&md5=679de0734e82b4a09ad11ea3c9661eebCoarse-grained models for protein aggregationWu, Chun; Shea, Joan-EmmaCurrent Opinion in Structural Biology (2011), 21 (2), 209-220CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The aggregation of sol. proteins into fibrillar species is a complex process that spans many lengths and time scales, and that involves the formation of numerous on-pathway and off-pathway intermediate species. Despite this complexity, several elements underlying the aggregation process appear to be universal. The kinetics typically follow a nucleation-growth process, and proteins with very different sequences aggregate to form similar fibril structures, populating intermediates with sufficient structural similarity to bind to a common antibody. Here, the authors focus on a computational approach that exploits the common features of aggregation to simplify or 'coarse-grain' the representation of the protein. The authors highlight recent developments in coarse-grained modeling and illustrate how these models have been able to shed new light into the mechanisms of protein aggregation and the nature of aggregation intermediates. The roles of aggregation-prone conformations in the monomeric state and the influence of inherent β-sheet and aggregation propensities in modulating aggregation pathways are discussed.
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27Takada, S. Coarse-grained molecular simulations of large biomolecules Curr. Opin. Struct. Biol. 2012, 22, 130– 137 DOI: 10.1016/j.sbi.2012.01.01027https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XjtFShsrY%253D&md5=bb72fc85efeeaf49eb9090bd3e66ebc4Coarse-grained molecular simulations of large biomoleculesTakada, ShojiCurrent Opinion in Structural Biology (2012), 22 (2), 130-137CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Recently, we saw a dramatic increase in the no. of researches that rely on coarse-grained (CG) simulations for large biomols. Here, first, we briefly describe recently developed and used CG models for proteins and nucleic acids. Balance between structure-based and physico-chem. terms is a key issue. We also discuss the multiscale algorithms used to derive CG parameters. Next, we comment on the dynamics used in CG simulations with an emphasis on the importance of hydrodynamic interactions. We then discuss the pros and cons of CG simulations. Finally, we overview recent exciting applications of CG simulations. Publicly available tools and software for CG simulations are also summarized.
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28Saunders, M. G.; Voth, G. A. Coarse-graining methods for computational biology Annu. Rev. Biophys. 2013, 42, 73– 93 DOI: 10.1146/annurev-biophys-083012-13034828https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFGrs7bN&md5=e1a9f1f7a2854af4d391d66a85386da9Coarse-graining methods for computational biologySaunders, Marissa G.; Voth, Gregory A.Annual Review of Biophysics (2013), 42 (), 73-93CODEN: ARBNCV; ISSN:1936-122X. (Annual Reviews)A review. Connecting the mol. world to biol. requires understanding how mol.-scale dynamics propagate upward in scale to define the function of biol. structures. To address this challenge, multiscale approaches, including coarse-graining methods, become necessary. We discuss here the theor. underpinnings and history of coarse-graining and summarize the state of the field, organizing key methodologies based on an emerging paradigm for multiscale theory and modeling of biomol. systems. This framework involves an integrated, iterative approach to couple information from different scales. The primary steps, which coincide with key areas of method development, include developing first-pass coarse-grained models guided by exptl. results, performing numerous large-scale coarse-grained simulations, identifying important interactions that drive emergent behaviors, and finally reconnecting to the mol. scale by performing all-atom mol. dynamics simulations guided by the coarse-grained results. The coarse-grained modeling can then be extended and refined, with the entire loop repeated iteratively if necessary.
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29Baaden, M.; Marrink, S. J. Coarse-grain modelling of protein-protein interactions Curr. Opin. Struct. Biol. 2013, 23, 878– 886 DOI: 10.1016/j.sbi.2013.09.00429https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs12ltLzE&md5=92149c04b75e0f627a47ae3219e1bec3Coarse-grain modelling of protein-protein interactionsBaaden, Marc; Marrink, Siewert J.Current Opinion in Structural Biology (2013), 23 (6), 878-886CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)Here, we review recent advances towards the modeling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behavior. PPI models of sol. proteins and membrane proteins are sep. described, but we note the parallel development that is present in both research fields with three important themes: firstly, combining CG modeling with knowledge-based approaches to predict and refine protein-protein complexes; secondly, using physics-based CG models for de novo prediction of protein-protein complexes; and thirdly modeling of large scale protein aggregates.
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30Kar, P.; Feig, M. Recent advances in transferable coarse-grained modeling of proteins Adv. Protein Chem. Struct. Biol. 2014, 96, 143– 180 DOI: 10.1016/bs.apcsb.2014.06.00530https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xht1yrtrfF&md5=dce9f8dac24bdf5addc50af8b0f045f6Recent advances in transferable coarse-grained modeling of proteinsKar, Parimal; Feig, MichaelAdvances in Protein Chemistry and Structural Biology (2014), 96 (Biomolecular Modelling and Simulations), 143-180CODEN: APCSG7; ISSN:1876-1623. (Elsevier Ltd.)Computer simulations are indispensable tools for studying the structure and dynamics of biol. macromols. Biochem. processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biol. systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chem. specificity. We restrict ourselves to CG models of sol. proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.
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31Morriss-Andrews, A.; Shea, J. E. Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained Models J. Phys. Chem. Lett. 2014, 5, 1899– 1908 DOI: 10.1021/jz500684731https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXnvV2itL4%253D&md5=3ca8def9b53dd013ba5dd92005f3a166Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained ModelsMorriss-Andrews, Alex; Shea, Joan-EmmaJournal of Physical Chemistry Letters (2014), 5 (11), 1899-1908CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)A review. This Perspective highlights recent computational approaches to protein aggregation, from coarse-grained models to atomistic simulations, using the islet amyloid polypeptide (IAPP) as a case study. We discuss salient open questions where simulations can make an impact, discuss the successes and challenges met by simulations, and explore new directions.
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32Ingolfsson, H. I.; Lopez, C. A.; Uusitalo, J. J.; de Jong, D. H.; Gopal, S. M.; Periole, X.; Marrink, S. J. The power of coarse graining in biomolecular simulations Wiley Interdiscip. Rev. Comput. Mol. Sci. 2014, 4, 225– 248 DOI: 10.1002/wcms.116932https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtl2isLo%253D&md5=42af65cc906e785223ce08e4284f1c41The power of coarse graining in biomolecular simulationsIngolfsson, Helgi I.; Lopez, Cesar A.; Uusitalo, Jaakko J.; de Jong, Djurre H.; Gopal, Srinivasa M.; Periole, Xavier; Marrink, Siewert J.Wiley Interdisciplinary Reviews: Computational Molecular Science (2014), 4 (3), 225-248CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)A review. Computational modeling of biol. systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resoln., coarse grained (CG), beads has opened the way to simulate large-scale biomol. processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomol. applications to date, focusing on models that retain chem. specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.
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33Voth, G. A. Coarse-Graining of Condensed Phase and Biomolecular Systems; CRC Press: Boca Raton, FL, 2008; p 456.There is no corresponding record for this reference.
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34Levitt, M.; Warshel, A. Computer-Simulation of Protein Folding Nature 1975, 253, 694– 698 DOI: 10.1038/253694a034https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE2MXkt1eksbw%253D&md5=fb6bbeb114d0c1a4d95d12a082e01ccfComputer simulation of protein foldingLevitt, Michael; Warshel, AriehNature (London, United Kingdom) (1975), 253 (5494), 694-8CODEN: NATUAS; ISSN:0028-0836.Computer simulation of protein folding was obtained by combining a simple representation of protein conformation, which averaged over the fine details, with convergent energy minimization and normal mode thermalization. Under certain conditions, the procedure reproduced the correct overall folding of bovine pancreatic trypsin inhibitor.
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35Warshel, A.; Levitt, M. Theoretical Studies of Enzymic Reactions - Dielectric, Electrostatic and Steric Stabilization of Carbonium-Ion in Reaction of Lysozyme J. Mol. Biol. 1976, 103, 227– 249 DOI: 10.1016/0022-2836(76)90311-935https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28XktFKhtr0%253D&md5=f34df33b5971b6b02bd03be95dcd7ba5Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozymeWarshel, A.; Levitt, M.Journal of Molecular Biology (1976), 103 (2), 227-49CODEN: JMOBAK; ISSN:0022-2836.A general method for detailed study of enzymic reactions is presented. The method considers the complete enzyme-substrate complex together with the surrounding solvent and evaluates all the different quantum mech. and classical energy factors that can affect the reaction pathway. These factors include the quantum mech. energies assocd. with bond cleavage and charge redistribution of the substrate and the classical energies of steric and electrostatic interactions between the substrate and the enzyme. The electrostatic polarization of the enzyme atoms and the orientation of the dipoles of the surrounding H2O mols. is simulated by a microscopic dielec. model. The solvation energy resulting from this polarization is considerable and must be included in any realistic calcn. of chem. reactions involving anything more than an isolated mol. in vacuo. Without it, acidic groups can never become ionized and the charge distribution on the substrate will not be reasonable. The same dielec. model can also be used to study the reaction of the substrate in soln. In this way the reaction in soln. can be compared with the enzymic reaction. The stability of the carbonium ion intermediate formed in the cleavage of a glycosidic bond by lysozyme was studied. Electrostatic stabilization is an important factor in increasing the rate of the reaction step that leads to the formation of the carbonium ion intermediate. Steric factors, such as the strain of the substrate on binding to lysozyme, do not seem to contribute significantly.
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36Levitt, M. Birth and future of multiscale modeling for macromolecular systems (Nobel Lecture) Angew. Chem., Int. Ed. 2014, 53, 10006– 10018 DOI: 10.1002/anie.20140369136https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtlWmtLzO&md5=a6b7d9a8ed3910b062df2741f501d33fBirth and Future of Multiscale Modeling for Macromolecular Systems (Nobel Lecture)Levitt, MichaelAngewandte Chemie, International Edition (2014), 53 (38), 10006-10018CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)Michael Levitt won the 2013 Nobel Prize in Chem. for the development of multiscale models for complex chem. systems.
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37Ayton, G. S.; Noid, W. G.; Voth, G. A. Multiscale modeling of biomolecular systems: in serial and in parallel Curr. Opin. Struct. Biol. 2007, 17, 192– 198 DOI: 10.1016/j.sbi.2007.03.00437https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXksFehtLc%253D&md5=5ab3d305cc8ce10d211e843644aa8548Multiscale modeling of biomolecular systems: in serial and in parallelAyton, Gary S.; Noid, Will G.; Voth, Gregory A.Current Opinion in Structural Biology (2007), 17 (2), 192-198CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Considerable progress has been recently achieved in the multiscale modeling of complex biol. processes. Multiscale models have now investigated the structure and dynamics of lipid membranes, proteins, peptides and DNA over length and time scales ranging from the at. to the macroscopic. Serial multiscale methods that parameterize low-resoln. coarse-grained models with data from high-resoln. models have studied long time or length scale phenomena that cannot be investigated with atomically detailed models. Parallel multiscale methods that directly couple high- and low-resoln. models have efficiently explored slow structural transitions and the importance of long-wavelength fluctuations for biol. mols. The success of such models relies upon new theories and methods for constructing accurate multiscale bridges that transfer information between models with different resolns.
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38Tozzini, V. Multiscale modeling of proteins Acc. Chem. Res. 2010, 43, 220– 230 DOI: 10.1021/ar900147638https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtFynsL%252FO&md5=c1487ea533c3bdc3be610265ab715984Multiscale Modeling of ProteinsTozzini, ValentinaAccounts of Chemical Research (2010), 43 (2), 220-230CODEN: ACHRE4; ISSN:0001-4842. (American Chemical Society)A review. The activity within a living cell is based on a complex network of interactions among biomols., exchanging information and energy through biochem. processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addn., a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, the author first reviews the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnol. and cell biol. strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomol. systems was recently confirmed by the assignment of two of the Nobel prizes in 2008: in chem. for the discovery of GFP and in medicine for the discovery of HIV. Accordingly, these proteins were studied with essentially all of the available modeling techniques, making them ideal examples for studying the details of multiscale approaches in protein modeling.
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39Kolinski, A. Multiscale Approaches to Protein Modeling; Springer: New York, 2011; p 355.There is no corresponding record for this reference.
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40Zhou, H. X. Theoretical frameworks for multiscale modeling and simulation Curr. Opin. Struct. Biol. 2014, 25, 67– 76 DOI: 10.1016/j.sbi.2014.01.00440https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXovFCisr4%253D&md5=b6339e2ddb338638b5544663d320fd27Theoretical frameworks for multiscale modeling and simulationZhou, Huan-XiangCurrent Opinion in Structural Biology (2014), 25 (), 67-76CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Biomol. systems have been modeled at a variety of scales, ranging from explicit treatment of electrons and nuclei to continuum description of bulk deformation or velocity. Many challenges of interfacing between scales have been overcome. Multiple models at different scales have been used to study the same system or calc. the same property (e.g., channel conductance). Accurate modeling of biochem. processes under in vivo conditions and the bridging of mol. and subcellular scales will likely soon become reality.
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41Sippl, M. J. Knowledge-based potentials for proteins Curr. Opin. Struct. Biol. 1995, 5, 229– 235 DOI: 10.1016/0959-440X(95)80081-641https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXlvVOrtro%253D&md5=114c7ee36aafe322305dbd86786cdbf9Knowledge-based potentials for proteinsSippl, Manfred J.Current Opinion in Structural Biology (1995), 5 (2), 229-35CODEN: COSBEF; ISSN:0959-440X. (Current Biology)A review, with 56 refs. Knowledge-based potentials and energy functions are extd. from a no. of databases of known protein structures. Recent developments have shown that this type of potential is successful in many areas of protein structure research. Among these are quality assessment and error recognition of folds and the prediction of unknown structures by fold-recognition techniques.
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42Carlsen, M.; Koehl, P.; Rogen, P. On the importance of the distance measures used to train and test knowledge-based potentials for proteins PLoS One 2014, 9, e109335 DOI: 10.1371/journal.pone.0109335There is no corresponding record for this reference.
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43Kolinski, A.; Skolnick, J. Lattice models of protein folding, dynamics, and thermodynamics; R. G. Landes: Austin, TX, 1996.There is no corresponding record for this reference.
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44Mirny, L.; Shakhnovich, E. Protein folding theory: from lattice to all-atom models Annu. Rev. Biophys. Biomol. Struct. 2001, 30, 361– 396 DOI: 10.1146/annurev.biophys.30.1.36144https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXkvVaqtr0%253D&md5=b36105834ba0ea25e55fa4d57297052fProtein folding theory: from lattice to all-atom modelsMirny, Leonid; Shakhnovich, EugeneAnnual Review of Biophysics and Biomolecular Structure (2001), 30 (), 361-396CODEN: ABBSE4; ISSN:1056-8700. (Annual Reviews Inc.)A review with 122 refs. This review focuses on recent advances in understanding protein folding kinetics in the context of nucleation theory. We present basic concepts such as nucleation, folding nucleus, and transition state ensemble and then discuss recent advances and challenges in theor. understanding of several key aspects of protein folding kinetics. We cover recent topol.-based approaches as well as evolutionary studies and mol. dynamics approaches to det. protein folding nucleus and analyze other aspects of folding kinetics. Finally, we briefly discuss successful all-atom Monte-Carlo simulations of protein folding and conclude with a brief outlook for the future.
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45Blaszczyk, M.; Gront, D.; Kmiecik, S.; Ziolkowska, K.; Panek, M.; Kolinski, A. In Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes: From Bioinformatics to Molecular Quantum Mechanics; Liwo, A., Ed.; Springer: Berlin, 2014.There is no corresponding record for this reference.
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46Park, H.; DiMaio, F.; Baker, D. CASP11 refinement experiments with ROSETTA Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24862There is no corresponding record for this reference.
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47Ovchinnikov, S.; Kim, D. E.; Wang, R. Y.; Liu, Y.; DiMaio, F.; Baker, D. Improved de novo structure prediction in CASP11 by incorporating Co-evolution information into rosetta Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24974There is no corresponding record for this reference.
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48Yang, J. Y.; Yan, R. X.; Roy, A.; Xu, D.; Poisson, J.; Zhang, Y. The I-TASSER Suite: protein structure and function prediction Nat. Methods 2014, 12, 7– 8 DOI: 10.1038/nmeth.3213There is no corresponding record for this reference.
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49Webb, B.; Lasker, K.; Velazquez-Muriel, J.; Schneidman-Duhovny, D.; Pellarin, R.; Bonomi, M.; Greenberg, C.; Raveh, B.; Tjioe, E.; Russel, D. Modeling of proteins and their assemblies with the Integrative Modeling Platform Methods Mol. Biol. 2014, 1091, 277– 295 DOI: 10.1007/978-1-62703-691-7_2049https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntFyisLo%253D&md5=a1ed8c1c96e5f5821574848c164f6546Modeling of Proteins and Their Assemblies with the Integrative Modeling PlatformWebb, Benjamin; Lasker, Keren; Velazquez-Muriel, Javier; Schneidman-Duhovny, Dina; Pellarin, Riccardo; Bonomi, Massimiliano; Greenberg, Charles; Raveh, Barak; Tjioe, Elina; Russel, Daniel; Sali, AndrejMethods in Molecular Biology (New York, NY, United States) (2014), 1091 (Structural Genomics), 277-295CODEN: MMBIED; ISSN:1940-6029. (Springer)To understand the workings of the living cell, we need to characterize protein assemblies that constitute the cell (for example, the ribosome, 26S proteasome, and the nuclear pore complex). A reliable high-resoln. structural characterization of these assemblies is frequently beyond the reach of current exptl. methods, such as X-ray crystallog., NMR spectroscopy, electron microscopy, footprinting, chem. crosslinking, FRET spectroscopy, small angle X-ray scattering, and proteomics. However, the information garnered from different methods can be combined and used to build models of the assembly structures that are consistent with all of the available datasets, and therefore more accurate, precise, and complete. Here, we describe a protocol for this integration, whereby the information is converted to a set of spatial restraints and a variety of optimization procedures can be used to generate models that satisfy the restraints as well as possible. These generated models can then potentially inform about the precision and accuracy of structure detn., the accuracy of the input datasets, and further data generation. We also demonstrate the Integrative Modeling Platform (IMP) software, which provides the necessary computational framework to implement this protocol, and several applications for specific use cases.
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50Sali, A.; Berman, H. M.; Schwede, T.; Trewhella, J.; Kleywegt, G.; Burley, S. K.; Markley, J.; Nakamura, H.; Adams, P.; Bonvin, A. M. Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop Structure 2015, 23, 1156– 1167 DOI: 10.1016/j.str.2015.05.01350https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtV2it7jI&md5=2d53115f311a1b407c3b4a77bb87f9c2Outcome of the First wwPDB Hybrid/Integrative Methods Task Force WorkshopSali, Andrej; Berman, Helen M.; Schwede, Torsten; Trewhella, Jill; Kleywegt, Gerard; Burley, Stephen K.; Markley, John; Nakamura, Haruki; Adams, Paul; Bonvin, Alexandre M. J. J.; Chiu, Wah; Dal Peraro, Matteo; Di Maio, Frank; Ferrin, Thomas E.; Grunewald, Kay; Gutmanas, Aleksandras; Henderson, Richard; Hummer, Gerhard; Iwasaki, Kenji; Johnson, Graham; Lawson, Catherine L.; Meiler, Jens; Marti-Renom, Marc A.; Montelione, Gaetano T.; Nilges, Michael; Nussinov, Ruth; Patwardhan, Ardan; Rappsilber, Juri; Read, Randy J.; Saibil, Helen; Schroder, Gunnar F.; Schwieters, Charles D.; Seidel, Claus A. M.; Svergun, Dmitri; Topf, Maya; Ulrich, Eldon L.; Velankar, Sameer; Westbrook, John D.Structure (Oxford, United Kingdom) (2015), 23 (7), 1156-1167CODEN: STRUE6; ISSN:0969-2126. (Elsevier Ltd.)Structures of biomol. systems are increasingly computed by integrative modeling that relies on varied types of exptl. data and theor. information. We describe here the proceedings and conclusions from the first wwPDB Hybrid/Integrative Methods Task Force Workshop held at the European Bioinformatics Institute in Hinxton, UK, on Oct. 6 and 7, 2014. At the workshop, experts in various exptl. fields of structural biol., experts in integrative modeling and visualization, and experts in data archiving addressed a series of questions central to the future of structural biol. How should integrative models be represented. How should the data and integrative models be validated. What data should be archived. How should the data and models be archived. What information should accompany the publication of integrative models.
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51Tamo, G. E.; Abriata, L. A.; Dal Peraro, M. The importance of dynamics in integrative modeling of supramolecular assemblies Curr. Opin. Struct. Biol. 2015, 31, 28– 34 DOI: 10.1016/j.sbi.2015.02.01851https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXktFOkt7w%253D&md5=c4a46436d0b6ded70f55833dc937e245The importance of dynamics in integrative modeling of supramolecular assembliesTamo, Giorgio E.; Abriata, Luciano A.; Dal Peraro, MatteoCurrent Opinion in Structural Biology (2015), 31 (), 28-34CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Revealing the atomistic architecture of supramol. complexes is a fundamental step toward a deeper understanding of cellular functioning. To date, this formidable task is facilitated by an emerging array of integrative modeling approaches that combine exptl. data from different sources. One major challenge these methods have to face is the treatment of the dynamic rearrangements of the individual subunits upon assembly. While this flexibility can be sampled at different levels, integrating native dynamic determinants with available exptl. inputs can provide an effective way to reveal the mol. recognition mechanisms at the basis of supramol. assembly.
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52Rodrigues, J. P.; Bonvin, A. M. Integrative computational modeling of protein interactions FEBS J. 2014, 281, 1988– 2003 DOI: 10.1111/febs.1277152https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmt1Wlsbo%253D&md5=40834335a6cf257d0509ac29728717f0Integrative computational modeling of protein interactionsRodrigues, Joao P. G. L. M.; Bonvin, Alexandre M. J. J.FEBS Journal (2014), 281 (8), 1988-2003CODEN: FJEOAC; ISSN:1742-464X. (Wiley-Blackwell)A review. Protein interactions define the homeostatic state of the cell. Our ability to understand these interactions and their role in both health and disease is tied to our knowledge of the 3D at. structure of the interacting partners and their complexes. Despite advances in exptl. method of structure detn., the majority of known protein interactions are still missing an at. structure. High-resoln. methods such as X-ray crystallog. and NMR spectroscopy struggle with the high-throughput demand, while low-resoln. techniques such as cryo-electron microscopy or small-angle X-ray scattering provide data that are too coarse. Computational structure prediction of protein complexes, or docking, was first developed to complement exptl. research and has since blossomed into an independent and lively field of research. Its most successful products are hybrid approaches that combine powerful algorithms with exptl. data from various sources to generate high-resoln. models of protein complexes. This minireview introduces the concept of docking and docking with the help of exptl. data, compares and contrasts the available integrative docking methods, and provides a guide for the exptl. researcher for what types of data and which particular software can be used to model a protein complex.
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53Reddy, T.; Sansom, M. S. Computational virology: From the inside out Biochim. Biophys. Acta, Biomembr. 2016, 1858, 1610 DOI: 10.1016/j.bbamem.2016.02.00753https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XisFWgsr8%253D&md5=570710fd4cb693d53bd54a99dd1345acComputational virology: From the inside outReddy, Tyler; Sansom, Mark S. P.Biochimica et Biophysica Acta, Biomembranes (2016), 1858 (7_Part_B), 1610-1618CODEN: BBBMBS; ISSN:0005-2736. (Elsevier B.V.)A review. Viruses typically pack their genetic material within a protein capsid. Enveloped viruses also have an outer membrane made up of a lipid bilayer and membrane-spanning glycoproteins. X-ray diffraction and cryoelectron microscopy provide high resoln. static views of viral structure. Mol. dynamics (MD) simulations may be used to provide dynamic insights into the structures of viruses and their components. There have been a no. of simulations of viral capsids and (in some cases) of the inner core of RNA or DNA packaged within them. These simulations have generally focussed on the structural integrity and stability of the capsid and/or on the influence of the nucleic acid core on capsid stability. More recently there have been a no. of simulation studies of enveloped viruses, including HIV-1, influenza A, and dengue virus. These have addressed the dynamic behavior of the capsid, the matrix, and/or of the outer envelope. Anal. of the dynamics of the lipid bilayer components of the envelopes of influenza A and of dengue virus reveals a degree of biophys. robustness, which may contribute to the stability of virus particles in different environments. Significant computational challenges need to be addressed to aid simulation of complex viruses and their membranes, including the need to integrate structural data from a range of sources to enable us to move towards simulations of intact virions. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.
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54Hyeon, C.; Thirumalai, D. Capturing the essence of folding and functions of biomolecules using coarse-grained models Nat. Commun. 2011, 2, 487 DOI: 10.1038/ncomms148154https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3Mfms1Wrug%253D%253D&md5=3bedb98bb3c16049d69b19358577592cCapturing the essence of folding and functions of biomolecules using coarse-grained modelsHyeon Changbong; Thirumalai DNature communications (2011), 2 (), 487 ISSN:.The distances over which biological molecules and their complexes can function range from a few nanometres, in the case of folded structures, to millimetres, for example, during chromosome organization. Describing phenomena that cover such diverse length, and also time, scales requires models that capture the underlying physics for the particular length scale of interest. Theoretical ideas, in particular, concepts from polymer physics, have guided the development of coarse-grained models to study folding of DNA, RNA and proteins. More recently, such models and their variants have been applied to the functions of biological nanomachines. Simulations using coarse-grained models are now poised to address a wide range of problems in biology.
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55Spiga, E.; Degiacomi, M. T.; Dal Peraro, M. New strategies for integrative dynamic modeling of macromolecular assembly Adv. Protein Chem. Struct. Biol. 2014, 96, 77– 111 DOI: 10.1016/bs.apcsb.2014.06.00855https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MzktVGnsg%253D%253D&md5=e61fecd39b9e290080c05ba899117711New strategies for integrative dynamic modeling of macromolecular assemblySpiga Enrico; Degiacomi Matteo Thomas; Dal Peraro MatteoAdvances in protein chemistry and structural biology (2014), 96 (), 77-111 ISSN:.Data reporting on structure and dynamics of cellular constituents are growing with increasing pace enabling, as never before, the understanding of fine mechanistic aspects of biological systems and providing the possibility to affect them in controlled ways. Nonetheless, experimental techniques do not yet allow for an arbitrary level of resolution on cellular processes in situ. By consistently integrating a variety of diverse experimental data, molecular modeling is optimally poised to enhance to near-atomistic resolution our understanding of molecular recognition in large assemblies. Within this integrative modeling context, we briefly review in this chapter the recent progresses of molecular simulations at the atomistic and coarse-grained level of resolution to explore protein-protein interactions. In particular, we discuss our recent contributions in this field, which aim at providing a robust bridge between novel optimization algorithms and multiscale molecular simulations for a consistent integration of experimental inputs. We expect that, with the ever-growing sampling ability of molecular simulations and the tireless progress of experimental methods, the impact of such dynamic-based approach could only be more effective with time, contributing to provide detailed description of cellular organization.
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56Levinthal, C. Are There Pathways for Protein Folding J. Chim. Phys. Pcb. 1968, 65, 44There is no corresponding record for this reference.
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57Levitt, M. A simplified representation of protein conformations for rapid simulation of protein folding J. Mol. Biol. 1976, 104, 59– 107 DOI: 10.1016/0022-2836(76)90004-857https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28XksFygtrY%253D&md5=cb52d597eedeac8aeade3c9263c103e2A simplified representation of protein conformations for rapid simulation of protein foldingLevitt, MichaelJournal of Molecular Biology (1976), 104 (1), 59-107CODEN: JMOBAK; ISSN:0022-2836.A new and highly simplified treatment of protein conformations is introduced. The representation of peptide renaturation is given in some detail. The concept of time-averaged forces are used to simplify conformational energy calcns. on globular proteins. A detailed description is given of the simplified mol. geometry, the parameterization of suitable force fields, the best energy minimization procedure, and the techniques for escaping from local minima. Extensive tests of the method on the native conformation of pancreatic trypsin inhibitor showed that the simplifications work well in representing the stable native conformation of this globular protein. Further tests show that simulated folding of pancreatic trypsin inhibitor from open chain conformations gives compact calcd. conformations that have many features in common with the actual native conformation. Folding simulations are done under a variety of conditions and the relevance of such calcns. to the actual in vitro folding process is discussed at some length. These same techniques have many potential applications including enzyme-substrate binding, changes in protein tertiary and quaternary structure, and protein-protein interactions.
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58Hagler, A. T.; Honig, B. On the formation of protein tertiary structure on a computer Proc. Natl. Acad. Sci. U. S. A. 1978, 75, 554– 558 DOI: 10.1073/pnas.75.2.554There is no corresponding record for this reference.
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59Wilson, C.; Doniach, S. A computer model to dynamically simulate protein folding: studies with crambin Proteins: Struct., Funct., Genet. 1989, 6, 193– 209 DOI: 10.1002/prot.340060208There is no corresponding record for this reference.
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60Crippen, G. M.; Ponnuswamy, P. K. Determination of an empirical energy function for protein conformational analysis by energy embedding J. Comput. Chem. 1987, 8, 972– 981 DOI: 10.1002/jcc.540080707There is no corresponding record for this reference.
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61Miyazawa, S.; Jernigan, R. L. Estimation of effective inter-residue contact energies from protein crystal structures: quasi-chemical approximation Macromolecules 1985, 18, 534– 552 DOI: 10.1021/ma00145a039There is no corresponding record for this reference.
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62Sun, S. Reduced representation model of protein structure prediction: statistical potential and genetic algorithms Protein Sci. 1993, 2, 762– 785 DOI: 10.1002/pro.556002050862https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3sXlslOjtLY%253D&md5=960b68be09f30ffddc8b266c1101a8f5Reduced representation model of protein structure prediction: statistical potential and genetic algorithmsSun, ShaojianProtein Science (1993), 2 (5), 762-85CODEN: PRCIEI; ISSN:0961-8368.A reduced representation model, which has been described in previous reports, was used to predict the folded structures of proteins from their primary sequences and random starting conformations. The mol. structure of each protein has been reduced to its backbone atoms (with ideal fixed bond lengths and valence angles) and each side chain approximated by a single virtual united-atom. The coordinate variables were the backbone dihedral angles φ and ψ. A statistical potential function, which included local and nonlocal interactions and was computed from known protein structures, was used in the structure minimization. A novel approach, employing the concepts of genetic algorithms, has been developed to simultaneously optimize a population of conformations. With the information of primary sequence and the radius of gyration of the crystal structure only, and starting from randomly generated initial conformations, the author have been able to fold melittin, a protein of 26 residues, with high computational convergence. The computed structures have a root mean square error of 1.66 Å (distance matrix error = 0.99 Å) on av. to the crystal structure. Similar results for avian pancreatic polypeptide inhibitor, a protein of 36 residues, are obtained. Application of the method to apamin, an 18-residue polypeptide with two disulfide bonds, shows that it folds apamin to native-like conformations with the correct disulfide bonds formed.
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63Wallqvist, A.; Ullner, M. A simplified amino acid potential for use in structure predictions of proteins Proteins: Struct., Funct., Genet. 1994, 18, 267– 280 DOI: 10.1002/prot.340180308There is no corresponding record for this reference.
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64Honeycutt, J. D.; Thirumalai, D. Metastability of the Folded States of Globular-Proteins Proc. Natl. Acad. Sci. U. S. A. 1990, 87, 3526– 3529 DOI: 10.1073/pnas.87.9.3526There is no corresponding record for this reference.
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65Covell, D. G. Folding Protein Alpha-Carbon Chains into Compact Forms by Monte-Carlo Methods Proteins: Struct., Funct., Genet. 1992, 14, 409– 420 DOI: 10.1002/prot.340140310There is no corresponding record for this reference.
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66Krigbaum, W. R.; Lin, S. F. Monte-Carlo Simulation of Protein Folding Using a Lattice Model Macromolecules 1982, 15, 1135– 1145 DOI: 10.1021/ma00232a035There is no corresponding record for this reference.
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67Skolnick, J.; Kolinski, A. Simulations of the folding of a globular protein Science 1990, 250, 1121– 1125 DOI: 10.1126/science.250.4984.1121There is no corresponding record for this reference.
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68Hinds, D. A.; Levitt, M. A Lattice Model for Protein-Structure Prediction at Low Resolution Proc. Natl. Acad. Sci. U. S. A. 1992, 89, 2536– 2540 DOI: 10.1073/pnas.89.7.2536There is no corresponding record for this reference.
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69Taketomi, H.; Kano, F.; Go, N. The effect of amino acid substitution on protein-folding and -unfolding transition studied by computer simulation Biopolymers 1988, 27, 527– 559 DOI: 10.1002/bip.360270402There is no corresponding record for this reference.
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70Voegler Smith, A.; Hall, C. K. alpha-helix formation: discontinuous molecular dynamics on an intermediate-resolution protein model Proteins: Struct., Funct., Genet. 2001, 44, 344– 360 DOI: 10.1002/prot.1100There is no corresponding record for this reference.
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71Rohl, C.; Strauss, C.; Misura, K.; Baker, D. In Numerical Computer Methods, Part D; Elsevier: Amsterdam, 2004; Vol. 383.There is no corresponding record for this reference.
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72Kolinski, A. Protein modeling and structure prediction with a reduced representation Acta Biochim. Polym. 2004, 51, 349– 37172https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXnslWjt78%253D&md5=9eeabaa4295d62c5f6ecf2e197f8a15fProtein modeling and structure prediction with a reduced representationKolinski, AndrzejActa Biochimica Polonica (2004), 51 (2), 349-371CODEN: ABPLAF; ISSN:0001-527X. (Polish Biochemical Society)Protein modeling can be done on various levels of structural detail, from simplified lattices or continuous representations, through high resoln. reduced models, employing the united atom representation, to all-atom models of the mol. mechanics. Here I describe a new high resoln.-reduced model, its force field and applications in structural proteomics. The model uses a lattice representation with 800 possible orientations of the virtual alpha carbon-alpha carbon bonds. The sampling scheme of the conformational space employs the Replica Exchange Monte Carlo method. Knowledge-based potentials of the force field include: generic protein-like conformational biases, statistical potentials for the short-range conformational propensities, a model of the main chain hydrogen bonds and context-dependent statistical potentials describing the side group interactions. The model is more accurate than the previously designed lattice models, and in many applications, it is complementary and competitive in respect to the all-atom techniques. The test applications include: an ab initio structure prediction, multitemplate comparative modeling and structure prediction based on sparse exptl. data. Esp., the new approach to comparative modeling could be a valuable tool for structural proteomics. It is shown that the new approach goes beyond the range of applicability of the traditional methods of protein comparative modeling.
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73Liwo, A.; Baranowski, M.; Czaplewski, C.; Golas, E.; He, Y.; Jagiela, D.; Krupa, P.; Maciejczyk, M.; Makowski, M.; Mozolewska, M. A. A unified coarse-grained model of biological macromolecules based on mean-field multipole-multipole interactions J. Mol. Model. 2014, 20, 2306 DOI: 10.1007/s00894-014-2306-573https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cbisVOltQ%253D%253D&md5=8c08629d36e08def25f51c717ab89812A unified coarse-grained model of biological macromolecules based on mean-field multipole-multipole interactionsLiwo Adam; Baranowski Maciej; Czaplewski Cezary; Golas Ewa; He Yi; Jagiela Dawid; Krupa Pawel; Maciejczyk Maciej; Makowski Mariusz; Mozolewska Magdalena A; Niadzvedtski Andrei; Oldziej Stanislaw; Scheraga Harold A; Sieradzan Adam K; Slusarz Rafal; Wirecki Tomasz; Yin Yanping; Zaborowski BartlomiejJournal of molecular modeling (2014), 20 (8), 2306 ISSN:.A unified coarse-grained model of three major classes of biological molecules--proteins, nucleic acids, and polysaccharides--has been developed. It is based on the observations that the repeated units of biopolymers (peptide groups, nucleic acid bases, sugar rings) are highly polar and their charge distributions can be represented crudely as point multipoles. The model is an extension of the united residue (UNRES) coarse-grained model of proteins developed previously in our laboratory. The respective force fields are defined as the potentials of mean force of biomacromolecules immersed in water, where all degrees of freedom not considered in the model have been averaged out. Reducing the representation to one center per polar interaction site leads to the representation of average site-site interactions as mean-field dipole-dipole interactions. Further expansion of the potentials of mean force of biopolymer chains into Kubo's cluster-cumulant series leads to the appearance of mean-field dipole-dipole interactions, averaged in the context of local interactions within a biopolymer unit. These mean-field interactions account for the formation of regular structures encountered in biomacromolecules, e.g., α-helices and β-sheets in proteins, double helices in nucleic acids, and helicoidally packed structures in polysaccharides, which enables us to use a greatly reduced number of interacting sites without sacrificing the ability to reproduce the correct architecture. This reduction results in an extension of the simulation timescale by more than four orders of magnitude compared to the all-atom representation. Examples of the performance of the model are presented.
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74Kolinski, A.; Jaroszewski, L.; Rotkiewicz, P.; Skolnick, J. An efficient Monte Carlo model of protein chains. Modeling the short-range correlations between side group centers of mass J. Phys. Chem. B 1998, 102, 4628– 4637 DOI: 10.1021/jp973371j74https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXjtVWiu7o%253D&md5=77338f48247fad6b125ebeb50dcc86a1An Efficient Monte Carlo Model of Protein Chains. Modeling the Short-Range Correlations between Side Group Centers of MassKolinski, Andrzej; Jaroszewski, Lukasz; Rotkiewicz, Piotr; Skolnick, JeffreyJournal of Physical Chemistry B (1998), 102 (23), 4628-4637CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)A new high-coordination lattice model of polypeptide chains has been designed and tested. The model employs a single united atom representation of amino acid residues. These atoms are centered on protein side groups. Characteristic short-range distance correlations have been built into the model, thereby providing a rather accurate description of protein-like conformational stiffness. Sequence-specific interaction schemes have been derived from sequence similarity and sequence-structure compatibility criteria. The conformations of the model chain obsd. in isothermal Monte Carlo simulations reproduce protein secondary structure with high fidelity. Implications for structural studies of protein systems are briefly discussed.
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75Shakhnovich, E. Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet Chem. Rev. 2006, 106, 1559– 1588 DOI: 10.1021/cr040425u75https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjsFKitbc%253D&md5=5de8c7b04e3f51a8450ba1475be1c61aProtein folding thermodynamics and dynamics: Where physics, chemistry, and biology meetShakhnovich, EugeneChemical Reviews (Washington, DC, United States) (2006), 106 (5), 1559-1588CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review. First, the author summarizes basic questions and presents simple, coarse-grained models that provide a basis for a fundamental understanding of protein folding thermodn. and kinetics. Then, the author discusses more recent developments (over the last 5 yr) that focus on detailed studies of folding mechanisms of specific proteins, and finally, he briefly discusses some outstanding questions and future directions.
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76Dill, K. A.; MacCallum, J. L. The protein-folding problem, 50 years on Science 2012, 338, 1042– 1046 DOI: 10.1126/science.121902176https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs12itrnF&md5=bd73e6103d437b24594ce4cd86ad25dcThe protein-folding problem, 50 years onDill, Ken A.; MacCallum, Justin L.Science (Washington, DC, United States) (2012), 338 (6110), 1042-1046CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)A review. The protein-folding problem was 1st posed about one half-century ago. The term refers to 3 broad questions: (1) What is the phys. code by which an amino acid sequence dictates a protein's native structure (2) How can proteins fold so fast and (3) Can one devise a computer algorithm to predict protein structures from their sequences. Here, the authors review progress on these problems. In a few cases, computer simulations of the phys. forces in chem. detailed models have now achieved the accurate folding of small proteins. It has been learned that proteins fold rapidly because random thermal motions cause conformational changes leading energetically downhill toward the native structure, a principle that is captured in funnel-shaped energy landscapes. And thanks in part to the large Protein Data Bank of known structures, predicting protein structures is now far more successful than was thought possible in earlier days. What began as 3 questions of basic science one half-century ago has now grown into the full-fledged research field of protein phys. science.
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77Yue, K.; Fiebig, K. M.; Thomas, P. D.; Chan, H. S.; Shakhnovich, E. I.; Dill, K. A. A test of lattice protein folding algorithms Proc. Natl. Acad. Sci. U. S. A. 1995, 92, 325– 329 DOI: 10.1073/pnas.92.1.32577https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXjtVensL0%253D&md5=c0b3e6cb5cc4eb468fb0ed4af12e1e58A test of lattice protein folding algorithmsYue, Kaizhi; Fiebig, Klaus M.; Thomas, Paul D.; Chan, Hue Sun; Shakhnovich, Eugene I.; Dill, Ken A.Proceedings of the National Academy of Sciences of the United States of America (1995), 92 (1), 325-9CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We report a blind test of lattice-model-based search strategies for finding global min. of model protein chains. One of us (E.I.S.) selected 10 compact conformations of 48-mer chains on the three-dimensional cubic lattice and used their inverse folding algorithm to design HP (H, hydrophobic; P, polar) sequences that should fold to those "target" structures. The sequences, but not the structures, were sent to the UCSF group (K.Y., K.M.F., P.D.T., H.S.C., and K.A.D.), who used two methods to attempt to find the globally optimal conformations: "hydrophobic zippers" and a constraint-based hydrophobic core construction (CHCC) method. The CHCC method found global min. in all cases, and the hydrophobic zippers method found global min. in some cases, in minutes to hours on workstations. In 9 out of 10 sequences, the CHCC method found lower energy conformations than the 48-mers were designed to fold to. Thus the search strategies succeed for the HP model but the design strategy dose not. For every sequence the global energy min. was found to have multiple degeneracy with 103 to 106 conformations. We discuss the implications of these results for (i) searching conformational spaces of simple models of proteins and (ii) how these simple models relate to proteins.
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78Dill, K. A.; Bromberg, S.; Yue, K.; Fiebig, K. M.; Yee, D. P.; Thomas, P. D.; Chan, H. S. Principles of protein folding--a perspective from simple exact models Protein Sci. 1995, 4, 561– 602 DOI: 10.1002/pro.556004040178https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXltFynur0%253D&md5=647bf25d9a62383f1be493a2aac8600fPrinciples of protein folding - a perspective from simple exact modelsDill, Ken A.; Bromberg, Sarina; Yue, Kaizhi; Fiebig, Klaus M.; Yee, David P.; Thomas, Paul D.; Chan, Hue SunProtein Science (1995), 4 (4), 561-602CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)A review, with ≈420 refs. General principles of protein structure, stability, and folding kinetics have recently been explored in computer simulations of simple exact lattice models. These models represent protein chains at a rudimentary level, but the involve few parameters, approxns., or implicit biases, and they allow complete explorations of conformational and sequence spaces. Such simulations have resulted in testable predictions that are sometimes unanticipated: The folding code is mainly binary and delocalized throughout the amino acid sequence. The secondary and tertiary structures of a protein are specified mainly by the sequence of polar and nonpolar monomers. More specific interactions may refine the structure, rather than dominate the folding code. Simple exact models can account for the properties that characterize protein folding: two-state cooperativity, secondary and tertiary structures, and multistage folding kinetics-fast hydrophobic collapse followed by slower annealing. These studies suggest the possibility of creating "foldable" chain mols. other than proteins. The encoding of a unique compact chain conformation may not require amino acids; it may require only the ability to synthesize specific monomer sequences in which at least one monomer type is solvent-averse.
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79Shakhnovich, E. I.; Gutin, A. M. Formation of Unique Structure in Polypeptide-Chains Theoretical Investigation with the Aid of a Replica Approach Biophys. Chem. 1989, 34, 187– 199 DOI: 10.1016/0301-4622(89)80058-4There is no corresponding record for this reference.
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80Bechini, A. On the Characterization and Software Implementation of General Protein Lattice Models. PLoS One 2013, 8. e59504 DOI: 10.1371/journal.pone.0059504There is no corresponding record for this reference.
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81Skolnick, J.; Kolinski, A.; Yaris, R. Monte Carlo simulations of the folding of beta-barrel globular proteins Proc. Natl. Acad. Sci. U. S. A. 1988, 85, 5057– 5061 DOI: 10.1073/pnas.85.14.5057There is no corresponding record for this reference.
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82Skolnick, J.; Kolinski, A. Dynamic Monte Carlo simulations of a new lattice model of globular protein folding, structure and dynamics J. Mol. Biol. 1991, 221, 499– 531 DOI: 10.1016/0022-2836(91)80070-BThere is no corresponding record for this reference.
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83Hao, M. H.; Scheraga, H. A. Monte-Carlo Simulation of a First-Order Transition for Protein-Folding J. Phys. Chem. 1994, 98, 4940– 4948 DOI: 10.1021/j100069a028There is no corresponding record for this reference.
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84Park, B. H.; Levitt, M. The Complexity and Accuracy of Discrete State Models of Protein-Structure J. Mol. Biol. 1995, 249, 493– 507 DOI: 10.1006/jmbi.1995.0311There is no corresponding record for this reference.
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85Godzik, A.; Kolinski, A.; Skolnick, J. Lattice Representations of Globular-Proteins - How Good Are They J. Comput. Chem. 1993, 14, 1194– 1202 DOI: 10.1002/jcc.540141009There is no corresponding record for this reference.
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86Alexander, P. A.; He, Y.; Chen, Y.; Orban, J.; Bryan, P. N. A minimal sequence code for switching protein structure and function Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 21149– 21154 DOI: 10.1073/pnas.090640810686https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXjvFOiu7o%253D&md5=6ba6060550fae5ae68474eedbfb99a10A minimal sequence code for switching protein structure and functionAlexander, Patrick A.; He, Yanan; Chen, Yihong; Orban, John; Bryan, Philip N.Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (50), 21149-21154, S21149/1-S21149/7CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)A structural and mechanistic description of how a protein changes its fold and function, mutation by mutation, is presented. The approach was to create 2 proteins that (i) are stably folded into 2 different folds, (ii) have 2 different functions, and (iii) are very similar in sequence. In this simplified sequence space, the mutational path from one fold to another is explored. It is shown that an IgG-binding, 4β+α fold can be transformed into an albumin-binding, 3-α fold via a mutational pathway in which neither function nor native structure is completely lost. The stabilities of all mutants along the pathway are evaluated, key high-resoln. structures are detd. by NMR, and an explanation of the switching mechanism is provided. It is shown that the conformational switch from 4β+α to 3-α structure can occur via a single amino acid substitution. On one side of the switch point, the 4β+α fold is > 90% populated (pH 7.2, 20 °C). A single mutation switches the conformation to the 3-α fold, which is > 90% populated (pH 7.2, 20 °C). It is further shown that a bifunctional protein exists at the switch point with affinity for both IgG and albumin.
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87Riniker, S.; Allison, J. R.; van Gunsteren, W. F. On developing coarse-grained models for biomolecular simulation: a review Phys. Chem. Chem. Phys. 2012, 14, 12423– 12430 DOI: 10.1039/c2cp40934h87https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1Cis7vO&md5=8f362f16e11bb9587daedac96acacb32On developing coarse-grained models for biomolecular simulation: a reviewRiniker, Sereina; Allison, Jane R.; van Gunsteren, Wilfred F.Physical Chemistry Chemical Physics (2012), 14 (36), 12423-12430CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)A review. So-called coarse-grained models are a popular type of model for accessing long time scales in simulations of biomol. processes. Such models are coarse-grained with respect to at. models. But any modeling of processes or substances involves coarse-graining, i.e. the elimination of non-essential degrees of freedom and interactions from a more fine-grained level of modeling. The basic ingredients of developing coarse-grained models based on the properties of fine-grained models are reviewed, together with the conditions that must be satisfied to preserve the correct phys. mechanisms in the coarse-graining process. This overview should help the reader to det. how realistic a coarse-grained model of a biomol. system is, i.e., whether it reflects the underlying phys. mechanisms or merely provides a set of pretty pictures of the process or substances of interest.
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88Trylska, J. Coarse-grained models to study dynamics of nanoscale biomolecules and their applications to the ribosome J. Phys.: Condens. Matter 2010, 22, 453101 DOI: 10.1088/0953-8984/22/45/45310188https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFartL3I&md5=a8c9f7a7dc4a1d26abd0e352e3652a6eCoarse-grained models to study dynamics of nanoscale biomolecules and their applications to the ribosomeTrylska, JoannaJournal of Physics: Condensed Matter (2010), 22 (45), 453101/1-453101/13CODEN: JCOMEL; ISSN:0953-8984. (Institute of Physics Publishing)A review. Biopolymers are of dynamic nature and undergo functional motions spanning a large spectrum of timescales. To study the internal dynamics of nano-sized mol. complexes that exceed hundred thousands of atoms with at. detail is computationally inefficient. Therefore, to achieve both the spatial and temporal scales of biol. interest coarse-grained models of macromols. are often used. By uniting groups of atoms into single interacting centers one decreases the resoln. of the system and gets rid of the irrelevant degrees of freedom. This simplification, even though it requires parameterization, makes the studies of biomol. dynamics computationally tractable and allows the authors to reach beyond the microsecond time frame. Here, the author reviews the coarse-grained models of macromols. composed of proteins and nucleic acids. The author gives examples of one-bead models that were developed to investigate the internal dynamics and focuses on their applications to the ribosome - the nanoscale protein synthesis machine.
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89Saunders, M. G.; Voth, G. A. Coarse-graining of multiprotein assemblies Curr. Opin. Struct. Biol. 2012, 22, 144– 150 DOI: 10.1016/j.sbi.2012.01.00389https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XltVamtbY%253D&md5=cedef5bf4f66fcadcfc15bdb005ce2b4Coarse-graining of multiprotein assembliesSaunders, Marissa G.; Voth, Gregory A.Current Opinion in Structural Biology (2012), 22 (2), 144-150CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Multiscale models are important tools to elucidate how small changes in local subunit conformations may propagate to affect the properties of macromol. complexes. We review recent advances in coarse-graining methods for poly-protein assemblies, systems that are composed of many copies of relatively few components, with a particular focus on viral capsids and cytoskeletal filaments. These methods are grouped into two broad categories - mapping methods, which use information from one scale of representation to parameterize a lower resoln. model, and bridging methods, which repeatedly connect different scales during simulation - and we provide examples of both classes at different levels of complexity. Collectively, these models illustrate the numerous approaches to information transfer between scales and demonstrate that the complexity required of the model depends in general on the nature of the information sought.
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90Mills, Z. G.; Mao, W.; Alexeev, A. Mesoscale modeling: solving complex flows in biology and biotechnology Trends Biotechnol. 2013, 31, 426– 434 DOI: 10.1016/j.tibtech.2013.05.00190https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXovVClu74%253D&md5=8c3cb32830268deaea4d516044ff082aMesoscale modeling: solving complex flows in biology and biotechnologyMills, Zachary Grant; Mao, Wenbin; Alexeev, AlexanderTrends in Biotechnology (2013), 31 (7), 426-434CODEN: TRBIDM; ISSN:0167-7799. (Elsevier Ltd.)A review. Fluids are involved in practically all physiol. activities of living organisms. However, biol. and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnol.
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91Coulon, A.; Beslon, G.; Gandrillon, O. Large multiprotein structures modeling and simulation: the need for mesoscopic models Methods Mol. Biol. 2008, 484, 537– 558 DOI: 10.1007/978-1-59745-398-1_3291https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFSgsLjF&md5=346be7c017efbb2bf784b6219f5bf169Large multiprotein structures modeling and simulation: the need for mesoscopic modelsCoulon, Antoine; Beslon, Guillaume; Gandrillon, OlivierMethods in Molecular Biology (Totowa, NJ, United States) (2008), 484 (Functional Proteomics), 537-558CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)Recent observational techniques based upon confocal microscopy make it possible to observe cells at a scale that has never been probed before: the mesoscopic scale. In the eukaryotic cell nucleus, many objects demonstrating phenomena occurring at this scale, such as nuclear bodies, are current subjects of investigations. But from a modeling perspective, this scale has not been widely explored, and hence there is a lack of suitable models for such studies. By reviewing higher and lower scale modeling techniques, we analyze their relevance in the context of mesoscale phenomena. We emphasize important characteristics that should be included in a mesoscopic model: an explicit continuous three-dimensional space with discrete simplified mols. that still have the characteristics of steric vol. exclusion and realistic distant interaction forces. Then we present 3DSPI, a model dedicated to studies of nuclear bodies based on a simple formalism inspired from mol. dynamics and coarse-grained models: particles interacting through a potential energy function and driven by an overdamped Langevin equation. Finally, we present the features expected to be included in the model, pointing out the difficulties that might arise.
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92Dama, J. F.; Sinitskiy, A. V.; McCullagh, M.; Weare, J.; Roux, B.; Dinner, A. R.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 1. General Principles J. Chem. Theory Comput. 2013, 9, 2466– 2480 DOI: 10.1021/ct400044492https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXktlyltLc%253D&md5=ed47184bb04790726e3f95f630defb87The Theory of Ultra-Coarse-Graining. 1. General PrinciplesDama, James F.; Sinitskiy, Anton V.; McCullagh, Martin; Weare, Jonathan; Roux, Benoit; Dinner, Aaron R.; Voth, Gregory A.Journal of Chemical Theory and Computation (2013), 9 (5), 2466-2480CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grained (CG) models provide a computationally efficient means to study biomol. and other soft matter processes involving large nos. of atoms correlated over distance scales of many covalent bond lengths and long time scales. Variational methods based on information from simulations of finer-grained (e.g., all-atom) models, for example the multiscale coarse-graining (MS-CG) and relative entropy minimization methods, provide attractive tools for the systematic development of CG models. However, these methods have important drawbacks when used in the "ultra-coarse-grained" (UCG) regime, e.g., at a resoln. level coarser or much coarser than one amino acid residue per effective CG particle in proteins. This is due to the possible existence of multiple metastable states "within" the CG sites for a given UCG model configuration. In this work, systematic variational UCG methods are presented that are specifically designed to CG entire protein domains and subdomains into single effective CG particles. This is accomplished by augmenting existing effective particle CG schemes to allow for discrete state transitions and configuration-dependent resoln. Addnl., certain conclusions of this work connect back to single-state force matching and open up new avenues for method development in that area. These results provide a formal statistical mech. basis for UCG methods related to force matching and relative entropy CG methods and suggest practical algorithms for constructing optimal approx. UCG models from fine-grained simulation data.
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93Davtyan, A.; Dama, J. F.; Sinitskiy, A. V.; Voth, G. A. The Theory of Ultra-Coarse-Graining. 2. Numerical Implementation J. Chem. Theory Comput. 2014, 10, 5265– 5275 DOI: 10.1021/ct500834t93https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFKqtbbN&md5=258cfd9c6f3e298f769682f3fc7e052fThe Theory of Ultra-Coarse-Graining. 2. Numerical ImplementationDavtyan, Aram; Dama, James F.; Sinitskiy, Anton V.; Voth, Gregory A.Journal of Chemical Theory and Computation (2014), 10 (12), 5265-5275CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The increasing interest in the modeling of complex macromol. systems in recent years has spurred the development of numerous coarse-graining (CG) techniques. However, many of the CG models are constructed assuming that all details beneath the resoln. of CG degrees of freedom are fast and av. out, which sets limits on the resoln. of feasible coarse-grainings and on the range of applications of the CG models. Ultra-coarse-graining (UCG) makes it possible to construct models at any desired resoln. while accounting for discrete conformational or chem. changes within the CG sites that can modulate the interactions between them. Here, we discuss the UCG methodol. and its numerical implementation. We pay particular attention to the numerical mechanism for including state transitions between different conformations within CG sites because this has not been discussed previously. Using a simple example of 1,2-dichloroethane, we demonstrate the ability of the UCG model to reproduce the multiconfigurational behavior of this mol. liq., even when each mol. is modeled with only one CG site. The methodol. can also be applied to other mol. liqs. and macromol. systems with time scale sepn. between conformational transitions and other intramol. motions and rotations.
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94Chen, J.; Xie, Z. R.; Wu, Y. Elucidating the general principles of cell adhesion with a coarse-grained simulation model Mol. BioSyst. 2016, 12, 205– 218 DOI: 10.1039/C5MB00612K94https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhslyqsLnP&md5=ae2e12e7d046e733655f29912cf06d28Elucidating the general principles of cell adhesion with a coarse-grained simulation modelChen, Jiawen; Xie, Zhong-Ru; Wu, YinghaoMolecular BioSystems (2016), 12 (1), 205-218CODEN: MBOIBW; ISSN:1742-2051. (Royal Society of Chemistry)Cell adhesion plays an indispensable role in coordinating physiol. functions in multicellular organisms. During this process, specific types of cell adhesion mols. interact with each other from the opposite sides of neighboring cells. Following this trans-interaction, many cell adhesion mols. further aggregate into clusters through cis interactions. Beyond the mol. level, adhesion can be affected by multiple cellular factors due to the complexity of membrane microenvironments, including its interplay with cell signaling. However, despite tremendous advances in exptl. developments, little is understood about the general principles of cell adhesion and its functional impacts. Here a mesoscopic simulation method is developed to tackle this problem. We illustrated that specific spatial patterns of membrane protein clustering are originated from different geometrical arrangements of their binding interfaces, while the size of clusters is closely regulated by mol. flexibility. Different scenarios of cooperation between trans and cis interactions of cell adhesion mols. were further tested. Addnl., impacts of membrane environments on cell adhesion were evaluated, such as the presence of a cytoskeletal meshwork, the membrane tension and the size effect of different membrane proteins on cell surfaces. Finally, by simultaneously simulating adhesion and oligomerization of signaling receptors, we found that the interplay between these two systems can be either pos. or neg., closely depending on the spatial and temporal patterns of their mol. interactions. Therefore, our computational model pave the way for understanding the mol. mechanisms of cell adhesion and its biol. functions in regulating cell signaling pathways.
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95Kolinski, A.; Skolnick, J. Assembly of protein structure from sparse experimental data: An efficient Monte Carlo model Proteins: Struct., Funct., Genet. 1998, 32, 475– 494 DOI: 10.1002/(SICI)1097-0134(19980901)32:4<475::AID-PROT6>3.3.CO;2-BThere is no corresponding record for this reference.
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96Kolinski, A.; Betancourt, M. R.; Kihara, D.; Rotkiewicz, P.; Skolnick, J. Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement Proteins: Struct., Funct., Genet. 2001, 44, 133– 149 DOI: 10.1002/prot.1080There is no corresponding record for this reference.
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97Kolinski, A.; Ilkowski, B.; Skolnick, J. Dynamics and thermodynamics of beta-hairpin assembly: insights from various simulation techniques Biophys. J. 1999, 77, 2942– 2952 DOI: 10.1016/S0006-3495(99)77127-4There is no corresponding record for this reference.
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98Boniecki, M.; Rotkiewicz, P.; Skolnick, J.; Kolinski, A. Protein fragment reconstruction using various modeling techniques J. Comput.-Aided Mol. Des. 2003, 17, 725– 738 DOI: 10.1023/B:JCAM.0000017486.83645.a098https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2c7nslyruw%253D%253D&md5=43f4acdbacf57fbc6358faf3f65c4b78Protein fragment reconstruction using various modeling techniquesBoniecki Michal; Rotkiewicz Piotr; Skolnick Jeffrey; Kolinski AndrzejJournal of computer-aided molecular design (2003), 17 (11), 725-38 ISSN:0920-654X.Recently developed reduced models of proteins with knowledge-based force fields have been applied to a specific case of comparative modeling. From twenty high resolution protein structures of various structural classes, significant fragments of their chains have been removed and treated as unknown. The remaining portions of the structures were treated as fixed - i.e., as templates with an exact alignment. Then, the missed fragments were reconstructed using several modeling tools. These included three reduced types of protein models: the lattice SICHO (Side Chain Only) model, the lattice CABS (Calpha + Cbeta + Side group) model and an off-lattice model similar to the CABS model and called REFINER. The obtained reduced models were compared with more standard comparative modeling tools such as MODELLER and the SWISS-MODEL server. The reduced model results are qualitatively better for the higher resolution lattice models, clearly suggesting that these are now mature, competitive and complementary (in the range of sparse alignments) to the classical tools of comparative modeling. Comparison between the various reduced models strongly suggests that the essential ingredient for the sucessful and accurate modeling of protein structures is not the representation of conformational space (lattice, off-lattice, all-atom) but, rather, the specificity of the force fields used and, perhaps, the sampling techniques employed. These conclusions are encouraging for the future application of the fast reduced models in comparative modeling on a genomic scale.
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99Stumpff-Kane, A. W.; Maksimiak, K.; Lee, M. S.; Feig, M. Sampling of near-native protein conformations during protein structure refinement using a coarse-grained model, normal modes, and molecular dynamics simulations Proteins: Struct., Funct., Genet. 2008, 70, 1345– 1356 DOI: 10.1002/prot.21674There is no corresponding record for this reference.
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100Kihara, D.; Zhang, Y.; Lu, H.; Kolinski, A.; Skolnick, J. Ab initio protein structure prediction on a genomic scale: application to the Mycoplasma genitalium genome Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 5993– 5998 DOI: 10.1073/pnas.092135699100https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XjslWgurg%253D&md5=f76d1902fcb122e6553b63971007d7d3Ab initio protein structure prediction on a genomic scale: application to the Mycoplasma genitalium genomeKihara, Daisuke; Zhang, Yang; Lu, Hui; Kolinski, Andrzej; Skolnick, JeffreyProceedings of the National Academy of Sciences of the United States of America (2002), 99 (9), 5993-5998CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)An ab initio protein structure prediction procedure, TOUCHSTONE, was applied to all 85 small proteins of the Mycoplasma genitalium genome. TOUCHSTONE is based on a Monte Carlo refinement of a lattice model of proteins, which uses threading-based tertiary restraints. Such restraints are derived by extg. consensus contacts and local secondary structure from at least weakly scoring structures that, in some cases, can lack any global similarity to the sequence of interest. Selection of the native fold was done by using the convergence of the simulation from two different conformational search schemes and the lowest energy structure by a knowledge-based at.-detailed potential. Among the 85 proteins, for 34 proteins with significant threading hits, the template structures were reasonably well reproduced. Of the remaining 51 proteins, 29 proteins converged to five or fewer clusters. In the test set, 84.8% of the proteins that converged to five or fewer clusters had a correct fold among the clusters. If this statistic is simply applied, 24 proteins (84.8% of the 29 proteins) may have correct folds. Thus, the topol. of a total of 58 proteins probably has been correctly predicted. Based on these results, ab initio protein structure prediction is becoming a practical approach.
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101Kmiecik, S.; Gront, D.; Kouza, M.; Kolinski, A. From coarse-grained to atomic-level characterization of protein dynamics: transition state for the folding of B domain of protein A J. Phys. Chem. B 2012, 116, 7026– 7032 DOI: 10.1021/jp301720w101https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xlt1aqsr8%253D&md5=0ac48f6b6153b0f09f651f0d5dff5463From Coarse-Grained to Atomic-Level Characterization of Protein Dynamics: Transition State for the Folding of B Domain of Protein AKmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Kolinski, AndrzejJournal of Physical Chemistry B (2012), 116 (23), 7026-7032CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Atomic-level mol. dynamics simulations are widely used for the characterization of the structural dynamics of proteins; however, they are limited to shorter time scales than the duration of most of the relevant biol. processes. Properly designed coarse-grained models that trade at. resoln. for efficient sampling allow access to much longer time-scales. In-depth understanding of the structural dynamics, however, must involve at. details. In this study, we tested a method for the rapid reconstruction of all-atom models from α carbon atom positions in the application to convert a coarse-grained folding trajectory of a well described model system: the B domain of protein A. The results show that the method and the spatial resoln. of the resulting coarse-grained models enable computationally inexpensive reconstruction of realistic all-atom models. Addnl., by means of structural clustering, we detd. the most persistent ensembles of the key folding step, the transition state. Importantly, the anal. of the overall structural topologies suggests a dominant folding pathway. This, together with the all-atom characterization of the obtained ensembles, in the form of contact maps, matches the exptl. results well.
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102Xu, D.; Zhang, Y. Improving the physical realism and structural accuracy of protein models by a two-step atomic-level energy minimization Biophys. J. 2011, 101, 2525– 2534 DOI: 10.1016/j.bpj.2011.10.024102https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsV2msb7E&md5=04fae8474e9816669a8e4e45850fb3efImproving the Physical Realism and Structural Accuracy of Protein Models by a Two-Step Atomic-Level Energy MinimizationXu, Dong; Zhang, YangBiophysical Journal (2011), 101 (10), 2525-2534CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Most protein structural prediction algorithms assemble structures as reduced models that represent amino acids by a reduced no. of atoms to speed up the conformational search. Building accurate full-atom models from these reduced models is a necessary step toward a detailed function anal. However, it is difficult to ensure that the at. models retain the desired global topol. while maintaining a sound local at. geometry because the reduced models often have unphys. local distortions. To address this issue, the authors developed a new program, called ModRefiner, to construct and refine protein structures from Cα traces based on a two-step, at.-level energy minimization. The main-chain structures are first constructed from initial Cα traces and the side-chain rotamers are then refined together with the backbone atoms with the use of a composite physics- and knowledge-based force field. The authors tested the method by performing an at. structure refinement of 261 proteins with the initial models constructed from both ab initio and template-based structure assemblies. Compared with other state-of-art programs, ModRefiner shows improvements in both global and local structures, which have more accurate side-chain positions, better hydrogen-bonding networks, and fewer at. overlaps. ModRefiner is freely available at http://zhanglab.ccmb.med.umich.edu/ModRefiner.
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103Kazmierkiewicz, R.; Liwo, A.; Scheraga, H. A. Addition of side chains to a known backbone with defined side-chain centroids Biophys. Chem. 2002, 100, 261– 280 DOI: 10.1016/S0301-4622(02)00285-5There is no corresponding record for this reference.
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104Das, R.; Baker, D. Macromolecular modeling with rosetta Annu. Rev. Biochem. 2008, 77, 363– 382 DOI: 10.1146/annurev.biochem.77.062906.171838104https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXos1ekurw%253D&md5=17d4f1cef8eb03c399a4e3b65c83dde0Macromolecular modeling with RosettaDas, Rhiju; Baker, DavidAnnual Review of Biochemistry (2008), 77 (), 363-382CODEN: ARBOAW; ISSN:0066-4154. (Annual Reviews Inc.)A review. Advances over the past few years have begun to enable prediction and design of macromol. structures at near-at. accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of mol. modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodol. enables the creation of novel mols. with useful functions and holds promise for accelerating exptl. structural inference. Emerging connections to crystallog. phasing, NMR modeling, and lower-resoln. approaches are described and critically assessed.
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105Gopal, S. M.; Mukherjee, S.; Cheng, Y. M.; Feig, M. PRIMO/PRIMONA: a coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracy Proteins: Struct., Funct., Genet. 2010, 78, 1266– 1281 DOI: 10.1002/prot.22645105https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhvFCqur4%253D&md5=a79b7eb92cd81853531d2d1ede857136PRIMO/PRIMONA: A coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracyGopal, Srinivasa M.; Mukherjee, Shayantani; Cheng, Yi-Ming; Feig, MichaelProteins: Structure, Function, and Bioinformatics (2010), 78 (5), 1266-1281CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)The new coarse graining model PRIMO/PRIMONA for proteins and nucleic acids is proposed. This model combines one to several heavy atoms into coarse-grained sites that are chosen to allow an anal., high-resoln. reconstruction of all-atom models based on mol. bonding geometry constraints. The accuracy of proposed reconstruction method in terms of structure and energetics is tested and compared with other popular reconstruction methods for a variety of protein and nucleic acid test sets. Proteins 2010. © 2009 Wiley-Liss, Inc.
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106Kar, P.; Gopal, S. M.; Cheng, Y. M.; Predeus, A.; Feig, M. PRIMO: A Transferable Coarse-grained Force Field for Proteins J. Chem. Theory Comput. 2013, 9, 3769– 3788 DOI: 10.1021/ct400230y106https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVWht7rM&md5=7fd81d83f708b223a00d0bfb707bd5d0PRIMO: A Transferable Coarse-Grained Force Field for ProteinsKar, Parimal; Gopal, Srinivasa Murthy; Cheng, Yi-Ming; Predeus, Alexander; Feig, MichaelJournal of Chemical Theory and Computation (2013), 9 (8), 3769-3788CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors describe here the PRIMO (protein intermediate model) force field, a physics-based fully transferable additive coarse-grained potential energy function that is compatible with an all-atom force field for multiscale simulations. The energy function consists of std. mol. dynamics energy terms plus a hydrogen-bonding potential term and is mainly parametrized based on the CHARMM22/CMAP force field in a bottom-up fashion. The solvent was treated implicitly via the generalized Born model. The bonded interactions are either harmonic or distance-based spline interpolated potentials. These potentials are defined on the basis of all-atom mol. dynamics (MD) simulations of dipeptides with the CHARMM22/CMAP force field. The nonbonded parameters are tuned by matching conformational free energies of diverse set of conformations with that of CHARMM all-atom results. PRIMO is designed to provide a correct description of conformational distribution of the backbone (φ/ψ) and side chains (χ1) for all amino acids with a CMAP correction term. The CMAP potential in PRIMO is optimized based on the new CHARMM C36 CMAP. The resulting optimized force field has been applied in MD simulations of several proteins of 36-155 amino acids and showed that the root-mean-squared-deviation of the av. structure from the corresponding crystallog. structure varies between 1.80 and 4.03 Å. PRIMO is shown to fold several small peptides to their native-like structures from extended conformations. These results suggest the applicability of the PRIMO force field in the study of protein structures in aq. soln., structure predictions, as well as ab initio folding of small peptides.
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107Skolnick, J. In quest of an empirical potential for protein structure prediction Curr. Opin. Struct. Biol. 2006, 16, 166– 171 DOI: 10.1016/j.sbi.2006.02.004107https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xjs1Grs7w%253D&md5=77640214385bc60a67e0c0ab171537a7In quest of an empirical potential for protein structure predictionSkolnick, JeffreyCurrent Opinion in Structural Biology (2006), 16 (2), 166-171CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Key to successful protein structure prediction is a potential that recognizes the native state from misfolded structures. Recent advances in empirical potentials based on known protein structures include improved ref. states for assessing random interactions, sidechain-orientation-dependent pair potentials, potentials for describing secondary or supersecondary structural preferences and, most importantly, optimization protocols that sculpt the energy landscape to enhance the correlation between native-like features and the energy. Improved clustering algorithms that select native-like structures on the basis of cluster d. also resulted in greater prediction accuracy. For template-based modeling, these advances allowed improvement in predicted structures relative to their initial template alignments over a wide range of target-template homol. This represents significant progress and suggests applications to proteome-scale structure prediction.
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108Vanommeslaeghe, K.; MacKerell, A. D., Jr. CHARMM additive and polarizable force fields for biophysics and computer-aided drug design Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 861– 871 DOI: 10.1016/j.bbagen.2014.08.004108https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVakt7fO&md5=5a4794d8d54c6fb181c1ba4487d48cfbCHARMM additive and polarizable force fields for biophysics and computer-aided drug designVanommeslaeghe, K.; MacKerell, A. D.Biochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 861-871CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Mol. Mechanics (MM) is the method of choice for computational studies of biomol. systems owing to its modest computational cost, which makes it possible to routinely perform mol. dynamics (MD) simulations on chem. systems of biophys. and biomedical relevance. As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomol. force fields. Addnl., we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodol. Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approxn. is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1 μs on proteins, DNA, lipids and carbohydrates. Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calcns. that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying phys. forces driving macromol. structures and dynamics. This article is part of a Special Issue entitled "Recent developments of mol. dynamics".
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109Oostenbrink, C.; Villa, A.; Mark, A.; van Gunsteren, W. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6 J. Comput. Chem. 2004, 25, 1656– 1676 DOI: 10.1002/jcc.20090109https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXmvVOhtr4%253D&md5=f2c0be6f44fe768128989c9031957e4eA biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6Oostenbrink, Chris; Villa, Alessandra; Mark, Alan E.; van Gunsteren, Wilfred F.Journal of Computational Chemistry (2004), 25 (13), 1656-1676CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Successive parameterizations of the GROMOS force field have been used successfully to simulate biomol. systems over a long period of time. The continuing expansion of computational power with time makes it possible to compute ever more properties for an increasing variety of mol. systems with greater precision. This has led to recurrent parameterizations of the GROMOS force field all aimed at achieving better agreement with exptl. data. Here we report the results of the latest, extensive reparameterization of the GROMOS force field. In contrast to the parameterization of other biomol. force fields, this parameterization of the GROMOS force field is based primarily on reproducing the free enthalpies of hydration and apolar solvation for a range of compds. This approach was chosen because the relative free enthalpy of solvation between polar and apolar environments is a key property in many biomol. processes of interest, such as protein folding, biomol. assocn., membrane formation, and transport over membranes. The newest parameter sets, 53A5 and 53A6, were optimized by first fitting to reproduce the thermodn. properties of pure liqs. of a range of small polar mols. and the solvation free enthalpies of amino acid analogs in cyclohexane (53A5). The partial charges were then adjusted to reproduce the hydration free enthalpies in water (53A6). Both parameter sets are fully documented, and the differences between these and previous parameter sets are discussed.
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110Fain, B.; Xia, Y.; Levitt, M. Design of an optimal Chebyshev-expanded discrimination function for globular proteins Protein Sci. 2002, 11, 2010– 2021 DOI: 10.1110/ps.0200702110https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XlslKntrc%253D&md5=1ddc1f776ff1b3c0a340428952bc3704Design of an optimal Chebyshev-expanded discrimination function for globular proteinsFain, Boris; Xia, Yu; Levitt, MichaelProtein Science (2002), 11 (8), 2010-2021CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)We describe the construction of a scoring function designed to model the free energy of protein folding. An optimization technique is used to det. the best functional forms of the hydrophobic, residue-residue and hydrogen-bonding components of the potential. The scoring function is expanded by use of Chebyshev polynomials, the coeffs. of which are detd. by minimizing the score, in units of std. deviation, of native structures in the ensembles of alternate decoy conformations. The derived effective potential is then tested on decoy sets used conventionally in such studies. Using our scoring function, we achieve a high level of discrimination between correct and incorrect folds. In addn., our method is able to represent functions of arbitrary shape with fewer parameters than the usual histogram potentials of similar resoln. Finally, our representation can be combined easily with many optimization methods, because the total energy is a linear function of the parameters. Our results show that the techniques of Z-score optimization and Chebyshev expansion work well.
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111Basdevant, N.; Borgis, D.; Ha-Duong, T. A coarse-grained protein-protein potential derived from an all-atom force field J. Phys. Chem. B 2007, 111, 9390– 9399 DOI: 10.1021/jp0727190111https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXns1CktrY%253D&md5=b79b8ceaeedd230e8a10debdf982d3f3A Coarse-Grained Protein-Protein Potential Derived from an All-Atom Force FieldBasdevant, Nathalie; Borgis, Daniel; Ha-Duong, TapJournal of Physical Chemistry B (2007), 111 (31), 9390-9399CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)In order to study protein-protein nonbonded interactions, we present the development of a new reduced protein model that represents each amino acid residue with one to three coarse grains, whose phys. properties are derived in a consistent bottom-up procedure from the higher-resoln. all-atom AMBER force field. The resulting potential energy function is pairwise additive and includes distinct van-der-Waals and Coulombic terms. The van-der-Waals effective interactions are deduced from preliminary mol. dynamics simulations of all possible amino acid homodimers. They are best represented by a soft 1/r6 repulsion and a Gaussian attraction, with parameters obeying Lorentz-Berthelot mixing rules. For the Coulombic interaction, coarse grain charges are optimized for each sep. protein in order to best represent the all-atom electrostatic potential outside the protein core. This approach leaves the possibility of using any implicit solvent model to describe solvation effects and electrostatic screening. The coarse-grained force field is tested carefully for a small homodimeric complex, the magainin. It is shown to reproduce satisfactorily the specificity of the all-atom underlying potential, in particular within a PB/SA solvation model. The coarse-grained potential is applied to the redocking prediction of three different protein-protein complexes: the magainin dimer, the barnase-barstar, and the trypsin-BPTI complexes. It is shown to provide per se an efficient and discriminating scoring energy function for the protein-protein docking problem that remains pertinent at both the global and refinement stage.
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112Cascella, M.; Vanni, S. In Chemical Modelling: Vol. 12; The Royal Society of Chemistry: London, 2016; Vol. 12.There is no corresponding record for this reference.
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113Brooks, B.; Bruccoleri, R.; Olafson, B.; States, D.; Swaminathan, S.; Karplus, M. CHARMM: A program for macromolecular energy, minimization, and dynamics calculations J. Comput. Chem. 1983, 4, 187– 217 DOI: 10.1002/jcc.540040211113https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaL3sXit1aiu7w%253D&md5=bd639b4299ac9934f4497c1a9fe750d2CHARMM: a program for macromolecular energy, minimization, and dynamics calculationsBrooks, Bernard R.; Bruccoleri, Robert E.; Olafson, Barry D.; States, David J.; Swaminathan, S.; Karplus, MartinJournal of Computational Chemistry (1983), 4 (2), 187-217CODEN: JCCHDD; ISSN:0192-8651.CHARMM (Chem. at HARvard Macromol. Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromol. systems. The program can read or model build structures, energy minimize them by first- or second-deriv. techniques, perform a normal mode or mol. dynamics simulation, and analyze the structural, equil., and dynamic properties detd. in these calcns. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.
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114Lee, S.; Tran, A.; Allsopp, M.; Lim, J. B.; Henin, J.; Klauda, J. B. CHARMM36 united atom chain model for lipids and surfactants J. Phys. Chem. B 2014, 118, 547– 556 DOI: 10.1021/jp410344g114https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFCjur%252FK&md5=4efa293c0ecf6be13a1c8d2b3299891aCHARMM36 United Atom Chain Model for Lipids and SurfactantsLee, Sarah; Tran, Alan; Allsopp, Matthew; Lim, Joseph B.; Henin, Jerome; Klauda, Jeffery B.Journal of Physical Chemistry B (2014), 118 (2), 547-556CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Mol. simulations of lipids and surfactants require accurate parameters to reproduce and predict exptl. properties. Previously, a united atom UA chain model was developed for the CHARMM27/27r lipids (Henin, J., et al. J. Phys. Chem. B. 2008, 112, 7008-7015) but suffers from the flaw that bilayer simulations using the model require an imposed surface area ensemble, which limits its use to pure bilayer systems. A UA-chain model has been developed based on the CHARMM36 C36 all-atom lipid parameters, termed C36-UA, and agreed well with bulk, lipid membrane, and micelle formation of a surfactant. Mol. dynamics MD simulations of alkanes heptane and pentadecane were used to test the validity of C36-UA on d., heat of vaporization, and liq. self-diffusion consts. Then, simulations using C36-UA resulted in accurate properties surface area per lipid, X-ray and neutron form factors, and chain order parameters of various satd.- and unsatd.-chain bilayers. When mixed with the all-atom cholesterol model and tested with a series of 1,2-dimyristoyl-sn-glycero-3-phosphocholine DMPC/cholesterol mixts., the C36-UA model performed well. Simulations of self-assembly of a surfactant dodecylphosphocholine, DPC using C36-UA suggest an aggregation no. of 53 ± 11 DPC mols. at 0.45 M of DPC, which agrees well with exptl. ests. Therefore, the C36-UA force field offers a useful alternative to the all-atom C36 lipid force field by requiring less computational cost while still maintaining the same level of accuracy, which may prove useful for large systems with proteins.
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115Schmid, N.; Eichenberger, A. P.; Choutko, A.; Riniker, S.; Winger, M.; Mark, A. E.; van Gunsteren, W. F. Definition and testing of the GROMOS force-field versions 54A7 and 54B7 Eur. Biophys. J. 2011, 40, 843– 856 DOI: 10.1007/s00249-011-0700-9115https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXnsVCgs74%253D&md5=a1cd133f1e663da949324060e00c950dDefinition and testing of the GROMOS force-field versions 54A7 and 54B7Schmid, Nathan; Eichenberger, Andreas P.; Choutko, Alexandra; Riniker, Sereina; Winger, Moritz; Mark, Alan E.; Gunsteren, Wilfred F.European Biophysics Journal (2011), 40 (7), 843-856CODEN: EBJOE8; ISSN:0175-7571. (Springer)New parameter sets of the GROMOS biomol. force field, 54A7 and 54B7, are introduced. These parameter sets summarize some previously published force field modifications: The 53A6 helical propensities are cor. through new φ/ψ torsional angle terms and a modification of the N-H, C=O repulsion, a new atom type for a charged -CH3 in the choline moiety is added, the Na+ and Cl- ions are modified to reproduce the free energy of hydration, and addnl. improper torsional angle types for free energy calcns. involving a chirality change are introduced. The new helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide. The stability of the proteins is improved in comparison with the 53A6 force field, and good agreement with a range of primary exptl. data is obtained.
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116de Jong, D. H.; Singh, G.; Bennett, W. F. D.; Arnarez, C.; Wassenaar, T. A.; Schafer, L. V.; Periole, X.; Tieleman, D. P.; Marrink, S. J. Improved Parameters for the Martini Coarse-Grained Protein Force Field J. Chem. Theory Comput. 2013, 9, 687– 697 DOI: 10.1021/ct300646g116https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1OnsrbO&md5=ffad32e5e861a8e1fdf62491d39d8450Improved Parameters for the Martini Coarse-Grained Protein Force Fieldde Jong, Djurre H.; Singh, Gurpreet; Bennett, W. F. Drew; Arnarez, Clement; Wassenaar, Tsjerk A.; Schaefer, Lars V.; Periole, Xavier; Tieleman, D. Peter; Marrink, Siewert J.Journal of Chemical Theory and Computation (2013), 9 (1), 687-697CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The Martini coarse-grained force field has been successfully used for simulating a wide range of (bio)mol. systems. Recent progress in our ability to test the model against fully atomistic force fields, however, has revealed some shortcomings. Most notable, phenylalanine and proline were too hydrophobic, and dimers formed by polar residues in apolar solvents did not bind strongly enough. Here, we reparametrize these residues either through reassignment of particle types or by introducing embedded charges. The new parameters are tested with respect to partitioning across a lipid bilayer, membrane binding of Wimley-White peptides, and dimerization free energy in solvents of different polarity. In addn., we improve some of the bonded terms in the Martini protein force field that lead to a more realistic length of α-helixes and to improved numerical stability for polyalanine and glycine repeats. The new parameter set is denoted Martini version 2.2.
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117Izvekov, S.; Parrinello, M.; Burnham, C.; Voth, G. Effective force fields for condensed phase systems from ab initio molecular dynamics simulation: A new method for force-matching J. Chem. Phys. 2004, 120, 10896– 10913 DOI: 10.1063/1.1739396117https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXksVCqt7w%253D&md5=604e711721e915c2dfbd6da3542c4faaEffective force fields for condensed phase systems from ab initio molecular dynamics simulation: A new method for force-matchingIzvekov, Sergei; Parrinello, Michele; Burnham, Christian J.; Voth, Gregory A.Journal of Chemical Physics (2004), 120 (23), 10896-10913CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)A novel least-squares fitting approach is presented to obtain classical force fields from trajectory and force databases produced by ab initio (e.g., Car-Parrinello) mol. dynamics (MD) simulations. The method was applied to derive effective nonpolarizable three-site force fields for liq. water at ambient conditions from Car-Parrinello MD simulations in the Becke-Lee-Yang-Parr approxn. to the electronic d. functional theory. The force-matching procedure includes a fit of short-ranged nonbonded forces, bonded forces, and at. partial charges. The various parameterizations of the water force field differ by an enforced smooth cut-off applied to the short-ranged interaction term. These were obtained by fitting to the trajectory and force data produced by Car-Parrinello MD simulations of systems of 32 and 64 H2O mols. The new water force fields were developed assuming both flexible or rigid mol. geometry. The simulated structural and self-diffusion properties of liq. water using the fitted force fields are in close agreement with those obsd. in the underlying Car-Parrinello MD simulations. The resulting empirical models compare to expt. much better than many conventional simple point charge (SPC) models. The fitted potential is also shown to combine well with more sophisticated intramol. potentials. Importantly, the computational cost of the new models is comparable to that for SPC-like potentials.
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118Ercolessi, F.; Adams, J. B. Interatomic Potentials from First-Principles Calculations: The Force-Matching Method Europhys. Lett. 1994, 26, 583 DOI: 10.1209/0295-5075/26/8/005118https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXks1KisLc%253D&md5=876903808d34a9bcacac16517e331480Interatomic potentials from first-principles calculations: the force-matching methodErcolessi, F.; Adams, J. B.Europhysics Letters (1994), 26 (8), 583-8CODEN: EULEEJ; ISSN:0295-5075.The authors present a new scheme to ext. numerically «optimal» interat. potentials from large amts. of data produced by first-principles calcns. The method is based on fitting the potential to ab initio at. forces of many at. configurations, including surfaces, clusters, liqs. and crystals at finite temp. The extensive data set overcomes the difficulties encountered by traditional fitting approaches when using rich and complex analytic forms, allowing to construct potentials with a degree of accuracy comparable to that obtained by ab initio methods. A glue potential for aluminum obtained with this method is presented and discussed.
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119Schommers, W. Pair potentials in disordered many-particle systems: A study for liquid gallium Phys. Rev. A: At., Mol., Opt. Phys. 1983, 28, 3599– 3605 DOI: 10.1103/PhysRevA.28.3599119https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaL2cXis1amsg%253D%253D&md5=6078da0587a429c9afd45a98c0bec882Pair potentials in disordered many-particle systems: A study for liquid galliumSchommers, W.Physical Review A: Atomic, Molecular, and Optical Physics (1983), 28 (6), 3599-605CODEN: PLRAAN; ISSN:0556-2791.Several methods are compared which connect the effective pair potential to the pair-correlation function. These methods are a self-consistent method using mol. dynamics, the so-called modified STLS (Singwi-Tosi-Land-Sjoelander) theory, the Weeks-Chandler-Andersen approach, the Percus-Yevick theory, the hypernetted-chain approxn., and the Born-Green equation. Since the pair potential is, in general, very sensitive to small variations in the pair-correlation functions, structure data were used with sufficient accuracy in the detn. of the pair potentials from the pair-correlation function. A. H. Narten (1972) performed measurements on liq. Ga with high precision, and, therefore, all calcns. were performed on the basis of his structure data. The self-consistent method and the Weeks-Chandler-Andersen approach led to reasonable results. The results for the pair potential obtained from the other methods are unsatisfactory and cannot be used in the detn. of liq.-Ga properties.
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120Henderson, R. L. A uniqueness theorem for fluid pair correlation functions Phys. Lett. A 1974, 49, 197– 198 DOI: 10.1016/0375-9601(74)90847-0There is no corresponding record for this reference.
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121Reith, D.; Pütz, M.; Müller-Plathe, F. Deriving effective mesoscale potentials from atomistic simulations J. Comput. Chem. 2003, 24, 1624– 1636 DOI: 10.1002/jcc.10307121https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXntFentL4%253D&md5=304cc4acd956aaa71f476992e656fd13Deriving effective mesoscale potentials from atomistic simulationsReith, Dirk; Puetz, Mathias; Mueller-Plathe, FlorianJournal of Computational Chemistry (2003), 24 (13), 1624-1636CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liq. systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few interactions. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 redn. of the degrees of freedom. This procedure was performed for PI solns. as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concn. regimes.
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122Moore, T. C.; Iacovella, C. R.; McCabe, C. Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion J. Chem. Phys. 2014, 140, 224104 DOI: 10.1063/1.4880555122https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpsFKmt7g%253D&md5=0897e6378ed6caabc10916c52a020312Derivation of coarse-grained potentials via multistate iterative Boltzmann inversionMoore, Timothy C.; Iacovella, Christopher R.; McCabe, ClareJournal of Chemical Physics (2014), 140 (22), 224104/1-224104/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)An extension is proposed to the std. iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodn. states than the std. IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the std. IBI method. Addnl., through the examn. of alkane monolayers, it is shown that the relative wt. given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of ref. atomistic and/or exptl. systems. (c) 2014 American Institute of Physics.
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123Lyubartsev, A.; Laaksonen, A. Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 1995, 52, 3730– 3737 DOI: 10.1103/PhysRevE.52.3730123https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXovVSgsrw%253D&md5=294e69e8830aeaa4ffb1cd17cc7af20eCalculation of effective interaction potentials from radial distribution functions: a reverse Monte Carlo approachLyubartsev, Alexander; Laaksonen, AattoPhysical Review E: Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics (1995), 52 (4-A), 3730-7CODEN: PLEEE8; ISSN:1063-651X. (American Physical Society)An approach is presented to solve the reverse problem of statistical mechanics: reconstruction of interaction potentials from radial distribution functions. The method consists of the iterative adjustment of the interaction potential to known radical distribution functions using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical avs. with Hamiltonian parameters. The method consists of the iterative adjustment of the interaction potential to known radical distribution functions using a Monte Carlo simulation technique and statistical-mechanics relations to connect deviations of canonical avs. with Hamiltonian parameters. The method is applied to calc. the effective interaction potentials between the ions in aq. NaCl solns. at two different concns. The ref. ion-ion radial distribution functions, calcd. in sep. mol. dynamics simulations with water mols., are reproduced in Monte Carlo simulations, using the effective interaction potentials for the hydrated ions. Applications of the present method should provide an effective and economical way to simulate equil. properties for very large mol. systems (e.g., polyelectrolytes) in the presence of hydrated ions, as well as to offer an approach to reduce a complexity in studies of various assocd. and aggregated systems in soln.
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124Lyubartsev, A.; Mirzoev, A.; Chen, L.; Laaksonen, A. Systematic coarse-graining of molecular models by the Newton inversion method. Faraday Discuss. 2010, 144, 43 DOI: 10.1039/B901511F124https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht12htrfL&md5=8da608a1d6b4259e79982e5be0c8bce4Systematic coarse-graining of molecular models by the Newton inversion methodLyubartsev, Alexander; Mirzoev, Alexander; Chen, Li-Jun; Laaksonen, AattoFaraday Discussions (2010), 144 (), 43-56CODEN: FDISE6; ISSN:1359-6640. (Royal Society of Chemistry)Systematic construction of coarse-grained mol. models from detailed atomistic simulations, and even from ab initio simulations is discussed. Atomistic simulations are first performed to ext. structural information about the system, which is then used to det. effective potentials for a coarse-grained model of the same system. The statistical-mech. equations expressing the canonical properties in terms of potential parameters can be inverted and solved numerically according to the iterative Newton scheme. In our previous applications, known as the Inverse Monte Carlo, radial distribution functions were inverted to reconstruct pair potential, while in a more general approach the targets can be other canonical avs. We have considered several examples of coarse-graining; for the united atom water model we suggest an easy way to overcome the known problem of high pressure. Further, we have developed coarse-grained models for L- and D-prolines, dissolved here in an org. solvent (dimethylsulfoxide), keeping their enantiomeric properties from the corresponding all-atom proline model. Finally, we have revisited the previously developed coarse-grained lipid model based on an updated all-at. force field. We use this model in large-scale meso-scale simulations demonstrating spontaneous formation of different structures, such as vesicles, micelles, and multi-lamellar structures, depending on thermodynamical conditions.
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125Izvekov, S.; Voth, G. A Multiscale Coarse-Graining Method for Biomolecular Systems J. Phys. Chem. B 2005, 109, 2469– 2473 DOI: 10.1021/jp044629q125https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXmtVSntQ%253D%253D&md5=3dd30b57cd2523f23d89ffc0c1782ac2A Multiscale Coarse-Graining Method for Biomolecular SystemsIzvekov, Sergei; Voth, Gregory A.Journal of Physical Chemistry B (2005), 109 (7), 2469-2473CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A new approach is presented for obtaining coarse-grained (CG) force fields from fully atomistic mol. dynamics (MD) trajectories. The method is demonstrated by applying it to derive a CG model for the dimyristoylphosphatidylcholine (DMPC) lipid bilayer. The coarse-graining of the interparticle force field is accomplished by an application of a force-matching procedure to the force data obtained from an explicit atomistic MD simulation of the biomol. system of interest. Hence, the method is termed a "multiscale" CG (MS-CG) approach in which explicit atomistic-level forces are propagated upward in scale to the coarse-grained level. The CG sites in the lipid bilayer application were assocd. with the centers-of-mass of at. groups because of the simplicity in the evaluation of the forces acting on them from the atomistic data. The resulting CG lipid bilayer model is shown to accurately reproduce the structural properties of the phospholipid bilayer.
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126Cho, H.; Chu, J.-W. Inversion of radial distribution functions to pair forces by solving the Yvon–Born–Green equation iteratively J. Chem. Phys. 2009, 131, 134107 DOI: 10.1063/1.3238547There is no corresponding record for this reference.
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127Lu, L.; Dama, J.; Voth, G. Fitting coarse-grained distribution functions through an iterative force-matching method J. Chem. Phys. 2013, 139, 121906 DOI: 10.1063/1.4811667127https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtVOjsLvI&md5=96fbee0c60c3130726d6c07e068188c0Fitting coarse-grained distribution functions through an iterative force-matching methodLu, Lanyuan; Dama, James F.; Voth, Gregory A.Journal of Chemical Physics (2013), 139 (12), 121906/1-121906/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)An iterative coarse-graining method is developed for systematically converting an atomistic force field to a model at lower resoln. that is able to accurately reproduce the distribution functions defined in the coarse-grained potential. The method starts from the multiscale coarse-graining (MS-CG) approach, and it iteratively refines the distribution functions using repeated applications of the MS-CG algorithm. It is justified on the basis of the force matching normal equation, which can be considered a discrete form of the Yvon-Born-Green equation in liq. state theory. Numerical results for mol. systems involving pairwise nonbonded and three-body bonded interactions are obtained, and comparison with other approaches in literature is provided. (c) 2013 American Institute of Physics.
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128Mullinax, J. W.; Noid, W. G. A Generalized-Yvon–Born–Green Theory for Determining Coarse-Grained Interaction Potentials† J. Phys. Chem. C 2010, 114, 5661– 5674 DOI: 10.1021/jp9073976There is no corresponding record for this reference.
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129Shell, S. The relative entropy is fundamental to multiscale and inverse thermodynamic problems J. Chem. Phys. 2008, 129, 144108 DOI: 10.1063/1.2992060129https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1KlsLnI&md5=6f0951ee8fc7308e822a1efadac0d713The relative entropy is fundamental to multiscale and inverse thermodynamic problemsShell, M. ScottJournal of Chemical Physics (2008), 129 (14), 144108/1-144108/7CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The relative entropy, Srel ≡ .sum.pT ln(pT/pM), provides a fundamental and unifying framework for multiscale anal. and for inverse mol.-thermodn. problems involving optimization of a model system (M) to reproduce the properties of a target one (T). The relative entropy serves as a generating function for principles in variational mean-field theory and uniqueness and gives intuitive results for simple case scenarios in model development. Moreover, the relative entropy provides a rigorous framework for multiscale simulations and offers new numerical techniques for linking models at different scales. Finally, by using it to quantify the deviations of a three-site model of water from simple liqs., it even predicts water's kinetic anomalies. (c) 2008 American Institute of Physics.
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130Bilionis, I.; Zabaras, N. A stochastic optimization approach to coarse-graining using a relative-entropy framework J. Chem. Phys. 2013, 138, 044313 DOI: 10.1063/1.4789308130https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFCkuro%253D&md5=bf925cd878859b24722ab884dd561cf3A stochastic optimization approach to coarse-graining using a relative-entropy frameworkBilionis, Ilias; Zabaras, NicholasJournal of Chemical Physics (2013), 138 (4), 044313/1-044313/12CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Relative entropy has been shown to provide a principled framework for the selection of coarse-grained potentials. Despite the intellectual appeal of it, its application has been limited by the fact that it requires the soln. of an optimization problem with noisy gradients. When using deterministic optimization schemes, one is forced to either decrease the noise by adequate sampling or to resolve to ad hoc modifications in order to avoid instabilities. The former increases the computational demand of the method while the latter is of questionable validity. In order to address these issues and make relative entropy widely applicable, we propose alternative schemes for the soln. of the optimization problem using stochastic algorithms. (c) 2013 American Institute of Physics.
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131Chaimovich, A.; Shell, S. Coarse-graining errors and numerical optimization using a relative entropy framework J. Chem. Phys. 2011, 134, 094112 DOI: 10.1063/1.3557038131https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXislentLs%253D&md5=4de895cbb35fda9c00d6dbec8a26b255Coarse-graining errors and numerical optimization using a relative entropy frameworkChaimovich, Aviel; Shell, M. ScottJournal of Chemical Physics (2011), 134 (9), 094112/1-094112/15CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The ability to generate accurate coarse-grained models from ref. fully at. (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex mol. systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, Srel, that measures the information lost upon coarse-graining. Here, we develop a broad theor. framework for this methodol. and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodol. and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theor. considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework. (c) 2011 American Institute of Physics.
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132Chaimovich, A.; Shell, S. Relative entropy as a universal metric for multiscale errors. Phys. Rev. E 2010, 81, DOI: 10.1103/PhysRevE.81.060104There is no corresponding record for this reference.
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133Espanol, P.; Zuniga, I. Obtaining fully dynamic coarse-grained models from MD Phys. Chem. Chem. Phys. 2011, 13, 10538– 10545 DOI: 10.1039/c0cp02826f133https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsFams7o%253D&md5=f1abb6b57b51940aebf9ab3a550d6e7cObtaining fully dynamic coarse-grained models from MDEspanol, Pep; Zuniga, IgnacioPhysical Chemistry Chemical Physics (2011), 13 (22), 10538-10545CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)We present a general method to obtain parametrised models for the drift and diffusion terms of the Fokker-Planck equation of a coarse-grained description of mol. systems. The method is based on the minimisation of the relative entropy defined in terms of the two-time joint probability and thus captures the full dynamics of the coarse-grained description. In addn., we show an alternative Bayesian argument that starts from the path probability of a diffusion process which allows one to obtain the best parametrised model that fits an actual obsd. path of the coarse-grained variables. Both approaches lead to exactly the same optimization function giving strong support to the methodol. We provide an heuristic argument that explains how both approaches are connected.
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134Murtola, T.; Karttunen, M.; Vattulainen, I. Systematic coarse graining from structure using internal states: application to phospholipid/cholesterol bilayer. J. Chem. Phys. 2009, 131, 055101 DOI: 10.1063/1.3167405There is no corresponding record for this reference.
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135Brini, E.; van der Vegt, N. F. Chemically transferable coarse-grained potentials from conditional reversible work calculations. J. Chem. Phys. 2012, 137, 154113 DOI: 10.1063/1.4758936135https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFCnsLjN&md5=6032a2473dc78d055c8e80a48200ce42Chemically transferable coarse-grained potentials from conditional reversible work calculationsBrini, E.; van der Vegt, N. F. A.Journal of Chemical Physics (2012), 137 (15), 154113/1-154113/8CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The representability and transferability of effective pair potentials used in multiscale simulations of soft matter systems is ill understood. In this paper, we study liq. state systems composed of n-alkanes, the coarse-grained (CG) potential of which may be assumed pairwise additive and has been obtained using the conditional reversible work (CRW) method. The CRW method is a free-energy-based coarse-graining procedure, which, by means of performing the coarse graining at pair level, rigorously provides a pair potential that describes the interaction free energy between two mapped atom groups (beads) embedded in their resp. chem. environments. The pairwise nature of the interactions combined with their dependence on the chem. bonded environment makes CRW potentials ideally suited in studies of chem. transferability. We report CRW potentials for hexane using a mapping scheme that merges two heavy atoms in one CG bead. It is shown that the model is chem. and thermodynamically transferable to alkanes of different chain lengths in the liq. phase at temps. between the melting and the b.p. under atm. (1 atm) pressure conditions. It is further shown that CRW-CG potentials may be readily obtained from a single simulation of the liq. state using the free energy perturbation method, thereby providing a fast and versatile mol. coarse graining method for aliph. mols. (c) 2012 American Institute of Physics.
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136Deichmann, G.; Marcon, V.; van der Vegt, N. Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method J. Chem. Phys. 2014, 141, 224109 DOI: 10.1063/1.4903454136https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFahs7fI&md5=8db8867e8a8bf48ae7b85947d9e4ef4eBottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work methodDeichmann, Gregor; Marcon, Valentina; van der Vegt, Nico F. A.Journal of Chemical Physics (2014), 141 (22), 224109/1-224109/9CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Mol. simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodn. properties can be quite accurately represented while the prediction of dynamic properties remains difficult, esp. for multi-component systems. In this work, we use constraint mol. dynamics simulations for calcg. dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived from fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These mol. liqs. are simulated with atomistic mol. dynamics, coarse-grained mol. dynamics, and DPD. We find that the CRW-DPD models reproduce the liq. structure and diffusive dynamics of the liq. systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads contg. five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale sepn. can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics. (c) 2014 American Institute of Physics.
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137Hadley, K.; McCabe, C. Coarse-Grained Molecular Models of Water: A Review Mol. Simul. 2012, 38, 671– 681 DOI: 10.1080/08927022.2012.671942137https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XpvVSmtr8%253D&md5=6501a25b1713de1bda758faf959ae6f9Coarse-grained molecular models of water: a reviewHadley, Kevin R.; McCabe, ClareMolecular Simulation (2012), 38 (8-9), 671-681CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)A review. Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems involving large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger time steps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biol. importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regard to how many waters each CG group or bead represents, whether anal. or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. How the models are parameterised, which typically depends on their application, is also discussed.
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138Tanaka, S.; Scheraga, H. A. Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins Macromolecules 1976, 9, 945– 950 DOI: 10.1021/ma60054a013138https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE2sXht1Kh&md5=74701630ff1fddd501492dd3075fa91fMedium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteinsTanaka, Seiji; Scheraga, Harold A.Macromolecules (1976), 9 (6), 945-50CODEN: MAMOBX; ISSN:0024-9297.A hypothesis for protein folding is discussed, in which the native structure is formed by a 3-step mechanism: (A) formation of ordered backbone structures by short-range interactions, (B) formation of small contact regions by medium-range interactions, and (C) assocn. of the small contact regions into the native structure by long-range interactions. The empirical interaction parameters, used as a measure of the medium- and long-range interactions (the std. free energy, ΔG°k,l, of formation of a contact between amino acids of species k and l) that include the role of the solvent (water) and det. the conformation of a protein in steps B and C are evaluated from the frequency of contacts in the x-ray structures of native proteins. The numerical values of ΔG°k,l for all possible pairs of the 20 naturally occurring amino acids are presented. Contacts between highly nonpolar side chains of amino acids such as isoleucine, phenylalanine, tryptophan, and leucine are shown quant. to be stable. On the contrary, contacts involving polar side chains of amino acids such as serine, aspartate, lysine, and glutamate are significantly less stable. While this implies, in a quant. manner, that it is generally more favorable for nonpolar groups to lie in the interior of the protein mol. and for the polar side chains to be exposed to the solvent (water) rather than to form contacts with other amino acids, many exceptions to this generalization are obsd.
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139Samudrala, R.; Moult, J. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction J. Mol. Biol. 1998, 275, 895– 916 DOI: 10.1006/jmbi.1997.1479139https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXhs12jtLc%253D&md5=b9b6226434dfe70a5b96d43d67c5097dAn all-atom distance-dependent conditional probability discriminatory function for protein structure predictionSamudrala, Ram; Moult, JohnJournal of Molecular Biology (1998), 275 (5), 895-916CODEN: JMOBAK; ISSN:0022-2836. (Academic Press Ltd.)We present a formalism to compute the probability of an amino acid sequence conformation being native-like, given a set of pairwise atom-atom distances. The formalism is used to derive three discriminatory functions with different types of representations for the atom-atom contacts obsd. in a database of protein structures. These functions include two virtual atom representations and one all-heavy atom representation. When applied to six different decoy sets contg. a range of correct and incorrect conformations of amino acid sequences, the all-atom distance-dependent discriminatory function is able to identify correct from incorrect more often than the discriminatory functions using approx. representations. We illustrate the importance of using a detailed at. description for obtaining the most accurate discrimination, and the necessity for testing discriminatory functions against a wide variety of decoys. The discriminatory function is also shown to be capable of capturing the fine details of atom-atom preferences. These results suggest that the all-atom distance-dependent discriminatory function will be useful for protein structure prediction and model refinement.
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140Simons, K. T.; Ruczinski, I.; Kooperberg, C.; Fox, B. A.; Bystroff, C.; Baker, D. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins Proteins: Struct., Funct., Genet. 1999, 34, 82– 95 DOI: 10.1002/(SICI)1097-0134(19990101)34:1<82::AID-PROT7>3.0.CO;2-AThere is no corresponding record for this reference.
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141Xia, Y.; Levitt, M. Extracting knowledge-based energy functions from protein structures by error rate minimization: Comparison of methods using lattice model J. Chem. Phys. 2000, 113, 9318– 9330 DOI: 10.1063/1.1320823141https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXnvFaiu7g%253D&md5=9a749625cdf3ea2dfb1119109e14d564Extracting knowledge-based energy functions from protein structures by error rate minimization: Comparison of methods using lattice modelXia, Yu; Levitt, MichaelJournal of Chemical Physics (2000), 113 (20), 9318-9330CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)We describe a general framework for extg. knowledge-based energy function from a set of native protein structures. In this scheme, the energy function is optimal when there is least chance that a random structure has a lower energy than the corresponding native structure. We first show that subject to certain approxns., most current database-derived energy functions fall within this framework, including mean-field potentials, Z-score optimization, and constraint satisfaction methods. We then propose a simple method for energy function parametrization derived from our anal. We go on to compare our method to other methods using a simple lattice model in the context of three different energy function scenarios. We show that our method, which is based on the most stringent criteria, performs best in all cases. The power and limitations of each method for deriving knowledge-based energy function is examd.
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142Sippl, M. J. Boltzmann’s principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures J. Comput.-Aided Mol. Des. 1993, 7, 473– 501 DOI: 10.1007/BF02337562There is no corresponding record for this reference.
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143Skolnick, J.; Kolinski, A.; Ortiz, A. Derivation of protein-specific pair potentials based on weak sequence fragment similarity Proteins: Struct., Funct., Genet. 2000, 38, 3– 16 DOI: 10.1002/(SICI)1097-0134(20000101)38:1<3::AID-PROT2>3.0.CO;2-S143https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXis1OmsQ%253D%253D&md5=8ceddaaf101fe7e269464144b91a1bd7Derivation of protein-specific pair potentials based on weak sequence fragment similaritySkolnick, Jeffrey; Kolinski, Andrzej; Ortiz, AngelProteins: Structure, Function, and Genetics (2000), 38 (1), 3-16CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)A method is presented for the derivation of knowledge-based pair potentials that corrects for the various compns. of different proteins. The resulting statistical pair potential is more specific than that derived from previous approaches as assessed by gapless threading results. Addnl., a methodol. is presented that interpolates between statistical potentials when no homologous examples to the protein of interest are in the structural database used to derive the potential, to a Go-like potential (in which native interactions are favorable and all nonnative interactions are not) when homologous proteins are present. For cases in which no protein exceeds 30% sequence identity, pairs of weakly homologous interacting fragments are employed to enhance the specificity of the potential. In gapless threading, the mean z score increases from -10.4 for the best statistical pair potential to -12.8 when the local sequence similarity, fragment-based pair potentials are used. Examn. of the ab initio structure prediction of four representative globular proteins consistently reveals a qual. improvement in the yield of structures in the 4 to 6 Å rmsd from native range when the fragment-based pair potential is used relative to that when the quasichem. pair potential is employed. This suggests that such protein-specific potentials provide a significant advantage relative to genetic quasichem. potentials.
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144Godzik, A.; Kolinski, A.; Skolnick, J. Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets Protein Sci. 1995, 4, 2107– 2117 DOI: 10.1002/pro.5560041016144https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXoslygt78%253D&md5=b6eb3c3c9e36bd2db5bf98e4bb9fd90bAre proteins ideal mixtures of amino acids? Analysis of energy parameter setsGodzik, Adam; Kolinski, Andrzej; Skolnick, JeffreyProtein Science (1995), 4 (10), 2107-17CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)Various existing derivations of the effective potentials of mean force for the two-body interactions between amino acid side chains in proteins are reviewed and compared to each other. The differences between different parameters sets can be traced to the ref. state used to define the zero of energy. Depending on the ref. state, the transfer free energy or other pseudo-one-body contributions can be present to various extents in two-body parameters sets. It is, however, possible to compare various derivations directly by concg. on the "excess" energy - a term that describes the difference between a real protein and an ideal soln. of amino acids. Furthermore, the no. of protein structures available for anal. allows one to check the consistency of the derivation and the errors by comparing parameters derived from various subsets of the whole database. It is shown that pair interaction preferences are very consistent throughout the database. Independently derived parameter sets have correlation coeffs. on the order of 0.8, with the mean difference between equiv. entries of 0.1 kT. Also, the low-quality (low resoln., little or no refinement) structures show similar regularities. There are, however, large differences between interaction parameters derived on the basis of crystallog. structures and structures obtained by the NMR refinement. The origin of the latter difference is not yet understood.
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145Skolnick, J.; Jaroszewski, L.; Kolinski, A.; Godzik, A. Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct? Protein Sci. 1997, 6, 676– 688 DOI: 10.1002/pro.5560060317145https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXhvVyjtLY%253D&md5=000d63b0a6f7eca713917b07d714031eDerivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct?Skolnick, Jeffrey; Jaroszewski, Lukasz; Kolinski, Andrzej; Godzik, AdamProtein Science (1997), 6 (3), 676-688CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)Many existing derivations of knowledge-based statistical pair potentials invoke the quasichem. approxn. to est. the expected side-chain contact frequency if there were no amino acid pair-specific interactions. At first glance, the quasichem. approxn. that treats the residues in a protein as being disconnected and expresses the side-chain contact probability as being proportional to the product of the mole fractions of the pair of residues would appear to be rather severe. To investigate the validity of this approxn., we introduce two new ref. states in which no specific pair interactions between amino acids are allowed, but in which the connectivity of the protein chain is retained. The first ests. the expected no. of side-chain contacts by treating the protein as a Gaussian random coil polymer. The second, more realistic ref. state includes the effects of chain connectivity, secondary structure, and chain compactness by estg. the expected side-chain contact probability by placing the sequence of interest in each member of a library of structures of comparable compactness to the native conformation. The side-chain contact maps are not allowed to readjust to the sequence of interest, i.e., the side chains cannot repack. This situation would hold rigorously if all amino acids were the same size. Both ref. states effectively permit the factorization of the side-chain contact probability into sequence-dependent and structure-dependent terms. Then, because the sequence distribution of amino acids in proteins is random, the quasichem. approxn. to each of these ref. states is shown to be excellent. Thus, the range of validity of the quasichem. approxn. is detd. by the magnitude of the side-chain repacking term, which is, at present, unknown. Finally, the performance of these two sets of pair interaction potentials as well as side-chain contact fraction-based interaction scales is assessed by inverse folding tests both without and with allowing for gaps.
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146Majek, P.; Elber, R. A coarse-grained potential for fold recognition and molecular dynamics simulations of proteins Proteins: Struct., Funct., Genet. 2009, 76, 822– 836 DOI: 10.1002/prot.22388There is no corresponding record for this reference.
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147Zhou, Y.; Zhou, H.; Zhang, C.; Liu, S. What is a desirable statistical energy function for proteins and how can it be obtained? Cell Biochem. Biophys. 2006, 46, 165– 174 DOI: 10.1385/CBB:46:2:165147https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht1yks7zP&md5=e1fbf180781f9d4a021e758a87998ca2What is a desirable statistical energy function for proteins and how can it be obtained?Zhou, Yaoqi; Zhou, Hongyi; Zhang, Chi; Liu, SongCell Biochemistry and Biophysics (2006), 46 (2), 165-174CODEN: CBBIFV; ISSN:1085-9195. (Humana Press Inc.)A review. Can one obtain a phys. energy function for proteins from statistical anal. of protein structures. A direct answer to this question is likely "no.". A less demanding question is whether one can produce a statistical energy function that has the desirable features of a phys.-based energy function. Such a desirable energy function would be founded on a phys. basis with few or no adjustable parameters, reproduce the known phys. characters of amino acid residues, be mostly database independent and transferable, and, more importantly, reasonably accurate in various applications. In this review, we show how such a desirable energy function can be obtained via introducing a simple phys.-based ref. state called DFIRE (Distance-scaled, Finite, Ideal-gas Ref. state).
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148Shen, M.-Y.; Sali, A. Statistical potential for assessment and prediction of protein structures Protein Sci. 2006, 15, 2507– 2524 DOI: 10.1110/ps.062416606148https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtFygsrfO&md5=f4e7ef56cd100164e347103a6888ee8eStatistical potential for assessment and prediction of protein structuresShen, Min-Yi; Sali, AndrejProtein Science (2006), 15 (11), 2507-2524CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Protein structures in the Protein Data Bank provide a wealth of data about the interactions that det. the native states of proteins. Using the probability theory, the authors derive an at. distance-dependent statistical potential from a sample of native structures that does not depend on any adjustable parameters (Discrete Optimized Protein Energy, or DOPE). DOPE is based on an improved ref. state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on a sample native structure; it thus accounts for the finite and spherical shape of the native structures. The DOPE potential was extd. from a nonredundant set of 1472 crystallog. structures. The authors tested DOPE and five other scoring functions by the detection of the native state among six multiple target decoy sets, the correlation between the score and model error, and the identification of the most accurate nonnative structure in the decoy set. For all decoy sets, DOPE is the best performing function in terms of all criteria, except for a tie in one criterion for one decoy set. To facilitate its use in various applications, such as model assessment, loop modeling, and fitting into cryo-electron microscopy mass d. maps combined with comparative protein structure modeling, DOPE was incorporated into the modeling package MODELLER-8.
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149Yang, Y.; Zhou, Y. Specific interactions for ab initio folding of protein terminal regions with secondary structures Proteins: Struct., Funct., Genet. 2008, 72, 793– 803 DOI: 10.1002/prot.21968149https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnvVWhtLY%253D&md5=76ea31cb102de1f066ef595662b70b86Specific interactions for ab initio folding of protein terminal regions with secondary structuresYang, Yuedong; Zhou, YaoqiProteins: Structure, Function, and Bioinformatics (2008), 72 (2), 793-803CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Proteins fold into unique three-dimensional structures by specific, orientation-dependent interactions between amino acid residues. Here, we ext. orientation-dependent interactions from protein structures by treating each polar atom as a dipole with a direction. The resulting statistical energy function successfully refolds 13 out of 16 fully unfolded secondary-structure terminal regions of 10-23 amino acid residues in 15 small proteins. Dissecting the orientation-dependent energy function reveals that the orientation preference between hydrogen-bonded atoms is not enough to account for the structural specificity of proteins. The result has significant implications on the theor. and exptl. searches for specific interactions involved in protein folding and mol. recognition between proteins and other biol. active mols.
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150Zhou, H.; Skolnick, J. GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction Biophys. J. 2011, 101, 2043– 2052 DOI: 10.1016/j.bpj.2011.09.012150https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtlarsLrN&md5=01a3d1248a993dd67b576813be074460GOAP: A Generalized Orientation-Dependent, All-Atom Statistical Potential for Protein Structure PredictionZhou, Hongyi; Skolnick, JeffreyBiophysical Journal (2011), 101 (8), 2043-2052CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)An accurate scoring function is a key component for successful protein structure prediction. To address this important unsolved problem, the authors develop a generalized orientation and distance-dependent all-atom statistical potential. The new statistical potential, generalized orientation-dependent all-atom potential (GOAP), depends on the relative orientation of the planes assocd. with each heavy atom in interacting pairs. GOAP is a generalization of previous orientation-dependent potentials that consider only representative atoms or blocks of side-chain or polar atoms. GOAP is decompd. into distance- and angle-dependent contributions. The DFIRE distance-scaled finite ideal gas ref. state is employed for the distance-dependent component of GOAP. GOAP was tested on 11 commonly used decoy sets contg. 278 targets, and recognized 226 native structures as best from the decoys, whereas DFIRE recognized 127 targets. The major improvement comes from decoy sets that have homol.-modeled structures that are close to native (all within ∼4.0 Å) or from the ROSETTA ab initio decoy set. For these two kinds of decoys, orientation-independent DFIRE or only side-chain orientation-dependent RWplus performed poorly. Although the OPUS-PSP block-based orientation-dependent, side-chain atom contact potential performs much better (recognizing 196 targets) than DFIRE, RWplus, and dDFIRE, it is still ∼15% worse than GOAP. Thus, GOAP is a promising advance in knowledge-based, all-atom statistical potentials. GOAP is available for download at http://cssb.biol.gatech.edu/GOAP/index.html.
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151Park, J.; Saitou, K. ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures BMC Bioinf. 2014, 15, 307 DOI: 10.1186/1471-2105-15-307151https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXmsVeitw%253D%253D&md5=cd6522b7bc813721e763fbf079dc17f2ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structuresPark, Jungkap; Saitou, KazuhiroBMC Bioinformatics (2014), 15 (), 307/1-307/16, 16 pp.CODEN: BBMIC4; ISSN:1471-2105. (BioMed Central Ltd.)Background: Multibody potentials accounting for cooperative effects of mol. interactions have shown better accuracy than typical pairwise potentials. The main challenge in the development of such potentials is to find relevant structural features that characterize the tightly folded proteins. Also, the side-chains of residues adopt several specific, staggered conformations, known as rotamers within protein structures. Different mol. conformations result in different dipole moments and induce charge reorientations. However, until now modeling of the rotameric state of residues had not been incorporated into the development of multibody potentials for modeling non-bonded interactions in protein structures. Results: In this study, we develop a new multibody statistical potential which can account for the influence of rotameric states on the specificity of at. interactions. In this potential, named "rotamer-dependent at. statistical potential" (ROTAS), the interaction between two atoms is specified by not only the distance and relative orientation but also by two state parameters concerning the rotameric state of the residues to which the interacting atoms belong. It was clearly found that the rotameric state is correlated to the specificity of at. interactions. Such rotamer-dependencies are not limited to specific type or certain range of interactions. The performance of ROTAS was tested using 13 sets of decoys and was compared to those of existing at.-level statistical potentials which incorporate orientation-dependent energy terms. The results show that ROTAS performs better than other competing potentials not only in native structure recognition, but also in best model selection and correlation coeffs. between energy and model quality. Conclusions: A new multibody statistical potential, ROTAS accounting for the influence of rotameric states on the specificity of at. interactions was developed and tested on decoy sets. The results show that ROTAS has improved ability to recognize native structure from decoy models compared to other potentials. The effectiveness of ROTAS may provide insightful information for the development of many applications which require accurate side-chain modeling such as protein design, mutation anal., and docking simulation.
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152Gront, D.; Kolinski, A. A new approach to prediction of short-range conformational propensities in proteins Bioinformatics 2005, 21, 981– 987 DOI: 10.1093/bioinformatics/bti080There is no corresponding record for this reference.
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153Amir, E.-A.; Kalisman, N.; Keasar, C. Differentiable, multi-dimensional, knowledge-based energy terms for torsion angle probabilities and propensities Proteins: Struct., Funct., Genet. 2008, 72, 62– 73 DOI: 10.1002/prot.21896There is no corresponding record for this reference.
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154Levy-Moonshine, A.; Amir, E.-a.; Keasar, C. Enhancement of beta-sheet assembly by cooperative hydrogen bonds potential Bioinformatics 2009, 25, 2639– 2645 DOI: 10.1093/bioinformatics/btp449There is no corresponding record for this reference.
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155Liwo, A.; Arlukowicz, P.; Czaplewski, C.; Oldziej, S.; Pillardy, J.; Scheraga, H. A. A method for optimizing potential-energy functions by a hierarchical design of the potential-energy landscape: application to the UNRES force field Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 1937– 1942 DOI: 10.1073/pnas.032675399155https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XitVSrs7g%253D&md5=b15e4aabda4291e16ed7f32ae383b506A method for optimizing potential-energy functions by a hierarchical design of the potential-energy landscape: application to the UNRES force fieldLiwo, Adam; Arlukowicz, Piotr; Czaplewski, Cezary; Oldziej, Stanislaw; Pillardy, Jaroslaw; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2002), 99 (4), 1937-1942CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)A method for optimizing potential-energy functions of proteins is proposed. The method assumes a hierarchical structure of the energy landscape, which means that the energy decreases as the no. of native-like elements in a structure increases, being lowest for structures from the native family and highest for structures with no native-like element. A level of the hierarchy is defined as a family of structures with the same no. of native-like elements (or degree of native likeness). Optimization of a potential-energy function is aimed at achieving such a hierarchical structure of the energy landscape by forcing appropriate free-energy gaps between hierarchy levels to place their energies in ascending order. This procedure is different from methods developed thus far, in which the energy gap and/or the Z score between the native structure and all non-native structures are maximized, regardless of the degree of native likeness of the non-native structures. The advantage of this approach lies in reducing the no. of structures with decreasing energy, which should ensure the searchability of the potential. The method was tested on two proteins, PDB ID codes 1FSD and 1IGD, with an off-lattice united-residue force field. For 1FSD, the search of the conformational space with the use of the conformational space annealing method and the newly optimized potential-energy function found the native structure very quickly, as opposed to the potential-energy functions obtained by former optimization methods. After even incomplete optimization, the force field obtained by using 1IGD located the native-like structures of two peptides, 1FSD and betanova (a designed three-stranded β-sheet peptide), as the lowest-energy conformations, whereas for the 46-residue N-terminal fragment of staphylococcal protein A, the native-like conformation was the second-lowest-energy conformation and had an energy 2 kcal/mol above that of the lowest-energy structure.
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156Mirny, L. A.; Shakhnovich, E. I. How to Derive a Protein Folding Potential? A New Approach to an Old Problem J. Mol. Biol. 1996, 264, 1164– 1179 DOI: 10.1006/jmbi.1996.0704156https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXnt12h&md5=07dd006c009b51f8572b6ad4189d50bfHow to drive a protein folding potential? A New approach to an old problemMirny, Leonid A.; Shakhnovich, Eugene I.Journal of Molecular Biology (1996), 264 (5), 1164-1179CODEN: JMOBAK; ISSN:0022-2836. (Academic)In this paper we introduce a novel method of deriving a pairwise potential of protein folding. The potential is obtained by an optimization procedure that simultaneously maximizes thermodn. stability for all proteins in the database. When applied to the representative dataset of proteins and with the energy function taken in pairwise contact approxn., our potential scored somewhat better than existing ones. However, the discrimination of the native structure from decoys is still not strong enough to make the potential useful for ab initio folding. Our results suggest that the problem lies with pairwise amino acid contact approxn. and/or simplified presentation of proteins rather than with the derivation of potential. We argue that more detail of protein structure and energetics should be taken into account to achieve energy gaps. The suggested method is general enough to allow us to systematically derive parameters for more sophisticated energy functions. The internal control of validity for the potential derived by our method is convergence to a unique soln. upon addn. of new proteins to the database. The method is tested on simple model systems where sequences are designed, using the preset "true" potential, to have low energy in a dataset of structures. Our procedure is able to recover the potential with correlation r ≈ 91% with the true one and we were able to old all model structures using the recovered potential. Other statistical knowledge-based approaches were tested using this model and the results indicate that they also can recover the true potential with high degree of accuracy.
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157Maiorov, V. N.; Grippen, G. M. Contact Potential That Recognizes the Correct Folding of Globular-Proteins J. Mol. Biol. 1992, 227, 876– 888 DOI: 10.1016/0022-2836(92)90228-CThere is no corresponding record for this reference.
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158Chiu, T.-L.; Goldstein, R. A. Optimizing energy potentials for success in protein tertiary structure prediction Folding Des. 1998, 3, 223– 228 DOI: 10.1016/S1359-0278(98)00030-3158https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXktVShsbw%253D&md5=deaeba089948a4fd8bc09ad7f042051dOptimizing energy potentials for success in protein tertiary structure predictionChiu, Ting-Lan; Goldstein, Richard A.Folding & Design (1998), 3 (3), 223-228CODEN: FODEFH; ISSN:1359-0278. (Current Biology Ltd.)Success in solving the protein structure prediction problem relies on the choice of an accurate potential energy function. For a single protein sequence, it has been shown that the potential energy function can be optimized for predictive success by maximizing the energy gap between the correct structure and the ensemble of random structures relative to the distribution of the energies of these random structures (the Z-score). Different methods have been described for implementing this procedure for an ensemble of database proteins. Here, we demonstrate a new approach. For a single protein sequence, the probability of success (i.e. the probability that the folded state is the lowest energy state) is derived. We then maximize the av. probability of success for a set of proteins to obtain the optimal potential energy function. This results in max. attention being focused on the proteins whose structures are difficult but not impossible to predict. Using a lattice model of proteins, we show that the optimal interaction potentials obtained by our method are both more accurate and more likely to produce successful predictions than those obtained by other averaging procedures.
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159Hao, M.-H.; Scheraga, H. A. Optimizing Potential Functions for Protein Folding J. Phys. Chem. 1996, 100, 14540– 14548 DOI: 10.1021/jp960856jThere is no corresponding record for this reference.
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160Sippl, M. J. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins J. Mol. Biol. 1990, 213, 859– 883 DOI: 10.1016/S0022-2836(05)80269-4160https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3cXkvFCgs7Y%253D&md5=e675356b4ab5e0114cd027ea92c00d90Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteinsSippl, Manfred J.Journal of Molecular Biology (1990), 213 (4), 859-83CODEN: JMOBAK; ISSN:0022-2836.A prototype of a new approach to the folding problem of polypeptide chains is presented. This approach is based on the anal. of known protein structures. It derives the energy potentials for the at. interactions of all amino acid residue pairs as a function of the distance between the involved atoms. These potentials are then used to calc. the energies of all conformations that exist in the data base with respect to a given sequence. Then, by using only the most stable conformations, clusters of the most probable conformations for the given sequence are obtained. The use of the method is demonstrated in the discussion of the identical oligopeptide sequences found in different conformations is unrelated proteins. VNTFV, for example, adopts a β-strand in RNase but it is found in an α-helical conformation in erythrocruorin. In the case of VNTFV the ensemble obtained consists of a single cluster of β-strand conformations, indicating that this may be the preferred conformation for the pentapeptide. When the flanking residues are included in the calcn. the hepapeptide P-VNTFV-H (RNase) again yields an ensemble of β-strands. However, in the ensemble of D-VNTFV-A (erythrocruorin) the major cluster is of α-helical type. The present study concs. on the local aspects of protein conformations. However, the theory presented is quite general and not restricted to oligopeptides. Extensions of the approach to the calcn. of global conformations of proteins as well as conceivable applications to a no. of mol. systems are discussed.
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161Hamelryck, T.; Borg, M.; Paluszewski, M.; Paulsen, J.; Frellsen, J.; Andreetta, C.; Boomsma, W.; Bottaro, S.; Ferkinghoff-Borg, J. Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized PLoS One 2010, 5, e13714 DOI: 10.1371/journal.pone.0013714There is no corresponding record for this reference.
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162Gniewek, P.; Leelananda, S. P.; Kolinski, A.; Jernigan, R. L.; Kloczkowski, A. Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models Proteins: Struct., Funct., Genet. 2011, 79, 1923– 1929 DOI: 10.1002/prot.23015There is no corresponding record for this reference.
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163Elhefnawy, W.; Chen, L.; Han, Y.; Li, Y. ICOSA: A Distance-Dependent, Orientation-Specific Coarse-Grained Contact Potential for Protein Structure Modeling J. Mol. Biol. 2015, 427, 2562– 2576 DOI: 10.1016/j.jmb.2015.05.022163https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtVWgu7bI&md5=dfedad9b22d1ad603e31ccc4389cbb2cICOSA: A Distance-Dependent, Orientation-Specific Coarse-Grained Contact Potential for Protein Structure ModelingElhefnawy, Wessam; Chen, Lin; Han, Yun; Li, YaohangJournal of Molecular Biology (2015), 427 (15), 2562-2576CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The relative distance and orientation in contacting residue pairs plays a significant role in protein folding and stabilization. We hereby devise a new knowledge-based, coarse-grained contact potential, so-called ICOSA, by correlating inter-residue contact distance and orientation in evaluating pair-wise inter-residue interactions. The rationale of our approach is to establish icosahedral local coordinates to est. the statistical residue contact distributions in all spherical triangular shells within a sphere. We extend the theory of finite ideal gas ref. state to icosahedral local coordinates. ICOSA incorporates long-range contact interactions, which is crit. to ICOSA sensitivity and is justified in statistical rigor. With only backbone atoms information, ICOSA is at least comparable to all-atom, fine-grained potentials such as Rosetta, DFIRE, I-TASSER, and OPUS in discriminating near-natives from misfold protein conformations in the Rosetta and I-TASSER protein decoy sets. ICOSA also outperforms a set of widely used coarse-grained potentials and is comparable to all-atom, fine-grained potentials in identifying CASP10 models.
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164Sankar, K.; Liu, J.; Wang, Y.; Jernigan, R. L. Distributions of experimental protein structures on coarse-grained free energy landscapes J. Chem. Phys. 2015, 143, 243153 DOI: 10.1063/1.4937940164https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVyns7nK&md5=90126ec718f1c24f3d6ce08968a54d58Distributions of experimental protein structures on coarse-grained free energy landscapesSankar, Kannan; Liu, Jie; Wang, Yuan; Jernigan, Robert L.Journal of Chemical Physics (2015), 143 (24), 243153/1-243153/12CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Predicting conformational changes of proteins is needed to fully comprehend functional mechanisms. With the large no. of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component anal. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. The authors use principal component anal. of exptl. structures of 50 diverse proteins to ext. the most important directions of their motions, sample structures along these directions, and est. their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ ATPase (SERCA), as examples, such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, also Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. (c) 2015 American Institute of Physics.
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165Zaborowski, B.; Jagieła, D.; Czaplewski, C.; Hałabis, A.; Lewandowska, A.; Żmudzińska, W.; Ołdziej, S.; Karczyńska, A.; Omieczynski, C.; Wirecki, T. A Maximum-Likelihood Approach to Force-Field Calibration J. Chem. Inf. Model. 2015, 55, 2050– 2070 DOI: 10.1021/acs.jcim.5b00395165https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlWiu73J&md5=13f2e4c5fa16d448e9019771678c2bb5A Maximum-Likelihood Approach to Force-Field CalibrationZaborowski, Bartlomiej; Jagiela, Dawid; Czaplewski, Cezary; Halabis, Anna; Lewandowska, Agnieszka; Zmudzinska, Wioletta; Oldziej, Stanislaw; Karczynska, Agnieszka; Omieczynski, Christian; Wirecki, Tomasz; Liwo, AdamJournal of Chemical Information and Modeling (2015), 55 (9), 2050-2070CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A new approach to the calibration of the force fields is proposed, in which the force-field parameters were obtained by max.-likelihood fitting of the calcd. conformational ensembles to the exptl. ensembles of training system(s). The max.-likelihood function is composed of logarithms of the Boltzmann probabilities of the exptl. conformations, calcd. with the current energy function. Because the theor. distribution is given as the simulated conformations only, the contributions from all of the simulated conformations, with Gaussian wts. in the distances from a given exptl. conformation, were added to give the contribution to the target function from this conformation. In contrast to earlier methods for force-field calibration, the approach does not suffer from the arbitrariness of dividing the decoy set into native-like and non-native structures; however, if such a division is made instead of using Gaussian wts., application of the max.-likelihood method results in the known energy-gap maximization. The computational procedure consists of cycles of decoy generation and max.-likelihood-function optimization, which are iterated until convergence is reached. The method was tested with Gaussian distributions and then applied to the physics-based coarse-grained UNRES force field for proteins. The NMR structures of the tryptophan cage, a small α-helical protein, detd. at three temps. (T = 280, 305, and 313 K) by Halabis et al., were used. Multiplexed replica-exchange mol. dynamics was used to generate the decoys. The iterative procedure exhibited steady convergence. Three variants of optimization were tried: optimization of the energy-term wts. alone and use of the exptl. ensemble of the folded protein only at T = 280 K (run 1); optimization of the energy-term wts. and use of exptl. ensembles at all three temps. (run 2); and optimization of the energy-term wts. and the coeffs. of the torsional and multibody energy terms and use of exptl. ensembles at all three temps. (run 3). The force fields were subsequently tested with a set of 14 α-helical and two α + β proteins. Optimization run 1 resulted in better agreement with the exptl. ensemble at T = 280 K compared with optimization run 2 and in comparable performance on the test set but poorer agreement of the calcd. folding temp. with the exptl. folding temp. Optimization run 3 resulted in the best fit of the calcd. ensembles to the exptl. ones for the tryptophan cage but in much poorer performance on the training set, suggesting that use of a small α-helical protein for extensive force-field calibration resulted in overfitting of the data for this protein at the expense of transferability. The optimized force field resulting from run 2 was found to fold 13 of the 14 tested α-helical proteins and one small α + β protein with the correct topologies; the av. structures of 10 of them were predicted with accuracies of ∼5 Å Cα root-mean-square deviation or better. Test simulations with an addnl. set of 12 α-helical proteins demonstrated that this force field performed better on α-helical proteins than the previous parametrizations of UNRES. The proposed approach is applicable to any problem of max.-likelihood parameter estn. when the contributions to the max.-likelihood function cannot be evaluated at the exptl. points and the dimension of the configurational space is too high to construct histograms of the exptl. distributions.
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166Rykunov, D.; Fiser, A. New statistical potential for quality assessment of protein models and a survey of energy functions BMC Bioinf. 2010, 11, 128 DOI: 10.1186/1471-2105-11-128166https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3c3lsVCjug%253D%253D&md5=a1288fb0ef40c65460b01e315d22c132New statistical potential for quality assessment of protein models and a survey of energy functionsRykunov Dmitry; Fiser AndrasBMC bioinformatics (2010), 11 (), 128 ISSN:.BACKGROUND: Scoring functions, such as molecular mechanic forcefields and statistical potentials are fundamentally important tools in protein structure modeling and quality assessment. RESULTS: The performances of a number of publicly available scoring functions are compared with a statistical rigor, with an emphasis on knowledge-based potentials. We explored the effect on accuracy of alternative choices for representing interaction center types and other features of scoring functions, such as using information on solvent accessibility, on torsion angles, accounting for secondary structure preferences and side chain orientation. Partially based on the observations made, we present a novel residue based statistical potential, which employs a shuffled reference state definition and takes into account the mutual orientation of residue side chains. Atom- and residue-level statistical potentials and Linux executables to calculate the energy of a given protein proposed in this work can be downloaded from http://www.fiserlab.org/potentials. CONCLUSIONS: Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality.
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167Fornes, O.; Garcia-Garcia, J.; Bonet, J.; Oliva, B. On the use of knowledge-based potentials for the evaluation of models of protein-protein, protein-DNA, and protein-RNA interactions Adv. Protein Chem. Struct. Biol. 2014, 94, 77– 120 DOI: 10.1016/B978-0-12-800168-4.00004-4167https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2crjs1ehsA%253D%253D&md5=24ac1ef22f2e5f88f0020f4c62ba3c28On the use of knowledge-based potentials for the evaluation of models of protein-protein, protein-DNA, and protein-RNA interactionsFornes Oriol; Garcia-Garcia Javier; Bonet Jaume; Oliva BaldoAdvances in protein chemistry and structural biology (2014), 94 (), 77-120 ISSN:.Proteins are the bricks and mortar of cells, playing structural and functional roles. In order to perform their function, they interact with each other as well as with other biomolecules such as DNA or RNA. Therefore, to fathom the function of a protein, we require knowing its partners and the atomic details of its interactions (i.e., the structure of the complex). However, the amount of protein interactions with an experimentally determined three-dimensional structure is scarce. Therefore, computational techniques such as homology modeling are foremost to fill this gap. Protein interactions can be modeled using as templates the interactions of homologous proteins, if the structure of the complex is known, or using docking methods. In both approaches, the estimation of the quality of models is essential. There are several ways to address this problem. In this review, we focus on the use of knowledge-based potentials for the analysis of protein interactions. We describe the procedure to derive statistical potentials and split them into different energetic terms that can be used for different purposes. We extensively discuss the fields where knowledge-based potentials have been successfully applied to (1) model protein-protein, protein-DNA, and protein-RNA interactions and (2) predict binding sites (in the protein and in the DNA). Moreover, we provide ready-to-use resources for docking and benchmarking protein interactions.
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168Lu, M.; Dousis, A. D.; Ma, J. OPUS-PSP: an orientation-dependent statistical all-atom potential derived from side-chain packing J. Mol. Biol. 2008, 376, 288– 301 DOI: 10.1016/j.jmb.2007.11.033168https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXpt1ymug%253D%253D&md5=739d2650194c03c57c2a93a18de75e4eOPUS-PSP: An Orientation-dependent Statistical All-atom Potential Derived from Side-chain PackingLu, Mingyang; Dousis, Athanasios D.; Ma, JianpengJournal of Molecular Biology (2008), 376 (1), 288-301CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Here we report an orientation-dependent statistical all-atom potential derived from side-chain packing, named OPUS-PSP. It features a basis set of 19 rigid-body blocks extd. from the chem. structures of all 20 amino acid residues. The potential is generated from the orientation-specific packing statistics of pairs of those blocks in a non-redundant structural database. The purpose of such an approach is to capture the essential elements of orientation dependence in mol. packing interactions. Tests of OPUS-PSP on commonly used decoy sets demonstrate that it significantly outperforms most of the existing knowledge-based potentials in terms of both its ability to recognize native structures and consistency in achieving high Z-scores across decoy sets. As OPUS-PSP excludes interactions among main-chain atoms, its success highlights the crucial importance of side-chain packing in forming native protein structures. Moreover, OPUS-PSP does not explicitly include solvation terms, and thus the potential should perform well when the solvation effect is difficult to det., such as in membrane proteins. Overall, OPUS-PSP is a generally applicable potential for protein structure modeling, esp. for handling side-chain conformations, one of the most difficult steps in high-accuracy protein structure prediction and refinement.
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169Buchete, N. V.; Straub, J. E.; Thirumalai, D. Anisotropic coarse-grained statistical potentials improve the ability to identify nativelike protein structures J. Chem. Phys. 2003, 118, 7658– 7671 DOI: 10.1063/1.1561616There is no corresponding record for this reference.
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170Zhang, Y.; Kolinski, A.; Skolnick, J. TOUCHSTONE II: a new approach to ab initio protein structure prediction Biophys. J. 2003, 85, 1145– 1164 DOI: 10.1016/S0006-3495(03)74551-2170https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXmtVyksLo%253D&md5=fc9f9be1925dfac8010d81ff268792edTOUCHSTONE II: A new approach to Ab initio protein structure predictionZhang, Yang; Kolinski, Andrzej; Skolnick, JeffreyBiophysical Journal (2003), 85 (2), 1145-1164CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting Cα atoms, with attached Cβ atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical anal. of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30×60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36∼120 residues) with predicted structures having a RMSD from native below 6.5 Å in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36∼174 residues) with structures having a RMSD to native below 6.5 Å in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, esp. when the accuracy of side-chain contact prediction is >20%. For native fold selection, we introduce quantities dependent on the cluster d. and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.
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171Kolinski, A.; Bujnicki, J. M. Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models Proteins: Struct., Funct., Genet. 2005, 61, 84– 90 DOI: 10.1002/prot.20723There is no corresponding record for this reference.
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172Xu, D.; Zhang, J.; Roy, A.; Zhang, Y. Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement Proteins: Struct., Funct., Genet. 2011, 79, 147– 160 DOI: 10.1002/prot.23111There is no corresponding record for this reference.
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173Roy, A.; Kucukural, A.; Zhang, Y. I-TASSER: a unified platform for automated protein structure and function prediction Nat. Protoc. 2010, 5, 725– 738 DOI: 10.1038/nprot.2010.5173https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXksVahs74%253D&md5=1ee011981433cbe8a3a6dae8cb6f68f7I-TASSER: a unified platform for automated protein structure and function predictionRoy, Ambrish; Kucukural, Alper; Zhang, YangNature Protocols (2010), 5 (4), 725-738CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) at. models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission nos. and Gene Ontol. terms. An est. of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.
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174Taketomi, H.; Ueda, Y.; Go, N. Studies on protein folding, unfolding and fluctuations by computer simulation. I. The effect of specific amino acid sequence represented by specific inter-unit interactions Int. J. Pept. Protein Res. 1975, 7, 445– 459 DOI: 10.1111/j.1399-3011.1975.tb02465.x174https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE28Xht1agsbg%253D&md5=fc31efb875d283eec9d07308a9ea5611Studies on protein folding, unfolding, and fluctuations by computer simulation. I. Effect of specific amino acid sequence represented by specific interunit interactionsTaketomi, Hiroshi; Ueda, Yuzo; Go, NobuhiroInternational Journal of Peptide & Protein Research (1975), 7 (6), 445-59CODEN: IJPPC3; ISSN:0367-8377.A lattice model of proteins with specific inter-unit interactions provided an effective method for studying the statistical mech. properties of conformations of globular proteins. The inter-unit interactions of strong limit, intermediate, and weak limit, resp., were studied. In the cases of the strong limit and intermediate specificities, denaturations were of the all or none type, whereas in the case of the weak limit specificity, denaturation was of the graded type.
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175Go, N.; Taketomi, H. Studies on protein folding, unfolding and fluctuations by computer simulation. IV. Hydrophobic interactions Int. J. Pept. Protein Res. 1979, 13, 447– 461 DOI: 10.1111/j.1399-3011.1979.tb01907.x175https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE1MXkvVGlu7Y%253D&md5=3fda0c140b409fb07ae35b3fa03430c8Studies on protein folding, unfolding and fluctuations by computer simulation. IV. Hydrophobic interactionsGo, Nobuhiro; Taketomi, HiroshiInternational Journal of Peptide & Protein Research (1979), 13 (5), 447-61CODEN: IJPPC3; ISSN:0367-8377.The theor. model of proteins on a 2-dimensional square lattice was extended to include hydrophobic interactions. Two proteins, with native conformations in different folded patterns, were studied. Units in the protein chains were classified into polar and nonpolar units. A vacant lattice point next to a nonpolar unit was interpreted as being occupied by solvent water and the entropy of the system was assumed to decrease by a certain amt. Besides these hydrophobic free energies, specific long-range interactions previously studied were assumed to be operative. Equil. properties of the folding and unfolding transitions of the 2 proteins were similar, even though 1 of them was predicted to unfold through a significant intermediate state when the hydrophobic interactions were strongly weighted. The failure of this prediction led to the development of a more refined model of transitions, a noninteracting local structure model. The assumed hydrophobic interactions have a character of nonspecific long-range interactions which decelerate the folding kinetics. The deceleration effect is less pronounced in the protein whose native conformation is stabilized by many pairs of medium-range interactions. Thus, medium-range interactions can cope with the decelerating effect of the nonspecific hydrophobic interactions.
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176Hills, R. D.; Brooks, C. L. Insights from Coarse-Grained Go Models for Protein Folding and Dynamics Int. J. Mol. Sci. 2009, 10, 889– 905 DOI: 10.3390/ijms10030889176https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXjtV2qt70%253D&md5=e622abb05cc31b984233b5d7a7a627e9Insights from coarse-grained Go models for protein folding and dynamicsHills, Ronald D., Jr.; Brooks, Charles L., IIIInternational Journal of Molecular Sciences (2009), 10 (3), 889-905CODEN: IJMCFK; ISSN:1422-0067. (Molecular Diversity Preservation International)A review. Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topol.-based Go models, which constitute a smooth and funnel-like approxn. to the folding landscape. We review the many variations of the Go model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topol. in folding. The role of local contact d. in detg. protein dynamics is also discussed and is used to explain the ability of Go-like models to capture sequence effects in folding and elucidate conformational transitions.
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177Bryngelson, J. D.; Onuchic, J. N.; Socci, N. D.; Wolynes, P. G. Funnels, pathways, and the energy landscape of protein folding: a synthesis Proteins: Struct., Funct., Genet. 1995, 21, 167– 195 DOI: 10.1002/prot.340210302177https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXks12qtrk%253D&md5=6ac46330d0690939667bac09f7cdd829Funnels, pathways, and the energy landscape of protein folding: a synthesisBryngelson, Joseph D.; Onuchic, Jose Nelson; Socci, Nicholas D.; Wolynes, Peter G.Proteins: Structure, Function, and Genetics (1995), 21 (3), 167-95CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss)A review, with 132 refs. The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking, a statistical approach to the energetics of protein conformation, i.e., the energy landscape. The statistical energy landscape approach explains when and why unique behaviors, such as specific folding pathways, occur in some proteins and more generally explains the distinction between folding processes common to all sequences and those peculiar to individual sequences. This approach also gives new, quant. insights into the interpretation of expts. and simulations of protein folding thermodn. and kinetics. Specifically, the picture provides simple explanations for folding as a two-state first-order phase transition, for the origin of metastable collapsed unfolded states and for the curved Arrhenius plots obsd. in both lab. expts. and discrete lattice simulations. The relation of these quant. ideas to folding pathways, to uniexponential vs. multiexponential behavior in protein folding expts. and to the effect of mutations on folding is also discussed. The success of energy landscape approach for analyzing data is illustrated with a quant. anal. of some recent simulations, and a qual. anal. of expts. on the folding of three proteins. The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodn. conditions.
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178Hills, R. D., Jr.; Brooks, C. L., 3rd Insights from coarse-grained Go models for protein folding and dynamics Int. J. Mol. Sci. 2009, 10, 889– 905 DOI: 10.3390/ijms10030889178https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXjtV2qt70%253D&md5=e622abb05cc31b984233b5d7a7a627e9Insights from coarse-grained Go models for protein folding and dynamicsHills, Ronald D., Jr.; Brooks, Charles L., IIIInternational Journal of Molecular Sciences (2009), 10 (3), 889-905CODEN: IJMCFK; ISSN:1422-0067. (Molecular Diversity Preservation International)A review. Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topol.-based Go models, which constitute a smooth and funnel-like approxn. to the folding landscape. We review the many variations of the Go model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topol. in folding. The role of local contact d. in detg. protein dynamics is also discussed and is used to explain the ability of Go-like models to capture sequence effects in folding and elucidate conformational transitions.
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179Lammert, H.; Schug, A.; Onuchic, J. N. Robustness and generalization of structure-based models for protein folding and function Proteins: Struct., Funct., Genet. 2009, 77, 881– 891 DOI: 10.1002/prot.22511179https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlSru7nF&md5=4f5d8b3f1a51933c5529ff5527b97962Robustness and generalization of structure-based models for protein folding and functionLammert, Heiko; Schug, Alexander; Onuchic, Jose N.Proteins: Structure, Function, and Bioinformatics (2009), 77 (4), 881-891CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Functional dynamics of native proteins share the energy landscape that guides folding into the native state. Folding simulations of structure-based protein models, using an minimally frustrated energy landscape dominated by native interactions, can describe the geometrical aspects of the folding mechanism. Tech. limitations imposed by the fixed shape of conventional contact potentials are a key obstacle toward advanced applications of structure-based models like allostery or ligand binding, which require multiple stable conformations. Generalizations of existing models, commonly using Lennard-Jones-like potentials, lead to inevitable clashes between their repulsive branches. To resolve these challenges, a new contact potential is developed that combines an attractive part based on Gaussians with a sep. repulsive term allowing flexibility for adjustments of the potential shape. With this new model multiple min. for studies of functional transitions can be introduced easily and consistently. A sensitivity anal. for five small proteins confirms the robust behavior of structure-based models with our adaptable potential and explores their capacity for quant. adjustment of the folding thermodn. We demonstrate its ability to incorporate alternative contact distances in simulations of structural transitions for the well-studied ROP dimer. Individual contact pairs can switch between distinct states to match the competing syn and anti structures. The flexibility of the new potential facilitates advanced uses of structure-based models. Depending on the application, features can be chosen from phys. considerations or to match expts. Generalized models can be built from multiple structures to study structural transitions or effects of disorder. Proteins 2009. © 2009 Wiley-Liss, Inc.
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180Hills, R. D., Jr. Balancing bond, nonbond, and go-like terms in coarse grain simulations of conformational dynamics Methods Mol. Biol. 2014, 1084, 123– 140 DOI: 10.1007/978-1-62703-658-0_7180https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnt1Crt7k%253D&md5=33c2aef7fa11efee13c071944336d390Balancing Bond, Nonbond, and G‾o-Like Terms in Coarse Grain Simulations of Conformational DynamicsHills, Ronald D., Jr.Methods in Molecular Biology (New York, NY, United States) (2014), 1084 (Protein Dynamics), 123-140CODEN: MMBIED; ISSN:1940-6029. (Springer)Characterization of the protein conformational landscape remains a challenging problem, whether it concerns elucidating folding mechanisms, predicting native structures or modeling functional transitions. Coarse-grained mol. dynamics simulation methods enable exhaustive sampling of the energetic landscape at resolns. of biol. interest. The general utility of structure-based models is reviewed along with their differing levels of approxn. Simple G‾o models incorporate attractive native interactions and repulsive nonnative contacts, resulting in an ideal smooth landscape. Non-G‾o coarse-grained models reduce the parameter set as needed but do not include bias to any desired native structure. While non-G‾o models have achieved limited success in protein coarse-graining, they can be combined with native structured-based potentials to create a balanced and powerful force field. Recent applications of such G‾o-like models have yielded insight into complex folding mechanisms and conformational transitions in large macromols. The accuracy and usefulness of reduced representations are also revealed to be a function of the math. treatment of the intrinsic bonded topol.
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181Christen, M.; van Gunsteren, W. On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: A review J. Comput. Chem. 2008, 29, 157– 166 DOI: 10.1002/jcc.20725181https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2sjktVOitQ%253D%253D&md5=c508200635d58b25f5ee678a9c016f87On searching in, sampling of, and dynamically moving through conformational space of biomolecular systems: A reviewChristen Markus; van Gunsteren Wilfred FJournal of computational chemistry (2008), 29 (2), 157-66 ISSN:0192-8651.Methods to search for low-energy conformations, to generate a Boltzmann-weighted ensemble of configurations, or to generate classical-dynamical trajectories for molecular systems in the condensed liquid phase are briefly reviewed with an eye to application to biomolecular systems. After having chosen the degrees of freedom and method to generate molecular configurations, the efficiency of the search or sampling can be enhanced in various ways: (i) efficient calculation of the energy function and forces, (ii) application of a plethora of search enhancement techniques, (iii) use of a biasing potential energy term, and (iv) guiding the sampling using a reaction or transition pathway. The overview of the available methods should help the reader to choose the combination that is most suitable for the biomolecular system, degrees of freedom, interaction function, and molecular or thermodynamic properties of interest.
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182Liwo, A.; Czaplewski, C.; Oldziej, S.; Scheraga, H. A. Computational techniques for efficient conformational sampling of proteins Curr. Opin. Struct. Biol. 2008, 18, 134– 139 DOI: 10.1016/j.sbi.2007.12.001182https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXkvFCmu7g%253D&md5=437b8d53b7fc1748852d75f842a10d20Computational techniques for efficient conformational sampling of proteinsLiwo, Adam; Czaplewski, Cezary; Oldziej, Stanislaw; Scheraga, Harold A.Current Opinion in Structural Biology (2008), 18 (2), 134-139CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. In this review, we summarize the computational methods for sampling the conformational space of biomacromols. We discuss the methods applicable to find only lowest energy conformations (global minimization of the potential-energy function) and to generate canonical ensembles (canonical Monte Carlo method and canonical mol. dynamics method and their extensions). Special attention is devoted to the use of coarse-grained models that enable simulations to be enhanced by several orders of magnitude.
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183Spiwok, V.; Sucur, Z.; Hosek, P. Enhanced sampling techniques in biomolecular simulations Biotechnol. Adv. 2015, 33, 1130– 1140 DOI: 10.1016/j.biotechadv.2014.11.011183https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVymu77J&md5=24cf1b57adcc4df3ed64bae3541266f2Enhanced sampling techniques in biomolecular simulationsSpiwok, Vojtech; Sucur, Zoran; Hosek, PetrBiotechnology Advances (2015), 33 (6_Part_2), 1130-1140CODEN: BIADDD; ISSN:0734-9750. (Elsevier)A review. Biomol. simulations are routinely used in biochem. and mol. biol. research; however, they often fail to match expectations of their impact on pharmaceutical and biotech industry. This is caused by the fact that a vast amt. of computer time is required to simulate short episodes from the life of biomols. Several approaches have been developed to overcome this obstacle, including application of massively parallel and special purpose computers or non-conventional hardware. Methodol. approaches are represented by coarse-grained models and enhanced sampling techniques. These techniques can show how the studied system behaves in long time-scales on the basis of relatively short simulations. This review presents an overview of new simulation approaches, the theory behind enhanced sampling methods and success stories of their applications with a direct impact on biotechnol. or drug design.
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184Bernardi, R. C.; Melo, M. C.; Schulten, K. Enhanced sampling techniques in molecular dynamics simulations of biological systems Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 872– 877 DOI: 10.1016/j.bbagen.2014.10.019184https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvVanurbN&md5=44e3ac1aa042c35ee08aa86a6a63e78eEnhanced sampling techniques in molecular dynamics simulations of biological systemsBernardi, Rafael C.; Melo, Marcelo C. R.; Schulten, KlausBiochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 872-877CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Mol. dynamics has emerged as an important research methodol. covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local min. sepd. by high-energy barriers, which govern the biomol. motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange mol. dynamics, metadynamics and simulated annealing. Here the authors present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biol. systems and the choice of a suitable method is connected to biol. and phys. characteristics of the system, in particular system size. While metadynamics and replica-exchange mol. dynamics are the most adopted sampling methods to study biomol. dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromol. complexes. Mol. dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biol. function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of mol. dynamics.
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185Hatfield, M. P.; Lovas, S. Conformational sampling techniques Curr. Pharm. Des. 2014, 20, 3303– 3313 DOI: 10.2174/13816128113199990603185https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpvVaks7g%253D&md5=3967e410c4bb073c425af1bbd26b0cbcConformational Sampling TechniquesHatfield, Marcus P. D.; Lovas, SandorCurrent Pharmaceutical Design (2014), 20 (20), 3303-3313CODEN: CPDEFP; ISSN:1381-6128. (Bentham Science Publishers Ltd.)A review. The potential energy hyper-surface of a protein relates the potential energy of the protein to its conformational space. This surface is useful in detg. the native conformation of a protein or in examg. a statistical-mech. ensemble of structures (canonical ensemble). In detg. the potential energy hyper-surface of a protein three aspects must be considered; reducing the degrees of freedom, a method to det. the energy of each conformation and a method to sample the conformational space. For reducing the degrees of freedom the choice of solvent, coarse graining, constraining degrees of freedom and periodic boundary conditions are discussed. The use of quantum mechanics vs. mol. mechanics and the choice of force fields are also discussed, as well as the sampling of the conformational space through deterministic and heuristic approaches. Deterministic methods include knowledge-based statistical methods, rotamer libraries, homol. modeling, the build-up method, self-consistent electrostatic field, deformation methods, tree-based elimination and eigenvector following routines. The heuristic methods include Monte Carlo chain growing, energy minimizations, metropolis monte carlo and mol. dynamics. In addn., various methods to enhance the conformational search including the deformation or smoothing of the surface, scaling of system parameters, and multi copy searching are also discussed.
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186Lee, J.; Scheraga, H. A.; Rackovsky, S. New optimization method for conformational energy calculations on polypeptides: Conformational space annealing J. Comput. Chem. 1997, 18, 1222– 1232 DOI: 10.1002/(SICI)1096-987X(19970715)18:9<1222::AID-JCC10>3.0.CO;2-7186https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXksVKmsLc%253D&md5=a340980c43561a4acc79ebbef01fee0aNew optimization method for conformational energy calculations on polypeptides: conformational space annealingLee, Jooyoung; Scheraga, Harold A.; Rackovsky, S.Journal of Computational Chemistry (1997), 18 (9), 1222-1232CODEN: JCCHDD; ISSN:0192-8651. (Wiley)A new optimization method is presented to search for the global min.-energy conformations of peptides. The method combines essential aspects of the build-up procedure and the genetic algorithm, and it introduces the important concept of "conformational space annealing.". Instead of considering a single conformation, attention is focused on a population of conformations while new conformations are obtained by modifying a "seed conformation.". The annealing is carried out by introducing a distance cutoff, Dcut, which is defined in the conformational space; Dcut effectively divides the whole conformational space of local min. into subdivisions. The value of Dcut is set to a large no. at the beginning of the algorithm to cover the whole conformational space, and annealing is achieved by slowly reducing it. Many distinct local min. designed to be distributed as far apart as possible in conformational space are investigated simultaneously. Therefore, the new method finds not only the global min.-energy conformation but also many other distinct local min. as byproducts. The method is tested on Met-enkephalin, a 24-dihedral angle problem. For all 100 independent runs, the accepted global min.-energy conformation was obtained after about 2600 minimizations on av.
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187Stein, A.; Kortemme, T. Improvements to robotics-inspired conformational sampling in rosetta PLoS One 2013, 8, e63090 DOI: 10.1371/journal.pone.0063090187https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXovVKgtro%253D&md5=9a319795b1e4add6bd12f5770e7ecb5eImprovements to robotics-inspired conformational sampling in RosettaStein, Amelie; Kortemme, TanjaPLoS One (2013), 8 (5), e63090CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)To accurately predict protein conformations in at. detail, a computational method must be capable of sampling models sufficiently close to the native structure. All-atom sampling is difficult because of the vast no. of possible conformations and extremely rugged energy landscapes. Here, we test three sampling strategies to address these difficulties: conformational diversification, intensification of torsion and omega-angle sampling and parameter annealing. We evaluate these strategies in the context of the robotics-based kinematic closure (KIC) method for local conformational sampling in Rosetta on an established benchmark set of 45 12-residue protein segments without regular secondary structure. We quantify performance as the fraction of sub-Angstrom models generated. While improvements with individual strategies are only modest, the combination of intensification and annealing strategies into a new "next-generation KIC" method yields a four-fold increase over std. KIC in the median percentage of sub-Angstrom models across the dataset. Such improvements enable progress on more difficult problems, as demonstrated on longer segments, several of which could not be accurately remodeled with previous methods. Given its improved sampling capability, next-generation KIC should allow advances in other applications such as local conformational remodeling of multiple segments simultaneously, flexible backbone sequence design, and development of more accurate energy functions.
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188Shmygelska, A.; Hoos, H. H. An ant colony optimization algorithm for the 2D and 3D hydrophobic polar protein folding problem BMC Bioinf. 2005, 6, 30 DOI: 10.1186/1471-2105-6-30188https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2M7ltFeitg%253D%253D&md5=c449e9eded1bbefad7d454fbcc8a9905An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problemShmygelska Alena; Hoos Holger HBMC bioinformatics (2005), 6 (), 30 ISSN:.BACKGROUND: The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model - the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model. RESULTS: We present an improvement of our previous ACO algorithm for the 2D HP model and its extension to the 3D HP model. We show that this new algorithm, dubbed ACO-HPPFP-3, performs better than previous state-of-the-art algorithms on sequences whose native conformations do not contain structural nuclei (parts of the native fold that predominantly consist of local interactions) at the ends, but rather in the middle of the sequence, and that it generally finds a more diverse set of native conformations. CONCLUSIONS: The application of ACO to this bioinformatics problem compares favourably with specialised, state-of-the-art methods for the 2D and 3D HP protein folding problem; our empirical results indicate that our rather simple ACO algorithm scales worse with sequence length but usually finds a more diverse ensemble of native states. Therefore the development of ACO algorithms for more complex and realistic models of protein structure holds significant promise.
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189Peter, E. K.; Lykov, K.; Pivkin, I. V. A polarizable coarse-grained protein model for dissipative particle dynamics Phys. Chem. Chem. Phys. 2015, 17, 24452– 24461 DOI: 10.1039/C5CP03479E189https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVahtLfJ&md5=d81eed1ffa5a3dac7369229f0bc5790eA polarizable coarse-grained protein model for dissipative particle dynamicsPeter, Emanuel K.; Lykov, Kirill; Pivkin, Igor V.Physical Chemistry Chemical Physics (2015), 17 (37), 24452-24461CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)The authors present a new coarse-grained polarizable protein model for dissipative particle dynamics (DPD) method. This method allows large timesteps in particle-based systems and speeds up sampling by many orders of magnitude. The authors' new model is based on the electrostatic polarization of the protein backbone and a detailed representation of the sidechains in combination with a polarizable water model. The authors define the authors' model parameters using the exptl. structures of two proteins, TrpZip2 and TrpCage. Backmapping and subsequent short replica-exchange mol. dynamics runs verify the authors' approach and show convergence to the exptl. structures on the atomistic level. The authors validate the authors' model on five different proteins: GB1, the WW-domain, the B-domain of Protein A, the peripheral binding subunit and villin headpiece.
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190Ermak, D.; McCammon, J. A. Brownian dynamics with hydrodynamic interactions J. Chem. Phys. 1978, 69, 1352– 1360 DOI: 10.1063/1.436761190https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE1cXls12huro%253D&md5=b11c679cdc7ac5bbecd8335b33f60e8fBrownian dynamics with hydrodynamic interactionsErmak, Donald L.; McCammon, J. A.Journal of Chemical Physics (1978), 69 (4), 1352-60CODEN: JCPSA6; ISSN:0021-9606.A method for simulating the Brownian dynamics of N particles with the inclusion of hydrodynamic interactions is described. The particles may also be subject to the usual interparticle or external forces (e.g., electrostatic) which were included in previous methods for simulating Brownian dynamics of particles in the absence of hydrodynamic interactions. The present method is derived from the Langevin equations for the N particle assembly, and the results are consistent with the corresponding Fokker-Planck results. Sample calcns. on small systems illustrate the importance of including hydrodynamic interactions in Brownian dynamics simulations. The method should be useful for simulation studies of diffusion limited reactions, polymer dynamics, protein folding, particle coagulation, and other phenomena in soln.
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191Proctor, E.; Dokholyan, N. Applications of Discrete Molecular Dynamics in biology and medicine Curr. Opin. Struct. Biol. 2016, 37, 9– 13 DOI: 10.1016/j.sbi.2015.11.001191https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVyqu7zM&md5=adf921c1d44f3597540eecc07746efa3Applications of Discrete Molecular Dynamics in biology and medicineProctor, Elizabeth A.; Dokholyan, Nikolay V.Current Opinion in Structural Biology (2016), 37 (), 9-13CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Discrete Mol. Dynamics (DMD) is a physics-based simulation method using discrete energetic potentials rather than traditional continuous potentials, allowing microsecond time scale simulations of biomol. systems to be performed on personal computers rather than supercomputers or specialized hardware. With the ongoing explosion in processing power even in personal computers, applications of DMD have similarly multiplied. In the past two years, researchers have used DMD to model structures of disease-implicated protein folding intermediates, study assembly of protein complexes, predict protein-protein binding conformations, engineer rescue mutations in disease-causative protein mutants, design a protein conformational switch to control cell signaling, and describe the behavior of polymeric dispersants for environmental cleanup of oil spills, among other innovative applications.
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192Urbanc, B.; Borreguero, J.; Cruz, L.; Stanley, E. Ab initio discrete molecular dynamics approach to protein folding and aggregation Methods Enzymol. 2006, 412, 314– 338 DOI: 10.1016/S0076-6879(06)12019-4192https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmtFKhsrc%253D&md5=298d035301793fc753c1b6032fdf5dbaAb initio discrete molecular dynamics approach to protein folding and aggregationUrbanc, Brigita; Borreguero, Jose M.; Cruz, Luis; Stanley, H. EugeneMethods in Enzymology (2006), 412 (Amyloid, Prions, and Other Protein Aggregates, Part B), 314-338CODEN: MENZAU; ISSN:0076-6879. (Elsevier)Understanding the toxicity of amyloidogenic protein aggregates and designing therapeutic approaches require the knowledge of their structure at. resoln. Although solid-state NMR, x-ray diffraction, and other exptl. techniques are capable of discerning the protein fibrillar structure, detg. the structures of early aggregates, called oligomers, is a challenging exptl. task. Computational studies by all-atom mol. dynamics, which provides a complete description of a protein in the solvent, are typically limited to study folding of smaller protein or aggregation of a small no. of short protein fragments. We reviewed an efficient ab initio computer simulation approach to protein folding and aggregation using discrete mol. dynamics (DMD) in combination with several coarse-grained protein models and implicit solvent. This approach involves different complexity levels in both the protein model and the interparticle interactions. Starting from the simplest protein model with minimal interactions, and gradually increasing its complexity, while guided by in vitro findings, we can systematically select the key features of the protein model and interactions that drive protein folding and aggregation. Because the method used in this DMD approach does not require any knowledge of the native or any other state of the protein, it can be applied to study degenerative disorders assocd. with protein misfolding and aberrant protein aggregation. The choice of the coarse-grained model depends on the complexity of the protein and specific questions to be addressed, which are mostly suggested by in vitro findings. Thus, we illustrate our approach on amyloid β-protein (Aβ) assocd. with Alzheimer's disease (AD). Despite the simplifications introduced in the DMD approach, the predicted Aβ conformations are in agreement with existing exptl. data. The in silico findings also provide further insights into the structure and dynamics of Aβ folding and oligomer formation that are amenable to in vitro testing.
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193Chen, Y.; Ding, F.; Dokholyan, N. V. Fidelity of the protein structure reconstruction from inter-residue proximity constraints J. Phys. Chem. B 2007, 111, 7432– 7438 DOI: 10.1021/jp068963tThere is no corresponding record for this reference.
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194Sfriso, P.; Hospital, A.; Emperador, A.; Orozco, M. Exploration of conformational transition pathways from coarse-grained simulations Bioinformatics 2013, 29, 1980– 1986 DOI: 10.1093/bioinformatics/btt324194https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFyhtLjM&md5=63745e42a6323f992e7a410b8f856886Exploration of conformational transition pathways from coarse-grained simulationsSfriso, Pedro; Hospital, Adam; Emperador, Agusti; Orozco, ModestoBioinformatics (2013), 29 (16), 1980-1986CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: A new algorithm to trace conformational transitions in proteins is presented. The method uses discrete mol. dynamics as engine to sample protein conformational space. A multiple min. Go-like potential energy function is used in combination with several enhancing sampling strategies, such as metadynamics, Maxwell Demon mol. dynamics and essential dynamics. The method, which shows an unprecedented computational efficiency, is able to trace a wide range of known exptl. transitions. Contrary to simpler methods our strategy does not introduce distortions in the chem. structure of the protein and is able to reproduce well complex non-linear conformational transitions. The method, called GOdMD, can easily introduce addnl. restraints to the transition (presence of ligand, known intermediate, known maintained contacts, ...) and is freely distributed to the community through the Spanish National Bioinformatics Institute (http://mmb.irbbarcelona.org/GOdMD).
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195Urbanc, B.; Cruz, L.; Ding, F.; Sammond, D.; Khare, S.; Buldyrev, S. V.; Stanley, H. E.; Dokholyan, N. V. Molecular dynamics simulation of amyloid beta dimer formation Biophys. J. 2004, 87, 2310– 2321 DOI: 10.1529/biophysj.104.040980195https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXot12nu7k%253D&md5=cbe7dd2a88a4e78d29da6c8e1ea3e819Molecular dynamics simulation of amyloid β dimer formationUrbanc, B.; Cruz, L.; Ding, F.; Sammond, D.; Khare, S.; Buldyrev, S. V.; Stanley, H. E.; Dokholyan, N. V.Biophysical Journal (2004), 87 (4), 2310-2321CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)Recent expts. with amyloid β (Aβ) peptide indicate that formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Aβ oligomers depends on their structure, which is governed by assembly dynamics. Due to limitations of current exptl. techniques, a detailed knowledge of oligomer structure at the at. level is missing. We introduce a mol. dynamics approach to study Aβ dimer formation. 1), We use discrete mol. dynamics simulations of a coarse-grained model to identify a variety of dimer conformations; and 2), we employ all-atom mol. mechanics simulations to est. thermodn. stability of all dimer conformations. Our simulations of a coarse-grained Aβ peptide model predicts 10 different planar β-strand dimer conformations. We then est. the free energies of all dimer conformations in all-atom mol. mechanics simulations with explicit water. We compare the free energies of Aβ(1-42) and Aβ(1-40) dimers. We find that 1), dimer conformations have higher free energies compared to their corresponding monomeric states; and 2), the free-energy difference between the Aβ(1-42) and the corresponding Aβ(1-40) dimer conformation is not significant. Our results suggest that Aβ oligomerization is not accompanied by the formation of thermodynamically stable planar β-strand dimers.
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196Vitalis, A.; Pappu, R. Methods for Monte Carlo simulations of biomacromolecules Annu. Rep. Comput. Chem. 2009, 5, 49– 76 DOI: 10.1016/S1574-1400(09)00503-9196https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhs1aiu7rN&md5=f2740f0aa97eee24e9dd4cecec45b5b6Methods for Monte Carlo simulations of biomacromoleculesVitalis, Andreas; Pappu, Rohit V.Annual Reports in Computational Chemistry (2009), 5 (), 49-76CODEN: ARCCC3; ISSN:1574-1400. (Elsevier B.V.)A review. The state-of-the-art for Monte Carlo (MC) simulations of biomacromols. is reviewed. Available methodologies for sampling conformational equil. and assocns. of biomacromols. in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves and the applicability of such methods to simulations of biomacromols. are discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, although underutilized in the biomacromol. simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, esp. when used in conjunction with implicit solvation models or other coarse-graining strategies.
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197Goujon, F.; Malfreyt, P.; Simon, J.-M.; Boutin, A.; Rousseau, B.; Fuchs, A. Monte Carlo versus molecular dynamics simulations in heterogeneous systems: An application to the n-pentane liquid-vapor interface J. Chem. Phys. 2004, 121, 12559– 12571 DOI: 10.1063/1.1819868197https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXhtFSnsrvP&md5=cbf1046208e13df79e04df4bb8660a72Monte Carlo versus molecular dynamics simulations in heterogeneous systems. An application to the n-pentane liquid-vapor interfaceGoujon, Florent; Malfreyt, Patrice; Simon, Jean-Marc; Boutin, Anne; Rousseau, Bernard; Fuchs, Alain H.Journal of Chemical Physics (2004), 121 (24), 12559-12571CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The Monte Carlo (MC) and mol. dynamics (MD) methodologies are now well established for computing equil. properties in homogeneous fluids. This is not yet the case for the direct simulation of 2-phase systems, which exhibit nonuniformity of the d. distribution across the interface. We have performed direct MC and MD simulations of the liq.-gas interface of n-pentane using a std. force-field model. We obtained d. and pressure components profiles along the direction normal to the interface that can be very different, depending on the truncation and long range correction strategies. We discuss the influence on predicted properties of different potential truncation schemes implemented in both MC and MD simulations. The MD and MC profiles can be made in agreement by a Lennard-Jones potential truncated via a polynomial function that makes the first and second derivs. of the potential continuous at the cutoff distance. In this case however, the predicted thermodn. properties (phase envelope, surface tension) deviate from expts., because of the changes made in the potential. A further readjustment of the potential parameters is needed if one wants to use this method. A straightforward use of bulk phase force fields in MD simulations may lead to some phys. inconsistencies when computing interfacial properties.
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198Schluttig, J.; Bachmann, M.; Janke, W. Comparative molecular dynamics and Monte Carlo study of statistical properties for coarse-grained heteropolymers J. Comput. Chem. 2008, 29, 2603– 2612 DOI: 10.1002/jcc.21003There is no corresponding record for this reference.
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199Lane, T. J.; Shukla, D.; Beauchamp, K. A.; Pande, V. S. To milliseconds and beyond: challenges in the simulation of protein folding Curr. Opin. Struct. Biol. 2013, 23, 58– 65 DOI: 10.1016/j.sbi.2012.11.002199https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVWgtLjF&md5=76f625b813b7c85cfbcabac6659155cdTo milliseconds and beyond: challenges in the simulation of protein foldingLane, Thomas J.; Shukla, Diwakar; Beauchamp, Kyle A.; Pande, Vijay S.Current Opinion in Structural Biology (2013), 23 (1), 58-65CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Quant. accurate all-atom mol. dynamics (MD) simulations of protein folding have long been considered a holy grail of computational biol. Due to the large system sizes and long timescales involved, such a pursuit was for many years computationally intractable. Further, sufficiently accurate forcefields needed to be developed in order to realistically model folding. This decade, however, saw the first reports of folding simulations describing kinetics on the order of milliseconds, placing many proteins firmly within reach of these methods. Progress in sampling and forcefield accuracy, however, presents a new challenge: how to turn huge MD datasets into scientific understanding. Here, we review recent progress in MD simulation techniques and show how the vast datasets generated by such techniques present new challenges for anal. We critically discuss the state of the art, including reaction coordinate and Markov state model (MSM) methods, and provide a perspective for the future.
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200Bowman, G. R.; Voelz, V. A.; Pande, V. S. Taming the complexity of protein folding Curr. Opin. Struct. Biol. 2011, 21, 4– 11 DOI: 10.1016/j.sbi.2010.10.006200https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhvFKhur8%253D&md5=aa258139210e793fd6829527c52d7ee9Taming the complexity of protein foldingBowman, Gregory R.; Voelz, Vincent A.; Pande, Vijay S.Current Opinion in Structural Biology (2011), 21 (1), 4-11CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. Protein folding is an important problem in structural biol. with significant medical implications, particularly for misfolding disorders like Alzheimer's disease. Solving the folding problem will ultimately require a combination of theory and expt., with theor. models providing a comprehensive view of folding and expts. grounding these models in reality. Here we review progress towards this goal over the past decade, with an emphasis on recent theor. advances that are empowering chem. detailed models of folding and the new results these technologies are providing. In particular, we discuss new insights made possible by Markov state models (MSMs), including the role of non-native contacts and the hub-like character of protein folded states.
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201Noe, F.; Fischer, S. Transition networks for modeling the kinetics of conformational change in macromolecules Curr. Opin. Struct. Biol. 2008, 18, 154– 162 DOI: 10.1016/j.sbi.2008.01.008There is no corresponding record for this reference.
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202Yin, Y.; Sieradzan, A. K.; Liwo, A.; He, Y.; Scheraga, H. A. Physics-based potentials for coarse-grained modeling of protein-DNA interactions J. Chem. Theory Comput. 2015, 11, 1792– 1808 DOI: 10.1021/ct5009558202https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkt1Ohsrw%253D&md5=8b732d52174fb072b8c37e47f43ec78bPhysics-Based Potentials for Coarse-Grained Modeling of Protein-DNA InteractionsYin, Yanping; Sieradzan, Adam K.; Liwo, Adam; He, Yi; Scheraga, Harold A.Journal of Chemical Theory and Computation (2015), 11 (4), 1792-1808CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Physics-based potentials have been developed for the interactions between proteins and DNA for simulations with the UNRES + NARES-2P force field. The mean-field interactions between a protein and a DNA mol. can be divided into eight categories: (1) nonpolar side chain-DNA base, (2) polar uncharged side chain-DNA base, (3) charged side chain-DNA base, (4) peptide group-phosphate group, (5) peptide group-DNA base, (6) nonpolar side chain-phosphate group, (7) polar uncharged side chain-phosphate group, and (8) charged side chain-phosphate group. Umbrella-sampling mol. dynamics simulations in explicit TIP3P water using the AMBER force field were carried out to det. the potentials of mean force (PMF) for all 105 pairs of interacting components. Approx. anal. expressions for the mean-field interaction energy of each pair of the different kinds of interacting mols. were then fitted to the PMFs to obtain the parameters of the anal. expressions. These anal. expressions can reproduce satisfactorily the PMF curves corresponding to different orientations of the interacting mols. The results suggest that the physics-based mean-field potentials of amino acid-nucleotide interactions presented here can be used in coarse-grained simulation of protein-DNA interactions.
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203Krupa, P.; Mozolewska, M. A.; Joo, K.; Lee, J.; Czaplewski, C.; Liwo, A. Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field J. Chem. Inf. Model. 2015, 55, 1271– 1281 DOI: 10.1021/acs.jcim.5b00117203https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXotFChsro%253D&md5=192c72efc38618c63ced5432d5d06e7dPrediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force FieldKrupa, Pawel; Mozolewska, Magdalena A.; Joo, Keehyoung; Lee, Jooyoung; Czaplewski, Cezary; Liwo, AdamJournal of Chemical Information and Modeling (2015), 55 (6), 1271-1281CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange mol. dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the mol., is used to search the conformational space, and the weighted histogram anal. method and cluster anal. are applied to det. the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.
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204Mozolewska, M. A.; Krupa, P.; Scheraga, H. A.; Liwo, A. Molecular modeling of the binding modes of the iron-sulfur protein to the Jac1 co-chaperone from Saccharomyces cerevisiae by all-atom and coarse-grained approaches Proteins: Struct., Funct., Genet. 2015, 83, 1414– 1426 DOI: 10.1002/prot.24824There is no corresponding record for this reference.
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205Blaszczyk, M.; Jamroz, M.; Kmiecik, S.; Kolinski, A. CABS-fold: Server for the de novo and consensus-based prediction of protein structure Nucleic Acids Res. 2013, 41, W406– 411 DOI: 10.1093/nar/gkt462There is no corresponding record for this reference.
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206Jamroz, M.; Kolinski, A. Modeling of loops in proteins: a multi-method approach BMC Struct. Biol. 2010, 10, 5 DOI: 10.1186/1472-6807-10-5206https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3c7nvF2gug%253D%253D&md5=8aacfca6f596ba6376691d007eb973a6Modeling of loops in proteins: a multi-method approachJamroz Michal; Kolinski AndrzejBMC structural biology (2010), 10 (), 5 ISSN:.BACKGROUND: Template-target sequence alignment and loop modeling are key components of protein comparative modeling. Short loops can be predicted with high accuracy using structural fragments from other, not necessairly homologous proteins, or by various minimization methods. For longer loops multiscale approaches employing coarse-grained de novo modeling techniques should be more effective. RESULTS: For a representative set of protein structures of various structural classes test predictions of loop regions have been performed using MODELLER, ROSETTA, and a CABS coarse-grained de novo modeling tool. Loops of various length, from 4 to 25 residues, were modeled assuming an ideal target-template alignment of the remaining portions of the protein. It has been shown that classical modeling with MODELLER is usually better for short loops, while coarse-grained de novo modeling is more effective for longer loops. Even very long missing fragments in protein structures could be effectively modeled. Resolution of such models is usually on the level 2-6 A, which could be sufficient for guiding protein engineering. Further improvement of modeling accuracy could be achieved by the combination of different methods. In particular, we used 10 top ranked models from sets of 500 models generated by MODELLER as multiple templates for CABS modeling. On average, the resulting molecular models were better than the models from individual methods. CONCLUSIONS: Accuracy of protein modeling, as demonstrated for the problem of loop modeling, could be improved by the combinations of different modeling techniques.
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207Kmiecik, S.; Kolinski, A. Characterization of protein-folding pathways by reduced-space modeling Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 12330– 12335 DOI: 10.1073/pnas.0702265104207https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXos1ehsbc%253D&md5=0085e0982f31abcefce8fd83bc2f2ce7Characterization of protein-folding pathways by reduced-space modelingKmiecik, Sebastian; Kolinski, AndrzejProceedings of the National Academy of Sciences of the United States of America (2007), 104 (30), 12330-12335CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Ab initio simulations of the folding pathways are currently limited to very small proteins. For larger proteins, some approxns. or simplifications in protein models need to be introduced. Protein folding and unfolding are among the basic processes in the cell and are very difficult to characterize in detail by expt. or simulation. Chymotrypsin inhibitor 2 (CI2) and barnase are probably the best characterized exptl. in this respect. For these model systems, initial folding stages were simulated by using CA-CB-side-chain (CABS), a reduced-space protein-modeling tool. CABS employs knowledge-based potentials that proved to be very successful in protein structure prediction. With the use of isothermal Monte Carlo (MC) dynamics, initiation sites with a residual structure and weak tertiary interactions were identified. Such structures are essential for the initiation of the folding process through a sequential redn. of the protein conformational space, overcoming the Levinthal paradox in this manner. Furthermore, nucleation sites that initiate a tertiary interactions network were located. The MC simulations corresponded perfectly to the results of exptl. and theor. research and brought insights into the CI2 folding mechanism: an unambiguous sequence of folding events was reported as well as cooperative substructures compatible with those obtained in recent mol. dynamics unfolding studies. The correspondence between the simulation and expt. showed that knowledge-based potentials are not only useful in protein structure predictions but are also capable of reproducing the folding pathways. Thus, the results of this work significantly extend the applicability range of reduced models in the theor. study of proteins.
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208Kmiecik, S.; Kolinski, A. Folding pathway of the b1 domain of protein G explored by multiscale modeling Biophys. J. 2008, 94, 726– 736 DOI: 10.1529/biophysj.107.116095208https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVahsrc%253D&md5=4793eb39e37f0fa9d875e6b0b1d8ed6fFolding pathway of the B1 domain of protein G explored by multiscale modelingKmiecik, Sebastian; Kolinski, AndrzejBiophysical Journal (2008), 94 (3), 726-736CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, the authors developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodn., and modeling of protein complexes. Here, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of exptl. facts and theor. findings for this protein. Performing unbiased, ab initio simulations, the authors demonstrated that GB1 folding proceeded via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions was found to drive the folding from the very beginning. The emerging comprehensive picture of GB1 folding was found to perfectly match and extend previous exptl. and theor. studies.
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209Kmiecik, S.; Kolinski, A. Simulation of chaperonin effect on protein folding: a shift from nucleation-condensation to framework mechanism J. Am. Chem. Soc. 2011, 133, 10283– 10289 DOI: 10.1021/ja203275fThere is no corresponding record for this reference.
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210Jamroz, M.; Kolinski, A.; Kmiecik, S. CABS-flex: Server for fast simulation of protein structure fluctuations Nucleic Acids Res. 2013, 41, W427– 431 DOI: 10.1093/nar/gkt332There is no corresponding record for this reference.
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211Jamroz, M.; Orozco, M.; Kolinski, A.; Kmiecik, S. Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field J. Chem. Theory Comput. 2013, 9, 119– 125 DOI: 10.1021/ct300854w211https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhslOmu7jN&md5=880ab5fbba6f9beb9ec1d30d30f79a21Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-FieldJamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, SebastianJournal of Chemical Theory and Computation (2013), 9 (1), 119-125CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)It is widely recognized that atomistic Mol. Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theor. study showing that various MD force-fields provide a consensus picture of protein fluctuations in aq. soln. [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biol. relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale mol. modeling of protein systems with atomistic resoln.
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212Kurcinski, M.; Kolinski, A.; Kmiecik, S. Mechanism of Folding and Binding of an Intrinsically Disordered Protein As Revealed by ab Initio Simulations J. Chem. Theory Comput. 2014, 10, 2224– 2231 DOI: 10.1021/ct500287c212https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXns1Cgsbg%253D&md5=36ed5e48c9d3893d0cb9e708497666d8Mechanism of Folding and Binding of an Intrinsically Disordered Protein As Revealed by ab Initio SimulationsKurcinski, Mateusz; Kolinski, Andrzej; Kmiecik, SebastianJournal of Chemical Theory and Computation (2014), 10 (6), 2224-2231CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A complex of the phosphorylated kinase-inducible domain (pKID) from transcription factor CREB with its interacting domain (KIX) from CREB-binding protein (CBP) is a model system for studies of mechanisms by which intrinsically unfolded proteins perform their functions. These mechanisms are not fully understood. Using an efficient coarse-grained model, ab initio simulations were performed of the coupled folding and binding of the pKID to the KIX. The simulations start from an unbound, randomly positioned and disordered pKID structure. During the simulations the pKID chain and its position remain completely unrestricted, while the KIX backbone is limited to near-native fluctuations. Ab initio simulations of such large-scale conformational transitions, unaffected by any knowledge about the bound pKID structure, remain inaccessible to classical simulations. Our simulations recover an ensemble of transient encounter complexes in good agreement with exptl. results. We find that a key folding and binding step is linked to the formation of weak native interactions between a preformed nativelike fragment of a pKID helix and KIX surface. Once that nucleus forms, the pKID chain may condense from a largely disordered encounter ensemble to a natively bound and ordered conformation. The obsd. mechanism is reminiscent of a nucleation-condensation model, a common scenario for folding of globular proteins.
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213Kurcinski, M.; Jamroz, M.; Blaszczyk, M.; Kolinski, A.; Kmiecik, S. CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site Nucleic Acids Res. 2015, 43, W419– 424 DOI: 10.1093/nar/gkv456213https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtVymtbrK&md5=3d72a394eafb7869513e622e1b361d47CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding siteKurcinski, Mateusz; Jamroz, Michal; Blaszczyk, Maciej; Kolinski, Andrzej; Kmiecik, SebastianNucleic Acids Research (2015), 43 (W1), W419-W424CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Protein-peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein-peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of nonredundant protein-peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Addnl., as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments.
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214Blaszczyk, M.; Kurcinski, M.; Kouza, M.; Wieteska, L.; Debinski, A.; Kolinski, A.; Kmiecik, S. Modeling of protein-peptide interactions using the CABS-dock web server for binding site search and flexible docking Methods 2016, 93, 72– 83 DOI: 10.1016/j.ymeth.2015.07.004214https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtF2ksL%252FN&md5=cf994902770c92eed25bfe3b7aa3189aModeling of protein-peptide interactions using the CABS-dock web server for binding site search and flexible dockingBlaszczyk, Maciej; Kurcinski, Mateusz; Kouza, Maksim; Wieteska, Lukasz; Debinski, Aleksander; Kolinski, Andrzej; Kmiecik, SebastianMethods (Amsterdam, Netherlands) (2016), 93 (), 72-83CODEN: MTHDE9; ISSN:1046-2023. (Elsevier B.V.)Protein-peptide interactions play essential functional roles in living organisms and their structural characterization is a hot subject of current exptl. and theor. research. Computational modeling of the structure of protein-peptide interactions is usually divided into two stages: prediction of the binding site at a protein receptor surface, and then docking (and modeling) the peptide structure into the known binding site. This paper presents a comprehensive CABS-dock method for the simultaneous search of binding sites and flexible protein-peptide docking, available as a user's friendly web server. We present example CABS-dock results obtained in the default CABS-dock mode and using its advanced options that enable the user to increase the range of flexibility for chosen receptor fragments or to exclude user-selected binding modes from docking search. Furthermore, we demonstrate a strategy to improve CABS-dock performance by assessing the quality of models with classical mol. dynamics. Finally, we discuss the promising extensions and applications of the CABS-dock method and provide a tutorial appendix for the convenient anal. and visualization of CABS-dock results. The CABS-dock web server is freely available at http://biocomp.chem.uw.edu.pl/CABSdock/.
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215Kar, P.; Gopal, S. M.; Cheng, Y. M.; Panahi, A.; Feig, M. Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix-Helix Association J. Chem. Theory Comput. 2014, 10, 3459– 3472 DOI: 10.1021/ct500443v215https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpslygsbY%253D&md5=1d78a59c87cd1c45911beba8fe46f915Transferring the PRIMO Coarse-Grained Force Field to the Membrane Environment: Simulations of Membrane Proteins and Helix-Helix AssociationKar, Parimal; Gopal, Srinivasa Murthy; Cheng, Yi-Ming; Panahi, Afra; Feig, MichaelJournal of Chemical Theory and Computation (2014), 10 (8), 3459-3472CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)An extension of the recently developed PRIMO coarse-grained force field to membrane environments, PRIMO-M, is described. The membrane environment is modeled with the heterogeneous dielec. generalized Born (HDGB) methodol. that simply replaces the std. generalized Born model in PRIMO without further parametrization. The resulting model was validated by comparing amino acid insertion free energy profiles and application in mol. dynamics simulations of membrane proteins and membrane-interacting peptides. Membrane proteins with 148-661 amino acids show stable root-mean-squared-deviations (RMSD) between 2 and 4 Å for most systems. Transmembrane helical peptides maintain helical shape and exhibit tilt angles in good agreement with exptl. or other simulation data. The assocn. of two glycophorin A (GpA) helixes was simulated using replica exchange mol. dynamics simulations yielding the correct dimer structure with a crossing angle in agreement with previous studies. Finally, conformational sampling of the influenza fusion peptide also generates structures in agreement with previous studies. Overall, these findings suggest that PRIMO-M can be used to study membrane bound peptides and proteins and validates the transferable nature of the PRIMO coarse-grained force field.
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216Marrink, S. J.; de Vries, A. H.; Mark, A. E. Coarse grained model for semiquantitative lipid simulations J. Phys. Chem. B 2004, 108, 750– 760 DOI: 10.1021/jp036508g216https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXptlKjsb4%253D&md5=53c1ca266631af0122f3b5577e9efb0bCoarse Grained Model for Semiquantitative Lipid SimulationsMarrink, Siewert J.; De Vries, Alex H.; Mark, Alan E.Journal of Physical Chemistry B (2004), 108 (2), 750-760CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)This paper describes the parametrization of a new coarse grained (CG) model for lipid and surfactant systems. Redn. of the no. of degrees of freedom together with the use of short range potentials makes it computationally very efficient. Compared to atomistic models a gain of 3-4 orders of magnitude can be achieved. Micrometer length scales or millisecond time scales are therefore within reach. To encourage applications, the model is kept very simple. Only a small no. of coarse grained atom types are defined, which interact using a few discrete levels of interaction. Despite the computational speed and the simplistic nature of the model, it proves to be both versatile in its applications and accurate in its predictions. We show that densities of liq. alkanes from decane up to eicosane can be reproduced to within 5%, and the mutual solubilities of alkanes in water and water in alkanes can be reproduced within 0.5 kT of the exptl. values. The CG model for dipalmitoylphosphatidylcholine (DPPC) is shown to aggregate spontaneously into a bilayer. Structural properties such as the area per headgroup and the phosphate-phosphate distance match the exptl. measured quantities closely. The same is true for elastic properties such as the bending modulus and the area compressibility, and dynamic properties such as the lipid lateral diffusion coeff. and the water permeation rate. The distribution of the individual lipid components along the bilayer normal is very similar to distributions obtained from atomistic simulations. Phospholipids with different headgroup (ethanolamine) or different tail lengths (lauroyl, stearoyl) or unsatd. tails (oleoyl) can also be modeled with the CG force field. The exptl. area per headgroup can be reproduced for most lipids within 0.02 nm2. Finally, the CG model is applied to nonbilayer phases. Dodecylphosphocholine (DPC) aggregates into small micelles that are structurally very similar to ones modeled atomistically, and DOPE forms an inverted hexagonal phase with structural parameters in agreement with exptl. data.
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217Monticelli, L.; Kandasamy, S. K.; Periole, X.; Larson, R. G.; Tieleman, D. P.; Marrink, S. J. The MARTINI coarse-grained force field: Extension to proteins J. Chem. Theory Comput. 2008, 4, 819– 834 DOI: 10.1021/ct700324x217https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXks1Onsrg%253D&md5=56f4bb722f339707787e946a15dba5faThe MARTINI Coarse-Grained Force Field: Extension to ProteinsMonticelli, Luca; Kandasamy, Senthil K.; Periole, Xavier; Larson, Ronald G.; Tieleman, D. Peter; Marrink, Siewert-JanJournal of Chemical Theory and Computation (2008), 4 (5), 819-834CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Many biol. interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biol. materials. Coarse-grained (CG) mol. modeling allows computer simulations to be run on length and time scales that are 2-3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. The authors developed a new CG model for proteins as an extension of the MARTINI force field. Here, the authors validate the model for its use in peptide-bilayer systems. To validate the model, the authors calcd. the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. The authors then compared amino acid assocn. consts., the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyristoylphosphatidylcholine and dipalmitoylphosphatidylcholine (DPPC) bilayers. A comparison with results obtained from atomistic models shows good agreement in all of the tests performed. The authors also performed a systematic investigation of the partitioning of five series of polyalanine-leucine peptides (with different lengths and compns.) in DPPC bilayers. As expected, the fraction of peptides partitioned at the interface increased with decreasing peptide length and decreasing leucine content, demonstrating that the CG model is capable of discriminating partitioning behavior arising from subtle differences in the amino acid compn. Finally, the authors simulated the concn.-dependent formation of transmembrane pores by magainin, an antimicrobial peptide. In line with atomistic simulation studies, disordered toroidal pores are formed. In conclusion, the model is computationally efficient and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.
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218Marrink, S. J.; Risselada, H. J.; Yefimov, S.; Tieleman, D. P.; de Vries, A. H. The MARTINI force field: Coarse grained model for biomolecular simulations J. Phys. Chem. B 2007, 111, 7812– 7824 DOI: 10.1021/jp071097f218https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmsVKmsLc%253D&md5=428d5750b94652e4917d905a30658235The MARTINI Force Field: Coarse Grained Model for Biomolecular SimulationsMarrink, Siewert J.; Risselada, H. Jelger; Yefimov, Serge; Tieleman, D. Peter; De Vries, Alex H.Journal of Physical Chemistry B (2007), 111 (27), 7812-7824CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)We present an improved and extended version of our coarse grained lipid model. The new version, coined the MARTINI force field, is parametrized in a systematic way, based on the reprodn. of partitioning free energies between polar and apolar phases of a large no. of chem. compds. To reproduce the free energies of these chem. building blocks, the no. of possible interaction levels of the coarse-grained sites has increased compared to those of the previous model. Application of the new model to lipid bilayers shows an improved behavior in terms of the stress profile across the bilayer and the tendency to form pores. An extension of the force field now also allows the simulation of planar (ring) compds., including sterols. Application to a bilayer/cholesterol system at various concns. shows the typical cholesterol condensation effect similar to that obsd. in all atom representations.
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219Shih, A. Y.; Arkhipov, A.; Freddolino, P. L.; Schulten, K. Coarse grained protein-lipid model with application to lipoprotein particles J. Phys. Chem. B 2006, 110, 3674– 3684 DOI: 10.1021/jp0550816219https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtF2qsA%253D%253D&md5=e7effac4070f205380c48b5dcaf35e1eCoarse Grained Protein-Lipid Model with Application to Lipoprotein ParticlesShih, Amy Y.; Arkhipov, Anton; Freddolino, Peter L.; Schulten, KlausJournal of Physical Chemistry B (2006), 110 (8), 3674-3684CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A coarse-grained model for mol. dynamics simulations is extended from lipids to proteins. In the framework of such models pioneered by Klein, atoms are described group-wise by beads, with the interactions between beads governed by effective potentials. The extension developed here is based on a coarse-grained lipid model developed previously by Marrink et al., although future versions will reconcile the approach taken with the systematic approach of Klein and other authors. Each amino acid of the protein is represented by two coarse-grained beads, one for the backbone (identical for all residues) and one for the side-chain (which differs depending on the residue type). The coarse-graining reduces the system size about 10-fold and allows integration time steps of 25-50 fs. The model is applied to simulations of discoidal high-d. lipoprotein particles involving water, lipids, and two primarily helical proteins. These particles are an ideal test system for the extension of coarse-grained models. Our model proved to be reliable in maintaining the shape of preassembled particles and in reproducing the overall structural features of high-d. lipoproteins (HDLs) accurately. Microsecond simulations of lipoprotein assembly revealed the formation of a protein-lipid complex in which two proteins are attached to either side of a discoidal lipid bilayer.
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220Bond, P. J.; Holyoake, J.; Ivetac, A.; Khalid, S.; Sansom, M. S. Coarse-grained molecular dynamics simulations of membrane proteins and peptides J. Struct. Biol. 2007, 157, 593– 605 DOI: 10.1016/j.jsb.2006.10.004220https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXisVCnsrk%253D&md5=6272050e9bf882316b47fe7cfdd87cceCoarse-grained molecular dynamics simulations of membrane proteins and peptidesBond, Peter J.; Holyoake, John; Ivetac, Anthony; Khalid, Syma; Sansom, Mark S. P.Journal of Structural Biology (2007), 157 (3), 593-605CODEN: JSBIEM; ISSN:1047-8477. (Elsevier)Mol. dynamics (MD) simulations provide a valuable approach to the dynamics, structure, and stability of membrane-protein systems. Coarse-grained (CG) models, in which small groups of atoms are treated as single particles, enable extended (>100 ns) timescales to be addressed. In this study, the authors explore how CG-MD methods that were developed for detergents and lipids may be extended to membrane proteins. In particular, CG-MD simulations of a no. of membrane peptides and proteins are used to characterize their interactions with lipid bilayers. CG-MD is used to simulate the insertion of synthetic model membrane peptides (WALPs and LS3) into a lipid (PC) bilayer. WALP peptides insert in a transmembrane orientation, while the LS3 peptide adopts an interfacial location, both in agreement with exptl. biophys. data. This approach is extended to a transmembrane fragment of the Vpu protein from HIV-1, and to the coat protein from fd phage. Again, simulated protein/membrane interactions are in good agreement with solid state NMR data for these proteins. CG-MD has also been applied to an M3-M4 fragment from the CFTR protein. Simulations of CFTR M3-M4 in a detergent micelle reveal formation of an α-helical hairpin, consistent with a variety of biophys. data. In an I231D mutant, the M3-M4 hairpin is addnl. stabilized via an inter-helix Q207/D231 interaction. Finally, CG-MD simulations are extended to a more complex membrane protein, the bacterial sugar transporter LacY. Comparison of a 200 ns CG-MD simulation of LacY in a DPPC bilayer with a 50 ns atomistic simulation of the same protein in a DMPC bilayer shows that the two methods yield comparable predictions of lipid-protein interactions. Taken together, these results demonstrate the utility of CG-MD simulations for studies of membrane/protein interactions.
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221Spiga, E.; Alemani, D.; Degiacomi, M. T.; Cascella, M.; Peraro, M. D. Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins J. Chem. Theory Comput. 2013, 9, 3515– 3526 DOI: 10.1021/ct400137q221https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpslKit74%253D&md5=1573eaf62983bed6cb1b1fa99307fddeElectrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of ProteinsSpiga, Enrico; Alemani, Davide; Degiacomi, Matteo T.; Cascella, Michele; Peraro, Matteo DalJournal of Chemical Theory and Computation (2013), 9 (8), 3515-3526CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of sol. proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with resp. ref. structures and all-atom mol. dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their mol. interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resoln. An efficient and robust heuristic algorithm based on particle swarm optimization was used for the derivation of CG parameters via a force-matching procedure. The ability of this protocol to deal with high dimensional search spaces suggests that the extension of this optimization procedure to larger data sets may give a fully transferable CG force field. At the present stage, these electrostatic-consistent CG potentials are easily and efficiently parametrized, show a good degree of transferability, and can be used to simulate sol. proteins or, more interestingly, large macromol. assemblies for which long all-atom simulations may not be easily affordable.
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222Alemani, D.; Collu, F.; Cascella, M.; Dal Peraro, M. A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure Elements J. Chem. Theory Comput. 2010, 6, 315– 324 DOI: 10.1021/ct900457z222https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsF2jsrrI&md5=048bb50a976cc55a5ff792617483ab72A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure ElementsAlemani, Davide; Collu, Francesca; Cascella, Michele; Dal Peraro, MatteoJournal of Chemical Theory and Computation (2010), 6 (1), 315-324CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We introduce a nonradial potential term for coarse-grained (CG) mol. simulations of proteins. This term mimics the backbone dipole-dipole interactions and accounts for the needed directionality to form stable folded secondary structure elements. We show that α-helical and β-sheet peptide chains are correctly described in dynamics without the need for introducing any a priori bias potentials or ad hoc parameterizations, which limit broader applicability of CG simulations for proteins. Moreover, our model is able to catch the formation of supersecondary structural motifs, like transitions from long single α-helixes to helix-coil-helix or β-hairpin assemblies. This novel scheme requires the structural information of Cα beads only; it does not introduce any addnl. degrees of freedom to the system and has a general formulation, which allows it to be used in synergy with various CG protocols, leading to an improved description of the structural and dynamic properties of protein assemblies and networks.
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223Arnarez, C.; Uusitalo, J. J.; Masman, M. F.; Ingolfsson, H. I.; de Jong, D. H.; Melo, M. N.; Periole, X.; de Vries, A. H.; Marrink, S. J. Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit Solvent J. Chem. Theory Comput. 2015, 11, 260– 275 DOI: 10.1021/ct500477k223https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVWiu7nP&md5=bc78f6059a8f9eb69cbc2d8fb9210790Dry Martini, a Coarse-Grained Force Field for Lipid Membrane Simulations with Implicit SolventArnarez, Clement; Uusitalo, Jaakko J.; Masman, Marcelo F.; Ingolfsson, Helgi I.; de Jong, Djurre H.; Melo, Manuel N.; Periole, Xavier; de Vries, Alex H.; Marrink, Siewert J.Journal of Chemical Theory and Computation (2015), 11 (1), 260-275CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grained (CG) models allow simulation of larger systems for longer times by decreasing the no. of degrees of freedom compared with all-atom models. Here we introduce an implicit-solvent version of the popular CG Martini model, nicknamed "Dry" Martini. To account for the omitted solvent degrees of freedom, the nonbonded interaction matrix underlying the Martini force field was reparametrized. The Dry Martini force field reproduces relatively well a variety of lipid membrane properties such as area per lipid, bilayer thickness, bending modulus, and coexistence of liq.-ordered and disordered domains. Furthermore, we show that the new model can be applied to study membrane fusion and tether formation, with results similar to those of the std. Martini model. Membrane proteins can also be included, but less quant. results are obtained. The absence of water in Dry Martini leads to a significant speedup for large systems, opening the way to the study of complex multicomponent membranes contg. millions of lipids.
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224Yesylevskyy, S. O.; Schafer, L. V.; Sengupta, D.; Marrink, S. J. Polarizable water model for the coarse-grained MARTINI force field PLoS Comput. Biol. 2010, 6, e1000810 DOI: 10.1371/journal.pcbi.1000810224https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3crgsVKisQ%253D%253D&md5=86162bc2c160c1bf7a1058eb82296455Polarizable water model for the coarse-grained MARTINI force fieldYesylevskyy Semen O; Schafer Lars V; Sengupta Durba; Marrink Siewert JPLoS computational biology (2010), 6 (6), e1000810 ISSN:.Coarse-grained (CG) simulations have become an essential tool to study a large variety of biomolecular processes, exploring temporal and spatial scales inaccessible to traditional models of atomistic resolution. One of the major simplifications of CG models is the representation of the solvent, which is either implicit or modeled explicitly as a van der Waals particle. The effect of polarization, and thus a proper screening of interactions depending on the local environment, is absent. Given the important role of water as a ubiquitous solvent in biological systems, its treatment is crucial to the properties derived from simulation studies. Here, we parameterize a polarizable coarse-grained water model to be used in combination with the CG MARTINI force field. Using a three-bead model to represent four water molecules, we show that the orientational polarizability of real water can be effectively accounted for. This has the consequence that the dielectric screening of bulk water is reproduced. At the same time, we parameterized our new water model such that bulk water density and oil/water partitioning data remain at the same level of accuracy as for the standard MARTINI force field. We apply the new model to two cases for which current CG force fields are inadequate. First, we address the transport of ions across a lipid membrane. The computed potential of mean force shows that the ions now naturally feel the change in dielectric medium when moving from the high dielectric aqueous phase toward the low dielectric membrane interior. In the second application we consider the electroporation process of both an oil slab and a lipid bilayer. The electrostatic field drives the formation of water filled pores in both cases, following a similar mechanism as seen with atomistically detailed models.
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225Marrink, S. J.; Tieleman, D. P. Perspective on the Martini model Chem. Soc. Rev. 2013, 42, 6801– 6822 DOI: 10.1039/c3cs60093a225https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtFeqtrbM&md5=9bd67bdef4bf230d9a861ca3f18bf2a8Perspective on the Martini modelMarrink, Siewert J.; Tieleman, D. PeterChemical Society Reviews (2013), 42 (16), 6801-6822CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)A review. The Martini model, a coarse-grained force field for biomol. simulations, has found a broad range of applications since its release a decade ago. Based on a building block principle, the model combines speed and versatility while maintaining chem. specificity. Here we review the current state of the model. We describe recent highlights as well as shortcomings, and our ideas on the further development of the model.
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226Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. GROMACS: fast, flexible, and free J. Comput. Chem. 2005, 26, 1701– 1718 DOI: 10.1002/jcc.20291226https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1SlsbbO&md5=4aa71b1dc0b5b4978a88b0568245a265GROMACS: Fast, flexible, and freeVan Der Spoel, David; Lindahl, Erik; Hess, Berk; Groenhof, Gerrit; Mark, Alan E.; Berendsen, Herman J. C.Journal of Computational Chemistry (2005), 26 (16), 1701-1718CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)This article describes the software suite GROMACS (Groningen MAchine for Chem. Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for mol. dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addn., it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequil. dynamics and free energy detns. are incorporated. Interfaces with popular quantum-chem. packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and anal. programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.
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227Bowers, K. J.; Chow, E.; Xu, H.; Dror, R. O.; Eastwood, M. P.; Gregersen, B. A.; Klepeis, J. L.; Kolossváry, I.; Moraes, M. A.; Sacerdoti, F. D.Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters. Proceedings of the ACM/IEEE Conference on Supercomputing (SC06), 2006.There is no corresponding record for this reference.
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228Baron, R.; Trzesniak, D.; de Vries, A. H.; Elsener, A.; Marrink, S. J.; van Gunsteren, W. F. Comparison of thermodynamic properties of coarse-grained and atomic-level simulation models ChemPhysChem 2007, 8, 452– 461 DOI: 10.1002/cphc.200600658228https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXis1alsr0%253D&md5=ae7ec9a5f5a0e40ffd411a79d4500225Comparison of thermodynamic properties of coarse-grained and atomic-level simulation modelsBaron, Riccardo; Trzesniak, Daniel; de Vries, Alex H.; Elsener, Andreas; Marrink, Siewert J.; van Gunsteren, Wilfred F.ChemPhysChem (2007), 8 (3), 452-461CODEN: CPCHFT; ISSN:1439-4235. (Wiley-VCH Verlag GmbH & Co. KGaA)Thermodn. data are often used to calibrate or test at.-level (AL) force fields for mol. dynamics (MD) simulations. In contrast, the majority of coarse-grained (CG) force fields do not rely extensively on thermodn. quantities. Recently, a CG force field for lipids, hydrocarbons, ions, and water, in which approx. four non-hydrogen atoms are mapped onto one interaction site, has been proposed and applied to study various aspects of lipid systems. To date, no extensive investigation of its capability to describe solvation thermodn. has been undertaken. In the present study, a detailed picture of vaporization, solvation, and phase-partitioning thermodn. for liq. hydrocarbons and water was obtained at CG and AL resolns., in order to compare the two types of models and evaluate their ability to describe thermodn. properties in the temp. range between 263 and 343 K. Both CG and AL models capture the exptl. dependence of the thermodn. properties on the temp., albeit a systematically weaker dependence is found for the CG model. Moreover, deviations are found for solvation thermodn. and for the corresponding enthalpy-entropy compensation for the CG model. Particularly water/oil repulsion seems to be overestimated. However, the results suggest that the thermodn. properties considered should be reproducible by a CG model provided it is re-parametrized on the basis of these liq.-phase properties.
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229Leaver-Fay, A.; Tyka, M.; Lewis, S.; Lange, O.; Thompson, J.; Jacak, R.; Kaufman, K.; Renfrew, D.; Smith, C.; Sheffler, W. ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules Methods Enzymol. 2011, 487, 545– 574 DOI: 10.1016/B978-0-12-381270-4.00019-6229https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXjtFCgtLo%253D&md5=ffd7fe5f3869975c3c0808c3cd43ace1Rosetta3: an obeject-oriented software suite for the simulation and design of macromoleculesLeaver-Fay, Andrew; Tyka, Michael; Lewis, Steven M.; Lange, Oliver F.; Thompson, James; Jacak, Ron; Kaufman, Kristian; Renfrew, P. Douglas; Smith, Colin A.; Sheffler, Will; Davis, Ian W.; Cooper, Seth; Treuille, Adrien; Mandell, Daniel J.; Richter, Florian; Ban, Yih-En Andrew; Fleishman, Sarel J.; Corn, Jacob E.; Kim, David E.; Lyskov, Sergey; Berrondo, Monica; Mentzer, Stuart; Popovic, Zoran; Havranek, James J.; Karanicolas, John; Das, Rhiju; Meiler, Jens; Kortemme, Tanja; Gray, Jeffrey J.; Kuhlman, Brian; Baker, David; Bradley, PhilipMethods in Enzymology (2011), 487 (Computer Methods, Part C), 545-574CODEN: MENZAU; ISSN:0076-6879. (Elsevier Inc.)A review. We have recently completed a full rearchitecturing of the rosetta mol. modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for mol. modeling. The source code of this rearchitecturing has been released as rosetta 3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.
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230Bradley, P.; Misura, K. M.; Baker, D. Toward high-resolution de novo structure prediction for small proteins Science 2005, 309, 1868– 1871 DOI: 10.1126/science.1113801230https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXpvFCisLo%253D&md5=a5f7f424c8af97c6113532cc6f102e7aToward High-Resolution de Novo Structure Prediction for Small ProteinsBradley, Philip; Misura, Kira M. S.; Baker, DavidScience (Washington, DC, United States) (2005), 309 (5742), 1868-1871CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)The prediction of protein structure from amino acid sequence is a grand challenge of computational mol. biol. By using a combination of improved low- and high-resoln. conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resoln. structure prediction (<1.5 Å) can be achieved for small protein domains (<85 residues). The primary bottleneck to consistent high-resoln. prediction appears to be conformational sampling.
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231Gront, D.; Kulp, D.; Vernon, R.; Strauss, C.; Baker, D. Generalized fragment picking in rosetta: design, protocols and applications PLoS One 2011, 6, e23294 DOI: 10.1371/journal.pone.0023294231https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtF2nsLzN&md5=89b6c669d014bb784b644cb3e44f60c7Generalized fragment picking in Rosetta: design, protocols and applicationsGront, Dominik; Kulp, Daniel W.; Vernon, Robert M.; Strauss, Charlie E. M.; Baker, DavidPLoS One (2011), 6 (8), e23294CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extd. from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible.
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232Smith, C.; Kortemme, T. Backrub-Like Backbone Simulation Recapitulates Natural Protein Conformational Variability and Improves Mutant Side-Chain Prediction J. Mol. Biol. 2008, 380, 742– 756 DOI: 10.1016/j.jmb.2008.05.023232https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnvVKgtL8%253D&md5=00a4e8cbeae56e34b083af49a138b61bBackrub-Like Backbone Simulation Recapitulates Natural Protein Conformational Variability and Improves Mutant Side-Chain PredictionSmith, Colin A.; Kortemme, TanjaJournal of Molecular Biology (2008), 380 (4), 742-756CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Incorporation of effective backbone sampling into protein simulation and design is an important step in increasing the accuracy of computational protein modeling. Recent anal. of high-resoln. crystal structures has suggested a new model, termed backrub, to describe localized, hinge-like alternative backbone and side-chain conformations obsd. in the crystal lattice. The model involves internal backbone rotations about axes between C-alpha atoms. Based on this observation, we have implemented a backrub-inspired sampling method in the Rosetta structure prediction and design program. We evaluate this model of backbone flexibility using three different tests. First, we show that Rosetta backrub simulations recapitulate the correlation between backbone and side-chain conformations in the high-resoln. crystal structures upon which the model was based. As a second test of backrub sampling, we show that backbone flexibility improves the accuracy of predicting point-mutant side-chain conformations over fixed backbone rotameric sampling alone. Finally, we show that backrub sampling of triosephosphate isomerase loop 6 can capture the millisecond/μs oscillation between the open and closed states obsd. in soln. Our results suggest that backrub sampling captures a sizable fraction of localized conformational changes that occur in natural proteins. Application of this simple model of backbone motions may significantly improve both protein design and atomistic simulations of localized protein flexibility.
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233Betancourt, M. Efficient Monte Carlo trial moves for polypeptide simulations J. Chem. Phys. 2005, 123, 174905 DOI: 10.1063/1.2102896There is no corresponding record for this reference.
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234Dunbrack, Jr.; Karplus, M. Backbone-dependent Rotamer Library for Proteins Application to Side-chain Prediction J. Mol. Biol. 1993, 230, 543– 574 DOI: 10.1006/jmbi.1993.1170234https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3sXisFWjsL0%253D&md5=b3a7eab18a6c8c4b61e8f3e3fb4aa492Backbone-dependent rotamer library for proteins. Application to side-chain predictionDunbrack, Roland L., Jr.; Karplus, MartinJournal of Molecular Biology (1993), 230 (2), 543-74CODEN: JMOBAK; ISSN:0022-2836.A backbone-dependent rotamer library for amino acid side chains was developed and used for constructing protein side-chain conformations from the main-chain coordinates. The rotamer library was obtained from 132 protein chains in the Brookhaven Protein Database. A grid of 20° by 20° blocks for the main-chain angles .vphi., ψ was used in the rotamer library. Significant correlations were found between side-chain dihedral angle probabilities and backbone .vphi., ψ values. These probabilities were used to place the side chains on the known backbone in test applications for 6 proteins for which high-resoln. crystal structures were available. A minimization scheme was used to reorient side chains that conflict with the backbone or other side chains after the initial placement. The initial placement yields 59% of both χ1 and χ2 values in the correct position (to within 40°) for thermolysin to 81% for crambin. After refinement the values range from 61% (lysozyme) to 89% (crambin). Apparently a single protein does not adequately test a prediction scheme. The computation time required by the method scales linearly with the no. of side chains. An initial prediction from the library takes only a few seconds of computer time, while the iterative refinement takes on the order of hours. The method is automated and can easily be applied to aid exptl. side chain detns. and homol. modeling. The high degree of correlation between backbone and side chain conformations may introduce a simplification in the protein folding process by reducing the available conformational space.
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235Kuhlman, B.; Dantas, G.; Ireton, G.; Varani, G.; Stoddard, B.; Baker, D. Design of a novel globular protein fold with atomic-level accuracy Science 2003, 302, 1364– 1368 DOI: 10.1126/science.1089427235https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXptVCqu7o%253D&md5=2339edc7b74a403e183d3567d966b677Design of a Novel Globular Protein Fold with Atomic-Level AccuracyKuhlman, Brian; Dantas, Gautam; Ireton, Gregory C.; Varani, Gabriele; Stoddard, Barry L.; Baker, DavidScience (Washington, DC, United States) (2003), 302 (5649), 1364-1368CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue α/β protein called Top7 with a novel sequence and topol. Top7 was found exptl. to be folded and extremely stable, and the X-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet obsd. in nature.
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236Davtyan, A.; Schafer, N. P.; Zheng, W.; Clementi, C.; Wolynes, P. G.; Papoian, G. A. AWSEM-MD: protein structure prediction using coarse-grained physical potentials and bioinformatically based local structure biasing J. Phys. Chem. B 2012, 116, 8494– 8503 DOI: 10.1021/jp212541y236https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XmtlCktLc%253D&md5=d7ba0f2efa1bedd47ed22c1962f5ab72AWSEM-MD: Protein Structure Prediction Using Coarse-Grained Physical Potentials and Bioinformatically Based Local Structure BiasingDavtyan, Aram; Schafer, Nicholas P.; Zheng, Weihua; Clementi, Cecilia; Wolynes, Peter G.; Papoian, Garegin A.Journal of Physical Chemistry B (2012), 116 (29), 8494-8503CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The associative memory, water mediated, structure and energy model (AWSEM) is a coarse-grained protein force field. AWSEM contains phys. motivated terms, such as hydrogen bonding, as well as a bioinformatically-based local structure biasing term, which efficiently takes into account many-body effects that are modulated by the local sequence. When combined with appropriate local or global alignments to choose memories, AWSEM can be used to perform de novo protein structure prediction. Herein we present structure prediction results for a particular choice of local sequence alignment method based on short residue sequences called fragments. We demonstrate the model's structure prediction capabilities for three levels of global homol. between the target sequence and those proteins used for local structure biasing, all of which assume that the structure of the target sequence is not known. When there are no homologues in the database of structures used for local structure biasing, AWSEM calcns. produce structural predictions that are somewhat improved compared with prior works using related approaches. The inclusion of a small no. of structures from homologous sequences improves structure prediction only marginally, but when the fragment search is restricted to only homologous sequences, AWSEM can perform high resoln. structure prediction and can be used for kinetics and dynamics studies.
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237Zheng, W.; Schafer, N. P.; Davtyan, A.; Papoian, G. A.; Wolynes, P. G. Predictive energy landscapes for protein-protein association Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 19244– 19249 DOI: 10.1073/pnas.1216215109237https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVagtrnI&md5=b81d0ab4a15468258d379e2820bc13a1Predictive energy landscapes for protein-protein associationZheng, Weihua; Schafer, Nicholas P.; Davtyan, Aram; Papoian, Garegin A.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (47), 19244-19249, S19244/1-S19244/3CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We investigate protein-protein assocn. using the associative-memory, water-mediated, structure, and energy model (AWSEM), a coarse-grained protein folding model that has been optimized using energy-landscape theory. The potential was originally parameterized by enforcing a funneled nature for a database of dimeric interfaces but was later further optimized to create funneled folding landscapes for individual monomeric proteins. The ability of the model to predict interfaces was not tested previously. The present results show that simulated annealing of the model indeed is able to predict successfully the native interfaces of eight homodimers and four heterodimers, thus amounting to a flexible docking algorithm. We go on to address the relative importance of monomer geometry, flexibility, and nonnative intermonomeric contacts in the assocn. process for the homodimers. Monomer surface geometry is found to be important in detg. the binding interface, but it is insufficient. Using a uniform binding potential rather than the water-mediated potential results in sampling of misbound structures that are geometrically preferred but are nonetheless energetically disfavored by AWSEM, as well as in nature. Depending on the stability of the unbound monomers, nonnative contacts play different roles in the assocn. process. For unstable monomers, thermodn. states stabilized by nonnative interactions correspond to productive, on-pathway intermediates and can, therefore, catalyze binding through a fly-casting mechanism. For stable monomers, in contrast, states stabilized by nonnative interactions generally correspond to traps that impede binding.
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238Zheng, W.; Schafer, N. P.; Wolynes, P. G. Frustration in the energy landscapes of multidomain protein misfolding Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 1680– 1685 DOI: 10.1073/pnas.1222130110238https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXislChsrc%253D&md5=885d2c562c11a63cc833d95b2702e9ffFrustration in the energy landscapes of multidomain protein misfoldingZheng, Weihua; Schafer, Nicholas P.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2013), 110 (5), 1680-1685, S1680/1-S1680/4CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Frustration from strong interdomain interactions can make misfolding a more severe problem in multidomain proteins than in single-domain proteins. On the basis of bioinformatic surveys, it has been suggested that lowering the sequence identity between neighboring domains is one of nature's solns. to the multidomain misfolding problem. We investigate folding of multidomain proteins using the associative-memory, water-mediated, structure and energy model (AWSEM), a predictive coarse-grained protein force field. We find that reducing sequence identity not only decreases the formation of domain-swapped contacts but also decreases the formation of strong self-recognition contacts between p-strands with high hydrophobic content. The ensembles of misfolded structures that result from forming these amyloid-like interactions are energetically disfavored compared with the native state, but entropically favored. Therefore, these ensembles are more stable than the native ensemble under denaturing conditions, such as high temp. Domain-swapped contacts compete with self-recognition contacts in forming various trapped states, and point mutations can shift the balance between the two types of interaction. We predict that multidomain proteins that lack these specific strong interdomain interactions should fold reliably.
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239Chen, M.; Zheng, W.; Wolynes, P. G. Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memory Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 5006 DOI: 10.1073/pnas.1602702113239https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xmt1ShtLg%253D&md5=6912630ec15eac17aa940c8ebbfa74a5Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memoryChen, Mingchen; Zheng, Weihua; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2016), 113 (18), 5006-5011CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Aplysia cytoplasmic polyadenylation element binding (CPEB) protein, a translational regulator that recruits mRNAs and facilitates translation, has been shown to be a key component in the formation of long-term memory. Exptl. data show that CPEB exists in at least a low-mol. wt. coiled-coil oligomeric form and an amyloid fiber form involving the Q-rich domain (CPEB-Q). Using a coarse-grained energy landscape model, we predict the structures of the low-mol. wt. oligomeric form and the dynamics of their transitions to the β-form. Up to the decamer, the oligomeric structures are predicted to be coiled coils. Free energy profiles confirm that the coiled coil is the most stable form for dimers and trimers. The structural transition from α to β is shown to be concn. dependent, with the transition barrier decreasing with increased concn. We observe that a mech. pulling force can facilitate the α-helix to β-sheet (α-to-β) transition by lowering the free energy barrier between the 2 forms. Interactome anal. of the CPEB protein suggests that its interactions with the cytoskeleton could provide the necessary mech. force. We propose that, by exerting mech. forces on CPEB oligomers, an active cytoskeleton can facilitate fiber formation. This mech. catalysis makes possible a pos. feedback loop that would help localize the formation of CPEB fibers to active synapse areas and mark those synapses for forming a long-term memory after the prion form is established. The functional role of the CPEB helical oligomers in this mechanism carries with it implications for targeting such species in neurodegenerative diseases.
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240Tsai, M. Y.; Zheng, W.; Balamurugan, D.; Schafer, N. P.; Kim, B. L.; Cheung, M. S.; Wolynes, P. G. Electrostatics, structure prediction, and the energy landscapes for protein folding and binding Protein Sci. 2016, 25, 255– 269 DOI: 10.1002/pro.2751240https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXht12mu7%252FK&md5=5ccb38d7e17eacec13d8cfc24169ca7fElectrostatics, structure prediction, and the energy landscapes for protein folding and bindingTsai, Min-Yeh; Zheng, Weihua; Balamurugan, D.; Schafer, Nicholas P.; Kim, Bobby L.; Cheung, Margaret S.; Wolynes, Peter G.Protein Science (2016), 25 (1), 255-269CODEN: PRCIEI; ISSN:1469-896X. (Wiley-Blackwell)While being long in range and therefore weakly specific, electrostatic interactions are able to modulate the stability and folding landscapes of some proteins. The relevance of electrostatic forces for steering the docking of proteins to each other is widely acknowledged, however, the role of electrostatics in establishing specifically funneled landscapes and their relevance for protein structure prediction are still not clear. By introducing Debye-Hueckel potentials that mimic long-range electrostatic forces into the Associative memory, Water mediated, Structure, and Energy Model (AWSEM), a transferable protein model capable of predicting tertiary structures, we assess the effects of electrostatics on the landscapes of thirteen monomeric proteins and four dimers. For the monomers, we find that adding electrostatic interactions does not improve structure prediction. Simulations of ribosomal protein S6 show, however, that folding stability depends monotonically on electrostatic strength. The trend in predicted melting temps. of the S6 variants agrees with exptl. observations. Electrostatic effects can play a range of roles in binding. The binding of the protein complex KIX-pKID is largely assisted by electrostatic interactions, which provide direct charge-charge stabilization of the native state and contribute to the funneling of the binding landscape. In contrast, for several other proteins, including the DNA-binding protein FIS, electrostatics causes frustration in the DNA-binding region, which favors its binding with DNA but not with its protein partner. This study highlights the importance of long-range electrostatics in functional responses to problems where proteins interact with their charged partners, such as DNA, RNA, as well as membranes.
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241Kim, B. L.; Schafer, N. P.; Wolynes, P. G. Predictive energy landscapes for folding alpha-helical transmembrane proteins Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 11031– 11036 DOI: 10.1073/pnas.1410529111There is no corresponding record for this reference.
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242Bereau, T.; Deserno, M. Generic coarse-grained model for protein folding and aggregation J. Chem. Phys. 2009, 130, 235106 DOI: 10.1063/1.3152842242https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnsFCktr8%253D&md5=f501aa4286a8b08d5070ac9b70670f30Generic coarse-grained model for protein folding and aggregationBereau, Tristan; Deserno, MarkusJournal of Chemical Physics (2009), 130 (23), 235106/1-235106/15CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)A generic coarse-grained (CG) protein model is presented. The intermediate level of resoln. (four beads per amino acid, implicit solvent) allows for accurate sampling of local conformations. It relies on simple interactions that emphasize structure, such as hydrogen bonds and hydrophobicity. Realistic α/β content is achieved by including an effective nearest-neighbor dipolar interaction. Parameters are tuned to reproduce both local conformations and tertiary structures. The thermodn. and kinetics of a three-helix bundle are studied. We check that the CG model is able to fold proteins with tertiary structures and amino acid sequences different from the one used for parameter tuning. By studying both helical and extended conformations, we make sure the force field is not biased toward any particular secondary structure. The accuracy involved in folding not only the test protein but also of other ones show strong evidence for amino acid cooperativity embedded in the model. Without any further adjustments or bias, a realistic oligopeptide aggregation scenario is obsd. (c) 2009 American Institute of Physics.
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243Bereau, T.; Bachmann, M.; Deserno, M. Interplay between secondary and tertiary structure formation in protein folding cooperativity J. Am. Chem. Soc. 2010, 132, 13129– 13131 DOI: 10.1021/ja105206w243https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFWru7zI&md5=3e9e4bda0651ac14195b49967a7698c6Interplay between Secondary and Tertiary Structure Formation in Protein Folding CooperativityBereau, Tristan; Bachmann, Michael; Deserno, MarkusJournal of the American Chemical Society (2010), 132 (38), 13129-13131CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Protein folding cooperativity is defined by the nature of the finite-size thermodn. transition exhibited upon folding: two-state transitions show a free-energy barrier between the folded and unfolded ensembles, while downhill folding is barrierless. A microcanonical anal., where the energy is the natural variable, has proved to be better suited than its canonical counterpart to unambiguously characterize the nature of the transition. Replica-exchange mol. dynamics simulations of a high-resoln. coarse-grained model allow for the accurate evaluation of the d. of states in order to ext. precise thermodn. information and measure its impact on structural features. The method has been applied to three helical peptides: a short helix shows sharp features of a two-state folder, while a longer helix and a three-helix bundle exhibit downhill and two-state transitions, resp. Extending the results of lattice simulations and theor. models, we have found that it is the interplay between secondary structure and the loss of non-native tertiary contacts that dets. the nature of the transition.
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244Arnold, A.; Lenz, O.; Kesselheim, S.; Weeber, R.; Fahrenberger, F.; Roehm, D.; Košovan, P.; Holm, C. In Meshfree Methods for Partial Differential Equations VI; Griebel, M.; Schweitzer, M. A., Eds.; Springer: Berlin, 2013; Vol. 89.There is no corresponding record for this reference.
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245Pronk, S.; Pall, S.; Schulz, R.; Larsson, P.; Bjelkmar, P.; Apostolov, R.; Shirts, M. R.; Smith, J. C.; Kasson, P. M.; van der Spoel, D. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit Bioinformatics 2013, 29, 845– 854 DOI: 10.1093/bioinformatics/btt055245https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXksFWmsrg%253D&md5=4b25fd6ab4e33725ae56b5da63f4ad68GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkitPronk, Sander; Pall, Szilard; Schulz, Roland; Larsson, Per; Bjelkmar, Paer; Apostolov, Rossen; Shirts, Michael R.; Smith, Jeremy C.; Kasson, Peter M.; van der Spoel, David; Hess, Berk; Lindahl, ErikBioinformatics (2013), 29 (7), 845-854CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: Mol. simulation has historically been a low-throughput technique, but faster computers and increasing amts. of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomols. with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomol. interaction and function in a manner directly testable by expt. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomols., such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these mols. built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.
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246Sterpone, F.; Melchionna, S.; Tuffery, P.; Pasquali, S.; Mousseau, N.; Cragnolini, T.; Chebaro, Y.; St-Pierre, J. F.; Kalimeri, M.; Barducci, A. The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems Chem. Soc. Rev. 2014, 43, 4871– 4893 DOI: 10.1039/c4cs00048jThere is no corresponding record for this reference.
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247Sterpone, F.; Derreumaux, P.; Melchionna, S. Protein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with Hydrodynamics J. Chem. Theory Comput. 2015, 11, 1843– 1853 DOI: 10.1021/ct501015h247https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkvVelsrw%253D&md5=88e635a720d6431800027baed091b35cProtein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with HydrodynamicsSterpone, Fabio; Derreumaux, Philippe; Melchionna, SimoneJournal of Chemical Theory and Computation (2015), 11 (4), 1843-1853CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A novel simulation framework that integrates the OPEP coarse-grained (CG) model for proteins with the Lattice Boltzmann (LB) methodol. to account for the fluid solvent at mesoscale level is presented. OPEP is a very efficient, water-free and electrostatic-free force field that reproduces at quasi-atomistic detail processes like peptide folding, structural rearrangements, and aggregation dynamics. The LB method is based on the kinetic description of the solvent to solve the fluid mechanics under a wide range of conditions, with the further advantage of being highly scalable on parallel architectures. The capabilities of the approach are presented, and the strategy is effective in exploring the role of hydrodynamics on protein relaxation and peptide aggregation. The end result is a strategy for modeling systems of thousands of proteins, such as in the case of dense protein suspensions. The future perspectives of the multiscale approach are also discussed.
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248Barducci, A.; Bonomi, M.; Derreumaux, P. Assessing the Quality of the OPEP Coarse-Grained Force Field J. Chem. Theory Comput. 2011, 7, 1928– 1934 DOI: 10.1021/ct100646f248https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmt1Gmu7o%253D&md5=caa588d09b7421d2b9d921cbbfb96d44Assessing the Quality of the OPEP Coarse-Grained Force FieldBarducci, Alessandro; Bonomi, Massimiliano; Derreumaux, PhilippeJournal of Chemical Theory and Computation (2011), 7 (6), 1928-1934CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A coarse-grained potential that could accurately describe the overall conformational landscape of proteins would be extremely valuable not only for structure prediction but also for studying protein dynamics, large conformational motions, and intrinsically disordered systems. Here, the authors assessed the quality of the OPEP coarse-grained potential by comparing the reconstructed free-energy surfaces (FESs) of two prototypical β-hairpin and α-helix peptides to all-atom calcns. in explicit solvent. The authors found remarkable agreement between the OPEP FES and those obtained using atomistic models, despite a general overstabilization of α- and β-structures by the coarse-grained potential. The use of advanced sampling techniques based on metadynamics and parallel tempering guaranteed a thorough exploration of the conformational space accessible to the two peptides studied.
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249Chebaro, Y.; Pasquali, S.; Derreumaux, P. The coarse-grained OPEP force field for non-amyloid and amyloid proteins J. Phys. Chem. B 2012, 116, 8741– 8752 DOI: 10.1021/jp301665f249https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xpt1Cht7c%253D&md5=43469f238822babca8176b8686845671The Coarse-Grained OPEP Force Field for Non-Amyloid and Amyloid ProteinsChebaro, Yassmine; Pasquali, Samuela; Derreumaux, PhilippeJournal of Physical Chemistry B (2012), 116 (30), 8741-8752CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Coarse-grained protein models with various levels of granularity and degrees of freedom offer the possibility to explore many phenomena including folding, assembly, and recognition in terms of dynamics and thermodn. that are inaccessible to all-atom representations in explicit aq. soln. Here, we present a refined version of the coarse-grained optimized potential for efficient protein structure prediction (OPEP) based on a six-bead representation. The OPEP version 4.0 parameter set, which uses a new anal. formulation for the nonbonded interactions and adds specific side-chain-side-chain interactions for α-helix, is subjected to three tests. First, we show that mol. dynamics simulations at 300 K preserve the exptl. rigid conformations of 17 proteins with 37-152 amino acids within a root-mean-square deviation (RMSD) of 3.1 Å after 30 ns. Extending the simulation time to 100 ns for five proteins does not change the RMSDs. Second, replica exchange mol. dynamics (REMD) simulations recover the NMR structures of three prototypical β-hairpin and α-helix peptides and the NMR three-stranded β-sheet topol. of a 37-residue WW domain, starting from randomly chosen states. Third, REMD simulations on the ccβ peptide show a temp. transition from a three-stranded coiled coil to amyloid-like aggregates consistent with expts., while simulations on low mol. wt. aggregates of the prion protein helix 1 do not. Overall, these studies indicate the effectiveness of our OPEP4 coarse-grained model for protein folding and aggregation, and report two future directions for improvement.
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250Chebaro, Y.; Dong, X.; Laghaei, R.; Derreumaux, P.; Mousseau, N. Replica exchange molecular dynamics simulations of coarse-grained proteins in implicit solvent J. Phys. Chem. B 2009, 113, 267– 274 DOI: 10.1021/jp805309eThere is no corresponding record for this reference.
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251Nasica-Labouze, J.; Nguyen, P. H.; Sterpone, F.; Berthoumieu, O.; Buchete, N. V.; Cote, S.; De Simone, A.; Doig, A. J.; Faller, P.; Garcia, A. Amyloid beta Protein and Alzheimer’s Disease: When Computer Simulations Complement Experimental Studies Chem. Rev. 2015, 115, 3518– 3563 DOI: 10.1021/cr500638n251https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXksl2hurs%253D&md5=fdd061847c9171aec5d4a4b9d871768dAmyloid β Protein and Alzheimer's Disease: When Computer Simulations Complement Experimental StudiesNasica-Labouze, Jessica; Nguyen, Phuong H.; Sterpone, Fabio; Berthoumieu, Olivia; Buchete, Nicolae-Viorel; Cote, Sebastien; De Simone, Alfonso; Doig, Andrew J.; Faller, Peter; Garcia, Angel; Laio, Alessandro; Mai, Suan Li; Melchionna, Simone; Mousseau, Normand; Mu, Yuguang; Paravastu, Anant; Pasquali, Samuela; Rosenman, David J.; Strodel, Birgit; Tarus, Bogdan; Viles, John H.; Zhang, Tong; Wang, Chunyu; Derreumaux, PhilippeChemical Reviews (Washington, DC, United States) (2015), 115 (9), 3518-3563CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review, discussing the contribution of biophys. and biochem. studies and computer simulations to characterize the mol. structures of Aβ1-40/1-42 monomers, oligomers, protofibrils, and amyloid fibrils in aq. soln.
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252Nasica-Labouze, J.; Meli, M.; Derreumaux, P.; Colombo, G.; Mousseau, N. A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion sup-35 PLoS Comput. Biol. 2011, 7, e1002051 DOI: 10.1371/journal.pcbi.1002051252https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXms1Knt7c%253D&md5=6b95b752d59bf8a758ebff2ffb660579A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion Sup-35Nasica-Labouze, Jessica; Meli, Massimiliano; Derreumaux, Philippe; Colombo, Giorgio; Mousseau, NormandPLoS Computational Biology (2011), 7 (5), e1002051CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)The self-organization of peptides into amyloidogenic oligomers is one of the key events for a wide range of mol. and degenerative diseases. Atomic-resoln. characterization of the mechanisms responsible for the aggregation process and the resulting structures is thus a necessary step to improve our understanding of the determinants of these pathologies. To address this issue, we combine the accelerated sampling properties of replica exchange mol. dynamics simulations based on the OPEP coarse-grained potential with the at. resoln. description of interactions provided by all-atom MD simulations, and investigate the oligomerization process of the GNNQQNY for three system sizes: 3-mers, 12-mers and 20-mers. Results for our integrated simulations show a rich variety of structural arrangements for aggregates of all sizes. Elongated fibril-like structures can form transiently in the 20-mer case, but they are not stable and easily interconvert in more globular and disordered forms. Our extensive characterization of the intermediate structures and their physico-chem. determinants points to a high degree of polymorphism for the GNNQQNY sequence that can be reflected at the macroscopic scale. Detailed mechanisms and structures that underlie amyloid aggregation are also provided.
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253Maupetit, J.; Derreumaux, P.; Tuffery, P. A fast method for large-scale de novo peptide and miniprotein structure prediction J. Comput. Chem. 2010, 31, 726– 738 DOI: 10.1002/jcc.21365253https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlentbk%253D&md5=1be85f82df7a0ce134cc65aad8aea313A fast method for large-scale De Novo peptide and miniprotein structure predictionMaupetit, Julien; Derreumaux, Philippe; Tuffery, PierreJournal of Computational Chemistry (2010), 31 (4), 726-738CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Although peptides have many biol. and biomedical implications, an accurate method predicting their equil. structural ensembles from amino acid sequences and suitable for large-scale expts. is still missing. The authors introduce a new approach - PEP-FOLD - to the de novo prediction of peptides and miniproteins. It first predicts, in the terms of a Hidden Markov Model-derived structural alphabet, a limited no. of local conformations at each position of the structure. It then performs their assembly using a greedy procedure driven by a coarse-grained energy score. On a benchmark of 52 peptides with 9-23 amino acids, PEP-FOLD generates lowest-energy conformations within 2.8 and 2.3 Å Cα root-mean-square deviation from the full NMR structures (NMR) and the NMR rigid cores, resp., outperforming previous approaches. For 13 miniproteins with 27-49 amino acids, PEP-FOLD reaches an accuracy of 3.6 and 4.6 Å Cα root-mean-square deviation for the most-native and lowest-energy conformations, using the nonflexible regions identified by NMR. PEP-FOLD simulations are fast - a few minutes only - opening therefore, the door to in silico large-scale rational design of new bioactive peptides and miniproteins. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010.
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254Maupetit, J.; Derreumaux, P.; Tuffery, P. PEP-FOLD: an online resource for de novo peptide structure prediction Nucleic Acids Res. 2009, 37, W498– 503 DOI: 10.1093/nar/gkp323254https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXosFSrsb0%253D&md5=4e6ba0b1daabcd8679203bf7cc7a542cPEP-FOLD: an online resource for de novo peptide structure predictionMaupetit, Julien; Derreumaux, Philippe; Tuffery, PierreNucleic Acids Research (2009), 37 (Web Server), W498-W503CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Rational peptide design and large-scale prediction of peptide structure from sequence remain a challenge for chem. biologists. The authors present PEP-FOLD, an online service, aimed at de novo modeling of 3D conformations for peptides between 9 and 25 amino acids in aq. soln. Using a hidden Markov model-derived structural alphabet (SA) of 27 four-residue letters, PEP-FOLD first predicts the SA letter profiles from the amino acid sequence and then assembles the predicted fragments by a greedy procedure driven by a modified version of the OPEP coarse-grained force field. Starting from an amino acid sequence, PEP-FOLD performs series of 50 simulations and returns the most representative conformations identified in terms of energy and population. Using a benchmark of 25 peptides with 9-23 amino acids, and considering the reproducibility of the runs, the authors find that, on av., PEP-FOLD locates lowest energy conformations differing by 2.6 Å Cα root mean square deviation from the full NMR structures. PEP-FOLD can be accessed at http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.
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255Pasi, M.; Lavery, R.; Ceres, N. PaLaCe: A Coarse-Grain Protein Model for Studying Mechanical Properties J. Chem. Theory Comput. 2013, 9, 785– 793 DOI: 10.1021/ct3007925255https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1GisbrI&md5=b724c1138b60543dd3c79a864bedbdbdPaLaCe: A Coarse-Grain Protein Model for Studying Mechanical PropertiesPasi, Marco; Lavery, Richard; Ceres, NicolettaJournal of Chemical Theory and Computation (2013), 9 (1), 785-793CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present a coarse-grain protein model PaLaCe (Pasi-Lavery-Ceres) that has been developed principally to allow fast computational studies of protein mechanics and to clarify the links between mechanics and function. PaLaCe uses a two-tier protein representation with one to three pseudoatoms representing each amino acid for the main nonbonded interactions, combined with at.-scale peptide groups and some side chain atoms to allow the explicit representation of backbone hydrogen bonds and to simplify the treatment of bonded interactions. The PaLaCe force field is composed of physics-based terms, parametrized using Boltzmann inversion of conformational probability distributions derived from a protein structure data set, and iteratively refined to reproduce the exptl. distributions. PaLaCe has been implemented in the MMTK simulation package and can be used for energy minimization, normal mode calcns., and mol. or stochastic dynamics. We present simulations with PaLaCe that test its ability to maintain stable structures for folded proteins, reproduce their dynamic fluctuations, and correctly model large-scale, force-induced conformational changes.
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256Frezza, E.; Lavery, R. Internal Normal Mode Analysis (iNMA) Applied to Protein Conformational Flexibility J. Chem. Theory Comput. 2015, 11, 5503– 5512 DOI: 10.1021/acs.jctc.5b00724256https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsFyrur3K&md5=f83807a88396dcbd824b5b55ade713e1Internal Normal Mode Analysis (iNMA) Applied to Protein Conformational FlexibilityFrezza, Elisa; Lavery, RichardJournal of Chemical Theory and Computation (2015), 11 (11), 5503-5512CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We analyze the capacity of normal modes to predict obsd. protein conformational changes, and, notably, those induced by the formation of protein-protein complexes. We show that normal modes calcd. in internal coordinate space (ICS) provide better predictions. For a large test set, using the ICS approach describes the conformational changes more completely, and with fewer low-frequency modes than the equiv. Cartesian coordinate modes, despite the fact that the internal coordinate calcns. were restricted to torsional angles. This can be attributed to the fact that the use of ICS extends the range over which movements along the corresponding eigenvectors remain close to the true conformational energy hypersurface. We also show that the PaLaCe coarse-grain protein model performs better than a simple elastic network model. We apply ICS normal-mode anal. to protein complexes and, by extending the approach of Sunada and G‾o. We show that we can couple an accurate view of the Cartesian coordinate movements induced by ICS modes with the detection of the key residues responsible for the movements.
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257Hinsen, K. The molecular modeling toolkit: A new approach to molecular simulations J. Comput. Chem. 2000, 21, 79– 85 DOI: 10.1002/(SICI)1096-987X(20000130)21:2<79::AID-JCC1>3.0.CO;2-B257https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXkt1Shuw%253D%253D&md5=dde47349669bdfcc5ce5c83ce04cf5e0The molecular modeling toolkit: A new approach to molecular simulationsHinsen, KonradJournal of Computational Chemistry (2000), 21 (2), 79-85CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)The Mol. Modeling Toolkit is a library that implements common mol. simulation techniques, with an emphasis on biomol. simulations. It uses modern software engineering techniques (object-oriented design, a high-level language) to overcome limitations assocd. with the large monolithic simulation programs that are commonly used for biomols. Its principal advantages are (1) easy extension and combination with other libraries due to modular library design; (2) a single high-level general-purpose programming language (Python) is used for library implementation as well as for application scripts; (3) use of documented and machine-independent formats for all data files; and (4) interfaces to other simulation and visualization programs.
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258Feig, M.; Karanicolas, J.; Brooks, C. L., 3rd MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology J. Mol. Graphics Modell. 2004, 22, 377– 395 DOI: 10.1016/j.jmgm.2003.12.005258https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXjt1Shur4%253D&md5=071e0c32c3114c5e57239d5f800c8e34MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biologyFeig, Michael; Karanicolas, John; Brooks, Charles L.Journal of Molecular Graphics & Modelling (2004), 22 (5), 377-395CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)We describe the Multiscale Modeling Tools for Structural Biol. (MMTSB) Tool Set (http://mmtsb.scripps.edu/software/mmtsbToolSet.html), which is a novel set of utilities and programming libraries that provide new enhanced sampling and multiscale modeling techniques for the simulation of proteins and nucleic acids. The tool set interfaces with the existing mol. modeling packages CHARMM and Amber for classical all-atom simulations, and with MONSSTER for lattice-based low-resoln. conformational sampling. In addn., it adds new functionality for the integration and translation between both levels of detail. The replica exchange method is implemented to allow enhanced sampling of both the all-atom and low-resoln. models. The tool set aims at applications in structural biol. that involve protein or nucleic acid structure prediction, refinement, and/or extended conformational sampling. With structure prediction applications in mind, the tool set also implements a facility that allows the control and application of modeling tasks on a large set of conformations in what we have termed ensemble computing. Ensemble computing encompasses loosely coupled, parallel computation on high-end parallel computers, clustered computational grids and desktop grid environments. This paper describes the design and implementation of the MMTSB Tool Set and illustrates its utility with three typical examples-scoring of a set of predicted protein conformations in order to identify the most native-like structures, ab initio folding of peptides in implicit solvent with the replica exchange method, and the prediction of a missing fragment in a larger protein structure.
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259Fleishman, S. J.; Corn, J. E.; Strauch, E. M.; Whitehead, T. A.; Andre, I.; Thompson, J.; Havranek, J. J.; Das, R.; Bradley, P.; Baker, D. Rosetta in CAPRI rounds 13–19 Proteins: Struct., Funct., Genet. 2010, 78, 3212– 3218 DOI: 10.1002/prot.22784There is no corresponding record for this reference.
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260Davis, I. W.; Baker, D. RosettaLigand docking with full ligand and receptor flexibility J. Mol. Biol. 2009, 385, 381– 392 DOI: 10.1016/j.jmb.2008.11.010260https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkt1WhsQ%253D%253D&md5=c8ff49fe105488dce94e1190346d0bb7RL Docking with Full Ligand and Receptor FlexibilityDavis, Ian W.; Baker, DavidJournal of Molecular Biology (2009), 385 (2), 381-392CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Summary: Computational docking of small-mol. ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently obsd. between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small mol. docking programs. We previously described the program RL, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RL that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the av. RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 Å RMSD for 64% (54/85) of cases overall.
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261Weitzner, B. D.; Kuroda, D.; Marze, N.; Xu, J.; Gray, J. J. Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization Proteins: Struct., Funct., Genet. 2014, 82, 1611– 1623 DOI: 10.1002/prot.24534There is no corresponding record for this reference.
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262DiMaio, F.; Echols, N.; Headd, J. J.; Terwilliger, T. C.; Adams, P. D.; Baker, D. Improved low-resolution crystallographic refinement with Phenix and Rosetta Nat. Methods 2013, 10, 1102– 1104 DOI: 10.1038/nmeth.2648262https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2c%252FitVynsA%253D%253D&md5=57a182ff1bb5970358d27fc6bcb1e559Improved low-resolution crystallographic refinement with Phenix and RosettaDiMaio Frank; Echols Nathaniel; Headd Jeffrey J; Terwilliger Thomas C; Adams Paul D; Baker DavidNature methods (2013), 10 (11), 1102-4 ISSN:.Refinement of macromolecular structures against low-resolution crystallographic data is limited by the ability of current methods to converge on a structure with realistic geometry. We developed a low-resolution crystallographic refinement method that combines the Rosetta sampling methodology and energy function with reciprocal-space X-ray refinement in Phenix. On a set of difficult low-resolution cases, the method yielded improved model geometry and lower free R factors than alternate refinement methods.
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263Mao, B. C.; Tejero, R.; Baker, D.; Montelione, G. T. Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures J. Am. Chem. Soc. 2014, 136, 1893– 1906 DOI: 10.1021/ja409845wThere is no corresponding record for this reference.
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264London, N.; Raveh, B.; Cohen, E.; Fathi, G.; Schueler-Furman, O. Rosetta FlexPepDock web server--high resolution modeling of peptide-protein interactions Nucleic Acids Res. 2011, 39, W249– 253 DOI: 10.1093/nar/gkr431264https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXosVOnt7o%253D&md5=c717db75b60ad3830be39c42c90b5f0aRosetta FlexPepDock web server-high resolution modeling of peptide-protein interactionsLondon, Nir; Raveh, Barak; Cohen, Eyal; Fathi, Guy; Schueler-Furman, OraNucleic Acids Research (2011), 39 (Web Server), W249-W253CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)Peptide-protein interactions are among the most prevalent and important interactions in the cell, but a large fraction of those interactions lack detailed structural characterization. The Rosetta FlexPepDock web server (http://flexpepdock.furmanlab.cs.huji.ac.il/) provides an interface to a high-resoln. peptide docking (refinement) protocol for the modeling of peptide-protein complexes, implemented within the Rosetta framework. Given a protein receptor structure and an approx., possibly inaccurate model of the peptide within the receptor binding site, the FlexPepDock server refines the peptide to high resoln., allowing full flexibility to the peptide backbone and to all side chains. This protocol was extensively tested and benchmarked on a wide array of non-redundant peptide-protein complexes, and was proven effective when applied to peptide starting conformations within 5.5 Å backbone root mean square deviation from the native conformation. FlexPepDock has been applied to several systems that are mediated and regulated by peptide-protein interactions. This easy to use and general web server interface allows non-expert users to accurately model their specific peptide-protein interaction of interest.
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265Liu, T.; Pan, X.; Chao, L.; Tan, W.; Qu, S.; Yang, L.; Wang, B.; Mei, H. Subangstrom accuracy in pHLA-I modeling by Rosetta FlexPepDock refinement protocol J. Chem. Inf. Model. 2014, 54, 2233– 2242 DOI: 10.1021/ci500393h265https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFylurjM&md5=fac070347e6405c9494b386f43f3646aSubangstrom Accuracy in pHLA-I Modeling by Rosetta FlexPepDock Refinement ProtocolLiu, Tengfei; Pan, Xianchao; Chao, Li; Tan, Wen; Qu, Sujun; Yang, Li; Wang, Bochu; Mei, HuJournal of Chemical Information and Modeling (2014), 54 (8), 2233-2242CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)Flexible peptides binding to human leukocyte antigen (HLA) play a key role in mediating human immune responses and are also involved in idiosyncratic adverse drug reactions according to recent research. However, the structural detns. of pHLA complexes remain challenging under the present conditions. In this paper, the performance of a new peptide docking method, namely FlexPepDock, was systematically investigated by a benchmark of 30 crystd. structures of peptide-HLA class I complexes. The docking results showed that the near-native pHLA-I models with peptide bb-RMSD less than 2 Å were ranked in the top 1 model for 100% (70/70) docking cases, and the subangstrom models with peptide bb-RMSD less than 1 Å were ranked in the top 5 lowest-energy models for 65.7% (46/70) docking cases. Furthermore, 10 out of 70 docking cases ranked the subangstrom all-atom models in the top 5 lowest-energy models. The results showed that the FlexPepDock can generate high-quality models of pHLA-I complexes and can be widely applied to pHLA-I modeling and mechanism research of peptide-mediated immune responses.
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266Thyme, S.; Baker, D. Redesigning the specificity of protein-DNA interactions with Rosetta Methods Mol. Biol. 2014, 1123, 265– 282 DOI: 10.1007/978-1-62703-968-0_17266https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cvjsFCqsg%253D%253D&md5=a900d735c00fe5b35bd24d12e876fbd5Redesigning the specificity of protein-DNA interactions with RosettaThyme Summer; Baker DavidMethods in molecular biology (Clifton, N.J.) (2014), 1123 (), 265-82 ISSN:.Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.
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267Lyskov, S.; Chou, F. C.; Conchuir, S. O.; Der, B. S.; Drew, K.; Kuroda, D.; Xu, J.; Weitzner, B. D.; Renfrew, P. D.; Sripakdeevong, P. Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE) PLoS One 2013, 8, e63906 DOI: 10.1371/journal.pone.0063906There is no corresponding record for this reference.
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268Basdevant, N.; Borgis, D.; Ha-Duong, T. Modeling Protein-Protein Recognition in Solution Using the Coarse-Grained Force Field SCORPION J. Chem. Theory Comput. 2013, 9, 803– 813 DOI: 10.1021/ct300943w268https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVSqtLjM&md5=8ccba3c59293c790a036e89ce29598efModeling Protein-Protein Recognition in Solution Using the Coarse-Grained Force Field SCORPIONBasdevant, Nathalie; Borgis, Daniel; Ha-Duong, TapJournal of Chemical Theory and Computation (2013), 9 (1), 803-813CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present here the SCORPION-Solvated COaRse-grained Protein interactION-force field, a physics-based simplified coarse-grained (CG) force field. It combines our previous CG protein model and a novel particle-based water model which makes it suitable for mol. dynamics (MD) simulations of protein assocn. processes. The protein model in SCORPION represents each amino acid with one to three beads, for which electrostatic and van der Waals effective interactions are fitted sep. to reproduce those of the all-atom AMBER force field. The protein internal flexibility is accounted for by an elastic network model (ENM). We now include in SCORPION a new Polarizable Coarse-Grained Solvent (PCGS) model, which is computationally efficient, consistent with the protein CG representation, and yields accurate electrostatic free energies of proteins. SCORPION is used here for the first time to perform hundreds-of-nanoseconds-long MD simulations of protein/protein recognition in water, here the case of the barnase/barstar complex. These MD simulations showed that, for five of a total of seven simulations starting from several initial conformations, and after a time going from 1 to 500 ns, the proteins bind in a conformation very close to the native bound structure and remain stable in this conformation for the rest of the simulation. An energetic anal. of these MD show that this recognition is driven both by van der Waals and electrostatic interactions between proteins. SCORPION appears therefore as a useful tool to study protein-protein recognition in a solvated environment.
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269Liwo, A.; Khalili, M.; Scheraga, H. A. Ab initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chains Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 2362– 2367 DOI: 10.1073/pnas.0408885102269https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhvFKit70%253D&md5=ca40abacca7b7226c7ce9aad8e186c5cAb initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chainsLiwo, Adam; Khalili, Mey; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2005), 102 (7), 2362-2367CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We report the application of Langevin dynamics to the physics-based united-residue (UNRES) force field developed in our lab. Ten trajectories were run on seven proteins [PDB ID codes 1BDD (α; 46 residues), 1GAB (α; 47 residues), 1LQ7 (α; 67 residues), 1CLB (α; 75 residues), 1E0L (β; 28 residues), and 1E0G (α+β; 48 residues), and 1IGD (α+β; 61 residues)] with the UNRES force field parameterized by using our recently developed method for obtaining a hierarchical structure of the energy landscape. All α-helical proteins and 1E0G folded to the native-like structures, whereas 1IGD and 1E0L yielded mostly nonnative α-helical folds although the native-like structures are lowest in energy for these two proteins, which can be attributed to neglecting the entropy factor in the current parameterization of UNRES. Av. folding times for successful folding simulations were of the order of nanoseconds, whereas even the ultrafast-folding proteins fold only in microseconds, which implies that the UNRES time scale is approx. three orders of magnitude larger than the exptl. time scale because the fast motions of the secondary degrees of freedom are averaged out. Folding with Langevin dynamics required 2-10 h of CPU time on av. with a single AMD Athlon MP 2800+ processor depending on the size of the protein. With the advantage of parallel processing, this process leads to the possibility to explore thousands of folding pathways and to predict not only the native structure but also the folding scenario of a protein together with its quant. kinetic and thermodn. characteristics.
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270Zhou, R.; Maisuradze, G. G.; Sunol, D.; Todorovski, T.; Macias, M. J.; Xiao, Y.; Scheraga, H. A.; Czaplewski, C.; Liwo, A. Folding kinetics of WW domains with the united residue force field for bridging microscopic motions and experimental measurements Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 18243– 18248 DOI: 10.1073/pnas.1420914111270https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVClu7bK&md5=9e7742558ba4d961885696b8099ad460Folding kinetics of WW domains with the united residue force field for bridging microscopic motions and experimental measurementsZhou, Rui; Maisuradze, Gia G.; Sunol, David; Todorovski, Toni; Macias, Maria J.; Xiao, Yi; Scheraga, Harold A.; Czaplewski, Cezary; Liwo, AdamProceedings of the National Academy of Sciences of the United States of America (2014), 111 (51), 18243-18248CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)To demonstrate the utility of the coarse-grained united-residue (UNRES) force field to compare exptl. and computed kinetic data for folding proteins, the authors performed long-time millisecond-timescale canonical Langevin mol. dynamics simulations of the triple β-strand from the formin-binding protein 28 (FBP28) WW domain and 6 nonnatural variants, using UNRES. The results were compared with available exptl. data in both a qual. and a quant. manner. Complexities of the folding pathways, which could not be detd. exptl., were revealed. The folding mechanisms obtained from the simulated folding kinetics were in agreement with the exptl. results, with a few discrepancies for which the authors accounted. The origins of single- and double-exponential kinetics and their correlations with 2- and 3-state folding scenarios were shown to be related to the relative barrier heights between the various states. The rate consts. obtained from time profiles of the fractions of the native, intermediate, and unfolded structures, and the kinetic equations fitted to them, correlated with the exptl. values; however, they were about 3 orders of magnitude larger than the exptl. ones for most of the systems. These differences were in agreement with the timescale extension derived by scaling down the friction of water and averaging out the fast degrees of freedom when passing from all-atom to a coarse-grained representation. These results indicate that the UNRES force field can provide accurate predictions of folding kinetics of these WW domains, often used as models for the study of the mechanisms of protein folding.
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271Maisuradze, G. G.; Senet, P.; Czaplewski, C.; Liwo, A.; Scheraga, H. A. Investigation of protein folding by coarse-grained molecular dynamics with the UNRES force field J. Phys. Chem. A 2010, 114, 4471– 4485 DOI: 10.1021/jp9117776271https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXitFaqu7c%253D&md5=5e091a0f996c23e80f3b3f4627a1a2b6Investigation of Protein Folding by Coarse-Grained Molecular Dynamics with the UNRES Force FieldMaisuradze, Gia G.; Senet, Patrick; Czaplewski, Cezary; Liwo, Adam; Scheraga, Harold A.Journal of Physical Chemistry A (2010), 114 (13), 4471-4485CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)Coarse-grained mol. dynamics (MD) simulations offer a dramatic extension of the time-scale of simulations compared to all-atom approaches. In this article, we describe the use of the physics-based united-residue (UNRES) force field, developed in our lab., in protein-structure simulations. We demonstrate that this force field offers about a 4000-times extension of the simulation time scale; this feature arises both from averaging out the fast-moving degrees of freedom and redn. of the cost of energy and force calcns. compared to all-atom approaches with explicit solvent. With massively parallel computers, microsecond folding simulation times of proteins contg. about 1000 residues can be obtained in days. A straightforward application of canonical UNRES/MD simulations, demonstrated with the example of the N-terminal part of the B-domain of staphylococcal protein A (PDB code: 1BDD, a three-α-helix bundle), discerns the folding mechanism and dets. kinetic parameters by parallel simulations of several hundred or more trajectories. Use of generalized-ensemble techniques, of which the multiplexed replica exchange method proved to be the most effective, enables us to compute thermodn. of folding and carry out fully physics-based prediction of protein structure, in which the predicted structure is detd. as a mean over the most populated ensemble below the folding-transition temp. By using principal component anal. of the UNRES folding trajectories of the formin-binding protein (FBP) WW domain (PDB code: 1E0L; a three-stranded antiparallel β-sheet) and 1BDD, we identified representative structures along the folding pathways and demonstrated that only a few (low-indexed) principal components can capture the main structural features of a protein-folding trajectory; the potentials of mean force calcd. along these essential modes exhibit multiple min., as opposed to those along the remaining modes that are unimodal. In addn., a comparison between the structures that are representative of the min. in the free-energy profile along the essential collective coordinates of protein folding (computed by principal component anal.) and the free-energy profile projected along the virtual-bond dihedral angles γ of the backbone revealed the key residues involved in the transitions between the different basins of the folding free-energy profile, in agreement with existing exptl. data for 1E0L.
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272Kachlishvili, K.; Maisuradze, G. G.; Martin, O. A.; Liwo, A.; Vila, J. A.; Scheraga, H. A. Accounting for a mirror-image conformation as a subtle effect in protein folding Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 8458– 8463 DOI: 10.1073/pnas.1407837111272https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXos1aqu70%253D&md5=903aa26bdac4da7f0b1f3c377b2bdd47Accounting for a mirror-image conformation as a subtle effect in protein foldingKachlishvili, Khatuna; Maisuradze, Gia G.; Martin, Osvaldo A.; Liwo, Adam; Vila, Jorge A.; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2014), 111 (23), 8458-8463CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)By using local (free-energy profiles along the amino acid sequence and 13Cα chem. shifts) and global (principal component) analyses to examine the mol. dynamics of protein-folding trajectories, generated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein A, we are able to (i) provide the main reason for formation of the mirror-image conformation of this protein, namely, a slow formation of the second loop and part of the third helix (Asp29-Asn35), caused by the presence of multiple local conformational states in this portion of the protein; (ii) show that formation of the mirror-image topol. is a subtle effect resulting from local interactions; (iii) provide a mechanism for how protein A overcomes the barrier between the metastable mirror-image state and the native state; and (iv) offer a plausible reason to explain why protein A does not remain in the metastable mirror-image state even though the mirror-image and native conformations are at least energetically compatible.
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273He, Y.; Mozolewska, M. A.; Krupa, P.; Sieradzan, A. K.; Wirecki, T. K.; Liwo, A.; Kachlishvili, K.; Rackovsky, S.; Jagiela, D.; Slusarz, R. Lessons from application of the UNRES force field to predictions of structures of CASP10 targets Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 14936– 14941 DOI: 10.1073/pnas.1313316110273https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFWrsrvO&md5=99e8f593f1e989338148ff13fda82c3cLessons from application of the UNRES force field to predictions of structures of CASP10 targetsHe, Yi; Mozolewska, Magdalena A.; Krupa, Pawel; Sieradzan, Adam K.; Wirecki, Tomasz K.; Liwo, Adam; Kachlishvili, Khatuna; Rackovsky, Shalom; Jagiela, Dawid; Slusarz, Rafal; Czaplewski, Cezary R.; Oldziej, Stanislaw; Scheraga, Harold A.Proceedings of the National Academy of Sciences of the United States of America (2013), 110 (37), 14936-14941,S14936/1-S14936/2CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our lab. for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families detd. by multiplexed replica-exchange simulations, from the 10th Community Wide Expt. on the Crit. Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two α + β domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the exptl. structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain-domain orientations, which is a significant advance in the state of the art.
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274Krupa, P.; Sieradzan, A. K.; Rackovsky, S.; Baranowski, M.; Oldziej, S.; Scheraga, H. A.; Liwo, A.; Czaplewski, C. Improvement of the treatment of loop structures in the UNRES force field by inclusion of coupling between backbone- and side-chain-local conformational states. J. Chem. Theory Comput. 2013, 9, 4620 DOI: 10.1021/ct4004977274https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhtlyjsrvO&md5=d6088df53b20d96e37e583d85d4fec76Improvement of the Treatment of Loop Structures in the UNRES Force Field by Inclusion of Coupling between Backbone- and Side-Chain-Local Conformational StatesKrupa, Pawel; Sieradzan, Adam K.; Rackovsky, S.; Baranowski, Maciej; Oldziej, Stanislaw; Scheraga, Harold A.; Liwo, Adam; Czaplewski, CezaryJournal of Chemical Theory and Computation (2013), 9 (10), 4620-4632CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The UNited RESidue (UNRES) coarse-grained model of polypeptide chains, developed in the authors' lab., enables the authors to carry out millisecond-scale mol.-dynamics simulations of large proteins effectively. It performs well in ab initio predictions of protein structure, as demonstrated in the last Community Wide Expt. on the Crit. Assessment of Techniques for Protein Structure Prediction (CASP10). However, the resoln. of the simulated structure is too coarse, esp. in loop regions, which results from insufficient specificity of the model of local interactions. To improve the representation of local interactions, the authors introduced new side-chain-backbone correlation potentials, derived from a statistical anal. of loop regions of 4585 proteins. To obtain sufficient statistics, the authors reduced the set of amino-acid-residue types to five groups, derived in the authors' earlier work on structurally optimized reduced alphabets, based on a statistical anal. of the properties of amino-acid structures. The new correlation potentials are expressed as one-dimensional Fourier series in the virtual-bond-dihedral angles involving side-chain centroids. The wt. of these new terms was detd. by a trial-and-error method, in which Multiplexed Replica Exchange Mol. Dynamics (MREMD) simulations were run on selected test proteins. The best av. root-mean-square deviations (RMSDs) of the calcd. structures from the exptl. structures below the folding-transition temps. were obtained with the wt. of the new side-chain-backbone correlation potentials equal to 0.57. The resulting conformational ensembles were analyzed in detail by using the Weighted Histogram Anal. Method (WHAM) and Ward's min.-variance clustering. This anal. showed that the RMSDs from the exptl. structures dropped by 0.5 Å on av., compared to simulations without the new terms, and the deviation of individual residues in the loop region of the computed structures from their counterparts in the exptl. structures (after optimum superposition of the calcd. and exptl. structure) decreased by up to 8 Å. Consequently, the new terms improve the representation of local structure.
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275Sieradzan, A. K.; Liwo, A.; Hansmann, U. H. Folding and self-assembly of a small protein complex J. Chem. Theory Comput. 2012, 8, 3416– 3422 DOI: 10.1021/ct300528r275https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1eksLjL&md5=93bc6e1c0bd60cfa649ad06111a02bb3Folding and self-assembly of a small protein complexSieradzan, Adam K.; Liwo, Adam; Hansmann, Ulrich H. E.Journal of Chemical Theory and Computation (2012), 8 (9), 3416-3422CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The synthetic homotetrameric ββα (BBAT1) protein possesses a stable quaternary structure with a ββα fold. Because of its small size (a total of 84 residues), the homotetramer is an excellent model system with which to study self-assembly and protein-protein interactions. The authors found from replica-exchange mol. dynamics simulations with the coarse-grain UNRES force field that the folding and assocn. pathway consisted of 3 well-sepd. steps, where assocn. to a tetramer preceded and facilitated the folding of the 4 chains. At room temp., the tetramer exists in an ensemble of diverse structures. The crystal structure became energetically favored only when the mol. was in a dense and crystal-like environment. The obsd. picture of folding promoted by assocn. may mirror the mechanism according to which intrinsically unfolded proteins assume their functional structures.
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276Rojas, A.; Liwo, A.; Browne, D.; Scheraga, H. A. Mechanism of fiber assembly: treatment of Abeta peptide aggregation with a coarse-grained united-residue force field J. Mol. Biol. 2010, 404, 537– 552 DOI: 10.1016/j.jmb.2010.09.057276https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVaisLzJ&md5=19246393bf0c0db34b22115bd9300d2bMechanism of Fiber Assembly: Treatment of Aβ Peptide Aggregation with a Coarse-Grained United-Residue Force FieldRojas, Ana; Liwo, Adam; Browne, Dana; Scheraga, Harold A.Journal of Molecular Biology (2010), 404 (3), 537-552CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The growth mechanism of β-amyloid (Aβ) peptide fibrils was studied by a physics-based coarse-grained united-residue model and mol. dynamics (MD) simulations. To identify the mechanism of monomer addn. to an Aβ1-40 fibril, we placed an unstructured monomer at a distance of 20 Å from a fibril template and allowed it to interact freely with the latter. The monomer was not biased towards fibril conformation by either the force field or the MD algorithm. With the use of a coarse-grained model with replica-exchange mol. dynamics, a longer timescale was accessible, making it possible to observe how the monomers probe different binding modes during their search for the fibril conformation. Although different assembly pathways were seen, they all follow a dock-lock mechanism with two distinct locking stages, consistent with exptl. data on fibril elongation. Whereas these expts. have not been able to characterize the conformations populating the different stages, we have been able to describe these different stages explicitly by following free monomers as they dock onto a fibril template and to adopt the fibril conformation (i.e., we describe fibril elongation step by step at the mol. level). During the first stage of the assembly ("docking"), the monomer tries different conformations. After docking, the monomer is locked into the fibril through two different locking stages. In the first stage, the monomer forms hydrogen bonds with the fibril template along one of the strands in a two-stranded β-hairpin; in the second stage, hydrogen bonds are formed along the second strand, locking the monomer into the fibril structure. The data reveal a free-energy barrier sepg. the two locking stages. The importance of hydrophobic interactions and hydrogen bonds in the stability of the Aβ fibril structure was examd. by carrying out addnl. canonical MD simulations of oligomers with different nos. of chains (4-16 chains), with the fibril structure as the initial conformation. The data confirm that the structures are stabilized largely by hydrophobic interactions and show that intermol. hydrogen bonds are highly stable and contribute to the stability of the oligomers as well.
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277Golas, E.; Maisuradze, G. G.; Senet, P.; Oldziej, S.; Czaplewski, C.; Scheraga, H. A.; Liwo, A. Simulation of the opening and closing of Hsp70 chaperones by coarse-grained molecular dynamics J. Chem. Theory Comput. 2012, 8, 1750– 1764 DOI: 10.1021/ct200680g277https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XjvFKks70%253D&md5=572811dcb87cc1d846be10e018e50a69Simulation of the Opening and Closing of Hsp70 Chaperones by Coarse-Grained Molecular DynamicsGolas, Ewa; Maisuradze, Gia G.; Senet, Patrick; Oldziej, Stanislaw; Czaplewski, Cezary; Scheraga, Harold A.; Liwo, AdamJournal of Chemical Theory and Computation (2012), 8 (5), 1750-1764CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Heat-shock proteins 70 (Hsp70s) are key mol. chaperones, which assist in the folding and refolding/disaggregation of proteins. Hsp70s, which consist of a nucleotide-binding domain (NBD, consisting of NBD-I and NBD-II subdomains) and a substrate-binding domain [SBD, further split into the β-sheet (SBD-β) and α-helical (SBD-α) subdomains], occur in two major conformations having (a) a closed SBD, in which the SBD and NBD domains do not interact, and (b) an open SBD, in which SBD-α interacts with NBD-I and SBD-β interacts with the top parts of NBD-I and NBD-II. In the SBD-closed conformation, SBD is bound to a substrate protein, with release occurring after transition to the open conformation. While the transition from the closed to the open conformation is triggered efficiently by binding of ATP to the NBD, it also occurs, although less frequently, in the absence of ATP. The reverse transition occurs after ATP hydrolysis. Here, we report canonical and multiplexed replica exchange simulations of the conformational dynamics of Hsp70s using a coarse-grained mol. dynamics approach with the UNRES force field. The simulations were run in the following three modes: (i) with the two halves of the NBD unrestrained relative to each other, (ii) with the two halves of the NBD restrained in an open geometry as in the SBD-closed form of DnaK (2KHO), and (iii) with the two halves of NBD restrained in a closed geometry as in known exptl. structures of ATP-bound NBD forms of Hsp70. Open conformations, in which the SBD interacted strongly with the NBD, formed spontaneously during all simulations; the no. of transitions was largest in simulations carried out with the closed NBD domain, and smallest in those carried out with the open NBD domain; this observation is in agreement with the exptl. obsd. influence of ATP-binding on the transition of Hsp70s from the SBD-closed to the SBD-open form. Two kinds of open conformations were obsd.: one in which SBD-α interacts with NBD-I and SBD-β interacts with the top parts of NBD-I and NBD-II (as obsd. in the structures of nucleotide exchange factors), and another one in which this interaction pattern is swapped. A third type of motion, in which SBD-α binds to NBD without dissocg. from SBD-β, was also obsd. It was found that the first stage of interdomain communication (approach of SBD-β, to NBD) is coupled with the rotation of the long axes of NBD-I and NBD-II toward each other. To the best of our knowledge, this is the first successful simulation of the full transition of an Hsp70 from the SBD-closed to the SBD-open conformation.
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278Boras, B. W.; Hirakis, S. P.; Votapka, L. W.; Malmstrom, R. D.; Amaro, R. E.; McCulloch, A. D. Bridging scales through multiscale modeling: a case study on protein kinase A Front. Physiol. 2015, 6, 250 DOI: 10.3389/fphys.2015.00250278https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC283ps1SmsQ%253D%253D&md5=42aff952a7e93e735382e39c1b39988bBridging scales through multiscale modeling: a case study on protein kinase ABoras Britton W; Hirakis Sophia P; Votapka Lane W; Malmstrom Robert D; Amaro Rommie E; McCulloch Andrew DFrontiers in physiology (2015), 6 (), 250 ISSN:.The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.
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279Ackerman, D. G.; Feigenson, G. W. Multiscale modeling of four-component lipid mixtures: domain composition, size, alignment, and properties of the phase interface J. Phys. Chem. B 2015, 119, 4240– 4250 DOI: 10.1021/jp511083z279https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXlsFGmtQ%253D%253D&md5=3c4110db7eea34ecd4811381fc1fa819Multiscale Modeling of Four-Component Lipid Mixtures: Domain Composition, Size, Alignment, and Properties of the Phase InterfaceAckerman, David G.; Feigenson, Gerald W.Journal of Physical Chemistry B (2015), 119 (11), 4240-4250CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Simplified lipid mixts. are often used to model the complex behavior of the cell plasma membrane. Indeed, as few as four components-a high-melting lipid, a nanodomain-inducing low-melting lipid, a macrodomain-inducing low-melting lipid, and cholesterol (chol)-can give rise to a wide range of domain sizes and patterns that are highly sensitive to lipid compns. Although these systems are studied extensively with expts., the mol.-level details governing their phase behavior are not yet known. We address this issue by using mol. dynamics simulations to analyze how phase sepn. evolves in a four-component system as it transitions from small domains to large domains. To do so, we fix concns. of the high-melting lipid 16:0,16:0-phosphatidylcholine (DPPC) and chol, and incrementally replace the nanodomain-inducing low-melting lipid 16:0,18:2-PC (PUPC) by the macrodomain-inducing low-melting lipid 18:2,18:2-PC (DUPC). Coarse-grained simulations of this four-component system reveal that lipid demixing increases as the amt. of DUPC increases. Addnl., we find that domain size and interleaflet alignment change sharply over a narrow range of replacement of PUPC by DUPC, indicating that intraleaflet and interleaflet behaviors are coupled. Corresponding united atom simulations show that only lipids within ∼2 nm of the phase interface are significantly perturbed regardless of domain compn. or size. Thus, whereas the fraction of interface-perturbed lipids is negligible for large domains, it is significant for smaller ones. Together, these results reveal characteristic traits of bilayer thermodn. behavior in four-component mixts., and provide a baseline for investigation of the effects of proteins and other lipids on membrane phase properties.
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280Hills, R. D., Jr.; McGlinchey, N. Model parameters for simulation of physiological lipids J. Comput. Chem. 2016, 37, 1112 DOI: 10.1002/jcc.24324280https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitlCqtr0%253D&md5=5a5c46ead0c4bfc00e896a66bc355280Model parameters for simulation of physiological lipidsHills, Ronald D., Jr.; McGlinchey, NicholasJournal of Computational Chemistry (2016), 37 (12), 1112-1118CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse grain simulation of proteins in their physiol. membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsatd. lipids DOPC and DOPE, mixed-chain satn. POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixts. with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid-protein interaction model, making the force field of general utility for studying membrane proteins in physiol. representative bilayers. © 2016 The Authors. Journal of Computational Chem. Published by Wiley Periodicals, Inc.
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281Bromfield, S. M.; Posocco, P.; Fermeglia, M.; Tolosa, J.; Herreros-Lopez, A.; Pricl, S.; Rodriguez-Lopez, J.; Smith, D. K. Shape-persistent and adaptive multivalency: rigid transgeden (TGD) and flexible PAMAM dendrimers for heparin binding Chem. - Eur. J. 2014, 20, 9666– 9674 DOI: 10.1002/chem.201402237281https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtVGqtbvK&md5=e52d5cad44dfef0a7817238f8e9e2bd1Shape-Persistent and Adaptive Multivalency: Rigid Transgeden (TGD) and Flexible PAMAM Dendrimers for Heparin BindingBromfield, Stephen M.; Posocco, Paola; Fermeglia, Maurizio; Tolosa, Juan; Herreros-Lopez, Ana; Pricl, Sabrina; Rodriguez-Lopez, Julian; Smith, David K.Chemistry - A European Journal (2014), 20 (31), 9666-9674CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)This study studies transgeden (TGD) dendrimers (polyamidoamine (PAMAM)-type dendrimers modified with rigid polyphenylenevinylene (PPV) cores) and compares their heparin-binding ability with com. available PAMAM dendrimers. Although the peripheral ligands are near-identical between the two dendrimer families, their heparin binding is very different. At low generation (G1), TGD outperforms PAMAM, but at higher generation (G2 and G3), the PAMAMs are better. Heparin binding also depends strongly on the dendrimer/heparin ratio. The authors explain these effects using multiscale modeling. TGD dendrimers exhibit "shape-persistent multivalency"; the rigidity means that small clusters of surface amines are locally well optimized for target binding, but it prevents the overall nanoscale structure from rearranging to maximize its contacts with a single heparin chain. Conversely, PAMAM dendrimers exhibit "adaptive multivalency"; the flexibility means individual surface ligands are not so well optimized locally to bind heparin chains, but the nanostructure can adapt more easily and maximize its binding contacts. As such, this study exemplifies important new paradigms in multivalent biomol. recognition.
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282Zavadlav, J.; Podgornik, R.; Praprotnik, M. Adaptive Resolution Simulation of a DNA Molecule in Salt Solution J. Chem. Theory Comput. 2015, 11, 5035– 5044 DOI: 10.1021/acs.jctc.5b00596282https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVyntL3I&md5=8b3e65b2088f3d1f9c4c34dc2b6fa277Adaptive resolution simulation of a DNA molecule in salt solutionZavadlav, Julija; Podgornik, Rudolf; Praprotnik, MatejJournal of Chemical Theory and Computation (2015), 11 (10), 5035-5044CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present a multiscale simulation of a DNA mol. in 1M NaCl salt soln. environment, employing the adaptive resoln. simulation approach that allows the solvent mols., i.e., water and ions, to change their resoln. from atomistic to coarse-grained and vice versa adaptively on-the-fly. The region of high resoln. moves together with the DNA center-of-mass so that the DNA itself is always modeled at high resoln. The authors show that their multiscale simulations yield a stable DNA-soln. system, with statistical properties similar to those produced by the conventional all-atom mol. dynamics simulation. Special attention is given to the collective properties, such as the dielec. const., as they provide a sensitive quality measure of this multiscale approach.
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283Panteva, M. T.; Dissanayake, T.; Chen, H.; Radak, B. K.; Kuechler, E. R.; Giambasu, G. M.; Lee, T. S.; York, D. M. Multiscale methods for computational RNA enzymology Methods Enzymol. 2015, 553, 335– 374 DOI: 10.1016/bs.mie.2014.10.064There is no corresponding record for this reference.
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284Ayton, G. S.; Voth, G. A. Systematic multiscale simulation of membrane protein systems Curr. Opin. Struct. Biol. 2009, 19, 138– 144 DOI: 10.1016/j.sbi.2009.03.001284https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkvVSqt7s%253D&md5=6fba0da15839d8df2b3b945d6f140772Systematic multiscale simulation of membrane protein systemsAyton, Gary S.; Voth, Gregory A.Current Opinion in Structural Biology (2009), 19 (2), 138-144CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. Current multiscale simulation approaches for membrane protein systems vary depending in their degree of connection to the underlying mol. scale interactions. Various approaches have been developed that include such information into coarse-grained models of both the membrane and the proteins. By contrast, other approaches employ parameterizations obtained from exptl. data. Mesoscopic models operate at larger scales and have also been employed to examine membrane remodeling, protein inclusions, and ion channel gating. When bridged together such that mol.-level information is propagated between the different scales, a systematic multiscale methodol. for membrane protein systems can be achieved.
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285Sharma, S.; Ding, F.; Dokholyan, N. V. Multiscale modeling of nucleosome dynamics Biophys. J. 2007, 92, 1457– 1470 DOI: 10.1529/biophysj.106.094805There is no corresponding record for this reference.
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286Gao, T.; Blackwell, R.; Glaser, M. A.; Betterton, M. D.; Shelley, M. J. Multiscale modeling and simulation of microtubule-motor-protein assemblies Phys. Rev. E Stat. Nonlin. Soft. Matter Phys. 2015, 92, 062709 DOI: 10.1103/PhysRevE.92.062709There is no corresponding record for this reference.
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287Xie, Z. R.; Chen, J.; Wu, Y. Multiscale Model for the Assembly Kinetics of Protein Complexes J. Phys. Chem. B 2016, 120, 621 DOI: 10.1021/acs.jpcb.5b08962287https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XjvFajsg%253D%253D&md5=3f36a348a09539ab56be6be719f0be55Multiscale Model for the Assembly Kinetics of Protein ComplexesXie, Zhong-Ru; Chen, Jiawen; Wu, YinghaoJournal of Physical Chemistry B (2016), 120 (4), 621-632CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The assembly of proteins into high-order complexes is a general mechanism for these biomols. to implement their versatile functions in cells. Natural evolution has developed various assembling pathways for specific protein complexes to maintain their stability and proper activities. Previous studies have provided numerous examples of the misassembly of protein complexes leading to severe biol. consequences. Although the research focusing on protein complexes has started to move beyond the static representation of quaternary structures to the dynamic aspect of their assembly, the current understanding of the assembly mechanism of protein complexes is still largely limited. To tackle this problem, we developed a new multiscale modeling framework. This framework combines a lower-resoln. rigid-body-based simulation with a higher-resoln. Cα-based simulation method so that protein complexes can be assembled with both structural details and computational efficiency. We applied this model to a homotrimer and a heterotetramer as simple test systems. Consistent with exptl. observations, our simulations indicated very different kinetics between protein oligomerization and dimerization. The formation of protein oligomers is a multistep process that is much slower than dimerization but thermodynamically more stable. Moreover, we showed that even the same protein quaternary structure can have very diverse assembly pathways under different binding consts. between subunits, which is important for regulating the functions of protein complexes. Finally, we revealed that the binding between subunits in a complex can be synergistically strengthened during assembly without considering allosteric regulation or conformational changes. Therefore, our model provides a useful tool to understand the general principles of protein complex assembly.
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288Zheng, J. J.; Wang, D. Q.; Thiel, W.; Shaik, S. QM/MM study of mechanisms for compound I formation in the catalytic cycle of cytochrome P450cam J. Am. Chem. Soc. 2006, 128, 13204– 13215 DOI: 10.1021/ja063439l288https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XpsF2itLo%253D&md5=3dbc9ad468ea2b9c2e5ebbee23345460QM/MM Study of Mechanisms for Compound I Formation in the Catalytic Cycle of Cytochrome P450camZheng, Jingjing; Wang, Dongqi; Thiel, Walter; Shaik, SasonJournal of the American Chemical Society (2006), 128 (40), 13204-13215CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)In the catalytic cycle of cytochrome P450cam, after mol. oxygen binds as a ligand to the heme iron atom to yield a ferrous dioxygen complex, there are fast proton transfers that lead to the formation of the active species, Compd. I (Cpd I), which are not well understood because they occur so rapidly. In the present work, the conversion of the ferric hydroperoxo complex (Cpd 0) to Cpd I has been investigated by combined quantum-mech./mol.-mech. (QM/MM) calcns. The residues Asp251 and Glu366 are considered as proton sources. In mechanism I, a proton is transported to the distal oxygen atom of the hydroperoxo group via a hydrogen bonding network to form protonated Cpd 0 (prot-Cpd0: FeOOH2), followed by heterolytic O-O bond cleavage that generates Cpd I and water. Although a local min. is found for prot-Cpd0 in the Glu366 channel, it is very high in energy (more than 20 kcal/mol above Cpd 0) and the barriers for its decay are only 3-4 kcal/mol (both toward Cpd 0 and Cpd I). In mechanism II, an initial O-O bond cleavage followed by a concomitant proton and electron transfer yields Cpd I and water. The rate-limiting step in mechanism II is O-O cleavage with a barrier of about 13-14 kcal/mol. According to the QM/MM calcns., the favored low-energy pathway to Cpd I is provided by mechanism II in the Asp251 channel. Cpd 0 and Cpd I are of similar energies, with a slight preference for Cpd I.
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289Rothlisberger, U.; Carloni, P.; Doclo, K.; Parrinello, M. A comparative study of galactose oxidase and active site analogs based on QM/MM Car Parrinello simulations JBIC, J. Biol. Inorg. Chem. 2000, 5, 236– 250 DOI: 10.1007/s007750050368289https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXjtVejtLg%253D&md5=834a6a840f44d88ac34efe023cadecdcA comparative study of galactose oxidase and active site analogs based on QM/MM Car-Parrinello simulationsRothlisberger, Ursula; Carloni, Paolo; Doclo, Karel; Parrinello, MicheleJBIC, Journal of Biological Inorganic Chemistry (2000), 5 (2), 236-250CODEN: JJBCFA; ISSN:0949-8257. (Springer-Verlag)A parallel study of the radical copper enzyme galactose oxidase (GOase) and a low mol. wt. analog of the active site was performed with dynamic d. functional and mixed quantum-classical calcns. This combined approach enables a direct comparison of the properties of the biomimetic and the natural systems throughout the course of the catalytic reaction. In both cases, five essential forms of the catalytic cycle have been investigated: the resting state in its semi-reduced (catalytically inactive) and its oxidized (catalytically active) form, Asemi and Aox, resp.; a protonated intermediate B; the transition state for the rate-detg. hydrogen abstraction step C, and its product D. For A and B the electronic properties of the biomimetic compd. are qual. very similar to the ones of the natural target. However, in agreement with the exptl. obsd. difference in catalytic activity, the calcd. activation energy for the hydrogen abstraction step is distinctly lower for GOase (16 kcal/mol) than for the mimetic compd. (21 kcal/mol). The enzymic transition state is stabilized by a delocalization of the unpaired spin d. over the sulfur-modified equatorial tyrosine Tyr272, an effect that for geometric reasons is essentially absent in the biomimetic compd. Further differences between the mimic and its natural target concern the structure of the product of the abstraction step, which is characterized by a weakly coordinated aldehyde complex for the latter and a tightly bound linear complex for the former.
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290Shurki, A.; Warshel, A. Structure/function correlations of proteins using MM, QM/MM, and related approaches: Methods, concepts, pitfalls, and current progress Adv. Protein Chem. 2003, 66, 249– 313 DOI: 10.1016/S0065-3233(03)66007-9290https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXos1yhug%253D%253D&md5=33490555b78d1a92c4ebf9073dc3dcaeStructure/function correlations of proteins using MM, QM/MM, and related approaches: methods, concepts, pitfalls, and current progressShurki, A.; Warshel, A.Advances in Protein Chemistry (2003), 66 (Protein Simulations), 249-313CODEN: APCHA2; ISSN:0065-3233. (Elsevier Science)A review on structure-function correlations of proteins using mol. mechanics (MM), quantum mechanics (QM)/MM, and related approaches including methods, concepts, pitfalls, and current progress.
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291Roy, S.; Kastner, J. Synergistic Substrate and Oxygen Activation in Salicylate Dioxygenase Revealed by QM/MM Simulations Angew. Chem., Int. Ed. 2016, 55, 1168– 1172 DOI: 10.1002/anie.201506363291https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFens7bP&md5=aa56b890dc951bccb5a884ddcdd9f1fcSynergistic Substrate and Oxygen Activation in Salicylate Dioxygenase Revealed by QM/MM SimulationsRoy, Subhendu; Kaestner, JohannesAngewandte Chemie, International Edition (2016), 55 (3), 1168-1172CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)Salicylate 1,2-dioxygenase (SDO) is the first enzyme to be discovered to catalyze the oxidative cleavage of a monohydroxylated arom. compd., namely salicylate, instead of the well-known electron-rich substrates. We have investigated the mechanism of dioxygen activation in SDO by QM/MM calcns. Our study reveals that the non-heme FeII center in SDO activates salicylate and O2 synergistically through a strong covalent interaction to facilitate the reductive cleavage of O2. A covalent salicylate-FeII-O2 complex is the reactive oxygen species in this case, and its electronic structure is best described as being between the two limiting cases, FeII-O2 and FeII-O2·-, with partial electron transfer from the activated salicylate to O2 via the Fe center. Thus SDO employs a synergistic strategy of substrate and oxygen activation to carry out the catalytic reaction, which is unprecedented in the family of iron dioxygenases. Moreover, O2 activation in SDO happens without the assistance of a proton source. Our study essentially shows a new mechanistic possibility for O2 activation.
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292Raich, L.; Borodkin, V.; Fang, W.; Castro-Lopez, J.; van Aalten, D. M.; Hurtado-Guerrero, R.; Rovira, C. A trapped covalent intermediate of a glycoside hydrolase on the pathway to transglycosylation. Insights from experiments and QM/MM simulations J. Am. Chem. Soc. 2016, 138, 3325 DOI: 10.1021/jacs.5b10092There is no corresponding record for this reference.
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293Kumar, R. P.; Roopa, L.; Nongthomba, U.; Sudheer Mohammed, M. M.; Kulkarni, N. Docking, molecular dynamics and QM/MM studies to delineate the mode of binding of CucurbitacinE to F-actin J. Mol. Graphics Modell. 2016, 63, 29– 37 DOI: 10.1016/j.jmgm.2015.11.007293https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFagtb7I&md5=dfda59d9f1031cd4b0b97d38eed1fdd5Docking, molecular dynamics and QM/MM studies to delineate the mode of binding of CucurbitacinE to F-actinKumar, R. Pravin; Roopa, L.; Nongthomba, Upendra; Sudheer Mohammed, M. M.; Kulkarni, NaveenJournal of Molecular Graphics & Modelling (2016), 63 (), 29-37CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)CucurbitacinE (CurE) has been known to bind covalently to F-actin and inhibit depolymn. However, the mode of binding of CurE to F-actin and the consequent changes in the F-actin dynamics have not been studied. Through quantum mech./mol. mech. (QM/MM) and d. function theory (DFT) simulations after the mol. dynamics (MD) simulations of the docked complex of F-actin and CurE, a detailed transition state (TS) model for the Michael reaction is proposed. The TS model shows nucleophilic attack of the sulfur of Cys257 at the β-carbon of Michael Acceptor of CurE producing an enol intermediate that forms a covalent bond with CurE. The MD results show a clear difference between the structure of the F-actin in free form and F-actin complexed with CurE. CurE affects the conformation of the nucleotide binding pocket increasing the binding affinity between F-actin and ADP, which in turn could affect the nucleotide exchange. CurE binding also limits the correlated displacement of the relatively flexible domain 1 of F-actin causing the protein to retain a flat structure and to transform into a stable "tense" state. This structural transition could inhibit depolymn. of F-actin. In conclusion, CurE allosterically modulates ADP and stabilizes F-actin structure, thereby affecting nucleotide exchange and depolymn. of F-actin.
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294Carvalho, A. T.; Barrozo, A.; Doron, D.; Kilshtain, A. V.; Major, D. T.; Kamerlin, S. C. Challenges in computational studies of enzyme structure, function and dynamics J. Mol. Graphics Modell. 2014, 54, 62– 79 DOI: 10.1016/j.jmgm.2014.09.003294https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Gms7nL&md5=c263bbbd97932a5d047dc6bbd2ec07c9Challenges in computational studies of enzyme structure, function and dynamicsCarvalho, Alexandra T. P.; Barrozo, Alexandre; Doron, Dvir; Kilshtain, Alexandra Vardi; Major, Dan Thomas; Kamerlin, Shina Caroline LynnJournal of Molecular Graphics & Modelling (2014), 54 (), 62-79CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)A review. In this review we give an overview of the field of Computational enzymol. We start by describing the birth of the field, with emphasis on the work of the 2013 chem. Nobel Laureates. We then present key features of the state-of-the-art in the field, showing what theory, accompanied by expts., has taught us so far about enzymes. We also briefly describe computational methods, such as quantum mechanics-mol. mechanics approaches, reaction coordinate treatment, and free energy simulation approaches. We finalize by discussing open questions and challenges.
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295Duarte, F.; Amrein, B. A.; Blaha-Nelson, D.; Kamerlin, S. C. Recent advances in QM/MM free energy calculations using reference potentials Biochim. Biophys. Acta, Gen. Subj. 2015, 1850, 954– 965 DOI: 10.1016/j.bbagen.2014.07.008295https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVOhtrfL&md5=83b7e4fa141b1bcce3858c1d510cee08Recent advances in QM/MM free energy calculations using reference potentialsDuarte, Fernanda; Amrein, Beat A.; Blaha-Nelson, David; Kamerlin, Shina C. L.Biochimica et Biophysica Acta, General Subjects (2015), 1850 (5), 954-965CODEN: BBGSB3; ISSN:0304-4165. (Elsevier B.V.)A review. Recent years have seen enormous progress in the development of methods for modeling (bio)mol. systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and phys. meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biol. systems has long been shown to be an effective way to overcome some of the limitations assocd. with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chem. reactivity in biomol. systems. However, the high cost involved in performing high-level QM calcns. has limited the applicability of these approaches when calcg. free energies of chem. processes. In this review, we present some of the advances in using ref. potentials and mean field approxns. to accelerate high-level QM/MM calcns. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of phys.-based simplifications has shown to effectively reduce the cost of high-level QM/MM calcns. In particular, lower-level ref. potentials enable one to reduce the cost of expensive free energy calcns., thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of mol. dynamics.
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296Senn, H. M.; Thiel, W. QM/MM methods for biomolecular systems Angew. Chem., Int. Ed. 2009, 48, 1198– 1229 DOI: 10.1002/anie.200802019296https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXitFOqs7g%253D&md5=c51da58b0525651c71f9c393a79023beQM/MM methods for biomolecular systemsSenn, Hans Martin; Thiel, WalterAngewandte Chemie, International Edition (2009), 48 (7), 1198-1229CODEN: ACIEF5; ISSN:1433-7851. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. Combined quantum-mechanics/mol.-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomol. systems. Quantum-mech. (QM) methods are required for describing chem. reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based mol. mechanics (MM) methods. Thus to model large biomols. the logical approach is to combine the two techniques and, to use a QM method for the chem. active region (e.g., substrates and co-factors in an enzymic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomol. systems at a reasonable computational effort while providing the necessary accuracy.
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297Quesne, M. G.; Borowski, T.; de Visser, S. P. Quantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and Breakthroughs Chem. - Eur. J. 2016, 22, 2562 DOI: 10.1002/chem.201503802297https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitVynsrrJ&md5=fd32a34ec04a5914450abd582856a88cQuantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and BreakthroughsQuesne, Matthew G.; Borowski, Tomasz; de Visser, Sam P.Chemistry - A European Journal (2016), 22 (8), 2562-2581CODEN: CEUJED; ISSN:0947-6539. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. Nature has developed large groups of enzymic catalysts with the aim to transfer substrates into useful products, which enables biosystems to perform all their natural functions. As such, all biochem. processes in our body (we drink, we eat, we breath, we sleep, etc.) are governed by enzymes. One of the problems assocd. with research on biocatalysts is that they react so fast that details of their reaction mechanisms cannot be obtained with exptl. work. In recent years, major advances in computational hardware and software have been made and now large (bio)chem. systems can be studied using accurate computational techniques. One such technique is the quantum mechanics/mol. mechanics (QM/MM) technique, which has gained major momentum in recent years. Unfortunately, it is not a black-box method that is easily applied, but requires careful set-up procedures. In this work we give an overview on the tech. difficulties and caveats of QM/MM and discuss work-protocols developed in our groups for running successful QM/MM calcns.
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298Kamerlin, S. C.; Haranczyk, M.; Warshel, A. Progress in ab initio QM/MM free-energy simulations of electrostatic energies in proteins: accelerated QM/MM studies of pKa, redox reactions and solvation free energies J. Phys. Chem. B 2009, 113, 1253– 1272 DOI: 10.1021/jp8071712298https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVKis7%252FM&md5=8611575d4a747adad1e7e623af24a2b7Progress in Ab Initio QM/MM Free-Energy Simulations of Electrostatic Energies in Proteins: Accelerated QM/MM Studies of pKa, Redox Reactions and Solvation Free EnergiesKamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, AriehJournal of Physical Chemistry B (2009), 113 (5), 1253-1272CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)A review. Hybrid quantum mech./mol. mech. (QM/MM) approaches have been used to provide a general scheme for chem. reactions in proteins. However, such approaches still present a major challenge to computational chemists, not only because of the need for very large computer time in order to evaluate the QM energy but also because of the need for proper computational sampling. This review focuses on the sampling issue in QM/MM evaluations of electrostatic energies in proteins. We chose this example since electrostatic energies play a major role in controlling the function of proteins and are key to the structure-function correlation of biol. mols. Thus, the correct treatment of electrostatics is essential for the accurate simulation of biol. systems. Although we will be presenting different types of QM/MM calcns. of electrostatic energies (and related properties) here, our focus will be on pKa calcns. This reflects the fact that pKa's of ionizable groups in proteins provide one of the most direct benchmarks for the accuracy of electrostatic models of macromols. While pKa calcns. by semimacroscopic models have given reasonable results in many cases, existing attempts to perform pKa calcns. using QM/MM-FEP have led to discrepancies between calcd. and exptl. values. In this work, we accelerate our QM/MM calcns. using an updated mean charge distribution and a classical ref. potential. We examine both a surface residue (Asp3) of the bovine pancreatic trypsin inhibitor and a residue buried in a hydrophobic pocket (Lys102) of the T4-lysozyme mutant. We demonstrate that, by using this approach, we are able to reproduce the relevant side chain pKa's with an accuracy of 3 kcal/mol. This is well within the 7 kcal/mol energy difference obsd. in studies of enzymic catalysis, and is thus sufficient accuracy to det. the main contributions to the catalytic energies of enzymes. We also provide an overall perspective of the potential of QM/MM calcns. in general evaluations of electrostatic free energies, pointing out that our approach should provide a very powerful and accurate tool to predict the electrostatics of not only soln. but also enzymic reactions, as well as the solvation free energies of even larger systems, such as nucleic acid bases incorporated into DNA.
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299Heath, A. P.; Kavraki, L. E.; Clementi, C. From coarse-grain to all-atom: toward multiscale analysis of protein landscapes Proteins: Struct., Funct., Genet. 2007, 68, 646– 661 DOI: 10.1002/prot.21371299https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXnvFymsbw%253D&md5=49cb2dbc1910ef4812dfdb5b0f08bf26From coarse-grain to all-atom: toward multiscale analysis of protein landscapesHeath, Allison P.; Kavraki, Lydia E.; Clementi, CeciliaProteins: Structure, Function, and Bioinformatics (2007), 68 (3), 646-661CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biol. relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolns. The authors present a method that efficiently generates realistic all-atom protein structures starting from the Cα atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calcd. using the coarse-grain structures vs. the all-atom structures shows good correspondence and little distortion in the protein folding landscape.
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300Machado, M. R.; Dans, P. D.; Pantano, S. A hybrid all-atom/coarse grain model for multiscale simulations of DNA Phys. Chem. Chem. Phys. 2011, 13, 18134– 18144 DOI: 10.1039/c1cp21248f300https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht1Gqsr%252FI&md5=e5ea22c365dad53edce51d7e06cd66ccA hybrid all-atom/coarse grain model for multiscale simulations of DNAMachado, Matias Rodrigo; Dans, Pablo Daniel; Pantano, SergioPhysical Chemistry Chemical Physics (2011), 13 (40), 18134-18144CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)Hybrid simulations of mol. systems, which combine all-atom (AA) with simplified (or coarse grain, CG) representations, propose an advantageous alternative to gain atomistic details on relevant regions while getting profit from the speedup of treating a bigger part of the system at the CG level. Here we present a reduced set of parameters derived to treat a hybrid interface in DNA simulations. Our method allows us to forthrightly link a state-of-the-art force field for AA simulations of DNA with a CG representation developed by our group. We show that no modification is needed for any of the existing residues (neither AA nor CG). Only the bonding parameters at the hybrid interface are enough to produce a smooth transition of electrostatic, mechanic and dynamic features in different AA/CG systems, which are studied by mol. dynamics simulations using an implicit solvent. The simplicity of the approach potentially permits us to study the effect of mutations/modifications as well as DNA binding mols. at the atomistic level within a significantly larger DNA scaffold considered at the CG level. Since all the interactions are computed within the same classical Hamiltonian, the extension to a quantum/classical/coarse-grain multilayer approach using QM/MM modules implemented in widely used simulation packages is straightforward.
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301Michel, J.; Orsi, M.; Essex, J. W. Prediction of partition coefficients by multiscale hybrid atomic-level/coarse-grain simulations J. Phys. Chem. B 2008, 112, 657– 660 DOI: 10.1021/jp076142y301https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlslyl&md5=b9b8ac43dad39e76f8a473e7121f9096Prediction of Partition Coefficients by Multiscale Hybrid Atomic-Level/Coarse-Grain SimulationsMichel, Julien; Orsi, Mario; Essex, Jonathan W.Journal of Physical Chemistry B (2008), 112 (3), 657-660CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)Coarse-grain models are becoming an increasingly important tool in computer simulations of a wide variety of mol. processes. In many instances it is, however, desirable to describe key portions of a mol. system at the at. level. There is therefore a strong interest in the development of simulation methodologies that allow representations of matter with mixed granularities in a multiscale fashion. We report here a strategy to conduct mixed at.-level and coarse-grain simulations of mol. systems with a recently developed coarse-grain model. The methodol. is validated by computing partition coeffs. of small mols. described in at. detail and solvated by water or octane, both of which are represented by coarse-grain models. Because the present coarse-grain force field retains electrostatic interactions, the simplified solvent particles can interact realistically with the all-atom solutes. The partition coeffs. computed by this approach rival the accuracy of fully atomistic simulations and are obtained at a fraction of their computational cost. The present methodol. is simple, robust and applicable to a wide variety of mol. systems.
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302Vieth, M.; Kolinski, A.; Brooks, C. L., 3rd; Skolnick, J. Prediction of the folding pathways and structure of the GCN4 leucine zipper J. Mol. Biol. 1994, 237, 361– 367 DOI: 10.1006/jmbi.1994.1239302https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXivFemsLg%253D&md5=3ebe03a90938c20b2829685dde451dd5Prediction of the folding pathways and structure of the GCN4 leucine zipperVieth, Michal; Kolinski, Andrzej; Brooks, Charles L., III; Skolnick, JeffreyJournal of Molecular Biology (1994), 237 (4), 361-7CODEN: JMOBAK; ISSN:0022-2836.A hierarchical approach is described for the prediction of the three-dimensional structure and folding pathway of the GCN4 leucine zipper. Dimer assembly is simulated by Monte Carlo dynamics. The resulting lowest energy structures undergo cooperative rearrangement of their hydrophobic core leading to side-chain fixation. The coarse-grained structures are further refined using a mol. dynamics annealing protocol. This produces full atom models with a backbone root-mean-square deviation from the crystal structure of 0.81 Å. Thus, the authors demonstrate the predictive ability of the authors' approach to yield high resoln. structures of small coiled coils from their sequence.
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303Mohanty, D.; Dominy, B. N.; Kolinski, A.; Brooks, C. L., 3rd; Skolnick, J. Correlation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipper Proteins: Struct., Funct., Genet. 1999, 35, 447– 452 DOI: 10.1002/(SICI)1097-0134(19990601)35:4<447::AID-PROT8>3.0.CO;2-O303https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXjs1yqtL4%253D&md5=8044de8535422b330f19dcc823dec1eaCorrelation between knowledge-based and detailed atomic potentials: application to the unfolding of the GCN4 leucine zipperMohanty, Debasisa; Dominy, Brian N.; Kolinski, Andrzej; Brooks, Charles L., III; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1999), 35 (4), 447-452CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)The relationship between the unfolding pseudo free energies of reduced and detailed at. models of the GCN4 leucine zipper is examd. Starting from the native crystal structure, a large no. of conformations ranging from folded to unfolded were generated by all-atom mol. dynamics unfolding simulations in an aq. environment at elevated temps. For the detailed at. model, the pseudo free energies are obtained by combining the CHARMM all-atom potential with a solvation component from the generalized Born, surface accessibility, GB/SA, model. Reduced model energies were evaluated using a knowledge-based potential. Both energies are highly correlated. In addn., both show a good correlation with the root mean square deviation, RMSD, of the backbone from native. These results suggest that knowledge-based potentials are capable of describing at least some of the properties of the folded as well as the unfolded states of proteins, even though they are derived from a database of native protein structures. Since only conformations generated from an unfolding simulation are used, we cannot assess whether these potentials can discriminate the native conformation from the manifold of alternative, low-energy misfolded states. Nevertheless, these results also have significant implications for the development of a methodol. for multiscale modeling of proteins that combines reduced and detailed at. models.
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304Fan, Z. Z.; Hwang, J. K.; Warshel, A. Using simplified protein representation as a reference potential for all-atom calculations of folding free energy Theor. Chem. Acc. 1999, 103, 77– 80 DOI: 10.1007/s002140050516304https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXjsV2htbk%253D&md5=9b2b5b18f1766f40ef67d2c5853c6917Using simplified protein representation as a reference potential for all-atom calculations of folding free energyFan, Z. Z.; Hwang, J.-K.; Warshel, A.Theoretical Chemistry Accounts (1999), 103 (1), 77-80CODEN: TCACFW; ISSN:1432-881X. (Springer-Verlag)An effective approach for evaluating folding free-energy surfaces of explicit all-atom models is developed and examd. This approach is based on using the potential of a simplified protein model as a ref. potential for calcg. the free energy of the corresponding explicit model. Preliminary results are presented for the folding free energy of a 12-residue helix. The potential of the method for studies of protein-folding processes is discussed, emphasizing the ability to det. the difference between the results of simplified and explicit models. This can help in establishing the validity of simplified folding models.
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305Zhang, J.; Li, W.; Wang, J.; Qin, M.; Wu, L.; Yan, Z.; Xu, W.; Zuo, G.; Wang, W. Protein folding simulations: from coarse-grained model to all-atom model IUBMB Life 2009, 61, 627– 643 DOI: 10.1002/iub.223305https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXmvFCmsL4%253D&md5=27c64c10758a3647b31a78d140d581e3Protein folding simulations: from coarse-grained model to all-atom modelZhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, WeiIUBMB Life (2009), 61 (6), 627-643CODEN: IULIF8; ISSN:1521-6543. (John Wiley & Sons Inc.)A review. Protein folding is an important and challenging problem in mol. biol. During the last 2 decades, mol. dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodn., and structure-stability-function relations. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal no. of amino acid or the evolution principle of protein families. Nowadays, MD simulation is still undergoing rapid developments. The 1st trend is to toward developing new coarse-grained models and studying larger and more complex mol. systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides. The 2nd trend is toward building high resoln. models and explore more detailed and accurate pictures of protein folding and the assocd. processes, such as coordination bond- or disulfide bond-involved folding, polarization, charge transfer and protonation/deprotonation processes involved in metal ion-coupled folding, and ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, the authors review several new subjects investigated by using MD simulations as well as corresponding developments of appropriate protein models. These include, but are not limited to, the attempt to go beyond the topol. based Go-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodn. and kinetics of disulfide bond-involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL, the development of discrete MD and its application in studying the α-β conformational conversion and oligomer assembly process, and the modeling of metal ion-involved protein folding.
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306Reith, D.; Putz, M.; Muller-Plathe, F. Deriving effective mesoscale potentials from atomistic simulations J. Comput. Chem. 2003, 24, 1624– 1636 DOI: 10.1002/jcc.10307306https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXntFentL4%253D&md5=304cc4acd956aaa71f476992e656fd13Deriving effective mesoscale potentials from atomistic simulationsReith, Dirk; Puetz, Mathias; Mueller-Plathe, FlorianJournal of Computational Chemistry (2003), 24 (13), 1624-1636CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liq. systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few interactions. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 redn. of the degrees of freedom. This procedure was performed for PI solns. as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concn. regimes.
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307Chu, J. W.; Voth, G. A. Coarse-grained modeling of the actin filament derived from atomistic-scale simulations Biophys. J. 2006, 90, 1572– 1582 DOI: 10.1529/biophysj.105.073924307https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XitVahtLg%253D&md5=d2b9d2bf8ace4e86de996c4c9b27f47aCoarse-grained modeling of the actin filament derived from atomistic-scale simulationsChu, Jhih-Wei; Voth, Gregory A.Biophysical Journal (2006), 90 (5), 1572-1582CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)A coarse-grained (CG) procedure that incorporates the information obtained from all-atom mol. dynamics (MD) simulations is presented and applied to actin filaments (F-actin). This procedure matches the averaged values and fluctuations of the effective internal coordinates that are used to define a CG model to the values extd. from atomistic MD simulations. The fluctuations of effective internal coordinates in a CG model are computed via normal-mode anal. (NMA), and the computed fluctuations are matched with the atomistic MD results in a self-consistent manner. Each actin monomer (G-actin) is coarse-grained into four sites, and each site corresponds to one of the subdomains of G-actin. The potential energy of a CG G-actin contains three bonds, two angles, and one dihedral angle; effective harmonic bonds are used to describe the intermonomer interactions in a CG F-actin. The persistence length of a CG F-actin was found to be sensitive to the cut-off distance of assigning intermonomer bonds. Effective harmonic bonds for a monomer with its third nearest neighboring monomers are found to be necessary to reproduce the values of persistence length obtained from all-atom MD simulations. Compared to the elastic network model, incorporating the information of internal coordinate fluctuations enhances the accuracy and robustness for a CG model to describe the shapes of low-frequency vibrational modes. Combining the fluctuation-matching CG procedure and NMA, the achievable time- and length scales of modeling actin filaments can be greatly enhanced. In particular, a method is described to compute the force-extension curve using the CG model developed in this work and NMA. It was found that F-actin is easily buckled under compressive deformation, and a writhing mode is developed as a result. In addn. to the bending and twisting modes, this novel writhing mode of F-actin could also play important roles in the interactions of F-actin with actin-binding proteins and in the force-generation process via polymn.
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308Shi, Q.; Izvekov, S.; Voth, G. A. Mixed atomistic and coarse-grained molecular dynamics: simulation of a membrane-bound ion channel J. Phys. Chem. B 2006, 110, 15045– 15048 DOI: 10.1021/jp062700h308https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XmvF2nur0%253D&md5=cfabe4f2253aab0a762d961788e34d70Mixed Atomistic and Coarse-Grained Molecular Dynamics: Simulation of a Membrane-Bound Ion ChannelShi, Qiang; Izvekov, Sergei; Voth, Gregory A.Journal of Physical Chemistry B (2006), 110 (31), 15045-15048CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The recently developed multiscale coarse-graining (MS-CG) method (Izvekov, S.; Voth, G. A. J. Phys. Chem. B 2005, 109, 2469; J. Chem. Phys. 2005, 123, 134105) is used to build a mixed all-atom and coarse-grained (AA-CG) model of the gramicidin A (gA) ion channel embedded in a dimyristoylphosphatidylcholine (DMPC) lipid bilayer and water environment. In this model, the gA peptide was described in full atomistic detail, while the lipid and water mols. were described using coarse-grained representations. The atom-CG and CG-CG interactions in the mixed AA-CG model were detd. using the MS-CG method. Mol. dynamics (MD) simulations were performed using the resulting AA-CG model. The results from simulations of the AA-CG model compare very favorably to those from all-atom MD simulations of the entire system. Since the MS-CG method employs a general and systematic approach to obtaining effective interactions from the underlying all-atom models, the present approach to rigorously developing mixed AA-CG models has the potential to be extended to many other systems.
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309Lyman, E.; Zuckerman, D. M. Resolution Exchange Simulation with Incremental Coarsening J. Chem. Theory Comput. 2006, 2, 656– 666 DOI: 10.1021/ct050337x309https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjslSlsb8%253D&md5=5edc56d3b1473383530e93a678e3e17bResolution Exchange Simulation with Incremental CoarseningLyman, Edward; Zuckerman, Daniel M.Journal of Chemical Theory and Computation (2006), 2 (3), 656-666CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors previously developed an algorithm, called "resoln. exchange", which improves canonical sampling of at. resoln. models by swapping conformations between high- and low-resoln. simulations. Here, the authors demonstrate a generally applicable incremental coarsening procedure and apply the algorithm to a larger peptide, met-enkephalin. In addn., the authors demonstrate a combination of resoln. and temp. exchange, in which the coarser simulations are also at elevated temps. Both simulations are implemented in a "top-down" mode, to allow efficient allocation of CPU time among the different replicas.
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310Villa, E.; Balaeff, A.; Schulten, K. Structural dynamics of the lac repressor-DNA complex revealed by a multiscale simulation Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 6783– 6788 DOI: 10.1073/pnas.0409387102There is no corresponding record for this reference.
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311Fujisaki, H.; Shiga, M.; Moritsugu, K.; Kidera, A. Multiscale enhanced path sampling based on the Onsager-Machlup action: Application to a model polymer. J. Chem. Phys. 2013, 139, 054117 DOI: 10.1063/1.4817209311https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1altL3E&md5=bfc296e159da1808e2422810c5ccd9c8Multiscale enhanced path sampling based on the Onsager-Machlup action: Application to a model polymerFujisaki, Hiroshi; Shiga, Motoyuki; Moritsugu, Kei; Kidera, AkinoriJournal of Chemical Physics (2013), 139 (5), 054117/1-054117/9CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)We propose a novel path sampling method based on the Onsager-Machlup (OM) action by generalizing the multiscale enhanced sampling technique suggested by. The basic idea of this method is that the system we want to study (for example, some mol. system described by mol. mechanics) is coupled to a coarse-grained (CG) system, which can move more quickly and can be computed more efficiently than the original system. We simulate this combined system (original + CG system) using Langevin dynamics where different heat baths are coupled to the two systems. When the coupling is strong enough, the original system is guided by the CG system, and is able to sample the configuration and path space with more efficiency. We need to correct the bias caused by the coupling, however, by employing the Hamiltonian replica exchange, where we prep. many path replicas with different coupling strengths. As a result, an unbiased path ensemble for the original system can be found in the weakest coupling path ensemble. This strategy is easily implemented because a wt. for a path calcd. by the OM action is formally the same as the Boltzmann wt. if we properly define the path "Hamiltonian." We apply this method to a model polymer with Asakura-Oosawa interaction, and compare the results with the conventional transition path sampling method. (c) 2013 American Institute of Physics.
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312Orsi, M.; Sanderson, W. E.; Essex, J. W. Permeability of Small Molecules through a Lipid Bilayer: A Multiscale Simulation Study J. Phys. Chem. B 2009, 113, 12019– 12029 DOI: 10.1021/jp903248s312https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXps1KmsL8%253D&md5=a5cd73050707209be5d4b4535ccf9808Permeability of Small Molecules through a Lipid Bilayer: A Multiscale Simulation StudyOrsi, Mario; Sanderson, Wendy E.; Essex, Jonathan W.Journal of Physical Chemistry B (2009), 113 (35), 12019-12029CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The transmembrane permeation of eight small (mol. wt. <100) org. mols. across a phospholipid bilayer is investigated by multiscale mol. dynamics simulation. The bilayer and hydrating water are represented by simplified, efficient coarse-grain models, whereas the permeating mols. are described by a std. at.-level force-field. Permeability properties are obtained through a refined version of the z-constraint algorithm. By constraining each permeant at selected depths inside the bilayer, we have sampled free energy differences and diffusion coeffs. across the membrane. These data have been combined, according to the inhomogeneous soly.-diffusion model, to yield the permeability coeffs. The results are generally consistent with previous at.-level calcns. and available exptl. data. Computationally, our multiscale approach proves 2 orders of magnitude faster than traditional at.-level methods.
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313Neri, M.; Anselmi, C.; Carnevale, V.; Vargiu, A. V.; Carloni, P. Molecular dynamics simulations of outer-membrane protease T from E-coli based on a hybrid coarse-grained/atomistic potential J. Phys.: Condens. Matter 2006, 18, S347– S355 DOI: 10.1088/0953-8984/18/14/S16There is no corresponding record for this reference.
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314Praprotnik, M.; Delle Site, L.; Kremer, K. Multiscale simulation of soft matter: From scale bridging to adaptive resolution Annu. Rev. Phys. Chem. 2008, 59, 545– 571 DOI: 10.1146/annurev.physchem.59.032607.093707314https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlvFWrtrs%253D&md5=a10479920f46503a44e1b716038bb485Multiscale simulation of soft matter: from scale bridging to adaptive resolutionPraprotnik, Matej; Delle Site, Luigi; Kremer, KurtAnnual Review of Physical Chemistry (2008), 59 (), 545-571CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)The relation between atomistic chem. structure, mol. architecture, mol. wt., and material properties is of basic concern in modern soft material science and includes std. properties of bulk materials and surface and interface aspects, as well as the relation between structure and function in nanoscopic objects and mol. assemblies of both synthetic and biol. origin. This all implies a thorough understanding on many length and correspondingly time scales, ranging from (sub)atomistic to macroscopic. Presently, computer simulations play an increasingly important, if not central, role. Some problems do not require specific atomistic details, whereas others require them only locally. However, in many cases this strict sepn. is not sufficient for a comprehensive understanding of systems, and flexible simulation schemes are required that link the different levels of resoln. We here give a general view of the problem regarding soft matter and discuss some specific examples of linked simulation techniques at different resoln. levels. We then discuss a recently developed flexible simulation scheme, the AdResS method, which allows one to adaptively change the resoln. in certain regions of space on demand.
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315Potestio, R.; Fritsch, S.; Espanol, P.; Delgado-Buscalioni, R.; Kremer, K.; Everaers, R.; Donadio, D. Hamiltonian Adaptive Resolution Simulation for Molecular Liquids Phys. Rev. Lett. 2013, 110, 110 DOI: 10.1103/PhysRevLett.110.108301There is no corresponding record for this reference.
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316Heyden, A.; Lin, H.; Truhlar, D. G. Adaptive partitioning in combined quantum mechanical and molecular mechanical calculations of potential energy functions for multiscale simulations J. Phys. Chem. B 2007, 111, 2231– 2241 DOI: 10.1021/jp0673617316https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhsFGjur4%253D&md5=7334a09f2aac2cbc3d90f1ff0d67f977Adaptive Partitioning in Combined Quantum Mechanical and Molecular Mechanical Calculations of Potential Energy Functions for Multiscale SimulationsHeyden, Andreas; Lin, Hai; Truhlar, Donald G.Journal of Physical Chemistry B (2007), 111 (9), 2231-2241CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)In many applications of multilevel/multiscale methods, an active zone must be modeled by a high-level electronic structure method, while a larger environmental zone can be safely modeled by a lower-level electronic structure method, mol. mechanics, or an analytic potential energy function. In some cases though, the active zone must be redefined as a function of simulation time. Examples include a reactive moiety diffusing through a liq. or solid, a dislocation propagating through a material, or solvent mols. in a second coordination sphere (which is environmental) exchanging with solvent mols. in an active first coordination shell. We present a procedure for combining the levels smoothly and efficiently in such systems in which atoms or groups of atoms move between high-level and low-level zones. The method dynamically partitions the system into the high-level and low-level zones and, unlike previous algorithms, removes all discontinuities in the potential energy and force whenever atoms or groups of atoms cross boundaries and change zones. The new adaptive partitioning (AP) method is compared to Rode's "hot spot" method and Morokuma's "ONIOM-XS" method that were designed for multilevel mol. dynamics (MD) simulations. MD simulations in the microcanonical ensemble show that the AP method conserves both total energy and momentum, while the ONIOM-XS method fails to conserve total energy and the hot spot method fails to conserve both total energy and momentum. Two versions of the AP method are presented, one scaling as O(2N) and one with linear scaling in N, where N is the no. of groups in a buffer zone sepg. the active high-level zone from the environmental low-level zone. The AP method is also extended to systems with multiple high-level zones to allow, for example, the study of ions and counterions in soln. using the multilevel approach.
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317Kerdcharoen, T.; Liedl, K. R.; Rode, B. M. A QM/MM simulation method applied to the solution of Li+ in liquid ammonia Chem. Phys. 1996, 211, 313– 323 DOI: 10.1016/0301-0104(96)00152-8317https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmvFCqsL0%253D&md5=899733c88da0c4ab90010be751cc217bA QM/MM simulation method applied to the solution of Li+ in liquid ammoniaKerdcharoen, Teerakiat; Liedl, Klaus R.; Rode, Bernd M.Chemical Physics (1996), 211 (1,2,3), 313-323CODEN: CMPHC2; ISSN:0301-0104. (Elsevier)A mol. dynamics simulation method based on combined quantum mech. and classical potentials is proposed. This method computes the interactions between particles in a focus region, we call it "Hot Spot", at quantum chem. level within a affordable computational effort. Application to soln. chem. was examd. by simulating Li+ solvation in liq. ammonia. The new method yields a coordination no. of 4 in contrast to 6 obtained from pair-potential simulation. Dynamical properties were found in agreement with the structural change of the solvation shell. The semi-empirical MNDO method was also tested within this approach, but proved inappropriate for electrolyte solns.
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318Hofer, T. S.; Pribil, A. B.; Randolf, B. R.; Rode, B. M. Structure and dynamics of solvated Sn(II) in aqueous solution: An ab initio QM/MM MD approach J. Am. Chem. Soc. 2005, 127, 14231– 14238 DOI: 10.1021/ja052700f318https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhtVWrtrvL&md5=0d703d87a11e0790b9197cfb0eb31ab3Structure and Dynamics of Solvated Sn(II) in Aqueous Solution: An ab Initio QM/MM MD ApproachHofer, Thomas S.; Pribil, Andreas B.; Randolf, Bernhard R.; Rode, Bernd M.Journal of the American Chemical Society (2005), 127 (41), 14231-14238CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Structural and dynamical properties of the hydrated Sn(II) ion have been investigated by ab initio quantum mech./mol. mech. (QM/MM) mol. dynamics (MD) simulations at double-ζ HF quantum mech. level. The results indicate Sn(II)aq to be a rather peculiar, if not unique, case of a hydrated ion: four of its eight first-shell ligands do not take place in the otherwise frequent ligand-exchange processes, forming an approx. tetrahedral cage around the ion. The remaining ligands, however, exchange at a rate that is rather comparable to monovalent than divalent ions. This very surprising behavior of ligand exchange not yet obsd. in any previous simulation of over 30 hydrated metal ions is consistently confirmed by vibrational spectra, bond lengths, and a detailed anal. of the trajectories of the simulation.
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319Kerdcharoen, T.; Morokuma, K. ONIOM-XS: an extension of the ONIOM method for molecular simulation in condensed phase Chem. Phys. Lett. 2002, 355, 257– 262 DOI: 10.1016/S0009-2614(02)00210-5319https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XjslWju78%253D&md5=2f5082a7695f451a6c78f77e553bf585ONIOM-XS: an extension of the ONIOM method for molecular simulation in condensed phaseKerdcharoen, Teerakiat; Morokuma, KeijiChemical Physics Letters (2002), 355 (3,4), 257-262CODEN: CHPLBC; ISSN:0009-2614. (Elsevier Science B.V.)A new technique based on ONIOM method was implemented for simulation of liqs. and solns., in which exchange of solvents (XS) between subsystems (i.e. between QM and MM parts) is allowed. In this method, a switching layer sandwiched between "high-level" and "low-level" subsystems was introduced to help morphing of exchanging particle from one region to another. Test on ionic soln. by mol. dynamics method shows that particle exchanges across the boundary negligibly disturb the equil. conditions. A rigorous treatment of the energy expression by this method also opens new opportunities for such as Monte Carlo and free energy simulations.
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320Iwata, Y.; Kasuya, A.; Miyamoto, S. An efficient method for reconstructing protein backbones from [alpha]-carbon coordinates J. Mol. Graphics Modell. 2002, 21, 119– 128 DOI: 10.1016/S1093-3263(02)00142-0320https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38Xms1yks7g%253D&md5=157e7eab65fdff1a21a8f9b067b2f62cAn efficient method for reconstructing protein backbones from α-carbon coordinatesIwata, Yoriko; Kasuya, Atsushi; Miyamoto, ShuichiJournal of Molecular Graphics & Modelling (2002), 21 (2), 119-128CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Science Inc.)We present an approach for building protein backbones from α-carbon (Cα) coordinates. The approach is anal. and based on the information of favored regions in the Ramachandran map. The backbone construction consists of three parts: prediction of (φ, ψ) angle pairs from the Cα trace, generation of at. coordinates with these (φ, ψ) angles, and refinement by subsequent energy minimization. Tests on several known protein structures show that the root mean square deviations in reconstructed backbones are 0.25-0.48 A for coordinates and 14-34° for φ and ψ angles. The results indicate that our method is one of the best methods proposed in terms of accuracy. It has also been revealed that the approach is not only robust against errors in Cα coordinates but is also capable of providing equiv. or more reasonable models compared to other known methods. Furthermore, backbone structures were found to be built accurately by using the (φ, ψ) angles from a different structure of the same protein. This suggests that the approach could be effective and useful in homol. modeling studies.
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321Purisima, E. O.; Scheraga, H. A. Conversion from a virtual-bond chain to a complete polypeptide backbone chain Biopolymers 1984, 23, 1207– 1224 DOI: 10.1002/bip.360230706There is no corresponding record for this reference.
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322Gront, D.; Kmiecik, S.; Kolinski, A. Backbone building from quadrilaterals: a fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinates J. Comput. Chem. 2007, 28, 1593– 1597 DOI: 10.1002/jcc.20624322https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXlslSgsLo%253D&md5=9d8e4ebf68affeefc13b11ddf0c54befBackbone Building from Quadrilaterals: a fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinatesGront, Dominik; Kmiecik, Sebastian; Kolinski, AndrzejJournal of Computational Chemistry (2007), 28 (9), 1593-1597CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)In this contribution, the authors present an algorithm for protein backbone reconstruction that comprises very high computational efficiency with high accuracy. Reconstruction of the main chain at. coordinates from the α carbon trace is a common task in protein modeling, including de novo structure prediction, comparative modeling, and processing exptl. data. The method employed follows the main idea of some earlier approaches to the problem. The details and careful design of the present approach are new and lead to the algorithm that outperforms all commonly used earlier applications. BBQ (Backbone Building from Quadrilaterals) program has been extensively tested both on native structures as well as on near-native decoy models and compared with the different available existing methods. Obtained results provide a comprehensive benchmark of existing tools and evaluate their applicability to a large scale modeling using a reduced representation of protein conformational space. The BBQ package is available for downloading from the authors' website at http://biocomp.chem.uw.edu.pl/services/BBQ/. This webpage also provides a user manual that describes BBQ functions in detail.
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323Rotkiewicz, P.; Skolnick, J. Fast procedure for reconstruction of full-atom protein models from reduced representations J. Comput. Chem. 2008, 29, 1460– 1465 DOI: 10.1002/jcc.20906323https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXmsFOhtrw%253D&md5=b78d84b5ffcb1b3967aab0c4c986e4c0Fast procedure for reconstruction of full-atom protein models from reduced representationsRotkiewicz, Piotr; Skolnick, JeffreyJournal of Computational Chemistry (2008), 29 (9), 1460-1465CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We introduce PULCHRA, a fast and robust method for the reconstruction of full-atom protein models starting from a reduced protein representation. The algorithm is particularly suitable as an intermediate step between coarse-grained model-based structure prediction and applications requiring an all-atom structure, such as mol. dynamics, protein-ligand docking, structure-based function prediction, or assessment of quality of the predicted structure. The accuracy of the method was tested on a set of high-resoln. crystallog. structures as well as on a set of low-resoln. protein decoys generated by a protein structure prediction algorithm TASSER.
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324Feig, M.; Rotkiewicz, P.; Kolinski, A.; Skolnick, J.; Brooks, C. L., 3rd Accurate reconstruction of all-atom protein representations from side-chain-based low-resolution models Proteins: Struct., Funct., Genet. 2000, 41, 86– 97 DOI: 10.1002/1097-0134(20001001)41:1<86::AID-PROT110>3.3.CO;2-PThere is no corresponding record for this reference.
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325Milik, M.; Kolinski, A.; Skolnick, J. Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinates J. Comput. Chem. 1997, 18, 80– 85 DOI: 10.1002/(SICI)1096-987X(19970115)18:1<80::AID-JCC8>3.0.CO;2-W325https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXhtVSksQ%253D%253D&md5=7769c831f78ee8c789b23095e1b8b185Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinatesMilik, Mariusz; Kolinski, Andrzej; Skolnick, JeffreyJournal of Computational Chemistry (1997), 18 (1), 80-85CODEN: JCCHDD; ISSN:0192-8651. (Wiley)A method for generating a full backbone protein structure from the coordinates of α-carbons, is presented. The method exts. information from known protein structures to generate positions for the reconstructed atoms. Tests on a set proteins structures show the algorithm to be of comparable accuracy to existing procedures. However, the basic advantage of the presented method is its simplicity and speed. In a test run, the present program is shown to be much faster than existing database searching algorithms, and reconstructs about 8000 residues per s. Thus, it may be included as an independent procedure in protein folding algorithms to rapidly generate approx. coordinates of backbone atoms.
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326Adcock, S. Peptide backbone reconstruction using dead-end elimination and a knowledge-based forcefield J. Comput. Chem. 2004, 25, 16– 27 DOI: 10.1002/jcc.10314There is no corresponding record for this reference.
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327Claessens, M.; van Cutsem, E.; Lasters, I.; Wodak, S. Modelling the polypeptide backbone with ’spare parts’ from known protein structures Protein Eng., Des. Sel. 1989, 2, 335– 345 DOI: 10.1093/protein/2.5.335There is no corresponding record for this reference.
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328Pierce, N. A.; Winfree, E. Protein design is NP-hard Protein Eng., Des. Sel. 2002, 15, 779– 782 DOI: 10.1093/protein/15.10.779328https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XptlOht7g%253D&md5=32a6f7e6da581d3fa92f8feeccda6bb2Protein design is NP-hardPierce, Niles A.; Winfree, ErikProtein Engineering (2002), 15 (10), 779-782CODEN: PRENE9; ISSN:0269-2139. (Oxford University Press)Biologists working in the area of computational protein design have never doubted the seriousness of the algorithmic challenges that face them in attempting in silico sequence selection. It turns out that in the language of the computer science community, this discrete optimization problem is NP-hard. The purpose of this paper is to explain the context of this observation, to provide a simple illustrative proof and to discuss the implications for future progress on algorithms for computational protein design.
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329Gordon, D. B.; Hom, G. K.; Mayo, S. L.; Pierce, N. A. Exact rotamer optimization for protein design J. Comput. Chem. 2003, 24, 232– 243 DOI: 10.1002/jcc.10121There is no corresponding record for this reference.
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330Bower, M. J.; Cohen, F. E.; Dunbrack, R. L., Jr. Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool J. Mol. Biol. 1997, 267, 1268– 1282 DOI: 10.1006/jmbi.1997.0926330https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXjtFWhu7w%253D&md5=9bd2bdee27b12c8b6a0e6dfa8c7543b8Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling toolBower, Michael J.; Cohen, Fred E.; Dunbrack, Roland L., Jr.Journal of Molecular Biology (1997), 267 (5), 1268-1282CODEN: JMOBAK; ISSN:0022-2836. (Academic)Modeling by homol. is the most accurate computational method for translating an amino acid sequence into a protein structure. Homol. modeling can be divided into two sub-problems, placing the polypeptide backbone and adding side-chains. We present a method for rapidly predicting the conformations of protein side-chains, starting from main-chain coordinates alone. The method involves using fewer from main-chain coordinates alone. The method involves using fewer than ten rotamers per residue from a backbone-dependent rotamer library and a search to remove steric conflicts. The method is initially tested on 299 high resoln. crystal structures by rebuilding side-chains onto the exptl. detd. backbone structures. A total of 77% of χ1 and 66% of χ1+2 dihedral angles are predicted within 40° of their crystal structure values. We then tested the method on the entire database of known structures in the Protein Data Bank. The predictive accuracy of the algorithm was strongly correlated with the resoln. of the structures. In an effort to simulate a realistic homol. modeling problem, 9424 homol. models were created using three different modeling strategies. For prediction purposes, pairs of structures were identified which shared between 30% and 90% sequence identity. One strategy results in 82% of χ1+2 dihedral angles predicted within 40° of the target crystal structure values, suggesting that movements of the backbone assocd. with this degree of sequence identity are not large enough to disrupt the predictive ability of our method for non-native backbones. These results compared favorably with existing methods over a comprehensive data set.
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331Subramaniam, S.; Senes, A. Backbone dependency further improves side chain prediction efficiency in the Energy-based Conformer Library (bEBL) Proteins: Struct., Funct., Genet. 2014, 82, 3177– 3187 DOI: 10.1002/prot.24685There is no corresponding record for this reference.
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332Holm, L.; Sander, C. Fast and simple Monte Carlo algorithm for side chain optimization in proteins: application to model building by homology Proteins: Struct., Funct., Genet. 1992, 14, 213– 223 DOI: 10.1002/prot.340140208There is no corresponding record for this reference.
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333Liang, S.; Grishin, N. V. Side-chain modeling with an optimized scoring function Protein Sci. 2002, 11, 322– 331 DOI: 10.1110/ps.24902333https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XosFyksg%253D%253D&md5=08a7de597b610fddbe4d7cfe533f5be0Side-chain modeling with an optimized scoring functionLiang, Shide; Grishin, Nick V.Protein Science (2002), 11 (2), 322-331CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Modeling side-chain conformations on a fixed protein backbone has a wide application in structure prediction and mol. design. Each effort in this field requires decisions about a rotamer set, scoring function, and search strategy. We have developed a new and simple scoring function, which operates on side-chain rotamers and consists of the following energy terms: contact surface, vol. overlap, backbone dependency, electrostatic interactions, and desolvation energy. The wts. of these energy terms were optimized to achieve the minimal av. root mean square (rms) deviation between the lowest energy rotamer and real side-chain conformation on a training set of high-resoln. protein structures. In the course of optimization, for every residue, its side chain was replaced by varying rotamers, whereas conformations for all other residues were kept as they appeared in the crystal structure. We obtained prediction accuracy of 90.4% for 1, 78.3% for 1+2, and 1.18 Α overall rms deviation. Furthermore, the derived scoring function combined with a Monte Carlo search algorithm was used to place all side chains onto a protein backbone simultaneously. The av. prediction accuracy was 87.9% for 1, 73.2% for 1+2, and 1.34 rms deviation for 30 protein structures. Our approach was compared with available side-chain construction methods and showed improvement over the best among them: 4.4% for 1, 4.7% for 1+2, and 0.21 for rms deviation. We hypothesize that the scoring function instead of the search strategy is the main obstacle in side-chain modeling. Addnl., we show that a more detailed rotamer library is expected to increase 1+2 prediction accuracy but may have little effect on 1 prediction accuracy.
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334Desmet, J.; De Maeyer, M.; Hazes, B.; Lasters, I. The dead-end elimination theorem and its use in protein side-chain positioning Nature 1992, 356, 539– 542 DOI: 10.1038/356539a0334https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK38XisFWls7Y%253D&md5=8da83d753310c7d9881cfbc207a630deThe dead-end elimination theorem and its use in protein side-chain positioningDesmet, Johan; De Maeyer, Marc; Hazes, Bart; Lasters, IgnaceNature (London, United Kingdom) (1992), 356 (6369), 539-42CODEN: NATUAS; ISSN:0028-0836.The authors present a theorem, referred to as the dead-end elimination theorem, which imposes a suitable condition to identify rotamers that cannot be members of the global min. energy conformation. Application of this theorem effectively controls the computational explosion of the rotamer combinatorial problem, thereby allowing the detn. of the global min. energy conformation of a large collection of side chains.
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335Looger, L. L.; Hellinga, H. W. Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics J. Mol. Biol. 2001, 307, 429– 445 DOI: 10.1006/jmbi.2000.4424335https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXhslSns70%253D&md5=3c1cf293c6c128c571e19989e8bd6a4eGeneralized Dead-end Elimination Algorithms Make Large-scale Protein Side-chain Structure Prediction Tractable: Implications for Protein Design and Structural GenomicsLooger, Loren L.; Hellinga, Homme W.Journal of Molecular Biology (2001), 307 (1), 429-445CODEN: JMOBAK; ISSN:0022-2836. (Academic Press)The dead-end elimination (DEE) theorems are powerful tools for the combinatorial optimization of protein side-chain placement in protein design and homol. modeling. In order to reach their full potential, the theorems must be extended to handle very hard problems. We present a suite of new algorithms within the DEE paradigm that significantly extend its range of convergence and reduce run time. As a demonstration, we show that a total protein design problem of 10115 combinations, a hydrophobic core design problem of 10244 combinations, and a side-chain placement problem of 101044 combinations are solved in less than two weeks, a day and a half, and an hour of CPU time, resp. This extends the range of the method by approx. 53, 144 and 851 log-units, resp., using modest computational resources. Small to av.-sized protein domains can now be designed automatically, and side-chain placement calcns. can be solved for nearly all sizes of proteins and protein complexes in the growing field of structural genomics. (c) 2001 Academic Press.
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336de Armas, H. N.; Dewilde, M.; Verbeke, K.; De Maeyer, M.; Declerck, P. J. Study of recombinant antibody fragments and PAI-1 complexes combining protein-protein docking and results from site-directed mutagenesis (vol 15, pg 1105, 2007) Structure 2007, 15, 1339– 1339 DOI: 10.1016/j.str.2007.09.002There is no corresponding record for this reference.
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337Lee, C.; Subbiah, S. Prediction of protein side-chain conformation by packing optimization J. Mol. Biol. 1991, 217, 373– 388 DOI: 10.1016/0022-2836(91)90550-P337https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3MXhtl2gt7o%253D&md5=ecba793ac8fdcc53dddd05b3a077af59Prediction of protein side-chain conformation by packing optimizationLee, Christopher; Subbiah, S.Journal of Molecular Biology (1991), 217 (2), 373-88CODEN: JMOBAK; ISSN:0022-2836.A rapid and completely automatic method was developed for prediction of protein side-chain conformation, applying the simulated annealing algorithm to optimization of side-chain packing (van der Waals) interactions. The method directly attacks the combinatorial problem of simultaneously predicting many residues' conformation, solving in 8 to 12 h problems for which the systematic search would require over 10300 central processing unit years. Over a test set of nine proteins ranging in size from 46 to 323 residues, the program's predictions for side-chain atoms had a root-mean-square (r.m.s.) deviation of 1.77Å overall vs. the native structures. More importantly, the predictions for core residues were esp. accurate, with an r.m.s. value of 1.25Å overall: 80 to 90% of the large hydrophobic side-chains dominating the internal core were correctly predicted, vs. 30 to 40% for most current methods. The predictions' main errors were in surface residues poorly constrained by packing and small residues with greater steric freedom and hydrogen bonding interactions, which were not included in the program's potential function. The van der Waals interactions appear to be the supreme determinant of the arrangement of side-chains in the core, enforcing a unique allowed packing that in every case so far examd. matches the native structure.
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338Ravindranath, P. A.; Forli, S.; Goodsell, D. S.; Olson, A. J.; Sanner, M. F. AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility PLoS Comput. Biol. 2015, 11, e1004586 DOI: 10.1371/journal.pcbi.1004586338https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XmtlajtLc%253D&md5=65b983947e0a16f01a5f9710120376c4AutoDockFR: advances in protein-ligand docking with explicitly specified binding site flexibilityRavindranath, Pradeep Anand; Forli, Stefano; Goodsell, David S.; Olson, Arthur J.; Sanner, Michel F.PLoS Computational Biology (2015), 11 (12), e1004586/1-e1004586/28CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Automated docking of drug-like mols. into receptors is an essential tool in structurebased drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: (1) exponential growth of the search space, demanding more efficient search methods; and (2) increased no. of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR- AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking expts. are based on two datasets: (1) SEQ17 -a receptor diversity set contg. 17 pairs of apo-holo structures; and (2) CDK2 -a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solns. found for 70.6% vs. 35.3% systems on SEQ17, and 76.9%vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in no. of top ranking solns. on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on av. 79.8%of all pairwise at. interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added.
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339Pedersen, J. T.; Moult, J. Genetic algorithms for protein structure prediction Curr. Opin. Struct. Biol. 1996, 6, 227– 231 DOI: 10.1016/S0959-440X(96)80079-0339https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XisVOjsrY%253D&md5=f3bab9ad7238e79ceac0f666bb4c9c9eGenetic algorithms for protein structure predictionPedersen, Jan T.; Moult, JohnCurrent Opinion in Structural Biology (1996), 6 (2), 227-31CODEN: COSBEF; ISSN:0959-440X. (Current Biology)A review with refs. Genetic algorithms are a general class of search methods that mimic natural gene-based optimization mechanisms. Mutation, cross-over and replication operations are performed on strings. When applied to structure to structure prediction, each string describes a particular conformation of a protein mol. There are many ways in which such search methods may be implemented. Recently results show potential for helping with protein structure prediction, but more data are needed before a complete assessment can be made.
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340Kingsford, C. L.; Chazelle, B.; Singh, M. Solving and analyzing side-chain positioning problems using linear and integer programming Bioinformatics 2005, 21, 1028– 1036 DOI: 10.1093/bioinformatics/bti144340https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXis1yjs7c%253D&md5=4f73e52ac5c95f9db71516056390634fSolving and analyzing side-chain positioning problems using linear and integer programmingKingsford, Carleton L.; Chazelle, Bernard; Singh, MonaBioinformatics (2005), 21 (7), 1028-1039CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: Side-chain positioning is a central component of homol. modeling and protein design. In a common formulation of the problem, the backbone is fixed, side-chain conformations come from a rotamer library, and a pairwise energy function is optimized. It is NP-complete to find even a reasonable approx. soln. to this problem. We seek to put this hardness result into practical context. Results: We present an integer linear programming (ILP) formulation of side-chain positioning that allows us to tackle large problem sizes. We relax the integrality constraint to give a polynomial-time linear programming (LP) heuristic. We apply LP to position side chains on native and homologous backbones and to choose side chains for protein design. Surprisingly, when positioning side chains on native and homologous backbones, optimal solns. using a simple, biol. relevant energy function can usually be found using LP. On the other hand, the design problem often cannot be solved using LP directly; however, optimal solns. for large instances can still be found using the computationally more expensive ILP procedure. While different energy functions also affect the difficulty of the problem, the LP/ILP approach is able to find optimal solns. Our anal. is the first large-scale demonstration that LP-based approaches are highly effective in finding optimal (and successive near-optimal) solns. for the side-chain positioning problem.
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341Xu, J.; Jiao, F.; Berger, B. A tree-decomposition approach to protein structure prediction Proc. IEEE Comput. Syst. Bioinform. Conf. 2005, 247– 256 DOI: 10.1109/CSB.2005.9341https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD28%252Fms1Wltg%253D%253D&md5=c0a5e80ff2ed1b79efba6fde09fcf0a9A tree-decomposition approach to protein structure predictionXu Jinbo; Jiao Feng; Berger BonnieProceedings / IEEE Computational Systems Bioinformatics Conference, CSB. IEEE Computational Systems Bioinformatics Conference (2005), (), 247-56 ISSN:1551-7497.This paper proposes a tree decomposition of protein structures, which can be used to efficiently solve two key subproblems of protein structure prediction: protein threading for backbone prediction and protein side-chain prediction. To develop a unified tree-decomposition based approach to these two subproblems, we model them as a geometric neighborhood graph labeling problem. Theoretically, we can have a low-degree polynomial time algorithm to decompose a geometric neighborhood graph G = (V, E) into components with size O( V ((2/3))log V ). The computational complexity of the tree-decomposition based graph labeling algorithms is O( V Delta(tw+1)) where Delta is the average number of possible labels for each vertex and tw( = O( V ((2/3))log V )) the tree width of G. Empirically, tw is very small and the tree-decomposition method can solve these two problems very efficiently. This paper also compares the computational efficiency of the tree-decomposition approach with the linear programming approach to these two problems and identifies the condition under which the tree-decomposition approach is more efficient than the linear programming approach. Experimental result indicates that the tree-decomposition approach is more efficient most of the time.
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342Canutescu, A. A.; Shelenkov, A. A.; Dunbrack, R. L., Jr. A graph-theory algorithm for rapid protein side-chain prediction Protein Sci. 2003, 12, 2001– 2014 DOI: 10.1110/ps.03154503342https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXmvVehs7s%253D&md5=e014e2e53ed1f0a3fc6b5a14e86d2e75A graph-theory algorithm for rapid protein side-chain predictionCanutescu, Adrian A.; Shelenkov, Andrew A.; Dunbrack, Roland L., Jr.Protein Science (2003), 12 (9), 2001-2014CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Fast and accurate side-chain conformation prediction is important for homol. modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the min. energy of these small biconnected components and combining the results to identify the global min. energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34,342 side chains in <7 min of computer time. The total χ1 and χ1 + 2 dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addn. of a more complex energy function and conformational flexibility, leading to increased accuracy.
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343Nagata, K.; Randall, A.; Baldi, P. SIDEpro: a novel machine learning approach for the fast and accurate prediction of side-chain conformations Proteins: Struct., Funct., Genet. 2012, 80, 142– 153 DOI: 10.1002/prot.23170There is no corresponding record for this reference.
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344Mendes, J.; Baptista, A. M.; Carrondo, M. A.; Soares, C. M. Improved modeling of side-chains in proteins with rotamer-based methods: a flexible rotamer model Proteins: Struct., Funct., Genet. 1999, 37, 530– 543 DOI: 10.1002/(SICI)1097-0134(19991201)37:4<530::AID-PROT4>3.3.CO;2-8There is no corresponding record for this reference.
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345Koehl, P.; Delarue, M. Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropy J. Mol. Biol. 1994, 239, 249– 275 DOI: 10.1006/jmbi.1994.1366345https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXkslOks7o%253D&md5=c0a0e04d22960dbdd981e149a6b36f06Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropyKoehl, Patrice; Delarue, MarcJournal of Molecular Biology (1994), 239 (2), 249-75CODEN: JMOBAK; ISSN:0022-2836.Understanding the relations between the conformation of the side-chains and the backbone geometry is crucial for structure prediction as well as for homol. modeling. To attempt to unravel these rules, the authors have developed a method which allows them to predict the position of the side-chains from the coordinates of the main-chain atoms. This method is based on a rotamer library and refines iteratively a conformational matrix of the side-chains of a protein, CM, such that its current element at each cycle CM(ij) gives the probability that side chain i of the protein adopts the conformation of its possible rotamer j. Each residue feels the av. of all possible environments, weighted by their resp. probabilities. The method converges in only a few cycles, thereby deserving the name of self consistent mean field method. Using the rotamer with the highest probability in the optimized conformational matrix to define the conformation of the side-chain leads to the result that on av. 72% of χ1, 75% of χ2 and 62% of χ1+2 are correctly predicted for a set of 30 proteins. Tests with six pairs of homologous proteins have shown that the method is quite successful even when the protein backbone deviates from the correct conformation. The second application of the optimized conformational matrix was to provide ests. of the conformational entropy of the side-chains in the folded state of the protein. The relevance of this entropy is discussed.
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346Desmet, J.; Spriet, J.; Lasters, I. Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization Proteins: Struct., Funct., Genet. 2002, 48, 31– 43 DOI: 10.1002/prot.10131346https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XksFGkt7w%253D&md5=5dde851593e9a3aacf429aa82c9bc43cFast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimizationDesmet, Johan; Spriet, Jan; Lasters, IgnaceProteins: Structure, Function, and Genetics (2002), 48 (1), 31-43CODEN: PSFGEY; ISSN:0887-3585. (Wiley-Liss, Inc.)We have developed an original method for global optimization of protein side-chain conformations, called the Fast and Accurate Side-Chain Topol. and Energy Refinement (FASTER) method. The method operates by systematically overcoming local min. of increasing order. Comparison of the FASTER results with those of the dead-end elimination (DEE) algorithm showed that both methods produce nearly identical results, but the FASTER algorithm is 100-1000 times faster than the DEE method and scales in a stable and favorable way as a function of protein size. We also show that low-order local min. may be almost as accurate as the global min. when evaluated against exptl. detd. structures. In addn., the new algorithm provides significant information about the conformational flexibility of individual side-chains. We obsd. that strictly rigid side-chains are concd. mainly in the core of the protein, whereas highly flexible side-chains are found almost exclusively among solvent-oriented residues.
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347Gront, D.; Kmiecik, S.; Blaszczyk, M.; Ekonomiuk, D.; Kolinski, A. Optimization of protein models Wires Comput. Mol. Sci. 2012, 2, 479– 493 DOI: 10.1002/wcms.1090There is no corresponding record for this reference.
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348Porebski, P. J.; Cymborowski, M.; Pasenkiewicz-Gierula, M.; Minor, W. Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations Acta Crystallogr. D Struct. Biol. 2016, 72, 266– 280 DOI: 10.1107/S2059798315024730348https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvFymsLc%253D&md5=362cd351b9f9e6ac84c82475c98d4780Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformationsPorebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, WladekActa Crystallographica, Section D: Structural Biology (2016), 72 (2), 266-280CODEN: ACSDAD; ISSN:2059-7983. (International Union of Crystallography)Improvements in crystallog. hardware and software have allowed automated structure-soln. pipelines to approach a near-'one-click' experience for initial detn. of macromol. structures. However, in many cases the resulting initial model requires laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallog. context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from exptl. data and prior information about rotamer frequencies to find optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-d. term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of highly discriminatory nature of electron-d. maps. This method has been implemented in program Fitmunk, which uses extensive conformational sampling. This improves accuracy of modeling and makes it a versatile tool for crystallog. model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving quality of crystallog. protein models, esp. at medium and low resolns.
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349Gront, D.; Kolinski, A. BioShell--a package of tools for structural biology computations Bioinformatics 2006, 22, 621– 622 DOI: 10.1093/bioinformatics/btk037There is no corresponding record for this reference.
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350Gront, D.; Kolinski, A. Utility library for structural bioinformatics Bioinformatics 2008, 24, 584– 585 DOI: 10.1093/bioinformatics/btm627350https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVKit7s%253D&md5=a8347823bb3c703344e98404c39ee28dUtility library for structural bioinformaticsGront, Dominik; Kolinski, AndrzejBioinformatics (2008), 24 (4), 584-585CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: In this Note we present a new software library for structural bioinformatics. The library contains programs, computing sequence- and profile-based alignments and a variety of structural calcns. with user-friendly handling of various data formats. The software organization is very flexible. Algorithms are written in Java language and may be used by Java programs. Moreover the modules can be accessed from Jython (Python scripting language implemented in Java) scripts. Finally, the new version of BioShell delivers several utility programs that can do typical bioinformatics task from a command-line level.
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351Eswar, N.; Webb, B.; Marti-Renom, M. A.; Madhusudhan, M. S.; Eramian, D.; Shen, M. Y.; Pieper, U.; Sali, A. Comparative protein structure modeling using MODELLER. Curr. Protoc. Protein Sci. 2007, Chapter 2, Unit 2 9. DOI: 10.1002/0471140864.ps0209s50There is no corresponding record for this reference.
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352Webb, B.; Sali, A. Protein structure modeling with MODELLER Methods Mol. Biol. 2014, 1137, 1– 15 DOI: 10.1007/978-1-4939-0366-5_1352https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXns12isrc%253D&md5=19709a3ffefe33fd6e5d8506258bd6f0Protein Structure Modeling with MODELLERWebb, Benjamin; Sali, AndrejMethods in Molecular Biology (New York, NY, United States) (2014), 1137 (Protein Structure Prediction), 1-15CODEN: MMBIED; ISSN:1940-6029. (Springer)Genome sequencing projects have resulted in a rapid increase in the no. of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at at. resoln. using exptl. structure detn. methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In this chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.
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353Peterson, R. W.; Dutton, P. L.; Wand, A. J. Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer library Protein Sci. 2004, 13, 735– 751 DOI: 10.1110/ps.03250104353https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXhvVCmtbo%253D&md5=5ed655f76c02436e899a17b47a425d24Improved side-chain prediction accuracy using an ab initio potential energy function and a very large rotamer libraryPeterson, Ronald W.; Dutton, P. Leslie; Wand, A. JoshuaProtein Science (2004), 13 (3), 735-751CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Accurate prediction of the placement and conformations of protein side chains given only the backbone trace has a wide range of uses in protein design, structure prediction, and functional anal. Prediction has most often relied on discrete rotamer libraries so that rapid fitness of side-chain rotamers can be assessed against some scoring function. Scoring functions are generally based on exptl. parameters from small-mol. studies or empirical parameters based on detd. protein structures. Here, we describe the NCN algorithm for predicting the placement of side chains. A predominantly first-principles approach was taken to develop the potential energy function incorporating van der Waals and electrostatics based on the OPLS parameters, and a hydrogen bonding term. The only empirical knowledge used is the frequency of rotameric states from the PDB. The rotamer library includes nearly 50,000 rotamers, and is the most extensive discrete library used to date. Although the computational time tends to be longer than most other algorithms, the overall accuracy exceeds all algorithms in the literature when placing rotamers on an accurate backbone trace. Considering only the most buried residues, 80% of the total residues tested, the placement accuracy reaches 92% for χ1, and 83% for χ1 + 2, and an overall RMS deviation of 1 Å. Addnl., we show that if information is available to restrict χ1 to one rotamer well, then this algorithm can generate structures with an av. RMS deviation of 1.0 Å for all heavy side-chains atoms and a corresponding overall χ1 + 2 accuracy of 85.0%.
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354Lu, M.; Dousis, A. D.; Ma, J. OPUS-Rota: a fast and accurate method for side-chain modeling Protein Sci. 2008, 17, 1576– 1585 DOI: 10.1110/ps.035022.108354https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtV2rsb%252FL&md5=2b9192640e8c51e4bec688d5f32a19ceOPUS-Rota: a fast and accurate method for side-chain modelingLu, Mingyang; Dousis, Athanasios D.; Ma, JianpengProtein Science (2008), 17 (9), 1576-1585CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)In this paper, we introduce a fast and accurate side-chain modeling method, named OPUS-Rota. In a benchmark comparison with the methods SCWRL, NCN, LGA, SPRUCE, Rosetta, and SCAP, OPUS-Rota is shown to be much faster than all the methods except SCWRL, which is comparably fast. In terms of overall χ1 and χ1+2 accuracies, however, OPUS-Rota is 5.4 and 8.8 percentage points better, resp., than SCWRL. Compared with NCN, which has the best accuracy in the literature, OPUS-Rota is 1.6 percentage points better for overall χ1+2 but 0.3 percentage points weaker for overall χ1. Hence, our algorithm is much more accurate than SCWRL with similar execution speed, and it has accuracy comparable to or better than the most accurate methods in the literature, but with a runtime that is one or two orders of magnitude shorter. In addn., OPUS-Rota consistently outperforms SCWRL on the Wallner and Elofsson homol.-modeling benchmark set when the sequence identity is greater than 40%. We hope that OPUS-Rota will contribute to high-accuracy structure refinement, and the computer program is freely available for academic users.
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355Wallner, B.; Elofsson, A. All are not equal: a benchmark of different homology modeling programs Protein Sci. 2005, 14, 1315– 1327 DOI: 10.1110/ps.041253405355https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXjvFSqt74%253D&md5=25e82375ff92544f4f0e4bf2141e48b9All are not equal: A benchmark of different homology modeling programsWallner, Bjoern; Elofsson, ArneProtein Science (2005), 14 (5), 1315-1327CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)Modeling a protein structure based on a homologous structure is a std. method in structural biol. today. In this process an alignment of a target protein sequence onto the structure of a template(s) is used as input to a program that constructs a 3D model. It has been shown that the most important factor in this process is the correctness of the alignment and the choice of the best template structure(s), while it is generally believed that there are no major differences between the best modeling programs. Therefore, a large no. of studies to benchmark the alignment qualities and the selection process have been performed. However, to our knowledge no large-scale benchmark has been performed to evaluate the programs used to transform the alignment to a 3D model. In this study, a benchmark of six different homol. modeling programs-Modeller, SegMod/ENCAD, SWISS-MODEL, 3D-JIGSAW, nest, and Builder-is presented. The performance of these programs is evaluated using physiochem. correctness and structural similarity to the correct structure. From our anal. it can be concluded that no single modeling program outperform the others in all tests. However, it is quite clear that three modeling programs, Modeller, nest, and SegMod/ENCAD, perform better than the others. Interestingly, the fastest and oldest modeling program, SegMod/ENCAD, performs very well, although it was written more than 10 years ago and has not undergone any development since. It can also be obsd. that none of the homol. modeling programs builds side chains as well as a specialized program (SCWRL), and therefore there should be room for improvement.
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356Liang, S.; Zheng, D.; Zhang, C.; Standley, D. M. Fast and accurate prediction of protein side-chain conformations Bioinformatics 2011, 27, 2913– 2914 DOI: 10.1093/bioinformatics/btr482356https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsLvN&md5=1c096f7ffd16004f918039967885dbc2Fast and accurate prediction of protein side-chain conformationsLiang, Shide; Zheng, Dandan; Zhang, Chi; Standley, Daron M.Bioinformatics (2011), 27 (20), 2913-2914CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: We developed a fast and accurate side-chain modeling program [Optimized Side Chain Atomic eneRgy (OSCAR)-star] based on orientation-dependent energy functions and a rigid rotamer model. The av. computing time was 18 s per protein for 218 test proteins with higher prediction accuracy (1.1% increase for χ1 and 0.8% increase for χ1+2) than the best performing program developed by other groups. We show that the energy functions, which were calibrated to tolerate the discrete errors of rigid rotamers, are appropriate for protein loop selection, esp. for decoys without extensive structural refinement. Availability: OSCAR-star and the 218 test proteins are available for download at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
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357Moore, B. L.; Kelley, L. A.; Barber, J.; Murray, J. W.; MacDonald, J. T. High-quality protein backbone reconstruction from alpha carbons using Gaussian mixture models J. Comput. Chem. 2013, 34, 1881– 1889 DOI: 10.1002/jcc.23330357https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXot1Gjtr4%253D&md5=26300aac868cfdad19941fb80b34365cHigh quality protein backbone reconstruction from alpha carbons using Gaussian mixture modelsMoore, Benjamin L.; Kelley, Lawrence A.; Barber, James; Murray, James W.; MacDonald, James T.Journal of Computational Chemistry (2013), 34 (22), 1881-1889CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse-grained protein structure models offer increased efficiency in structural modeling, but these must be coupled with fast and accurate methods to revert to a full-atom structure. Here, we present a novel algorithm to reconstruct mainchain models from C traces. This has been parameterized by fitting Gaussian mixt. models (GMMs) to short backbone fragments centered on idealized peptide bonds. The method we have developed is statistically significantly more accurate than several competing methods, both in terms of RMSD values and dihedral angle differences. The method produced Ramachandran dihedral angle distributions that are closer to that obsd. in real proteins and better Phaser mol. replacement log-likelihood gains. Amino acid residue sidechain reconstruction accuracy using SCWRL4 was found to be statistically significantly correlated to backbone reconstruction accuracy. Finally, the PD2 method was found to produce significantly lower energy full-atom models using Rosetta which has implications for multiscale protein modeling using coarse-grained models. A webserver and C++ source code is freely available for noncommercial use from: http://www.sbg.bio.ic.ac.uk/phyre2/PD2_ca2main/.
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358Xiang, Z. X.; Honig, B. Extending the accuracy limits of prediction for side-chain conformations (vol 311, pg 421, 2001) J. Mol. Biol. 2001, 312, 419– 419 DOI: 10.1006/jmbi.2001.4985There is no corresponding record for this reference.
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359Wang, J. M.; Wolf, R. M.; Caldwell, J. W.; Kollman, P. A.; Case, D. A. Development and testing of a general amber force field J. Comput. Chem. 2004, 25, 1157– 1174 DOI: 10.1002/jcc.20035359https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXksFakurc%253D&md5=2992017a8cf51f89290ae2562403b115Development and testing of a general Amber force fieldWang, Junmei; Wolf, Romain M.; Caldwell, James W.; Kollman, Peter A.; Case, David A.Journal of Computational Chemistry (2004), 25 (9), 1157-1174CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)We describe here a general Amber force field (GAFF) for org. mols. GAFF is designed to be compatible with existing Amber force fields for proteins and nucleic acids, and has parameters for most org. and pharmaceutical mols. that are composed of H, C, N, O, S, P, and halogens. It uses a simple functional form and a limited no. of atom types, but incorporates both empirical and heuristic models to est. force consts. and partial at. charges. The performance of GAFF in test cases is encouraging. In test I, 74 crystallog. structures were compared to GAFF minimized structures, with a root-mean-square displacement of 0.26 Å, which is comparable to that of the Tripos 5.2 force field (0.25 Å) and better than those of MMFF 94 and CHARMm (0.47 and 0.44 Å, resp.). In test II, gas phase minimizations were performed on 22 nucleic acid base pairs, and the minimized structures and intermol. energies were compared to MP2/6-31G* results. The RMS of displacements and relative energies were 0.25 Å and 1.2 kcal/mol, resp. These data are comparable to results from Parm99/RESP (0.16 Å and 1.18 kcal/mol, resp.), which were parameterized to these base pairs. Test III looked at the relative energies of 71 conformational pairs that were used in development of the Parm99 force field. The RMS error in relative energies (compared to expt.) is about 0.5 kcal/mol. GAFF can be applied to wide range of mols. in an automatic fashion, making it suitable for rational drug design and database searching.
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360Li, Y.; Zhang, Y. REMO: A new protocol to refine full atomic protein models from C-alpha traces by optimizing hydrogen-bonding networks Proteins: Struct., Funct., Genet. 2009, 76, 665– 676 DOI: 10.1002/prot.22380There is no corresponding record for this reference.
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361Maupetit, J.; Gautier, R.; Tuffery, P. SABBAC: online structural alphabet-based protein backbone reconstruction from alpha-carbon trace Nucleic Acids Res. 2006, 34, W147– W151 DOI: 10.1093/nar/gkl289361https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xps1yhtrk%253D&md5=ed09065314c2656171a6c7020f3c6954SABBAC: online Structural Alphabet-based protein BackBone reconstruction from Alpha-Carbon traceMaupetit, Julien; Gautier, R.; Tuffery, PierreNucleic Acids Research (2006), 34 (Web Server), W147-W151CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)SABBAC is an online service devoted to protein backbone reconstruction from alpha-carbon trace. It is based on the assembly of fragments taken from a library of reduced size, selected from the encoding of the protein trace in a hidden Markov model-derived structural alphabet. The assembly of the fragments is achieved by a greedy algorithm, using an energy-based scoring. Alpha-carbon coordinates remain unaffected. SABBAC simply positions the missing backbone atoms, no further refinement is performed. From the authors' tests, SABBAC performs equal or better than other similar online approach and is robust to deviations on the alpha-carbon coordinates. It can be accessed at http://bioserv.rpbs.jussieu.fr/SABBAC.html.
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362Xu, J. B. Rapid protein side-chain packing via tree decomposition Research in Computational Molecular Biology, Proceedings 2005, 3500, 423– 439 DOI: 10.1007/11415770_32There is no corresponding record for this reference.
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363Krivov, G. G.; Shapovalov, M. V.; Dunbrack, R. L., Jr. Improved prediction of protein side-chain conformations with SCWRL4 Proteins: Struct., Funct., Genet. 2009, 77, 778– 795 DOI: 10.1002/prot.22488363https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlSru7nN&md5=515b93d349447312958d8d7ebfe784c7Improved prediction of protein side-chain conformations with SCWRL4Krivov, Georgii G.; Shapovalov, Maxim V.; Dunbrack, Roland L., Jr.Proteins: Structure, Function, and Bioinformatics (2009), 77 (4), 778-795CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Detn. of side-chain conformations is an important step in protein structure prediction and protein design. Many such methods have been presented, although only a small no. are in widespread use. SCWRL is one such method, and the SCWRL3 program (2003) has remained popular because of its speed, accuracy, and ease-of-use for the purpose of homol. modeling. However, higher accuracy at comparable speed is desirable. This has been achieved in a new program SCWRL4 through: (1) a new backbone-dependent rotamer library based on kernel d. ests.; (2) averaging over samples of conformations about the positions in the rotamer library; (3) a fast anisotropic hydrogen bonding function; (4) a short-range, soft van der Waals atom-atom interaction potential; (5) fast collision detection using k-discrete oriented polytopes; (6) a tree decompn. algorithm to solve the combinatorial problem; and (7) optimization of all parameters by detg. the interaction graph within the crystal environment using symmetry operators of the crystallog. space group. Accuracies as a function of electron d. of the side chains demonstrate that side chains with higher electron d. are easier to predict than those with low-electron d. and presumed conformational disorder. For a testing set of 379 proteins, 86% of χ1 angles and 75% of χ1+2 angles are predicted correctly within 40° of the X-ray positions. Among side chains with higher electron d. (25-100th percentile), these nos. rise to 89 and 80%. The new program maintains its simple command-line interface, designed for homol. modeling, and is now available as a dynamic-linked library for incorporation into other software programs. Proteins 2009. © 2009 Wiley-Liss, Inc.
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364Pearlman, D. A.; Case, D. A.; Caldwell, J. W.; Ross, W. S.; Cheatham, T. E.; Debolt, S.; Ferguson, D.; Seibel, G.; Kollman, P. Amber, a Package of Computer-Programs for Applying Molecular Mechanics, Normal-Mode Analysis, Molecular-Dynamics and Free-Energy Calculations to Simulate the Structural and Energetic Properties of Molecules Comput. Phys. Commun. 1995, 91, 1– 41 DOI: 10.1016/0010-4655(95)00041-D364https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXps1Wrtrw%253D&md5=8dc71939a46bbc17d5da08782d4e6ec8"AMBER", a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to stimulate the structural and energetic properties of moleculesPearlman, David A.; Case, David A.; Caldwell, James W.; Ross, Wilson S.; Cheatham, Thomas E. III; DeBolt, Steve; Ferguson, David; Seibel, George; Kollman, PeterComputer Physics Communications (1995), 91 (1-3), 1-42CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier)We describe the development, current features, and some directions for future development of the AMBER package of computer programs. This package has evolved from a program that was constructed to do Assisted Model Building and Energy Refinement to a group of programs embodying a no. of the powerful tools of modern computational chem.-mol. dynamics and free energy calcns.
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365Skolnick, J.; Kolinski, A.; Ortiz, A. R. MONSSTER: a method for folding globular proteins with a small number of distance restraints J. Mol. Biol. 1997, 265, 217– 241 DOI: 10.1006/jmbi.1996.0720365https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2sXpvVWjtg%253D%253D&md5=c6debfd1961a7c24893d001cc4339eacMONSSTER: a method for folding globular proteins with a small number of distance restraintsSkolnick, Jeffrey; Kolinski, Andrzej; Ortiz, Angle R.Journal of Molecular Biology (1997), 265 (2), 217-241CODEN: JMOBAK; ISSN:0022-2836. (Academic)The MONSSTER (MOdeling of New Structures from Secondary and TErtiary Restraints) method for folding of proteins using a small no. of long-distance restraints (which can be up to seven times less than the total no. of residues) and some knowledge of the secondary structure of regular fragments is described. The method employs a high-coordination lattice representation of the protein chain that incorporates a variety of potentials designed to produce protein-like behavior. These include statistical preferences for secondary structure, side-chain burial interactions, and a hydrogen-bond potential. Using this algorithm, several globular proteins (1ctf, 2gbl, 2trx, 3fxn, 1mba, 1pcy and 6pti) have been folded to moderate-resoln., native-like compact state. For example, the 68 residue 1ctf mol. having ten loosely defined, long-range restraints was reproducibly obtained with a Cα-backbone root-mean-square deviation (RMSD) from native of about 4Å. Flavodoxin with 35 restraints has been folded to structures whose av. RMSD is 4.28 Å. Furthermore, using just 20 restraints, myoglobin, which is a 146 residue helical protein, has been folded to structures whose av. RMSD from native is 5.65 Å. Plastocyanin with 25 long-range restraints adopts conformations whose av. RMSD is 5.44 Å. Possible applications of the proposed approach to the refinement of structures from NMR data, homol. model-building and the detn. of tertiary structure when the secondary structure and a small no. of restraints are predicted are briefly discussed.
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366Wan, C. K.; Han, W.; Wu, Y. D. Parameterization of PACE Force Field for Membrane Environment and Simulation of Helical Peptides and Helix-Helix Association J. Chem. Theory Comput. 2012, 8, 300– 313 DOI: 10.1021/ct2004275366https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVelt77O&md5=6a13f21ca23aeb96d637e36e6179b4a6Parameterization of PACE Force Field for Membrane Environment and Simulation of Helical Peptides and Helix-Helix AssociationWan, Cheuk-Kin; Han, Wei; Wu, Yun-DongJournal of Chemical Theory and Computation (2012), 8 (1), 300-313CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The recently developed PACE force field was further parametrized so that it can be applied to the studies of membrane systems. Parameters for the interactions between united-atom protein particles and lipid hydrophobic tails were developed by reproducing the solvation free energies of small org. mols. in hexadecane. Interactions between protein particles and lipid heads were parametrized by fitting the potential of mean force of the corresponding all-atom simulation. The force field was applied to the study of five helical peptides in membrane environments. The calcd. tilt angles of WALP and GWALP and their mutations are in good agreement with exptl. data. The assocn. of two glycophorin A (GpA) helixes was simulated for 6 μs. Root-mean-square-deviation of the simulated dimer from the NMR structure was found to be 0.272 nm, better than all results obtained so far. These findings demonstrate the high accuracy and applicability of the PACE force field in studying membrane proteins.
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367Han, W.; Schulten, K. Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains J. Chem. Theory Comput. 2012, 8, 4413– 4424 DOI: 10.1021/ct300696c367https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsVylu7vF&md5=7cfa25a7a8d28093a933fba246cba4caFurther Optimization of a Hybrid United-Atom and Coarse-Grained Force Field for Folding Simulations: Improved Backbone Hydration and Interactions between Charged Side ChainsHan, Wei; Schulten, KlausJournal of Chemical Theory and Computation (2012), 8 (11), 4413-4424CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)PACE, a hybrid force field that couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve its efficiency for folding simulations. Backbone hydration parameters have been reoptimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE to provide a more realistic description of interactions between charged groups. Using replica exchange mol. dynamics, ab initio folding using the new PACE has been achieved for seven small proteins (16-23 residues) with different structural motifs. Exptl. data about folded states, such as their stability at room temp., m.p., and NMR nuclear Overhauser effect constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temp. has been made with expts., through std. mol. dynamics simulations, showing that the new PACE may accelerate the actual folding kinetics 5-10-fold, permitting now the study of folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, α3D, in multiple 10-30 μs simulations, to its native states (Cα root-mean-square deviation of ∼0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.
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368Perez, A.; Marchan, I.; Svozil, D.; Sponer, J.; Cheatham, T. E., 3rd; Laughton, C. A.; Orozco, M. Refinement of the AMBER force field for nucleic acids: improving the description of alpha/gamma conformers Biophys. J. 2007, 92, 3817– 3829 DOI: 10.1529/biophysj.106.097782368https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXls1ygu7Y%253D&md5=e0f8d87e5fe7710e59cc41f5e8c25f7bRefinement of the AMBER force field for nucleic acids: improving the description of α/γ conformersPerez, Alberto; Marchan, Ivan; Svozil, Daniel; Sponer, Jiri; Cheatham, Thomas E., III; Laughton, Charles A.; Orozco, ModestoBiophysical Journal (2007), 92 (11), 3817-3829CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We present here the parmbsc0 force field, a refinement of the AMBER parm99 force field, where emphasis has been made on the correct representation of the α/γ concerted rotation in nucleic acids (NAs). The modified force field corrects overpopulations of the α/γ = (g+,t) backbone that were seen in long (more than 10 ns) simulations with previous AMBER parameter sets (parm94-99). The force field has been derived by fitting to high-level quantum mech. data and verified by comparison with very high-level quantum mech. calcns. and by a very extensive comparison between simulations and exptl. data. The set of validation simulations includes two of the longest trajectories published to date for the DNA duplex (200 ns each) and the largest variety of NA structures studied to date (15 different NA families and 97 individual structures). The total simulation time used to validate the force field includes near 1 μs of state-of-the-art mol. dynamics simulations in aq. soln.
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369Dans, P. D.; Zeida, A.; Machado, M. R.; Pantano, S. A Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit Electrostatics J. Chem. Theory Comput. 2010, 6, 1711– 1725 DOI: 10.1021/ct900653p369https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXkslKgsrk%253D&md5=1544bb59f4bceedf250ccc86e9b2b15fA Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit ElectrostaticsDans, Pablo D.; Zeida, Ari; Machado, Matias R.; Pantano, SergioJournal of Chemical Theory and Computation (2010), 6 (5), 1711-1725CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Coarse-grain (CG) techniques allow considerable extension of the accessible size and time scales in simulations of biol. systems. Although many CG representations are available for the most common biomacromols., very few have been reported for nucleic acids. Here, the authors present a CG model for mol. dynamics simulations of DNA on the multi-microsecond time scale. The authors' model maps the complexity of each nucleotide onto six effective superatoms keeping the "chem. sense" of specific Watson-Crick recognition. Mol. interactions are evaluated using a classical Hamiltonian with explicit electrostatics calcd. under the framework of the generalized Born approach. This CG representation is able to accurately reproduce exptl. structures, breathing dynamics, and conformational transitions from the A to the B form in double helical fragments. The model achieves a good qual. reprodn. of temp.-driven melting and its dependence on size, ionic strength, and sequence specificity. Reconstruction of atomistic models from CG trajectories give remarkable agreement with structural, dynamic, and energetic features obtained from fully atomistic simulation, opening the possibility to acquire nearly at. detail data from CG trajectories.
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370Predeus, A. V.; Gul, S.; Gopal, S. M.; Feig, M. Conformational sampling of peptides in the presence of protein crowders from AA/CG-multiscale simulations J. Phys. Chem. B 2012, 116, 8610– 8620 DOI: 10.1021/jp300129u370https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktVynsb8%253D&md5=1422e75e835e493a2d9a6c2cdb266a1cConformational Sampling of Peptides in the Presence of Protein Crowders from AA/CG-Multiscale SimulationsPredeus, Alexander V.; Gul, Seref; Gopal, Srinivasa M.; Feig, MichaelJournal of Physical Chemistry B (2012), 116 (29), 8610-8620CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Macromol. crowding is recognized as an important factor influencing folding and conformational dynamics of proteins and nucleic acids. Previous views of crowding have focused on the mostly entropic vol. exclusion effect of crowding, but recent studies are indicating the importance of enthalpic effects, in particular, changes in electrostatic interactions due to crowding. Here, temp. replica exchange mol. dynamics simulations of trp-cage and melittin in the presence of explicit protein crowders are presented to further examine the effect of protein crowders on peptide dynamics. The simulations involve a three-component multiscale modeling scheme where the peptides are represented at an atomistic level, the crowder proteins at a coarse-grained level, and the surrounding aq. solvent as implicit solvent. This scheme optimally balances a phys. realistic description for the peptide with computational efficiency. The multiscale simulations were compared with simulations of the same peptides in different dielec. environments with dielec. consts. ranging from 5 to 80. It is found that the sampling in the presence of the crowders resembles sampling with reduced dielec. consts. between 10 and 40. Furthermore, diverse conformational ensembles are generated in the presence of crowders including partially unfolded states for trp-cage. These findings emphasize the importance of enthalpic interactions over vol. exclusion effects in describing the effects of cellular crowding.
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371Zacharias, M. Protein-protein docking with a reduced protein model accounting for side-chain flexibility Protein Sci. 2003, 12, 1271– 1282 DOI: 10.1110/ps.0239303371https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXktV2lsL4%253D&md5=c96e82d1896942dc8bcc137e3ee87238Protein-protein docking with a reduced protein model accounting for side-chain flexibilityZacharias, MartinProtein Science (2003), 12 (6), 1271-1282CODEN: PRCIEI; ISSN:0961-8368. (Cold Spring Harbor Laboratory Press)A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking min. on the protein surfaces. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chem. character. Energy minimization of protein test complexes in the reduced representation results in geometries close to expt. with backbone root mean square deviations (RMSDs) of ∼1 to 3 Å for the mobile protein partner from the exptl. geometry. For most test cases, the energy-minimized exptl. structure scores among the top five energy min. in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a soln. within ∼2 to 3.5 Å RMSD of the full mobile partner from the exptl. geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.
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372Lin, Z. X.; Gunsteren, W. F. Refinement of the Application of the GROMOS 54A7 Force Field to beta-Peptides J. Comput. Chem. 2013, 34, 2796– 2805 DOI: 10.1002/jcc.23459There is no corresponding record for this reference.
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373Fiorucci, S.; Zacharias, M. Binding site prediction and improved scoring during flexible protein-protein docking with ATTRACT Proteins: Struct., Funct., Genet. 2010, 78, 3131– 3139 DOI: 10.1002/prot.22808373https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVSqsbrN&md5=26aaea3a7c1144176e7ebcf855b89ce8Binding site prediction and improved scoring during flexible protein-protein docking with ATTRACTFiorucci, Sebastien; Zacharias, MartinProteins: Structure, Function, and Bioinformatics (2010), 78 (15), 3131-3139CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)The ATTRACT protein-protein docking program combined with a coarse-grained protein model has been used to predict protein-protein complex structures in CAPRI rounds 13-19. For six targets acceptable or better quality solns. have been submitted (high quality predictions for targets 32, 40, 41, and 42). The improved performance compared to previous rounds can be attributed in part to the inclusion of conformational flexibility during systematic searches and an optimized scoring function. In addn., a recently developed method for the prediction of putative protein binding sites based on the electrostatic penalty to place neutral low dielec. probes on the protein surface was applied to the most recent targets. The approach resulted in useful predictions of putative binding sites that can help to limit the systematic docking searches. Possible improvements of the docking approach in particular at the scoring and refinement steps are discussed.
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374Maupetit, J.; Tuffery, P.; Derreumaux, P. A coarse-grained protein force field for folding and structure prediction Proteins: Struct., Funct., Genet. 2007, 69, 394– 408 DOI: 10.1002/prot.21505374https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtVykt7vL&md5=e6769e5f853e816fe0eafa13e9e4fed2A coarse-grained protein force field for folding and structure predictionMaupetit, Julien; Tuffery, P.; Derreumaux, PhilippeProteins: Structure, Function, and Bioinformatics (2007), 69 (2), 394-408CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)We have revisited the protein coarse-grained optimized potential for efficient structure prediction (OPEP). The training and validation sets consist of 13 and 16 protein targets. Because optimization depends on details of how the ensemble of decoys is sampled, trial conformations are generated by mol. dynamics, threading, greedy, and Monte Carlo simulations, or taken from publicly available databases. The OPEP parameters are varied by a genetic algorithm using a scoring function which requires that the native structure has the lowest energy, and the native-like structures have energy higher than the native structure but lower than the remote conformations. Overall, we find that OPEP correctly identifies 24 native or native-like states for 29 targets and has very similar capability to the all-atom discrete optimized protein energy model (DOPE), found recently to outperform five currently used energy models.
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375Goga, N.; Melo, M. N.; Rzepiela, A. J.; de Vries, A. H.; Hadar, A.; Marrink, S. J.; Berendsen, H. J. Benchmark of Schemes for Multiscale Molecular Dynamics Simulations J. Chem. Theory Comput. 2015, 11, 1389– 1398 DOI: 10.1021/ct501102b375https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXkt1Oit7Y%253D&md5=89403c635fecbbd481ab6be9fb96b691Benchmark of Schemes for Multiscale Molecular Dynamics SimulationsGoga, N.; Melo, M. N.; Rzepiela, A. J.; de Vries, A. H.; Hadar, A.; Marrink, S. J.; Berendsen, H. J. C.Journal of Chemical Theory and Computation (2015), 11 (4), 1389-1398CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)In multiscale mol. dynamics simulations the accuracy of detailed models is combined with the efficiency of a reduced representation. For several applications - namely those of sampling enhancement - it is desirable to combine fine-grained (FG) and coarse-grained (CG) approaches into a single hybrid approach with an adjustable mixing parameter. We present a benchmark of three algorithms that use a mixing of the two representation layers using a Lagrangian formalism. The three algorithms use three different approaches for keeping the particles at the FG level of representation together: (1) addn. of forces, (2) mass scaling, and (3) temp. scaling. The benchmark is applied to liq. hexadecane and includes an evaluation of the av. configurational entropy of the FG and CG subsystems. The temp.-scaling scheme achieved a 3-fold sampling speedup with little deviation of FG properties. The addn.-of-forces scheme kept FG properties the best but provided little sampling speedup. The mass-scaling scheme yielded a 5-fold speedup but deviated the most from FG properties.
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376Nielsen, S. O.; Bulo, R. E.; Moore, P. B.; Ensing, B. Recent progress in adaptive multiscale molecular dynamics simulations of soft matter Phys. Chem. Chem. Phys. 2010, 12, 12401– 12414 DOI: 10.1039/c004111d376https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1OgtrbL&md5=6484a83415e3732fb9cd89b039aa06d8Recent progress in adaptive multiscale molecular dynamics simulations of soft matterNielsen, Steven O.; Bulo, Rosa E.; Moore, Preston B.; Ensing, BerndPhysical Chemistry Chemical Physics (2010), 12 (39), 12401-12414CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)A review. Understanding mesoscopic phenomena in terms of the fundamental motions of atoms and electrons poses a severe challenge for mol. simulation. This challenge is being met by multiscale modeling techniques that aim to bridge between the microscopic and mesoscopic time and length scales. In such techniques different levels of theory are combined to describe a system at a no. of scales or resolns. Here we review recent advancements in adaptive hybrid simulations, in which the different levels are used in sep. spatial domains and matter can diffuse from one region to another with an accompanying resoln. change. We discuss what it means to simulate such a system, and how to enact the resoln. changes. We show how to construct efficient adaptive hybrid quantum mechanics/mol. mechanics (QM/MM) and atomistic/coarse grain (AA/CG) mol. dynamics methods that use an intermediate healing region to smoothly couple the regions together. This coupling is formulated to use only the native forces inherent to each region. The total energy is conserved through the use of auxiliary bookkeeping terms. Error control, and the choice of time step and healing region width, is obtained by careful anal. of the energy flow between the different representations. We emphasize the CG AA reverse mapping problem and show how this problem is resolved through the use of rigid atomistic fragments located within each CG particle whose orientation is preconditioned for a possible resoln. change through a rotational dynamics scheme. These advancements are shown to enable the adaptive hybrid multiscale mol. dynamics simulation of macromol. soft matter systems.
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377Zhang, Y. Template-based modeling and free modeling by I-TASSER in CASP7 Proteins: Struct., Funct., Genet. 2007, 69, 108– 117 DOI: 10.1002/prot.21702There is no corresponding record for this reference.
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378Kim, D. E.; Chivian, D.; Baker, D. Protein structure prediction and analysis using the Robetta server Nucleic Acids Res. 2004, 32, W526– 531 DOI: 10.1093/nar/gkh468378https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXlvFKmsrY%253D&md5=198eb7740579b1da7ad0b15616aae22dProtein structure prediction and analysis using the Robetta serverKim, David E.; Chivian, Dylan; Baker, DavidNucleic Acids Research (2004), 32 (Web Server), W526-W531CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and anal. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Exptl. NMR constraints data can also be submitted with a query sequence for RosettaNMR de novo structure detn. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.
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379Kelley, L. A.; Mezulis, S.; Yates, C. M.; Wass, M. N.; Sternberg, M. J. The Phyre2 web portal for protein modeling, prediction and analysis Nat. Protoc. 2015, 10, 845– 858 DOI: 10.1038/nprot.2015.053379https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnvFSqurs%253D&md5=e69b1b5c799cc3b8e3a562c90299a813The Phyre2 web portal for protein modeling, prediction and analysisKelley, Lawrence A.; Mezulis, Stefans; Yates, Christopher M.; Wass, Mark N.; Sternberg, Michael J. E.Nature Protocols (2015), 10 (6), 845-858CODEN: NPARDW; ISSN:1750-2799. (Nature Publishing Group)Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which the authors previously published a paper in Nature Protocols. In this updated protocol, the authors describe Phyre2, which uses advanced remote homol. detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they det. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain compn. and model quality. A range of addnl. available tools is described to find a protein structure in a genome, to submit large no. of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.
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380Jefferys, B. R.; Kelley, L. A.; Sternberg, M. J. Protein folding requires crowd control in a simulated cell J. Mol. Biol. 2010, 397, 1329– 1338 DOI: 10.1016/j.jmb.2010.01.074There is no corresponding record for this reference.
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381Schindler, C. E.; de Vries, S. J.; Zacharias, M. Fully Blind Peptide-Protein Docking with pepATTRACT Structure 2015, 23, 1507– 1515 DOI: 10.1016/j.str.2015.05.021381https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFaiu7fE&md5=4fe4ebb645e424f4f00b4f7918cab5dcFully Blind Peptide-Protein Docking with pepATTRACTSchindler, Christina E. M.; de Vries, Sjoerd J.; Zacharias, MartinStructure (Oxford, United Kingdom) (2015), 23 (8), 1507-1515CODEN: STRUE6; ISSN:0969-2126. (Elsevier Ltd.)Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement exptl. characterization of these complexes, but current protocols are not applicable on the proteome scale. Here, we present a new fully blind flexible peptide-protein docking protocol, pepATTRACT, which combines a rapid coarse-grained global peptide docking search of the entire protein surface with a two-stage atomistic flexible refinement. Global unbound-unbound docking yielded near-native models for 70% of the docking cases when testing the protocol on the largest benchmark of peptide-protein complexes available to date. This performance is similar to that of state-of-the-art local docking protocols that rely on information about the binding site. Upon restricting the search to the peptide binding region, the resulting pepATTRACT-local approach outperformed existing methods. Docking scripts for pepATTRACT and pepATTRACT-local can be generated via a web interface at www.attract.ph.tum.de/peptide.html.
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382Schindler, C. E.; de Vries, S. J.; Zacharias, M. iATTRACT: simultaneous global and local interface optimization for protein-protein docking refinement Proteins: Struct., Funct., Genet. 2015, 83, 248– 258 DOI: 10.1002/prot.24728There is no corresponding record for this reference.
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383Raveh, B.; London, N.; Zimmerman, L.; Schueler-Furman, O. Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors PLoS One 2011, 6, e18934 DOI: 10.1371/journal.pone.0018934383https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXls1Kksb0%253D&md5=ac5099b6dfa6d7a3b8e45d8c8c45a816Rosetta FlexPepDockab-initio: simultaneous folding, docking and refinement of peptides onto their receptorsRaveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, OraPLoS One (2011), 6 (4), e18934CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)Flexible peptides that fold upon binding to another protein mol. mediate a large no. of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDockab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approx. specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDockab-initio samples efficiently and simultaneously sampled the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resoln. models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resoln. peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions.
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384Jamroz, M.; Kolinski, A.; Kmiecik, S. CABS-flex predictions of protein flexibility compared with NMR ensembles Bioinformatics 2014, 30, 2150– 2154 DOI: 10.1093/bioinformatics/btu184384https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht1SqtL7N&md5=3771bee8bed66b23da3a9dee99309f33CABS-flex predictions of protein flexibility compared with NMR ensemblesJamroz, Michal; Kolinski, Andrzej; Kmiecik, SebastianBioinformatics (2014), 30 (15), 2150-2154CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)A review. Motivation: Identification of flexible regions of protein structures is important for understanding of their biol. functions. Recently, we have developed a fast approach for predicting protein structure fluctuations from a single protein model: the CABS-flex. CABS-flex was shown to be an efficient alternative to conventional all-atom mol. dynamics (MD). In this work, we evaluate CABS-flex and MD predictions by comparison with protein structural variations within NMR ensembles. Results: Based on a benchmark set of 140 proteins, we show that the relative fluctuations of protein residues obtained from CABS-flex are well correlated to those of NMR ensembles. On av., this correlation is stronger than that between MD and NMR ensembles. In conclusion, CABS-flex is useful and complementary to MD in predicting protein regions that undergo conformational changes as well as the extent of such changes.
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385Kruger, D. M.; Ahmed, A.; Gohlke, H. NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins Nucleic Acids Res. 2012, 40, W310– 316 DOI: 10.1093/nar/gks478There is no corresponding record for this reference.
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386Camps, J.; Carrillo, O.; Emperador, A.; Orellana, L.; Hospital, A.; Rueda, M.; Cicin-Sain, D.; D’Abramo, M.; Gelpi, J. L.; Orozco, M. FlexServ: an integrated tool for the analysis of protein flexibility Bioinformatics 2009, 25, 1709– 1710 DOI: 10.1093/bioinformatics/btp304386https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnsFygtLo%253D&md5=27989bd30d186c47a4bb567af66a5bb8FlexServ: an integrated tool for the analysis of protein flexibilityCamps, Jordi; Carrillo, Oliver; Emperador, Agusti; Orellana, Laura; Hospital, Adam; Rueda, Manuel; Cicin-Sain, Damjan; D'Abramo, Marco; Gelpi, Josep Lluis; Orozco, ModestoBioinformatics (2009), 25 (13), 1709-1710CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Summary: FlexServ is a web-based tool for the anal. of protein flexibility. The server incorporates powerful protocols for the coarse-grained detn. of protein dynamics using different versions of Normal Mode Anal. (NMA), Brownian dynamics (BD) and Discrete Dynamics (DMD). It can also analyze user provided trajectories. The server allows a complete anal. of flexibility using a large variety of metrics, including basic geometrical anal., B-factors, essential dynamics, stiffness anal., collectivity measures, Lindemann's indexes, residue correlation, chain-correlations, dynamic domain detn., hinge point detections, etc. Data is presented through a web interface as plain text, 2D and 3D graphics.
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387de Vries, S. J.; Schindler, C. E.; Chauvot de Beauchene, I.; Zacharias, M. A web interface for easy flexible protein-protein docking with ATTRACT Biophys. J. 2015, 108, 462– 465 DOI: 10.1016/j.bpj.2014.12.015387https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXntVWjsQ%253D%253D&md5=a5ed83a84633c95201596986df45f460A Web Interface for Easy Flexible Protein-Protein Docking with ATTRACTde Vries, Sjoerd J.; Schindler, Christina E. M.; Chauvot de Beauchene, Isaure; Zacharias, MartinBiophysical Journal (2015), 108 (3), 462-465CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Protein-protein docking programs can give valuable insights into the structure of protein complexes in the absence of an exptl. complex structure. Web interfaces can facilitate the use of docking programs by structural biologists. Here, we present an easy web interface for protein-protein docking with the ATTRACT program. While aimed at nonexpert users, the web interface still covers a considerable range of docking applications. The web interface supports systematic rigid-body protein docking with the ATTRACT coarse-grained force field, as well as various kinds of protein flexibility. The execution of a docking protocol takes up to a few hours on a std. desktop computer.
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388May, A.; Zacharias, M. Protein-protein docking in CAPRI using ATTRACT to account for global and local flexibility Proteins: Struct., Funct., Genet. 2007, 69, 774– 780 DOI: 10.1002/prot.21735There is no corresponding record for this reference.
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389Zacharias, M. ATTRACT: protein-protein docking in CAPRI using a reduced protein model Proteins: Struct., Funct., Genet. 2005, 60, 252– 256 DOI: 10.1002/prot.20566There is no corresponding record for this reference.
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390de Vries, S.; Zacharias, M. Flexible docking and refinement with a coarse-grained protein model using ATTRACT Proteins: Struct., Funct., Genet. 2013, 81, 2167– 2174 DOI: 10.1002/prot.24400There is no corresponding record for this reference.
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391Dehouck, Y.; Kwasigroch, J. M.; Rooman, M.; Gilis, D. BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations Nucleic Acids Res. 2013, 41, W333– 339 DOI: 10.1093/nar/gkt450There is no corresponding record for this reference.
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392Dehouck, Y.; Gilis, D.; Rooman, M. A new generation of statistical potentials for proteins Biophys. J. 2006, 90, 4010– 4017 DOI: 10.1529/biophysj.105.079434392https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XltF2mt7s%253D&md5=9e0b446c406d4d388bb2a4ad0ef271e4A new generation of statistical potentials for proteinsDehouck, Y.; Gilis, D.; Rooman, M.Biophysical Journal (2006), 90 (11), 4010-4017CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)We propose a novel and flexible derivation scheme of statistical, database-derived, potentials, which allows one to take simultaneously into account specific correlations between several sequence and structure descriptors. This scheme leads to the decompn. of the total folding free energy of a protein into a sum of lower order terms, thereby giving the possibility to analyze independently each contribution and clarify its significance and importance, to avoid overcounting certain contributions, and to deal more efficiently with the limited size of the database. In addn., this derivation scheme appears as quite general, for many previously developed potentials can be expressed as particular cases of our formalism. We use this formalism as a framework to generate different residue-based energy functions, whose performances are assessed on the basis of their ability to discriminate genuine proteins from decoy models. The optimal potential is generated as a combination of several coupling terms, measuring correlations between residue types, backbone torsion angles, solvent accessibilities, relative positions along the sequence, and interresidue distances. This potential outperforms all tested residue-based potentials, and even several atom-based potentials. Its incorporation in algorithms aiming at predicting protein structure and stability should therefore substantially improve their performances.
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393Dehouck, Y.; Grosfils, A.; Folch, B.; Gilis, D.; Bogaerts, P.; Rooman, M. Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0 Bioinformatics 2009, 25, 2537– 2543 DOI: 10.1093/bioinformatics/btp445393https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtFyhtbbF&md5=59f9acfcafd822a7f3a27eb3cf3538cdFast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0Dehouck, Yves; Grosfils, Aline; Folch, Benjamin; Gilis, Dimitri; Bogaerts, Philippe; Rooman, MarianneBioinformatics (2009), 25 (19), 2537-2543CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)The rational design of proteins with modified properties, through amino acid substitutions, is of crucial importance in a large variety of applications. Given the huge no. of possible substitutions, every protein engineering project would benefit strongly from the guidance of in silico methods able to predict rapidly, and with reasonable accuracy, the stability changes resulting from all possible mutations in a protein. The authors exploit newly developed statistical potentials, based on a formalism that highlights the coupling between 4 protein sequence and structure descriptors, and take into account the amino acid vol. variation upon mutation. The stability change is expressed as a linear combination of these energy functions, whose proportionality coeffs. vary with the solvent accessibility of the mutated residue and are identified with the help of a neural network. A correlation coeff. of R = 0.63 and a root mean square error of σc = 1.15 kcal/mol between measured and predicted stability changes are obtained upon cross-validation. These scores reach R = 0.79, and σc = 0.86 kcal/mol after exclusion of 10% outliers. The predictive power of the authors' method is shown to be significantly higher than that of other programs described in the literature.
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394Viswanath, S.; Ravikant, D. V.; Elber, R. DOCK/PIERR: web server for structure prediction of protein-protein complexes Methods Mol. Biol. 2014, 1137, 199– 207 DOI: 10.1007/978-1-4939-0366-5_14394https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXns12is7w%253D&md5=a3b91ed176c57f88ba7c9e580a48421bDOCK/PIERR: Web Server for Structure Prediction of Protein-Protein ComplexesViswanath, Shruthi; Ravikant, D. V. S.; Elber, RonMethods in Molecular Biology (New York, NY, United States) (2014), 1137 (Protein Structure Prediction), 199-207CODEN: MMBIED; ISSN:1940-6029. (Springer)In protein docking we aim to find the structure of the complex formed when two proteins interact. Protein-protein interactions are crucial for cell function. Here we discuss the usage of DOCK/PIERR. In DOCK/PIERR, a uniformly discrete sampling of orientations of one protein with respect to the other, are scored, followed by clustering, refinement, and reranking of structures. The novelty of this method lies in the scoring functions used. These are obtained by examg. hundreds of millions of correctly and incorrectly docked structures, using an algorithm based on math. programming, with provable convergence properties.
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395Ravikant, D. V.; Elber, R. PIE-efficient filters and coarse grained potentials for unbound protein-protein docking Proteins: Struct., Funct., Genet. 2010, 78, 400– 419 DOI: 10.1002/prot.22550There is no corresponding record for this reference.
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396Viswanath, S.; Ravikant, D. V.; Elber, R. Improving ranking of models for protein complexes with side chain modeling and atomic potentials Proteins: Struct., Funct., Genet. 2013, 81, 592– 606 DOI: 10.1002/prot.24214There is no corresponding record for this reference.
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397Frappier, V.; Chartier, M.; Najmanovich, R. J. ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability Nucleic Acids Res. 2015, 43, W395– 400 DOI: 10.1093/nar/gkv343There is no corresponding record for this reference.
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398Lyskov, S.; Gray, J. J. The RosettaDock server for local protein-protein docking Nucleic Acids Res. 2008, 36, W233– 238 DOI: 10.1093/nar/gkn216398https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXptlKkurs%253D&md5=689113abd16fae2d161cf812b4fb720bThe RosettaDock server for local protein-protein dockingLyskov, Sergey; Gray, Jeffrey J.Nucleic Acids Research (2008), 36 (Web Server), W233-W238CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The RosettaDock server (http://rosettadock.graylab.jhu.edu) identifies low-energy conformations of a protein-protein interaction near a given starting configuration by optimizing rigid-body orientation and side-chain conformations. The server requires two protein structures as inputs and a starting location for the search. RosettaDock generates 1000 independent structures, and the server returns pictures, coordinate files and detailed scoring information for the 10 top-scoring models. A plot of the total energy of each of the 1000 models created shows the presence or absence of an energetic binding funnel. RosettaDock has been validated on the docking benchmark set and through the Crit. Assessment of PRedicted Interactions blind prediction challenge.
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399London, N.; Schueler-Furman, O. FunHunt: model selection based on energy landscape characteristics Biochem. Soc. Trans. 2008, 36, 1418– 1421 DOI: 10.1042/BST0361418399https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVCgsb3I&md5=3a0c9e7496f43424ac9ff149bda47f32FunHunt: model selection based on energy landscape characteristicsLondon, Nir; Schueler-Furman, OraBiochemical Society Transactions (2008), 36 (6), 1418-1421CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)Protein folding and binding is commonly depicted as a search for the min. energy conformation in a vast energy landscape. Indeed, modeling of protein complex structures by RosettaDock often results in a set of low-energy conformations near the native structure. Ensembles of low-energy conformations can appear, however, in other regions of the energy landscape, esp. when backbone movements occur upon binding. What then characterizes the energy landscape near the correct orientation. The authors have applied a machine learning algorithm to distinguish ensembles of low-energy conformations around the native conformation from other low-energy ensembles. FunHunt, the resulting classifier, identified the native orientation for 50/52 protein complexes in a test set, and for all of 12 recent CAPRI targets. FunHunt is also able to choose the near-native orientation among models created by algorithms other than RosettaDock, demonstrating its general applicability for model selection. The features used by FunHunt teach us about the nature of native interfaces. Remarkably, the energy decrease of trajectories toward near-native orientations is significantly larger than for other orientations. This provides a possible explanation for the stability of assocn. in the native orientation. The FunHunt approach, discriminating models based on ensembles of structures that map the nearby energy landscape, can be adapted and extended to addnl. tasks, such as ab initio model selection, protein interface design and specificity predictions.
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400Sircar, A.; Kim, E. T.; Gray, J. J. RosettaAntibody: antibody variable region homology modeling server Nucleic Acids Res. 2009, 37, W474– 479 DOI: 10.1093/nar/gkp387400https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXosFSktLw%253D&md5=a997ea013edd9949901aacddbe8247b1RosettaAntibody: antibody variable region homology modeling serverSircar, Aroop; Kim, Eric T.; Gray, Jeffrey J.Nucleic Acids Research (2009), 37 (Web Server), W474-W479CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The RosettaAntibody server (http://antibody.graylab.jhu.edu) predicts the structure of an antibody variable region given the amino-acid sequences of the resp. light and heavy chains. In an initial stage, the server identifies and displays the most sequence homologous template structures for the light and heavy framework regions and each of the complementarity detg. region (CDR) loops. Subsequently, the most homologous templates are assembled into a side-chain optimized crude model, and the server returns a picture and coordinate file. For users requesting a high-resoln. model, the server executes the full RosettaAntibody protocol which addnl. models the hyper-variable CDR H3 loop. The high-resoln. protocol also relieves steric clashes by optimizing the CDR backbone torsion angles and by simultaneously perturbing the relative orientation of the light and heavy chains. RosettaAntibody generates 2000 independent structures, and the server returns pictures, coordinate files, and detailed scoring information for the 10 top-scoring models. The 10 models enable users to use rational judgment in choosing the best model or to use the set as an ensemble for further studies such as docking. The high-resoln. models generated by RosettaAntibody have been used for the successful prediction of antibody-antigen complex structures.
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401Shaw, D. E.; Maragakis, P.; Lindorff-Larsen, K.; Piana, S.; Dror, R. O.; Eastwood, M. P.; Bank, J. A.; Jumper, J. M.; Salmon, J. K.; Shan, Y. Atomic-level characterization of the structural dynamics of proteins Science 2010, 330, 341– 346 DOI: 10.1126/science.1187409401https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1OisL%252FN&md5=85c9d897881e8684fc39d69b2b6b2fadAtomic-Level Characterization of the Structural Dynamics of ProteinsShaw, David E.; Maragakis, Paul; Lindorff-Larsen, Kresten; Piana, Stefano; Dror, Ron O.; Eastwood, Michael P.; Bank, Joseph A.; Jumper, John M.; Salmon, John K.; Shan, Yibing; Wriggers, WillyScience (Washington, DC, United States) (2010), 330 (6002), 341-346CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)Mol. dynamics (MD) simulations are widely used to study protein motions at an at. level of detail, but they have been limited to time scales shorter than those of many biol. crit. conformational changes. We examd. two fundamental processes in protein dynamics-protein folding and conformational change within the folded state-by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equil. simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; sep. simulations of the protein's constituent substructures shed light on possible determinants of this pathway. A 1-ms simulation of the folded protein BPTI reveals a small no. of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.
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402Freddolino, P. L.; Liu, F.; Gruebele, M.; Schulten, K. Ten-microsecond molecular dynamics simulation of a fast-folding WW domain Biophys. J. 2008, 94, L75– 77 DOI: 10.1529/biophysj.108.131565402https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXlsF2htL0%253D&md5=f443f76d09c6f846d9df6c5cc0988c22Ten-microsecond molecular dynamics simulation of a fast-folding WW domainFreddolino, Peter L.; Liu, Feng; Gruebele, Martin; Schulten, KlausBiophysical Journal (2008), 94 (10), L75-L77CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)All-atom mol. dynamics (MD) simulations of protein folding allow anal. of the folding process at an unprecedented level of detail. Unfortunately, such simulations have not yet reached their full potential both due to difficulties in sufficiently sampling the microsecond timescales needed for folding, and because the force field used may yield neither the correct dynamical sequence of events nor the folded structure. The ongoing study of protein folding through computational methods thus requires both improvements in the performance of MD programs to make longer timescales accessible, and testing of force fields in the context of folding simulations. Here, the authors report a 10-μs simulation of an incipient downhill-folding peptidylprolyl isomerase Pin1 WW domain mutant along with measurement of a mol. time and activated folding time of 1.5 and 13.3 μs, resp. The protein simulated in explicit solvent exhibited several metastable states with incorrect topol. and did not assume the native state during the present simulations.
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403Fersht, A. R. From the first protein structures to our current knowledge of protein folding: delights and scepticisms Nat. Rev. Mol. Cell Biol. 2008, 9, 650– 654 DOI: 10.1038/nrm2446403https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXosl2rsLg%253D&md5=bdc2c8fe953a92119410aa1354e3bd44From the first protein structures to our current knowledge of protein folding: Delights and scepticismsFersht, Alan R.Nature Reviews Molecular Cell Biology (2008), 9 (8), 650-654CODEN: NRMCBP; ISSN:1471-0072. (Nature Publishing Group)A review. Every breakthrough that opens new vistas also removes the ground from under the feet of other scientists. The scientific joy of those who have seen the new light is accompanied by the dismay of those whose way of life has been changed forever. The publication of the first structures of proteins at at. resoln. 50 years ago astounded and inspired scientists in every field but caused others to flee or scoff. That advance and every subsequent paradigm-shifting breakthrough in protein science have met with some resistance before universal acceptance. I relate these events and their impact on the field of protein folding.
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404Schaeffer, R. D.; Fersht, A.; Daggett, V. Combining experiment and simulation in protein folding: closing the gap for small model systems Curr. Opin. Struct. Biol. 2008, 18, 4– 9 DOI: 10.1016/j.sbi.2007.11.007404https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXitVGit74%253D&md5=404efb9a9af6c1b1b59f9abe09f0d919Combining experiment and simulation in protein folding: closing the gap for small model systemsSchaeffer, R. Dustin; Fersht, Alan; Daggett, ValerieCurrent Opinion in Structural Biology (2008), 18 (1), 4-9CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. All-atom mol. dynamics (MD) simulations on increasingly powerful computers have been combined with expts. to characterize protein folding in detail over wider time ranges. The folding of small ultrafast folding proteins is being simulated on μs timescales, leading to improved structural predictions and folding rates. To what extent is closing the gap' between simulation and expt. for such systems providing insights into general mechanisms of protein folding.
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405Sułkowska, J. I.; Cieplak, M. Selection of Optimal Variants of Go̅-Like Models of Proteins through Studies of Stretching Biophys. J. 2008, 95, 3174– 3191 DOI: 10.1529/biophysj.107.127233405https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1Srs7nP&md5=bd53abc8f364c55d61481dce316f5c7aSelection of optimal variants of G‾o-like models of proteins through studies of stretchingSulkowska, Joanna I.; Cieplak, MarekBiophysical Journal (2008), 95 (7), 3174-3191CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The G‾o-like models of proteins are constructed based on the knowledge of the native conformation. However, there are many possible choices of a Hamiltonian for which the ground state coincides with the native state. Here, we propose to use exptl. data on protein stretching to det. what choices are most adequate phys. This criterion is motivated by the fact that stretching processes usually start with the native structure, in the vicinity of which the G‾o-like models should work the best. Our selection procedure is applied to 62 different versions of the G‾o model and is based on 28 proteins. We consider different potentials, contact maps, local stiffness energies, and energy scales-uniform and nonuniform. In the latter case, the strength of the nonuniformity was governed either by specificity or by properties related to positioning of the side groups. Among them is the simplest variant: uniform couplings with no i, i + 2 contacts. This choice also leads to good folding properties in most cases. We elucidate relationship between the local stiffness described by a potential which involves local chirality and the one which involves dihedral and bond angles. The latter stiffness improves folding but there is little difference between them when it comes to stretching.
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406Prieto, L.; Rey, A. Topology-based potentials and the study of the competition between protein folding and aggregation J. Chem. Phys. 2009, 130, 115101 DOI: 10.1063/1.3089708There is no corresponding record for this reference.
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407Takada, S.; Kanada, R.; Tan, C.; Terakawa, T.; Li, W.; Kenzaki, H. Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations Acc. Chem. Res. 2015, 48, 3026– 3035 DOI: 10.1021/acs.accounts.5b00338407https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFyjsr7O&md5=99733b902bdbf0e19e835d73c44772f9Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular SimulationsTakada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, HirooAccounts of Chemical Research (2015), 48 (12), 3026-3035CODEN: ACHRE4; ISSN:0001-4842. (American Chemical Society)A review. Due to hierarchic nature of biomol. systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations were used to address long-time dynamics of large systems. Here, the authors review recent developments and applications of CG modeling methods, focusing on the authors' methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomol. simulator, CafeMol. The authors' CG model has resoln. such that ∼10 non-hydrogen atoms are grouped into one CG particle on av. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. The authors first describe two representative minimal models of proteins, called the elastic network model and the classic G‾o model. The authors then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, the authors describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodn. exptl. data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded vol. terms for nonspecific cases. The authors also discuss the time scale mapping in CG mol. dynamics simulations. While the apparent single time step of the authors' CGMD is ∼10 times larger than that in the fully atomistic mol. dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude using CG model and a low friction const. in Langevin dynamics. Next, the authors present four examples of applications. First, the classic G‾o model was used to emulate one ATP cycle of a mol. motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, the authors simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concn.-dependent compaction. Finally, many of limitations in the current approaches and future directions are discussed. Esp., more accurate electrostatic treatment and a phospholipid model that matches the authors' CG resolns. are of immediate importance.
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408Zhang, Z.; Chan, H. S. Competition between native topology and nonnative interactions in simple and complex folding kinetics of natural and designed proteins Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 2920– 2925 DOI: 10.1073/pnas.0911844107408https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXis1Clt7c%253D&md5=bdb9b4ee6b45aadbbf1b0d05e93cc7ecCompetition between native topology and nonnative interactions in simple and complex folding kinetics of natural and designed proteinsZhang, Zhuqing; Chan, Hue SunProceedings of the National Academy of Sciences of the United States of America (2010), 107 (7), 2920-2925, S2920/1-S2920/7CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)We compared folding properties of designed protein Top7 and natural protein S6 by using coarse-grained chain models with a mainly native-centric construct that accounted also for nonnative hydrophobic interactions and desolvation barriers. Top7 and S6 have similar secondary structure elements and are approx. equal in length and hydrophobic compn. Yet their exptl. folding kinetics were drastically different. Consistent with expt., our simulated folding chevron arm for Top7 exhibited a severe rollover, whereas that for S6 was essentially linear, and Top7 model kinetic relaxation was multiphasic under strongly folding conditions. The peculiar behavior of Top7 was assocd. with several classes of kinetic traps in our model. Significantly, the amino acid residues participating in nonnative interactions in trapped conformations in our Top7 model overlapped with those deduced exptl. These affirmations suggest that the simple ingredients of native topol. plus sequence-dependent nonnative interactions are sufficient to account for some key features of protein folding kinetics. Notably, when nonnative interactions were absent in the model, Top7 chevron rollover was not correctly predicted. In contrast, nonnative interactions had little effect on the quasi linearity of the model folding chevron arm for S6. This intriguing distinction indicates that folding cooperativity is governed by a subtle interplay between the sequence-dependent driving forces for native topol. and the locations of favorable nonnative interactions entailed by the same sequence. Constructed with a capability to mimic this interplay, our simple modeling approach should be useful in general for assessing a designed sequence's potential to fold cooperatively.
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409Shan, B.; Eliezer, D.; Raleigh, D. P. The unfolded state of the C-terminal domain of the ribosomal protein L9 contains both native and non-native structure Biochemistry 2009, 48, 4707– 4719 DOI: 10.1021/bi802299j409https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXlvFWnsbc%253D&md5=3481c5177f3bd7b35d56e5109234c9fbThe unfolded state of the C-terminal domain of the ribosomal protein L9 contains both native and non-native structureShan, Bing; Eliezer, David; Raleigh, Daniel P.Biochemistry (2009), 48 (22), 4707-4719CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)Interest in the structural and dynamic properties of unfolded proteins has increased in recent years owing to continued interest in protein folding and misfolding. Knowledge of the unfolded state under native conditions is particularly important for obtaining a complete picture of the protein folding process. The C-terminal domain of ribosomal protein L9 (CTL9) is a globular α,β protein with an unusual mixed parallel and antiparallel β-strand structure. The folding kinetics and equil. unfolding of CTL9 strongly depended on pH, and followed a simple 2-state model. Both the native and the unfolded state could be significantly populated at pH 3.8 in the absence of denaturant, allowing the native state and the unfolded state to be characterized under identical conditions. Backbone 15N, 13C, 1H and side-chain 13Cβ, 1Hβ chem. shifts, amide proton NOEs, and 15N R2 relaxation rates were obtained for the 2 conformational states at pH 3.8. All of the data indicated that the pH 3.8 native state was well folded and was similar to the native state at neutral pH. There was significant residual structure in the pH 3.8 unfolded state. The regions corresponding to the 2 native state α-helixes showed strong preference to populate helical φ and ψ angles. The segment that connects α-helix 2 and β-strand 2 had a significant tendency to form non-native α-helical structure. Comparison with the pH 2.0 unfolded state and the urea unfolded state indicated that the tendency to adopt both native and non-native helical structure was stronger at pH 3.8, demonstrating that the unfolded state of CTL9 under native-like conditions was more structured. The implications for the folding of CTL9 are discussed.
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410Rothwarf, D. M.; Scheraga, H. A. Role of non-native aromatic and hydrophobic interactions in the folding of hen egg white lysozyme Biochemistry 1996, 35, 13797– 13807 DOI: 10.1021/bi9608119410https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XmtVOmurg%253D&md5=32f25454758763f7ddadb0ed769b4851Role of non-native aromatic and hydrophobic interactions in the folding of hen egg white lysozymeRothwarf, David M.; Scheraga, Harold A.Biochemistry (1996), 35 (43), 13797-13807CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)The folding kinetics were detd. for hen egg white lysozyme and 2 mutants in which Trp-62 and Trp-108 were individually replaced by tyrosine (Tyr-62-lysozyme and Tyr-108-lysozyme, resp.). An earlier study of wild-type lysozyme had indicated that 2 transient intermediates were formed during the early stages of refolding. Both intermediates were characterized by substantial quenching of tryptophan fluorescence which suggested that, during the refolding process, Trp-62 and/or Trp-108 was involved in a non-native tertiary interaction(s). Both Tyr-108- and Tyr-62-lysozyme fold significantly faster than wild-type lysozyme (7- and 13-fold, resp.). These results indicate that the rate-limiting step in the folding of lysozyme arises not from any inherent slowness in the formation of the native structure but rather as a consequence of the formation of a highly stable intermediate which contains significant non-native structure which must be disrupted prior to, or in concert with, subsequent folding. The data suggest that arom. and hydrophobic interactions play a pivotal role in the formation of the non-native intermediate. The general role that non-native interactions play in the folding process is discussed.
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411Jana, B.; Morcos, F.; Onuchic, J. N. From structure to function: the convergence of structure based models and co-evolutionary information Phys. Chem. Chem. Phys. 2014, 16, 6496– 6507 DOI: 10.1039/c3cp55275fThere is no corresponding record for this reference.
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412Okazaki, K.; Koga, N.; Takada, S.; Onuchic, J. N.; Wolynes, P. G. Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: Structure-based molecular dynamics simulations Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 11844– 11849 DOI: 10.1073/pnas.0604375103412https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XosVSgs7k%253D&md5=341dd37d5e9528521eec63bbcacb5190Multiple-basin energy landscapes for large-amplitude conformational motions of proteins: structure-based molecular dynamics simulationsOkazaki, Kei-ichi; Koga, Nobuyasu; Takada, Shoji; Onuchic, Jose N.; Wolynes, Peter G.Proceedings of the National Academy of Sciences of the United States of America (2006), 103 (32), 11844-11849CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Biomols. often undergo large-amplitude motions when they bind or release other mols. Unlike macroscopic machines, these biomol. machines can partially disassemble (unfold) and then reassemble (fold) during such transitions. Here we put forward a minimal structure-based model, the multiple-basin model, that can directly be used for mol. dynamics simulation of even very large biomol. systems so long as the endpoints of the conformational change are known. We investigate the model by simulating large-scale motions of four proteins: glutamine-binding protein, S100A6, dihydrofolate reductase, and HIV-1 protease. The mechanisms of conformational transition depend on the protein basin topologies and change with temp. near the folding transition. The conformational transition rate varies linearly with driving force over a fairly large range. This linearity appears to be a consequence of partial unfolding during the conformational transition.
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413Li, W.; Wang, W.; Takada, S. Energy landscape views for interplays among folding, binding, and allostery of calmodulin domains Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 10550– 10555 DOI: 10.1073/pnas.1402768111413https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFCnsrfM&md5=92ebcafe17e570c174fc20b8bf250f4dEnergy landscape views for interplays among folding, binding, and allostery of calmodulin domainsLi, Wenfei; Wang, Wei; Takada, ShojiProceedings of the National Academy of Sciences of the United States of America (2014), 111 (29), 10550-10555CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Ligand binding modulates the energy landscape of proteins, thus altering their folding and allosteric conformational dynamics. To investigate such interplay, calmodulin (CaM) has been a model protein. Despite much attention, fully resolved mechanisms of CaM folding/binding have not been elucidated. Here, by constructing a computational model that can integrate folding, binding, and allosteric motions, the authors studied the in-depth folding of isolated CaM domains coupled with binding of 2 Ca2+ ions and assocd. allosteric conformational changes. First, mech. pulled simulations revealed the coexistence of 3 distinct conformational states: the unfolded, the closed, and the open states, which was in accord with and augmented the structural understanding of recent single-mol. expts. Second, near the denaturation temp., the authors found the same 3 conformational states as well as 3 distinct binding states: 0, 1, and 2 Ca2+ ion-bound states, leading to as many as 9 states. Third, in terms of the 9-state representation, the authors found multi-route folding/binding pathways and shifts in their probabilities with the Ca2+ concn. At a lower Ca2+ concns., "combined spontaneous folding and induced fit" occurred, whereas at a higher concns., "binding-induced folding" dominated. Even without Ca2+ binding, the authors obsd. that the folding pathway of CaM domains could be modulated by the presence of metastable states. Finally, full-length CaM also exhibited an intriguing coupling between 2 domains when applying tension.
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414Koga, N.; Takada, S. Folding-based molecular simulations reveal mechanisms of the rotary motor F1-ATPase Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 5367– 5372 DOI: 10.1073/pnas.0509642103414https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XjslaqurY%253D&md5=758f7e9f4187b943136f0b1e72f85af3Folding-based molecular simulations reveal mechanisms of the rotary motor F1-ATPaseKoga, Nobuyasu; Takada, ShojiProceedings of the National Academy of Sciences of the United States of America (2006), 103 (14), 5367-5372CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Biomol. machines fulfill their function through large conformational changes that typically occur on the millisecond time scale or longer. Conventional atomistic simulations can only reach microseconds at the moment. Here, extending the minimalist model developed for protein folding, we propose the "switching G‾o model" and use it to simulate the rotary motion of the ATP-driven mol. motor F1-ATPase. The simulation recovers the unidirectional 120° rotation of the γ-subunit, the rotor. The rotation was induced solely by steric repulsion from the α3β3 subunits, the stator, which undergo conformational changes during ATP hydrolysis. In silico alanine mutagenesis further elucidated which residues play specific roles in the rotation. Finally, regarding the mechanochem. coupling scheme, we found that the tri-site model does not lead to successful rotation but that the always-bi-site model produces ≈30° and ≈90° substeps, perfectly in accord with expts. In the always-bi-site model, the no. of sites occupied by nucleotides is always two during the hydrolysis cycle. This study opens up an avenue of simulating functional dynamics of huge biomols. that occur on the millisecond time scales involving large-amplitude conformational change.
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415Han, W.; Schulten, K. Characterization of folding mechanisms of Trp-cage and WW-domain by network analysis of simulations with a hybrid-resolution model J. Phys. Chem. B 2013, 117, 13367– 13377 DOI: 10.1021/jp404331d415https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXht1Wlt7vE&md5=ae252e12cd28f5b4d75b143b7f21988cCharacterization of Folding Mechanisms of Trp-Cage and WW-Domain by Network Analysis of Simulations with a Hybrid-Resolution ModelHan, Wei; Schulten, KlausJournal of Physical Chemistry B (2013), 117 (42), 13367-13377CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)In this study, we apply a hybrid-resoln. model, namely, PACE, to characterize the free energy surfaces (FESs) of Trp-cage and a WW-domain variant along with the resp. folding mechanisms. Unbiased, independent simulations with PACE are found to achieve together multiple folding and unfolding events for both proteins, allowing us to perform network anal. of the FESs to identify folding pathways. PACE reproduces for both proteins expected complexity hidden in the folding FESs, in particular metastable non-native intermediates. Pathway anal. shows that some of these intermediates are, actually, on-pathway folding intermediates and that intermediates kinetically closest to the native states can be either crit. on-pathway or off-pathway intermediates, depending on the protein. Apart from general insights into folding, specific folding mechanisms of the proteins are resolved. We find that Trp-cage folds via a dominant pathway in which hydrophobic collapse occurs before the N-terminal helix forms; full incorporation of Trp6 into the hydrophobic core takes place as the last step of folding, which, however, may not be the rate-limiting step. For the WW-domain variant studied, we observe two main folding pathways with opposite orders of formation of the two hairpins involved in the structure; for either pathway, formation of hairpin 1 is more likely to be the rate-limiting step. Altogether, our results suggest that PACE combined with network anal. is a computationally efficient and valuable tool for the study of protein folding.
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416Han, W.; Wan, C. K.; Jiang, F.; Wu, Y. D. PACE Force Field for Protein Simulations. 1. Full Parameterization of Version 1 and Verification J. Chem. Theory Comput. 2010, 6, 3373– 3389 DOI: 10.1021/ct1003127416https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtleiurzK&md5=22cf63c37da26e873bd06048150ce14bPACE Force Field for Protein Simulations. 1. Full Parameterization of Version 1 and VerificationHan, Wei; Wan, Cheuk-Kin; Jiang, Fan; Wu, Yun-DongJournal of Chemical Theory and Computation (2010), 6 (11), 3373-3389CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)A further parametrization of a united-atom protein model coupled with coarse-grained water has been carried out to cover all amino acids (AAs). The local conformational features of each AA have been fitted on the basis of restricted coil-library statistics of high-resoln. X-ray crystal structures of proteins. Potential functions were developed on the basis of combined backbone and side chain rotamer conformational preferences, or rotamer Ramachandran plots (.vphi., Ψ, χ1). Side chain-side chain and side chain-backbone interaction potentials were parametrized to fit the potential mean forces of corresponding all-atom simulations. The force field has been applied in mol. dynamics simulations of several proteins of 56-108 AA residues whose X-ray crystal and/or NMR structures are available. Starting from the crystal structures, each protein was simulated for about 100 ns. The Cα RMSDs of the calcd. structures are 2.4-4.2 Å with respect to the crystal and/or NMR structures, which are still larger than but close to those of all-atom simulations (1.1-3.6 Å). Starting from the PDB structure of malate synthase G of 723 AA residues, the wall-clock time of a 30 ns simulation is about three days on a 2.65 GHz dual-core CPU. The RMSD to the exptl. structure is about 4.3 Å. These results implicate the applicability of the force field in the study of protein structures.
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417Thorpe, I. F.; Zhou, J.; Voth, G. A. Peptide folding using multiscale coarse-grained models J. Phys. Chem. B 2008, 112, 13079– 13090 DOI: 10.1021/jp8015968417https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFelt7fM&md5=e7e6883526fac062d9c7be8d108f9df8Peptide Folding Using Multiscale Coarse-Grained ModelsThorpe, Ian F.; Zhou, Jian; Voth, Gregory A.Journal of Physical Chemistry B (2008), 112 (41), 13079-13090CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)The multiscale coarse-graining (MS-CG) method has been previously used to describe the equil. properties of peptides. The present study reveals that MS-CG models of α-helical polyalanine and the β-hairpin V5PGV5 possess the capacity to efficiently refold in simulations initiated from unfolded configurations. The MS-CG peptides exhibit free energy landscapes that are funneled toward folded configurations and two-state folding behavior, consistent with the known characteristics of small, rapidly folding peptides. Moreover, the models demonstrate enhanced sampling capabilities when compared to systems with full at. detail. The significance of these observations with respect to the theor. basis of the MS-CG approach is discussed. The MS-CG peptides were used to reconstruct atomically detailed configurations in order to evaluate the extent to which MS-CG ensembles embody all-atom peptide free energy landscapes. Ensembles obtained from these reconstructed configurations display good agreement with the all-atom simulation data used to generate the MS-CG models and also corroborate the presence of features obsd. in the MS-CG peptide free energy landscapes. These findings suggest that MS-CG models may be of significant utility in the study of peptide folding.
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418Hills, R. D., Jr.; Lu, L.; Voth, G. A. Multiscale coarse-graining of the protein energy landscape PLoS Comput. Biol. 2010, 6, e1000827 DOI: 10.1371/journal.pcbi.1000827There is no corresponding record for this reference.
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419Adhikari, A. N.; Freed, K. F.; Sosnick, T. R. De novo prediction of protein folding pathways and structure using the principle of sequential stabilization Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 17442– 17447 DOI: 10.1073/pnas.1209000109419https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhvVSltLrK&md5=f6a8bda849c6adf37982a28401b72eaaDe novo prediction of protein folding pathways and structure using the principle of sequential stabilizationAdhikari, Aashish N.; Freed, Karl F.; Sosnick, Tobin R.Proceedings of the National Academy of Sciences of the United States of America (2012), 109 (43), 17442-17447, S17442/1-S17442/10CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Motivated by the relation between the folding mechanism and the native structure, the authors develop a unified approach for predicting folding pathways and tertiary structure using only the primary sequence as input. Simulations begin from a realistic unfolded state devoid of secondary structure and use a chain representation lacking explicit side-chains, rendering the simulations many orders of magnitude faster than mol. dynamics simulations. The multiple round nature of the algorithm mimics the authentic folding process and tests the effectiveness of sequential stabilization (SS) as a search strategy wherein 2° structural elements add onto existing structures in a process of progressive learning and stabilization of structure found in prior rounds of folding. Because no a priori knowledge is used, the authors can identify kinetically significant non-native interactions and intermediates, sometimes generated by only 2 mutations, while the evolution of contact matrixes is often consistent with expts. Moreover, structure prediction improves substantially by incorporating information from prior rounds. The success of this simple, homol.-free approach affirms the validity of the description of the primary determinants of folding pathways and structure, and the effectiveness of SS as a search strategy.
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420Adhikari, A. N.; Freed, K. F.; Sosnick, T. R. Simplified protein models: predicting folding pathways and structure using amino acid sequences Phys. Rev. Lett. 2013, 111, 028103 DOI: 10.1103/PhysRevLett.111.028103There is no corresponding record for this reference.
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421Rodrigues, J. P.; Levitt, M.; Chopra, G. KoBaMIN: a knowledge-based minimization web server for protein structure refinement Nucleic Acids Res. 2012, 40, W323– 328 DOI: 10.1093/nar/gks376421https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjtVCru7Y%253D&md5=a55ebd0571d0f1c268d9e6016aaa0ccfKoBaMIN: a knowledge-based minimization web server for protein structure refinementRodrigues, Joao P. G. L. M.; Levitt, Michael; Chopra, GauravNucleic Acids Research (2012), 40 (W1), W323-W328CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The KoBaMIN web server provides an online interface to a simple, consistent and computationally efficient protein structure refinement protocol based on minimization of a knowledge-based potential of mean force. The server can be used to refine either a single protein structure or an ensemble of proteins starting from their unrefined coordinates in PDB format. The refinement method is particularly fast and accurate due to the underlying knowledge-based potential derived from structures deposited in the PDB; as such, the energy function implicitly includes the effects of solvent and the crystal environment. Our server allows for an optional but recommended step that optimizes stereochem. using the MESHI software. The KoBaMIN server also allows comparison of the refined structures with a provided ref. structure to assess the changes brought about by the refinement protocol. The performance of KoBaMIN has been benchmarked widely on a large set of decoys, all models generated at the seventh worldwide expts. on crit. assessment of techniques for protein structure prediction (CASP7) and it was also shown to produce top-ranking predictions in the refinement category at both CASP8 and CASP9, yielding consistently good results across a broad range of model quality values. The web server is fully functional and freely available at http://csb.stanford.edu/kobamin.
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422Zhou, H. X.; Rivas, G.; Minton, A. P. Macromolecular crowding and confinement: biochemical, biophysical, and potential physiological consequences Annu. Rev. Biophys. 2008, 37, 375– 397 DOI: 10.1146/annurev.biophys.37.032807.125817422https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXnsVGlurg%253D&md5=2e1fe7edb342b273b68868b02a8d137bMacromolecular crowding and confinement: Biochemical, biophysical, and potential physiological consequencesZhou, Huan-Xiang; Rivas, German; Minton, Allen P.Annual Review of Biophysics (2008), 37 (), 375-397CODEN: ARBNCV ISSN:. (Annual Reviews Inc.)A review. Expected and obsd. effects of vol. exclusion on the free energy of rigid and flexible macromols. in crowded and confined systems, and consequent effects of crowding and confinement on macromol. reaction rates and equil. are summarized. Findings from relevant theor./simulation and exptl. literature published from 2004 onward are reviewed. Addnl. complexity arising from the heterogeneity of local environments in biol. media, and the presence of nonspecific interactions between macromols. over and above steric repulsion, are discussed. Theor. and exptl. approaches to the characterization of crowding- and confinement-induced effects in systems approaching the complexity of living organisms are suggested.
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423Feig, M.; Sugita, Y. Reaching new levels of realism in modeling biological macromolecules in cellular environments J. Mol. Graphics Modell. 2013, 45, 144– 156 DOI: 10.1016/j.jmgm.2013.08.017423https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1Wksr%252FE&md5=c56d5feaa6f0d3fde059ee3a3998a4e6Reaching new levels of realism in modeling biological macromolecules in cellular environmentsFeig, Michael; Sugita, YujiJournal of Molecular Graphics & Modelling (2013), 45 (), 144-156CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)A review. An increasing no. of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are addnl. challenges in integrating different aspects ranging from questions about biomol. stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomols. in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomols., as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.
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424Derreumaux, P. Coarse-grained models for protein folding and aggregation Methods Mol. Biol. 2013, 924, 585– 600 DOI: 10.1007/978-1-62703-017-5_22424https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXit1Gnurc%253D&md5=359fa9262e07fe6c98105e484be8e4acCoarse-grained models for protein folding and aggregationDerreumaux, PhilippeMethods in Molecular Biology (New York, NY, United States) (2013), 924 (Biomolecular Simulations), 585-600CODEN: MMBIED; ISSN:1064-3745. (Springer)A review. Coarse-grained models for protein folding and aggregation are used to explore large dimension scales and timescales that are inaccessible to all-atom models in explicit aq. soln. Combined with enhanced configuration search methods, these simplified models with various levels of granularity offer the possibility to det. equil. structures, compare folding kinetics and thermodn. with expts. for single proteins and understand the dynamic assembly of amyloid proteins leading to neurodegenerative diseases. I shall describe recent progress in developing such models, and discuss their potentials and limitations in probing the folding and misfolding of proteins with computer simulations.
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425Borgia, M. B.; Borgia, A.; Best, R. B.; Steward, A.; Nettels, D.; Wunderlich, B.; Schuler, B.; Clarke, J. Single-molecule fluorescence reveals sequence-specific misfolding in multidomain proteins Nature 2011, 474, 662– 665 DOI: 10.1038/nature10099425https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmslSrs7w%253D&md5=18747a3a3792b08e7004677b6be7d29bSingle-molecule fluorescence reveals sequence-specific misfolding in multidomain proteinsBorgia, Madeleine B.; Borgia, Alessandro; Best, Robert B.; Steward, Annette; Nettels, Daniel; Wunderlich, Bengt; Schuler, Benjamin; Clarke, JaneNature (London, United Kingdom) (2011), 474 (7353), 662-665CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)A large range of debilitating medical conditions is linked to protein misfolding, which may compete with productive folding particularly in proteins contg. multiple domains. Of the eukaryotic proteome, 75% consists of multidomain proteins; yet it is not understood how interdomain misfolding is avoided. It has been proposed that maintaining low sequence identity between covalently linked domains is a mechanism to avoid misfolding. Here, the authors used single-mol. FRET to detect and quantify rare misfolding events in tandem Ig domains from the I band of titin under native conditions. About 5.5% of mols. with identical domains misfolded during refolding in vitro and formed an unexpectedly stable state with an unfolding half-time of several days. Tandem arrays of Ig-like domains in humans showed significantly lower sequence identity between neighboring domains than between non-adjacent domains. In particular, the sequence identity of neighboring domains was found to be preferentially below 40%. The authors obsd. no misfolding for a tandem of naturally neighboring domains with low sequence identity (24%), whereas misfolding occurred between domains that were 42% identical. Coarse-grained mol. simulations predicted the formation of domain-swapped structures that were in excellent agreement with the obsd. transfer efficiency of the misfolded species. The authors infer that the interactions underlying misfolding are very specific and result in a sequence-specific domain-swapping mechanism. Diversifying the sequence between neighboring domains seems to be a successful evolutionary strategy to avoid misfolding in multidomain proteins.
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426Morriss-Andrews, A.; Shea, J. E. Computational studies of protein aggregation: methods and applications Annu. Rev. Phys. Chem. 2015, 66, 643– 666 DOI: 10.1146/annurev-physchem-040513-103738426https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXnvFartL4%253D&md5=8f49c01fff7cdd66562ee8820ff9a48fComputational studies of protein aggregation: methods and applicationsMorriss-Andrews, Alex; Shea, Joan-EmmaAnnual Review of Physical Chemistry (2015), 66 (), 643-666CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews)A review. Protein aggregation involves the self-assembly of normally sol. proteins into large supramol. assemblies. The typical end product of aggregation is the amyloid fibril, an extended structure enriched in β-sheet content. The aggregation process has been linked to a no. of diseases, most notably Alzheimer's disease, but fibril formation can also play a functional role in certain organisms. This review focuses on theor. studies of the process of fibril formation, with an emphasis on the computational models and methods commonly used to tackle this problem.
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427Shental-Bechor, D.; Smith, M. T.; Mackenzie, D.; Broom, A.; Marcovitz, A.; Ghashut, F.; Go, C.; Bralha, F.; Meiering, E. M.; Levy, Y. Nonnative interactions regulate folding and switching of myristoylated protein Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 17839– 17844 DOI: 10.1073/pnas.1201803109427https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhsl2ktbzJ&md5=4b8ca8d0e384730e60914b2a1a1b2fbaNonnative interactions regulate folding and switching of myristoylated proteinShental-Bechor, Dalit; Smith, Martin T. J.; MacKenzie, Duncan; Broom, Aron; Marcovitz, Amir; Ghashut, Fadila; Go, Chris; Bralha, Fernando; Meiering, Elizabeth M.; Levy, YaakovProceedings of the National Academy of Sciences of the United States of America (2012), 109 (44), 17839-17844, S17839/1-S17839/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The authors present an integrated exptl. and computational study of the mol. mechanisms by which myristoylation affects protein folding and function, which has been little characterized to date. Myristoylation, the covalent linkage of a hydrophobic C14 fatty acyl chain to the N-terminal Gly residue in a protein, is a common modification that plays a crit. role in vital regulated cellular processes by undergoing reversible energetic and conformational switching. Coarse-grained folding simulations for the model pH-dependent actin- and membrane-binding protein hisactophilin (I) revealed that non-native hydrophobic interactions of the myristoyl group with the protein as well as non-native electrostatic interactions had a pronounced effect on folding rates and thermodn. stability. Folding measurements for hydrophobic residue mutations of I and atomistic simulations indicated that the non-native interactions of the myristoyl group in the folding transition state were nonspecific and robust, and thus smoothed the energy landscape for folding. In contrast, myristoyl interactions in the native state were highly specific and tuned for sensitive control of switching functionality. Simulations and amide H-exchange measurements provided evidence for increases as well as decreases in stability localized on one side of the myristoyl binding pocket in the protein, implicating strain and altered dynamics in switching. The effects of folding and function arising from myristoylation were profoundly different from the effects of other post-translational modifications.
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428Lu, D.; Yang, C.; Liu, Z. How hydrophobicity and the glycosylation site of glycans affect protein folding and stability: a molecular dynamics simulation J. Phys. Chem. B 2012, 116, 390– 400 DOI: 10.1021/jp203926r428https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsFansb7E&md5=838b7a9371ce78243d32176fb0d3876eHow hydrophobicity and the glycosylation site of glycans affect protein folding and stability: A molecular dynamics simulationLu, Diannan; Yang, Cheng; Liu, ZhengJournal of Physical Chemistry B (2012), 116 (1), 390-400CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Glycosylation is one of the most common post-translational modifications in the biosynthesis of protein, but its effect on the protein conformational transitions underpinning folding and stabilization is poorly understood. Here, the authors present a coarse-grained off-lattice 46-β barrel model protein glycosylated by glycans with different hydrophobicity and glycosylation sites to examine the effect of glycans on protein folding and stabilization using a Langevin dynamics simulation, in which an H term was proposed as the index of the hydrophobicity of glycan. Compared with its native counterpart, introducing glycans of suitable hydrophobicity (0.1 < H < 0.4) at flexible peptide residues of this model protein not only facilitated folding of the protein but also increased its conformation stability significantly. On the contrary, when glycans were introduced at the restricted peptide residues of the protein, only those hydrophilic (H = 0) or very weak hydrophobic (H < 0.2) ones contributed slightly to protein stability but hindered protein folding due to increased free energy barriers. The glycosylated protein retained the 2-step folding mechanism in terms of hydrophobic collapse and structural rearrangement. Glycan chains located in a suitable site with an appropriate hydrophobicity facilitated both collapse and rearrangement, whereas others, although accelerating collapse, hindered rearrangement. In addn. to entropy effects, i.e., narrowing the space of the conformations of the unfolded state, the presence of glycans with suitable hydrophobicity at suitable glycosylation site strengthened the folded state via hydrophobic interaction, i.e., the enthalpy effect. The simulations showed both the stabilization and the destabilization effects of glycosylation, as exptl. reported in the literature, and provided mol. insight into glycosylated proteins. The understanding of the effects of glycans with different hydrophobicities on the folding and stability of proteins, as attempted by the present work, is helpful not only to explain the stabilization and destabilization effect of real glycoproteins but also to design protein-polymer conjugates for biotechnol. purposes.
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429Chan, H. S.; Zhang, Z.; Wallin, S.; Liu, Z. Cooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained models Annu. Rev. Phys. Chem. 2011, 62, 301– 326 DOI: 10.1146/annurev-physchem-032210-103405429https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVWmt74%253D&md5=f32eb4a2142f630a149077d93afffb4aCooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained modelsChan, Hue Sun; Zhang, Zhuqing; Wallin, Stefan; Liu, ZhirongAnnual Review of Physical Chemistry (2011), 62 (), 301-326CODEN: ARPLAP; ISSN:0066-426X. (Annual Reviews Inc.)A review. Coarse-grained, self-contained polymer models are powerful tools in the study of protein folding. They are also essential to assess predictions from less rigorous theor. approaches that lack an explicit-chain representation. Here we review advances in coarse-grained modeling of cooperative protein folding, noting in particular that the Levinthal paradox was raised in response to the exptl. discovery of two-state-like folding in the late 1960s, rather than to the problem of conformational search per se. Comparisons between theory and expt. indicate a prominent role of desolvation barriers in cooperative folding, which likely emerges generally from a coupling between local conformational preferences and nonlocal packing interactions. Many of these principles have been elucidated by native-centric models, wherein nonnative interactions may be treated perturbatively. We discuss these developments as well as recent applications of coarse-grained chain modeling to knotted proteins and to intrinsically disordered proteins.
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430Qin, M.; Wang, W.; Thirumalai, D. Protein folding guides disulfide bond formation Proc. Natl. Acad. Sci. U. S. A. 2015, 112, 11241– 11246 DOI: 10.1073/pnas.1503909112430https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlyjt73M&md5=bc556b6cf6d4142ac1ef749ddf7836f9Protein folding guides disulfide bond formationQin, Meng; Wang, Wei; Thirumalai, D.Proceedings of the National Academy of Sciences of the United States of America (2015), 112 (36), 11241-11246CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The Anfinsen principle that the protein sequence uniquely dets. its structure is based on expts. on oxidative refolding of a protein with disulfide bonds. The problem of how protein folding drives disulfide bond formation is poorly understood. Here, we have solved this long-standing problem by creating a general method for implementing the chem. of disulfide bond formation and rupture in coarse-grained mol. simulations. As a case study, we investigate the oxidative folding of bovine pancreatic trypsin inhibitor (BPTI). After confirming the exptl. findings that the multiple routes to the folded state contain a network of states dominated by native disulfides, we show that the entropically unfavorable native single disulfide [14-38] between Cys14 and Cys38 forms only after polypeptide chain collapse and complete structuring of the central core of the protein contg. an antiparallel β-sheet. Subsequent assembly, resulting in native two-disulfide bonds and the folded state, involves substantial unfolding of the protein and transient population of nonnative structures. The rate of [14-38] formation increases as the β-sheet stability increases. The flux to the native state, through a network of kinetically connected native-like intermediates, changes dramatically by altering the redox conditions. Disulfide bond formation between Cys residues not present in the native state are relevant only on the time scale of collapse of BPTI. The finding that formation of specific collapsed native-like structures guides efficient folding is applicable to a broad class of single-domain proteins, including enzyme-catalyzed disulfide proteins.
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431Jewett, A. I.; Shea, J. E. Reconciling theories of chaperonin accelerated folding with experimental evidence Cell. Mol. Life Sci. 2010, 67, 255– 276 DOI: 10.1007/s00018-009-0164-6431https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXis1ejsQ%253D%253D&md5=6afcd22f8a0e21189a778281cb7e3dafReconciling theories of chaperonin accelerated folding with experimental evidenceJewett, Andrew I.; Shea, Joan-EmmaCellular and Molecular Life Sciences (2010), 67 (2), 255-276CODEN: CMLSFI; ISSN:1420-682X. (Birkhaeuser Verlag)A review. For the last 20 yr, a large vol. of exptl. and theor. work has been undertaken to understand how chaperones like GroEL can assist protein folding in the cell. The most accepted explanation appears to be the simplest: GroEL, like most other chaperones, helps proteins fold by preventing aggregation. However, evidence suggests that, under some conditions, GroEL can play a more active role by accelerating protein folding. A large no. of models have been proposed to explain how this could occur. Focused expts. have been designed and carried out using different protein substrates with conclusions that support many different mechanisms. Here, the authors attempt to see the forest through the trees. The authors review all suggested mechanisms for chaperonin-mediated folding and weigh the plausibility of each in light of what is now known about the most stringent, essential, GroEL-dependent protein substrates.
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432Lucent, D.; England, J.; Pande, V. Inside the chaperonin toolbox: theoretical and computational models for chaperonin mechanism Phys. Biol. 2009, 6, 015003 DOI: 10.1088/1478-3975/6/1/015003There is no corresponding record for this reference.
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433Stan, G.; Lorimer, G. H.; Thirumalai, D.; Brooks, B. R. Coupling between allosteric transitions in GroEL and assisted folding of a substrate protein Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 8803– 8808 DOI: 10.1073/pnas.0700607104There is no corresponding record for this reference.
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434Orozco, M.; Orellana, L.; Hospital, A.; Naganathan, A. N.; Emperador, A.; Carrillo, O.; Gelpi, J. L. Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomings Adv. Protein Chem. Struct. Biol. 2011, 85, 183– 215 DOI: 10.1016/B978-0-12-386485-7.00005-3434https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVKhs7bN&md5=a6e041025028248e487fd3f29c6a2466Coarse-grained representation of protein flexibility. Foundations, successes, and shortcomingsOrozco, Modesto; Orellana, Laura; Hospital, Adam; Naganathan, Athi N.; Emperador, Agusti; Carrillo, Oliver; Gelpi, J. L.Advances in Protein Chemistry and Structural Biology (2011), 85 (Computational Chemistry Methods in Structural Biology), 183-215CODEN: APCSG7; ISSN:1876-1623. (Elsevier Ltd.)A review. Flexibility is the key magnitude to understand the variety of functions of proteins. Unfortunately, its exptl. study is quite difficult, and in fact, most exptl. procedures are designed to reduce flexibility and allow a better definition of the structure. Theor. approaches have become then the alternative but face serious timescale problems, since many biol. relevant deformation movements happen in a timescale that is far beyond the possibility of current atomistic models. In this complex scenario, coarse-grained simulation methods have emerged as a powerful and inexpensive alternative. Along this chapter, we will review these coarse-grained methods, and explain their phys. foundations and their range of applicability.
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435Piana, S.; Lindorff-Larsen, K.; Shaw, D. E. How Robust Are Protein Folding Simulations with Respect to Force Field Parameterization? Biophys. J. 2011, 100, L47– L49 DOI: 10.1016/j.bpj.2011.03.051435https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXlsFagsr8%253D&md5=e861a2c068b5044251664c17552da5b8How Robust Are Protein Folding Simulations with Respect to Force Field Parameterization?Piana, Stefano; Lindorff-Larsen, Kresten; Shaw, David E.Biophysical Journal (2011), 100 (9), L47-L49CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Mol. dynamics simulations hold the promise of providing an at.-level description of protein folding that cannot easily be obtained from expts. Here, we examine the extent to which the mol. mechanics force field used in such simulations might influence the obsd. folding pathways. To that end, we performed equil. simulations of a fast-folding variant of the villin headpiece using four different force fields. In each simulation, we obsd. a large no. of transitions between the unfolded and folded states, and in all four cases, both the rate of folding and the structure of the native state were in good agreement with expts. We found, however, that the folding mechanism and the properties of the unfolded state depend substantially on the choice of force field. We thus conclude that although it is important to match a single, exptl. detd. structure and folding rate, this does not ensure that a given simulation will provide a unique and correct description of the full free-energy surface and the mechanism of folding.
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436Martin-Garcia, F.; Papaleo, E.; Gomez-Puertas, P.; Boomsma, W.; Lindorff-Larsen, K. Comparing Molecular Dynamics Force Fields in the Essential Subspace. PLoS One 2015, 10, e0121114 DOI: 10.1371/journal.pone.0121114There is no corresponding record for this reference.
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437Palazzesi, F.; Prakash, M. K.; Bonomi, M.; Barducci, A. Accuracy of current all-atom force-fields in modeling protein disordered states J. Chem. Theory Comput. 2015, 11, 2– 7 DOI: 10.1021/ct500718s437https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitFeit7bO&md5=997c50dda2779cd92286484bd4d3b951Accuracy of Current All-Atom Force-Fields in Modeling Protein Disordered StatesPalazzesi, Ferruccio; Prakash, Meher K.; Bonomi, Massimiliano; Barducci, AlessandroJournal of Chemical Theory and Computation (2015), 11 (1), 2-7CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. Dynamics (MD) plays a fundamental role in characterizing protein disordered states that are emerging as crucial actors in many biol. processes. Here the authors assess the accuracy of three current force-fields in modeling disordered peptides by combining enhanced-sampling MD simulations with NMR data. These force-fields generate significantly different conformational ensembles, and AMBER03w provides the best agreement with expts., which is further improved by adding the ILDN corrections.
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438Rueda, M.; Ferrer-Costa, C.; Meyer, T.; Perez, A.; Camps, J.; Hospital, A.; Gelpi, J. L.; Orozco, M. A consensus view of protein dynamics Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 796– 801 DOI: 10.1073/pnas.0605534104438https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtVegsbY%253D&md5=13f810bed01cd1a3f40f21268fe6a75bA consensus view of protein dynamicsRueda, Manuel; Ferrer-Costa, Carles; Meyer, Tim; Perez, Alberto; Camps, Jordi; Hospital, Adam; Gelpi, Josep Lluis; Orozco, ModestoProceedings of the National Academy of Sciences of the United States of America (2007), 104 (3), 796-801CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The dynamics of proteins in aq. soln. has been investigated through a massive approach based on "state of the art" mol. dynamics simulations performed for all protein metafolds using the four most popular force fields (OPLS, CHARMM, AMBER, and GROMOS). A detailed anal. of the massive database of trajectories (>1.5 terabytes of data obtained using ≈50 years of CPU) allowed us to obtain a robust-consensus picture of protein dynamics in aq. soln.
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439Emperador, A.; Carrillo, O.; Rueda, M.; Orozco, M. Exploring the suitability of coarse-grained techniques for the representation of protein dynamics Biophys. J. 2008, 95, 2127– 2138 DOI: 10.1529/biophysj.107.119115There is no corresponding record for this reference.
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440Emperador, A.; Meyer, T.; Orozco, M. United-Atom Discrete Molecular Dynamics of Proteins Using Physics-Based Potentials J. Chem. Theory Comput. 2008, 4, 2001– 2010 DOI: 10.1021/ct8003832440https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlGrsrnI&md5=d242feabd72c9be192436614ff2b1cc8United-Atom Discrete Molecular Dynamics of Proteins Using Physics-Based PotentialsEmperador, Agusti; Meyer, Tim; Orozco, ModestoJournal of Chemical Theory and Computation (2008), 4 (12), 2001-2010CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We present a method for the efficient simulation of the equil. dynamics of proteins based on the well established discrete mol. dynamics algorithm, which avoids integration of Newton equations of motion at short time steps, allowing then the derivation of very large trajectories for proteins with a reduced computational cost. In the presented implementation we used an all heavy-atoms description of proteins, with simple potentials describing the conformational region around the exptl. structure based on local phys. interactions (covalent structure, hydrogen bonds, hydrophobic contacts, solvation, steric hindrance, and bulk dispersion interactions). The method shows a good ability to describe the flexibility of 33 diverse proteins in water as detd. by atomistic mol. dynamics simulation and can be useful for massive simulation of proteins in crowded environments or for refinement of protein structure in large complexes.
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441Bowman, G. R. Accurately modeling nanosecond protein dynamics requires at least microseconds of simulation J. Comput. Chem. 2016, 37, 558– 566 DOI: 10.1002/jcc.23973441https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXpvFWnt7s%253D&md5=658f38891f310f844edc4cd5377eb453Accurately modeling nanosecond protein dynamics requires at least microseconds of simulationBowman, Gregory R.Journal of Computational Chemistry (2016), 37 (6), 558-566CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Advances in hardware and algorithms have greatly extended the timescales accessible to mol. simulation. This article assesses whether such long timescale simulations improve our ability to calc. order parameters that describe conformational heterogeneity on ps-ns timescales or if force fields are now a limiting factor. Order parameters from expt. are compared with order parameters calcd. in three different ways from simulations ranging from 10 ns to 100 μs in length. Importantly, bootstrapping is employed to assess the variability in results for each simulation length. The results of 10-100 ns timescale simulations are highly variable, possibly explaining the variation in levels of agreement between simulation and expt. in published works examg. different proteins. Fortunately, microsecond timescale simulations improve both the accuracy and precision of calcd. order parameters, at least so long as the full exponential fit or truncated av. approxn. is used instead of the common long-time limit approxn. The improved precision of these long timescale simulations allows a statistically sound comparison of a no. of modern force fields, such as Amber03, Amber99sb-ILDN, and Charmm27. While there is some variation between these force fields, they generally give very similar results for sufficiently long simulations. The fact that so much simulation is required to precisely capture ps-ns timescale processes suggests that extremely extensive simulations are required for slower processes. Advanced sampling techniques could aid greatly, however, such methods will need to maintain accurate kinetics if they are to be of value for calcg. dynamical properties like order parameters. © 2015 Wiley Periodicals, Inc.
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442Bahar, I.; Rader, A. J. Coarse-grained normal mode analysis in structural biology Curr. Opin. Struct. Biol. 2005, 15, 586– 592 DOI: 10.1016/j.sbi.2005.08.007442https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXhtVKjsLzE&md5=2bb5bbf564b14a0977452a28e28b8374Coarse-grained normal mode analysis in structural biologyBahar, Ivet; Rader, A. J.Current Opinion in Structural Biology (2005), 15 (5), 586-592CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The realization that exptl. obsd. functional motions of proteins can be predicted by coarse-grained normal mode anal. has renewed interest in applications to structural biol. Notable applications include the prediction of biol. relevant motions of proteins and supramol. structures driven by their structure-encoded collective dynamics; the refinement of low-resoln. structures, including those detd. by cryo-electron microscopy; and the identification of conserved dynamic patterns and mech. key regions within protein families. Addnl., hybrid methods that couple at. simulations with deformations derived from coarse-grained normal mode anal. are able to sample collective motions beyond the range of conventional mol. dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.
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443Ma, J. Usefulness and limitations of normal mode analysis in modeling dynamics of biomolecular complexes Structure 2005, 13, 373– 380 DOI: 10.1016/j.str.2005.02.002443https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXit1Chsbs%253D&md5=820348ab7b6039233f65129dcbf67db5Usefulness and Limitations of Normal Mode Analysis in Modeling Dynamics of Biomolecular ComplexesMa, JianpengStructure (Cambridge, MA, United States) (2005), 13 (3), 373-380CODEN: STRUE6; ISSN:0969-2126. (Cell Press)A review. Various types of large-amplitude mol. deformation are ubiquitously involved in the functions of biol. macromols., esp. supramol. complexes. They can be very effectively analyzed by normal mode anal. with well-established procedures. However, despite its enormous success in numerous applications, certain issues related to the applications of normal mode anal. require further discussion. In this review, the author addresses some common issues so as to raise the awareness of the usefulness and limitations of the method in the general community of structural biol.
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444Lexa, K. W.; Carlson, H. A. Full protein flexibility is essential for proper hot-spot mapping J. Am. Chem. Soc. 2011, 133, 200– 202 DOI: 10.1021/ja1079332444https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsFKjtbbJ&md5=e534a799461ee66ddf75c6a0571ca983Full Protein Flexibility is Essential for Proper Hot-Spot MappingLexa, Katrina W.; Carlson, Heather A.Journal of the American Chemical Society (2011), 133 (2), 200-202CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)A traditional technique for structure-based drug design (SBDD) is mapping of protein surfaces with probe mols. to identify "hot spots" where key functional groups can best complement the receptor. Common methods, such as minimization of probes or calcn. of grids, use a fixed protein structure in the gas phase, ignoring both protein flexibility and proper competition between the probes and water. As a result, the potential surface is quite rugged, and many spurious local min. are identified. In this work, the authors compared rigid and fully flexible proteins in mixed-solvent mol. dynamics, which allows for flexibility and full solvent effects. The authors were surprised to find that the large no. of local min. are still found when a protein's conformational sampling is restricted; the dynamic averaging of probes and competition with water do not smooth the potential surface as one might expect. Only when a protein is allowed to be fully flexible in the simulation are the proper min. located and the spurious ones eliminated. The authors' results indicate that inclusion of full protein flexibility is crit. to accurate hot-spot mapping for SBDD.
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445Antunes, D. A.; Devaurs, D.; Kavraki, L. E. Understanding the challenges of protein flexibility in drug design Expert Opin. Drug Discovery 2015, 10, 1301– 1313 DOI: 10.1517/17460441.2015.1094458445https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvFOmt7fL&md5=20d2e716785ecac65a223c7954ef0b16Understanding the challenges of protein flexibility in drug designAntunes, Dinler A.; Devaurs, Didier; Kavraki, Lydia E.Expert Opinion on Drug Discovery (2015), 10 (12), 1301-1313CODEN: EODDBX; ISSN:1746-0441. (Taylor & Francis Ltd.)Protein-ligand interactions play key roles in various metabolic pathways, and the proteins involved in these interactions represent major targets for drug discovery. Mol. docking is widely used to predict the structure of protein-ligand complexes, and protein flexibility stands out as one of the most important and challenging issues for binding mode prediction. Various docking methods accounting for protein flexibility have been proposed, tackling problems of ever-increasing dimensionality. This paper presents an overview of conformational sampling methods treating target flexibility during mol. docking. Special attention is given to approaches considering full protein flexibility. Contrary to what is frequently done, this review does not rely on classical biomol. recognition models to classify existing docking methods. Instead, it applies algorithmic considerations, focusing on the level of flexibility accounted for. This review also discusses the diversity of docking applications, from virtual screening (VS) of small drug-like compds. to geometry prediction (GP) of protein-peptide complexes. Considering the diversity of docking methods presented here, deciding which one is the best at treating protein flexibility depends on the system under study and the research application. In VS expts., ensemble docking can be used to implicitly account for large-scale conformational changes, and selective docking can addnl. consider local binding-site rearrangements. In other cases, on-the-fly exploration of the whole protein-ligand complex might be needed for accurate GP of the binding mode. Among other things, future methods are expected to provide alternative binding modes, which will better reflect the dynamic nature of protein-ligand interactions.
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446Alvarez-Garcia, D.; Barril, X. Relationship between Protein Flexibility and Binding: Lessons for Structure-Based Drug Design J. Chem. Theory Comput. 2014, 10, 2608– 2614 DOI: 10.1021/ct500182z446https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotlWjtLs%253D&md5=53099fb844bc5037d5ed9689f74497b2Relationship between protein flexibility and binding: Lessons for structure-based drug designAlvarez-Garcia, Daniel; Barril, XavierJournal of Chemical Theory and Computation (2014), 10 (6), 2608-2614CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Conceptually, the simplistic lock and key model has been superseded by more realistic views of mol. recognition that take into account the intrinsic dynamics of biol. macromols. However, it is still common for structure-based drug discovery methods to represent the receptor as static structures. The practical advantages of this approxn., the notable success attained over the past few decades with such simple models, and the absence of clear guidelines for weighing the pros and cons of accounting for flexibility may prompt some investigators to stretch the rigid model beyond its scope. Here, the authors investigated the relation between protein flexibility and binding free energy and present some useful hints for understanding when, and to what extent, flexibility should be considered. Using mol. dynamics simulations of hen egg-white lysozyme (HEWL) with explicit aq./org. solvent mixts. and a range of restraint conditions, the authors found out how artificially restricted mobility affects binding hot spots. Barring sampling errors or an inappropriate choice of ref. structure, it was found that decreased mobility (measured as B-factors) leads to artifactually more neg. binding free energies, but a logarithmic relation between both terms attenuates the errors. Consequently, ignoring flexibility may be an acceptable approxn. for intrinsically rigid regions (such as the active site of enzymes), but may lead to larger errors elsewhere. For the same reason, local conformational sampling yields very accurate predictions and, owing to its practical advantages, may be preferable to full conformational sampling for many applications.
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447Zhang, J.; Minary, P.; Levitt, M. Multiscale natural moves refine macromolecules using single-particle electron microscopy projection images Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 9845– 9850 DOI: 10.1073/pnas.1205945109447https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKksLjE&md5=301bdc0f581d6fd3d497e7150cf6b589Multiscale natural moves refine macromolecules using single-particle electron microscopy projection imagesZhang, Junjie; Minary, Peter; Levitt, MichaelProceedings of the National Academy of Sciences of the United States of America (2012), 109 (25), 9845-9850, S9845/1-S9845/10CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The method presented here refines mol. conformations directly against projections of single particles measured by electron microscopy. By optimizing the orientation of the projection at the same time as the conformation, the method is well-suited to two-dimensional class avs. from cryoelectron microscopy. Such direct use of two-dimensional images circumvents the need for a three-dimensional d. map, which may be difficult to reconstruct from projections due to structural heterogeneity or preferred orientations of the sample on the grid. Our refinement protocol exploits Natural Move Monte Carlo to model a macromol. as a small no. of segments connected by flexible loops, on multiple scales. After tests on artificial data from lysozyme, we applied the method to the Methonococcus maripaludis chaperonin. We successfully refined its conformation from a closed-state initial model to an open-state final model using just one class-averaged projection. We also used Natural Moves to iteratively refine against heterogeneous projection images of Methonococcus maripaludis chaperonin in a mix of open and closed states. Our results suggest a general method for electron microscopy refinement specially suited to macromols. with significant conformational flexibility. The algorithm is available in the program Methodologies for Optimization and Sampling In Computational Studies.
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448Consortium, T. U. UniProt: a hub for protein information. Nucleic Acids Res. 2014.There is no corresponding record for this reference.
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449Berman, H. M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T. N.; Weissig, H.; Shindyalov, I. N.; Bourne, P. E. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235– 242 DOI: 10.1093/nar/28.1.235449https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXhvVKjt7w%253D&md5=227fb393f754be2be375ab727bfd05dcThe Protein Data BankBerman, Helen M.; Westbrook, John; Feng, Zukang; Gilliland, Gary; Bhat, T. N.; Weissig, Helge; Shindyalov, Ilya N.; Bourne, Philip E.Nucleic Acids Research (2000), 28 (1), 235-242CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The Protein Data Bank (PDB; http://www.rcsb.org/pdb/)is the single worldwide archive of structural data of biol. macromols. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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450Rost, B. Twilight zone of protein sequence alignments Protein Eng., Des. Sel. 1999, 12, 85– 94 DOI: 10.1093/protein/12.2.85There is no corresponding record for this reference.
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451Liang, S.; Zhang, C.; Zhou, Y. LEAP: highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains J. Comput. Chem. 2014, 35, 335– 341 DOI: 10.1002/jcc.23509451https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFSktLzM&md5=22748e325288183d4e908476f37fbd1bLEAP: Highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chainsLiang, Shide; Zhang, Chi; Zhou, YaoqiJournal of Computational Chemistry (2014), 35 (4), 335-341CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Prediction of protein loop conformations without any prior knowledge (ab initio prediction) is an unsolved problem. Its soln. will significantly impact protein homol. and template-based modeling as well as ab initio protein-structure prediction. Here, we developed a coarse-grained, optimized scoring function for initial sampling and ranking of loop decoys. The resulting decoys are then further optimized in backbone and side-chain conformations and ranked by all-atom energy scoring functions. The final integrated technique called loop prediction by energy-assisted protocol achieved a median value of 2.1 Å root mean square deviation (RMSD) for 325 12-residue test loops and 2.0 Å RMSD for 45 12-residue loops from crit. assessment of structure-prediction techniques (CASP) 10 target proteins with native core structures (backbone and side chains). If all side-chain conformations in protein cores were predicted in the absence of the target loop, loop-prediction accuracy only reduces slightly (0.2 Å difference in RMSD for 12-residue loops in the CASP target proteins). The accuracy obtained is about 1 Å RMSD or more improvement over other methods we tested. The executable file for a Linux system is freely available for academic users at http://sparks-lab.org.
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452Kmiecik, S.; Jamroz, M.; Kolinski, M. Structure prediction of the second extracellular loop in G-protein-coupled receptors Biophys. J. 2014, 106, 2408– 2416 DOI: 10.1016/j.bpj.2014.04.022452https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpvVahtbo%253D&md5=e1e5e9ff7ba2fbd508fa4b20a52139b0Structure prediction of the second extracellular loop in G-protein-coupled receptorsKmiecik, Sebastian; Jamroz, Michal; Kolinski, MichalBiophysical Journal (2014), 106 (11), 2408-2416CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to det. their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theor. predictions of ECL2 secondary structure and exptl. constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystd. GPCRs.
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453Goldfeld, D. A.; Zhu, K.; Beuming, T.; Friesner, R. A. Loop prediction for a GPCR homology model: algorithms and results Proteins: Struct., Funct., Genet. 2013, 81, 214– 228 DOI: 10.1002/prot.24178There is no corresponding record for this reference.
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454Kolinski, M.; Filipek, S. Study of a structurally similar kappa opioid receptor agonist and antagonist pair by molecular dynamics simulations J. Mol. Model. 2010, 16, 1567– 1576 DOI: 10.1007/s00894-010-0678-8454https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1Kjt7rN&md5=1350be2c7b8c77acaebb26ea3676bca6Study of a structurally similar kappa opioid receptor agonist and antagonist pair by molecular dynamics simulationsKolinski, Michal; Filipek, SlawomirJournal of Molecular Modeling (2010), 16 (10), 1567-1576CODEN: JMMOFK; ISSN:0948-5023. (Springer GmbH)Among the structurally similar guanidinonaltrindole (GNTI) compds., 5'-GNTI is an antagonist while 6'-GNTI is an agonist of the κOR opioid receptor. To explore how a subtle alteration of the ligand structure influences the receptor activity, we investigated two concurrent processes: the final steps of ligand binding at the receptor binding site and the initial steps of receptor activation. To trace these early activation steps, the membranous part of the receptor was built on an inactive receptor template while the extracellular loops were built using the ab initio CABS method. We used the simulated annealing procedure for ligand docking and all-atom mol. dynamics simulations to det. the immediate changes in the structure of the ligand-receptor complex. The binding of an agonist, in contrast to an antagonist, induced the breakage of the "3-7 lock" between helixes TM3 and TM7. We also obsd. an action of the extended rotamer toggle switch which suggests that those two switches are interdependent.
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455Zhang, Y. Interplay of I-TASSER and QUARK for template-based and ab initio protein structure prediction in CASP10 Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 175– 187 DOI: 10.1002/prot.24341There is no corresponding record for this reference.
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456Szilagyi, A.; Zhang, Y. Template-based structure modeling of protein-protein interactions Curr. Opin. Struct. Biol. 2014, 24, 10– 23 DOI: 10.1016/j.sbi.2013.11.005456https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtVamsr8%253D&md5=4d1e5e76bae7ce18946b7ddab49158f9Template-based structure modeling of protein-protein interactionsSzilagyi, Andras; Zhang, YangCurrent Opinion in Structural Biology (2014), 24 (), 10-23CODEN: COSBEF; ISSN:0959-440X. (Elsevier Ltd.)A review. The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homol.-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Crit. improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput exptl. data. Nevertheless, bottlenecks exist due to the incompleteness of the protein-protein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement.
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457Iacoangeli, A.; Marcatili, P.; Tramontano, A. Exploiting homology information in nontemplate based prediction of protein structures J. Chem. Theory Comput. 2015, 11, 5045– 5051 DOI: 10.1021/acs.jctc.5b00371457https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsFWhs7nI&md5=6e331ada2054a825678e3a21a11cfc56Exploiting Homology Information in Nontemplate Based Prediction of Protein StructuresIacoangeli, Alfredo; Marcatili, Paolo; Tramontano, AnnaJournal of Chemical Theory and Computation (2015), 11 (10), 5045-5051CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors describe a novel strategy for exploring the conformational space of proteins and show that this leads to better models for proteins the structure of which is not amenable to template based methods. The authors' strategy is based on the assumption that the energy global min. of homologous proteins must correspond to similar conformations, while the precise profiles of their energy landscape, and consequently the positions of the local min., are likely to be different. In line with this hypothesis, the authors apply a replica exchange Monte Carlo simulation protocol that, rather than using different parameters for each parallel simulation, uses the sequences of homologous proteins. The authors' results are competitive with respect to alternative methods, including those producing the best model for each of the analyzed targets in the CASP10 (10th Crit. Assessment of techniques for protein Structure Prediction) expt. free modeling category.
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458Zhang, W.; Yang, J.; He, B.; Walker, S. E.; Zhang, H.; Govindarajoo, B.; Virtanen, J.; Xue, Z.; Shen, H. B.; Zhang, Y. Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11 Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24930There is no corresponding record for this reference.
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459Xu, D.; Zhang, Y. Ab Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignment Sci. Rep. 2013, 3, 1895 DOI: 10.1038/srep01895459https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3snotVOntQ%253D%253D&md5=b735f3b8756f7f75c23137f4efa4cb7aAb Initio structure prediction for Escherichia coli: towards genome-wide protein structure modeling and fold assignmentXu Dong; Zhang YangScientific reports (2013), 3 (), 1895 ISSN:.Genome-wide protein structure prediction and structure-based function annotation have been a long-term goal in molecular biology but not yet become possible due to difficulties in modeling distant-homology targets. We developed a hybrid pipeline combining ab initio folding and template-based modeling for genome-wide structure prediction applied to the Escherichia coli genome. The pipeline was tested on 43 known sequences, where QUARK-based ab initio folding simulation generated models with TM-score 17% higher than that by traditional comparative modeling methods. For 495 unknown hard sequences, 72 are predicted to have a correct fold (TM-score > 0.5) and 321 have a substantial portion of structure correctly modeled (TM-score > 0.35). 317 sequences can be reliably assigned to a SCOP fold family based on structural analogy to existing proteins in PDB. The presented results, as a case study of E. coli, represent promising progress towards genome-wide structure modeling and fold family assignment using state-of-the-art ab initio folding algorithms.
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460Thevenet, P.; Shen, Y.; Maupetit, J.; Guyon, F.; Derreumaux, P.; Tuffery, P. PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides Nucleic Acids Res. 2012, 40, W288– 293 DOI: 10.1093/nar/gks419460https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXjtVCkurs%253D&md5=ba2fc12d7a8d5067fa975a085a98f244PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptidesThevenet, Pierre; Shen, Yimin; Maupetit, Julien; Guyon, Frederic; Derreumaux, Philippe; Tuffery, PierreNucleic Acids Research (2012), 40 (W1), W288-W293CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)In the context of the renewed interest of peptides as therapeutics, it is important to have an online resource for 3D structure prediction of peptides with well-defined structures in aq. soln. We present an updated version of PEP-FOLD allowing the treatment of both linear and disulfide bonded cyclic peptides with 9-36 amino acids. The server makes possible to define disulfide bonds and any residue-residue proximity under the guidance of the biologists. Using a benchmark of 34 cyclic peptides with one, two and three disulfide bonds, the best PEP-FOLD models deviate by an av. RMS of 2.75 Å from the full NMR structures. Using a benchmark of 37 linear peptides, PEP-FOLD locates lowest-energy conformations deviating by 3 Å RMS from the NMR rigid cores. The evolution of PEP-FOLD comes as a new online service to supersede the previous server. The server is available at: http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.
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461Thévenet, P.; Rey, J.; Moroy, G.; Tuffery, P. In Computational Peptidology; Zhou, P.; Huang, J., Eds.; Springer: New York, 2015; Vol. 1268.There is no corresponding record for this reference.
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462Samudrala, R.; Xia, Y.; Huang, E.; Levitt, M. Ab initio protein structure prediction using a combined hierarchical approach Proteins: Struct., Funct., Genet. 1999, 37 (Suppl 3) 194– 198 DOI: 10.1002/(SICI)1097-0134(1999)37:3+<194::AID-PROT24>3.0.CO;2-FThere is no corresponding record for this reference.
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463Kolinski, A.; Skolnick, J. Monte Carlo simulations of protein folding. II. Application to protein A, ROP, and crambin Proteins: Struct., Funct., Genet. 1994, 18, 353– 366 DOI: 10.1002/prot.340180406463https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXktlSnsr8%253D&md5=07940835aa95056f96420f05052cd5a6Monte Carlo simulations of protein folding. II. Application to protein A, ROP, and CrambinKolinski, Andrzej; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1994), 18 (4), 353-66CODEN: PSFGEY; ISSN:0887-3585.The hierarchy of lattice Monte Carlo models is applied to the simulation of protein folding and the prediction of 3-dimensional structure. Using sequence information alone, 3 proteins have been successfully folded: the B domain of staphylococcal protein A, a 120 residue, monomeric version of ROP dimer, and crambin. Starting from a random expanded conformation, the model proteins fold along relatively well-defined folding pathways. These involve a collection of early intermediates, which are followed by the final (and rate-detg.) transition from compact intermediates closely resembling the molten globule state to the native-like state. The predicted structures are rather unique, with native-like packing of the side chains. The accuracy of the predicted native conformations is better than those obtained in previous folding simulations. The best fold of protein A have a coordinate rms of 2.25 Å from the native Cαs trace, and the best coordinate rms from crambin is 3.18 Å. For ROP monomer, the lowest coordinate rms from equiv. Cαs of ROP dimer is 3.65 Å. Thus, for two simple helical proteins and a small α/β protein, the ability to predict protein structure from sequence has been demonstrated.
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464Kolinski, A.; Skolnick, J. Monte Carlo simulations of protein folding. I. Lattice model and interaction scheme Proteins: Struct., Funct., Genet. 1994, 18, 338– 352 DOI: 10.1002/prot.340180405464https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2cXktlSnsr4%253D&md5=2d1c1da84b7574a5b401686f3dfc26c4Monte Carlo simulations of protein folding. I. Lattice model and interaction schemeKolinski, Andrzej; Skolnick, JeffreyProteins: Structure, Function, and Genetics (1994), 18 (4), 338-52CODEN: PSFGEY; ISSN:0887-3585.A new hierarchical method for the simulation of the protein folding process and the de novo prediction of protein three-dimensional structure is proposed. The reduced representation of the protein α-carbon backbone employs lattice discretizations of increasing geometrical resoln. and a single ball representation of side chain rotamers. In particular, coarser and finer lattice backbone descriptions are used. The coarser (finer) lattice represents Cα traces of native proteins with an accuracy of 1.0 (0.7) Å rms. Folding is simulated by means of very fast Monte Carlo lattice dynamics. The potential of mean force, predominantly of statistical origin, contains several novel terms that facilitate the cooperative assembly of secondary structure elements and the cooperative packing of the side chains. Particular contributions to the interaction scheme are discussed in detail.
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465Tai, C. H.; Bai, H.; Taylor, T. J.; Lee, B. Assessment of template-free modeling in CASP10 and ROLL Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 57– 83 DOI: 10.1002/prot.24470465https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFentLbP&md5=40ee48832f8e2baa18d63815e9511141Assessment of template-free modeling in CASP10 and ROLLTai, Chin-Hsien; Bai, Hongjun; Taylor, Todd J.; Lee, ByungkookProteins: Structure, Function, and Bioinformatics (2014), 82 (S2), 57-83CODEN: PSFBAF ISSN:. (Wiley-Blackwell)We present the assessment of predictions for Template-Free Modeling in CASP10 and a report on the first ROLL expt. wherein predictions are collected year round for review at the regular CASP season. Models were first clustered so that duplicated or very similar ones were grouped together and represented by one model in the cluster. The representatives were then compared with targets using GDT_TS, QCS, and three addnl. superposition-independent score functions newly developed for CASP10. For each target, the top 15 representatives by each score were pooled to form the Top15Union set. All models in this set were visually inspected by four of us independently using the new plugin, EvalScore, which we developed with the UCSF Chimera group. The best models were selected for each target after extensive debate among the four examiners. Groups were ranked by the no. of targets (hits) for which a group's model was selected as one of the best models. The Keasar group had most hits in both categories, with four of 19 FM and eight of 36 ROLL targets. The most successful prediction servers were QUARK from Zhang's group for FM category with three hits and Zhang-server for the ROLL category with seven hits. As obsd. in CASP9, many successful groups were not true "template-free" modelers but used remote templates and/or server models to obtain their winning models. The results of the first ROLL expt. were broadly similar to those of the CASP10 FM exercise. Proteins 2013. © 2013 Wiley Periodicals, Inc.
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466Kinch, L.; Yong Shi, S.; Cong, Q.; Cheng, H.; Liao, Y.; Grishin, N. V. CASP9 assessment of free modeling target predictions Proteins: Struct., Funct., Genet. 2011, 79 (Suppl 10) 59– 73 DOI: 10.1002/prot.23181There is no corresponding record for this reference.
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467Ben-David, M.; Noivirt-Brik, O.; Paz, A.; Prilusky, J.; Sussman, J. L.; Levy, Y. Assessment of CASP8 structure predictions for template free targets Proteins: Struct., Funct., Genet. 2009, 77 (59) 50– 65 DOI: 10.1002/prot.22591There is no corresponding record for this reference.
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468Xu, D.; Zhang, Y. Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field Proteins: Struct., Funct., Genet. 2012, 80, 1715– 1735 DOI: 10.1002/prot.24065468https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XlsFyitLY%253D&md5=756720149740253705d28afc82234207Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force fieldXu, Dong; Zhang, YangProteins: Structure, Function, and Bioinformatics (2012), 80 (7), 1715-1735CODEN: PSFBAF ISSN:. (Wiley-Blackwell)Ab initio protein folding is one of the major unsolved problems in computational biol. owing to the difficulties in force field design and conformational search. The authors developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1-20 residues where multiple fragment structures are retrieved at each position from unrelated exptl. structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A no. of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed. QUARK prediction procedure is depicted and tested on the structure modeling of 145 nonhomologous proteins. Although no global templates were used and all fragments from exptl. structures with template modeling score >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in one-third cases of short proteins up to 100 residues. In the ninth community-wide Crit. Assessment of protein Structure Prediction expt., QUARK server outperformed the second and third best servers by 18 and 47% based on the cumulative Z-score of global distance test-total scores in the FM category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress toward the soln. of the most important problem in the field. Proteins 2012; © 2012 Wiley Periodicals, Inc.
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469Moult, J.; Fidelis, K.; Kryshtafovych, A.; Schwede, T.; Tramontano, A. Critical assessment of methods of protein structure prediction (CASP)--round x Proteins: Struct., Funct., Genet. 2014, 82 (Suppl 2) 1– 6 DOI: 10.1002/prot.24452There is no corresponding record for this reference.
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470Kinch, L. N.; Li, W.; Monastyrskyy, B.; Kryshtafovych, A.; Grishin, N. V. Evaluation of free modeling targets in CASP11 and ROLL Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24973There is no corresponding record for this reference.
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471Kim, H.; Kihara, D. Protein structure prediction using residue- and fragment-environment potentials in CASP11 Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24920There is no corresponding record for this reference.
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472Feig, M.; Mirjalili, V. Protein structure refinement via molecular-dynamics simulations: What works and what does not? Proteins: Struct., Funct., Genet. 2015, n/a DOI: 10.1002/prot.24871There is no corresponding record for this reference.
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473Berggard, T.; Linse, S.; James, P. Methods for the detection and analysis of protein-protein interactions Proteomics 2007, 7, 2833– 2842 DOI: 10.1002/pmic.200700131473https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2svpsVWksA%253D%253D&md5=7b359c9eaecb7b91b6c1aa3dc1807f4aMethods for the detection and analysis of protein-protein interactionsBerggard Tord; Linse Sara; James PeterProteomics (2007), 7 (16), 2833-42 ISSN:1615-9853.A large number of methods have been developed over the years to study protein-protein interactions. Many of these techniques are now available to the nonspecialist researcher thanks to new affordable instruments and/or resource centres. A typical protein-protein interaction study usually starts with an initial screen for novel binding partners. We start this review by describing three techniques that can be used for this purpose: (i) affinity-tagged proteins (ii) the two-hybrid system and (iii) some quantitative proteomic techniques that can be used in combination with, e.g., affinity chromatography and coimmunoprecipitation for screening of protein-protein interactions. We then describe some public protein-protein interaction databases that can be searched to identify previously reported interactions for a given bait protein. Four strategies for validation of protein-protein interactions are presented: confocal microscopy for intracellular colocalization of proteins, coimmunoprecipitation, surface plasmon resonance (SPR) and spectroscopic studies. Throughout the review we focus particularly on the advantages and limitations of each method.
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474Setny, P.; Bahadur, R. P.; Zacharias, M. Protein-DNA docking with a coarse-grained force field BMC Bioinf. 2012, 13, 228 DOI: 10.1186/1471-2105-13-228474https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpvFalsQ%253D%253D&md5=974e69804e1f5eb13ebae186f43b887dProtein-DNA docking with a coarse-grained force fieldSetny, Piotr; Bahadur, Ranjit Prasad; Zacharias, MartinBMC Bioinformatics (2012), 13 (), 228CODEN: BBMIC4; ISSN:1471-2105. (BioMed Central Ltd.)Background: Protein-DNA interactions are important for many cellular processes, however structural knowledge for a large fraction of known and putative complexes is still lacking. Computational docking methods aim at the prediction of complex architecture given detailed structures of its constituents. They are becoming an increasingly important tool in the field of macromol. assemblies, complementing particularly demanding protein-nucleic acids X ray crystallog. and providing means for the refinement and integration of low resoln. data coming from rapidly advancing methods such as cryoelectron microscopy. Results: We present a new coarse-grained force field suitable for protein-DNA docking. The force field is an extension of previously developed parameter sets for protein-RNA and protein-protein interactions. The docking is based on potential energy minimization in translational and orientational degrees of freedom of the binding partners. It allows for fast and efficient systematic search for native-like complex geometry without any prior knowledge regarding binding site location. Conclusions: We find that the force field gives very good results for bound docking. The quality of predictions in the case of unbound docking varies, depending on the level of structural deviation from bound geometries. We analyze the role of specific protein-DNA interactions on force field performance, both with respect to complex structure prediction, and the reprodn. of exptl. binding affinities. We find that such direct, specific interactions only partially contribute to protein-DNA recognition, indicating an important role of shape complementarity and sequence-dependent DNA internal energy, in line with the concept of indirect protein-DNA readout mechanism.
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475Uusitalo, J. J.; Ingolfsson, H. I.; Akhshi, P.; Tieleman, D. P.; Marrink, S. J. Martini Coarse-Grained Force Field: Extension to DNA J. Chem. Theory Comput. 2015, 11, 3932– 3945 DOI: 10.1021/acs.jctc.5b00286475https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtFGiur7I&md5=f66edb14d055b00005a6bf140fbfc602Martini Coarse-Grained Force Field: Extension to DNAUusitalo, Jaakko J.; Ingolfsson, Helgi I.; Akhshi, Parisa; Tieleman, D. Peter; Marrink, Siewert J.Journal of Chemical Theory and Computation (2015), 11 (8), 3932-3945CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors systematically parameterized a coarse-grained (CG) model for DNA that is compatible with the Martini force field. The model maps each nucleotide into six to seven CG beads and is parameterized following the Martini philosophy. The CG nonbonded interactions are based on partitioning of the nucleobases between polar and nonpolar solvents as well as base-base potential of mean force calcns. The bonded interactions are fit to single-stranded DNA (ssDNA) atomistic simulations and an elastic network was used to retain double-stranded DNA (dsDNA) and other specific DNA conformations. The authors present the implementation of the Martini DNA model and demonstrate the properties of individual bases, ssDNA as well as dsDNA, and DNA-protein complexes. The model opens up large-scale simulations of DNA interacting with a wide range of other (bio)mols. that are available within the Martini framework.
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476Hori, N.; Takada, S. Coarse-Grained Structure-Based Model for RNA-Protein Complexes Developed by Fluctuation Matching J. Chem. Theory Comput. 2012, 8, 3384– 3394 DOI: 10.1021/ct300361j476https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtV2gtrzN&md5=39feafbb08d9681d6b532c2dbeba6a9eCoarse-Grained Structure-Based Model for RNA-Protein Complexes Developed by Fluctuation MatchingHori, Naoto; Takada, ShojiJournal of Chemical Theory and Computation (2012), 8 (9), 3384-3394CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)RNA and RNA-protein complexes have recently been intensively studied in expts., but the corresponding mol. simulation work is much less abundant, primarily due to its large system size and the long time scale involved. Here, to overcome these bottlenecks, the authors develop a coarse-grained (CG) structure-based simulation model for RNA and RNA-protein complexes and test it for several mol. systems. The CG model for RNA contains three particles per nucleotide, each for phosphate, sugar, and a base. Focusing on RNA mols. that fold to well-defined native structures, the authors employed a structure-based potential, which is similar to the Go-like potential successfully used in CG modeling of proteins. In addn., the authors tested three means to approx. electrostatic interactions. Many parameters involved in the CG potential were detd. via a multiscale method: the authors matched the native fluctuation of the CG model with that by all-atom simulations for 16 RNA mols. and 10 RNA-protein complexes, from which the authors derived a generic set of CG parameters. The derived parameters can reproduce native fluctuations well for four RNA and two RNA-protein complexes. For tRNA, the native fluctuation in soln. includes large-amplitude motions that reach conformations nearly corresponding to the hybrid state P/E and EF-Tu-bound state A/T seen in the complexes with ribosome. Finally, large-amplitude modes of ribosome are briefly described.
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477Setny, P.; Zacharias, M. A coarse-grained force field for Protein-RNA docking Nucleic Acids Res. 2011, 39, 9118– 9129 DOI: 10.1093/nar/gkr636477https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsFCisLnJ&md5=2ccae666029f2c4bc9e1046d9ce18db7A coarse-grained force field for Protein-RNA dockingSetny, Piotr; Zacharias, MartinNucleic Acids Research (2011), 39 (21), 9118-9129CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)The awareness of important biol. role played by functional, non coding (nc) RNA has grown tremendously in recent years. To perform their tasks, ncRNA mols. typically unite with protein partners, forming ribonucleoprotein complexes. Structural insight into their architectures can be greatly supplemented by computational docking techniques, as they provide means for the integration and refinement of exptl. data that is often limited to fragments of larger assemblies or represents multiple levels of spatial resoln. Here, we present a coarse-grained force field for protein-RNA docking, implemented within the framework of the ATTRACT program. Complex structure prediction is based on energy minimization in rotational and translational degrees of freedom of binding partners, with possible extension to include structural flexibility. The coarse-grained representation allows for fast and efficient systematic docking search without any prior knowledge about complex geometry.
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478Negami, T.; Shimizu, K.; Terada, T. Coarse-Grained Molecular Dynamics Simulations of Protein-Ligand Binding J. Comput. Chem. 2014, 35, 1835– 1845 DOI: 10.1002/jcc.23693478https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFyqt7jE&md5=8b2fdf3912387ac20c2c32f8092a553aCoarse-grained molecular dynamics simulations of protein-ligand bindingNegami, Tatsuki; Shimizu, Kentaro; Terada, TohruJournal of Computational Chemistry (2014), 35 (25), 1835-1845CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)Coarse-grained mol. dynamics (CGMD) simulations with the MARTINI force field were performed to reproduce the protein-ligand binding processes. The authors chose two protein-ligand systems, the levansucrase-sugar (glucose or sucrose), and LinB-1,2-dichloroethane systems, as target systems that differ in terms of the size and shape of the ligand-binding pocket and the physicochem. properties of the pocket and the ligand. Spatial distributions of the Coarse-grained (CG) ligand mols. revealed potential ligand-binding sites on the protein surfaces other than the real ligand-binding sites. The ligands bound most strongly to the real ligand-binding sites. The binding and unbinding rate consts. obtained from the CGMD simulation of the levansucrase-sucrose system were ∼10 times greater than the exptl. values; this is mainly due to faster diffusion of the CG ligand in the CG water model. The authors could obtain dissocn. consts. close to the exptl. values for both systems. Anal. of the ligand fluxes demonstrated that the CG ligand mols. entered the ligand-binding pockets through specific pathways. The ligands tended to move through grooves on the protein surface. Thus, the CGMD simulations produced reasonable results for the two different systems overall and are useful for studying the protein-ligand binding processes.
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479Li, D.; Liu, M. S.; Ji, B.; Hwang, K.; Huang, Y. Coarse-grained molecular dynamics of ligands binding into protein: The case of HIV-1 protease inhibitors J. Chem. Phys. 2009, 130, 215102 DOI: 10.1063/1.3148022There is no corresponding record for this reference.
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480Prasanna, X.; Chattopadhyay, A.; Sengupta, D. Cholesterol modulates the dimer interface of the beta(2)-adrenergic receptor via cholesterol occupancy sites Biophys. J. 2014, 106, 1290– 1300 DOI: 10.1016/j.bpj.2014.02.002480https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXks1Wntro%253D&md5=7e1fcfd905abd3f6cb3ab9182a006129Cholesterol Modulates the Dimer Interface of the β2-Adrenergic Receptor via Cholesterol Occupancy SitesPrasanna, Xavier; Chattopadhyay, Amitabha; Sengupta, DurbaBiophysical Journal (2014), 106 (6), 1290-1300CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The β2-adrenergic receptor is an important member of the G-protein-coupled receptor (GPCR) superfamily, whose stability and function are modulated by membrane cholesterol. The recent high-resoln. crystal structure of the β2-adrenergic receptor revealed the presence of possible cholesterol-binding sites in the receptor. However, the functional relevance of cholesterol binding to the receptor remains unexplored. The authors used MARTINI coarse-grained mol.-dynamics simulations to explore dimerization of the β2-adrenergic receptor in lipid bilayers contg. cholesterol. A novel (to the authors' knowledge) aspect of the authors' results is that receptor dimerization is modulated by membrane cholesterol. The authors show that cholesterol binds to transmembrane helix IV, and cholesterol occupancy at this site restricts its involvement at the dimer interface. With increasing cholesterol concn., an increased presence of transmembrane helixes I and II, but a reduced presence of transmembrane helix IV, is obsd. at the dimer interface. To the authors' knowledge, this study is one of the first to explore the correlation between cholesterol occupancy and GPCR organization. The authors' results indicate that dimer plasticity is relevant not just as an organizational principle but also as a subtle regulatory principle for GPCR function. The authors believe these results constitute an important step toward designing better drugs for GPCR dimer targets.
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481Zacharias, M. Combining coarse-grained nonbonded and atomistic bonded interactions for protein modeling Proteins: Struct., Funct., Genet. 2013, 81, 81– 92 DOI: 10.1002/prot.24164There is no corresponding record for this reference.
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482Solernou, A.; Fernandez-Recio, J. pyDockCG: new coarse-grained potential for protein-protein docking J. Phys. Chem. B 2011, 115, 6032– 6039 DOI: 10.1021/jp112292bThere is no corresponding record for this reference.
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483de Vries, S. J.; Zacharias, M. ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM maps PLoS One 2012, 7, e49733 DOI: 10.1371/journal.pone.0049733483https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXksV2l&md5=1e5df4fa9d20ac1c6bcb7dde33fc2f54ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM mapsde Vries, Sjoerd J.; Zacharias, MartinPLoS One (2012), 7 (12), e49733CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)Many of the most important functions in the cell are carried out by proteins organized in large mol. machines. Cryo-electron microscopy (cryo-EM) is increasingly being used to obtain low resoln. d. maps of these large assemblies. A new method, ATTRACT-EM, for the computational assembly of mol. assemblies from their components has been developed. Based on concepts from the protein-protein docking field, it utilizes cryo-EM d. maps to assemble mol. subunits at near at. detail, starting from millions of initial subunit configurations. The search efficiency was further enhanced by recombining partial solns., the inclusion of symmetry information, and refinement using a mol. force field. The approach was tested on the GroES-GroEL system, using an exptl. cryo-EM map at 23.5 Å resoln., and on several smaller complexes. Inclusion of exptl. information on the symmetry of the systems and the application of a new gradient vector matching algorithm allowed the efficient identification of docked assemblies in close agreement with expt. Application to the GroES-GroEL complex resulted in a top ranked model with a deviation of 4.6 Å (and a 2.8 Å model within the top 10) from the GroES-GroEL crystal structure, a significant improvement over existing methods.
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484Periole, X.; Knepp, A. M.; Sakmar, T. P.; Marrink, S. J.; Huber, T. Structural determinants of the supramolecular organization of G protein-coupled receptors in bilayers J. Am. Chem. Soc. 2012, 134, 10959– 10965 DOI: 10.1021/ja303286e484https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xot1anurg%253D&md5=54e1d9387db3ea3debfad724d5db8a7aStructural Determinants of the Supramolecular Organization of G Protein-Coupled Receptors in BilayersPeriole, Xavier; Knepp, Adam M.; Sakmar, Thomas P.; Marrink, Siewert J.; Huber, ThomasJournal of the American Chemical Society (2012), 134 (26), 10959-10965CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The G protein-coupled receptor (GPCR) rhodopsin self-assembles into supramol. structures in native bilayers, but the structural determinants of receptor oligomerization are not known. We carried out multiple self-assembly coarse-grained mol. dynamics (CGMD) simulations of model membranes contg. up to 64 mols. of the visual receptor rhodopsin over time scales reaching 100 μs. The simulations show strong preferential interaction modes between receptors. Two primary modes of receptor-receptor interactions are consistent with umbrella sampling/potential of mean force (PMF) calcns. as a function of the distance between a pair of receptors. The preferential interfaces, involving helixes (H) 1/8, 4/5 and 5, present no energy barrier to forming a very stable receptor dimer. Most notably, the PMFs show that the preferred rhodopsin dimer exists in a tail-to-tail conformation, with the interface comprising transmembrane H1/H2 and amphipathic H8 at the extracellular and cytoplasmic surfaces, resp. This dimer orientation is in line with earlier electron microscopy, x-ray, and crosslinking expts. of rhodopsin and other GPCRs. Less stable interfaces, involving H4 and H6, have a free energy barrier for desolvation (delipidation) of the interfaces and appear to be designed to stabilize 'lubricated' (i.e., lipid-coated) dimers. The overall CGMD strategy used here is general and can be applied to study the homo- and heterodimerization of GPCRs and other transmembrane proteins. Systematic extension of the work will deepen our understanding of the forces involved in the membrane organization of integral membrane proteins.
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485Steczkiewicz, K.; Zimmermann, M. T.; Kurcinski, M.; Lewis, B. A.; Dobbs, D.; Kloczkowski, A.; Jernigan, R. L.; Kolinski, A.; Ginalski, K. Human telomerase model shows the role of the TEN domain in advancing the double helix for the next polymerization step Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 9443– 9448 DOI: 10.1073/pnas.1015399108There is no corresponding record for this reference.
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486Liu, S.; Vakser, I. A. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking BMC Bioinf. 2011, 12, 280 DOI: 10.1186/1471-2105-12-280486https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3MjitVajtQ%253D%253D&md5=3c0322a42123dad1b6c68d0c33d1d733DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein dockingLiu Shiyong; Vakser Ilya ABMC bioinformatics (2011), 12 (), 280 ISSN:.BACKGROUND: Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom) pairs in the non-interaction state. RESULTS: The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK) potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. CONCLUSIONS: A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of the potentials.
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487Ghoorah, A. W.; Devignes, M. D.; Smail-Tabbone, M.; Ritchie, D. W. Spatial clustering of protein binding sites for template based protein docking Bioinformatics 2011, 27, 2820– 2827 DOI: 10.1093/bioinformatics/btr493487https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXht12qsL3E&md5=d1d7c3abfd064fdb629ff482bb73758cSpatial clustering of protein binding sites for template based protein dockingGhoorah, Anisah W.; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Ritchie, David W.Bioinformatics (2011), 27 (20), 2820-2827CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)In recent years, much structural information on protein domains and their pair-wise interactions has been made available in public databases. However, it is not yet clear how best to use this information to discover general rules or interaction patterns about structural protein-protein interactions. Improving our ability to detect and exploit structural interaction patterns will help to provide a better 3D picture of the known protein interactome, and will help to guide docking-based predictions of the 3D structures of unsolved protein complexes. This article presents KBDOCK, a 3D database approach for spatially clustering protein binding sites and for performing template-based (knowledge-based) protein docking. KBDOCK combines residue contact information from the 3DID database with the Pfam protein domain family classification together with coordinate data from the Protein Data Bank. This allows the 3D configurations of all known hetero domain-domain interactions to be superposed and clustered for each Pfam family. We find that most Pfam domain families have up to four hetero binding sites, and over 60% of all domain families have just one hetero binding site. The utility of this approach for template-based docking is demonstrated using 73 complexes from the Protein Docking Benchmark. Overall, up to 45 out of 73 complexes may be modelled by direct homol. to existing domain interfaces, and key binding site information is found for 24 of the 28 remaining complexes. These results show that KBDOCK can often provide useful information for predicting the structures of unknown protein complexes.
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488Andreani, J.; Faure, G.; Guerois, R. InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution Bioinformatics 2013, 29, 1742– 1749 DOI: 10.1093/bioinformatics/btt260There is no corresponding record for this reference.
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489Solernou, A.; Fernandez-Recio, J. pyDockCG: new coarse-grained potential for protein-protein docking J. Phys. Chem. B 2011, 115, 6032– 6039 DOI: 10.1021/jp112292bThere is no corresponding record for this reference.
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490Frembgen-Kesner, T.; Elcock, A. H. Absolute protein-protein association rate constants from flexible, coarse-grained Brownian dynamics simulations: the role of intermolecular hydrodynamic interactions in barnase-barstar association Biophys. J. 2010, 99, L75– 77 DOI: 10.1016/j.bpj.2010.09.006490https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlKkur3I&md5=157dd5f426bcafbe782bca9210a6fec0Absolute Protein-Protein Association Rate Constants from Flexible, Coarse-Grained Brownian Dynamics Simulations: The Role of Intermolecular Hydrodynamic Interactions in Barnase-Barstar AssociationFrembgen-Kesner, Tamara; Elcock, Adrian H.Biophysical Journal (2010), 99 (9), L75-L77CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Theory and computation have long been used to rationalize the exptl. assocn. rate consts. of protein-protein complexes, and Brownian dynamics (BD) simulations in particular have been successful in reproducing the relative rate consts. of wild-type and mutant protein pairs. Missing from previous BD studies of assocn. kinetics, however, has been the description of hydrodynamic interactions (HIs) between and within the diffusing proteins. Here we address this issue by rigorously including HIs in BD simulations of the barnase-barstar assocn. reaction. We first show that even very simplified representations of the proteins - involving approx. one pseudoatom for every three residues in the protein - can provide excellent reprodn. of the abs. assocn. rate consts. of wild-type and mutant protein pairs. We then show that simulations that include intermol. HIs also produce excellent ests. of assocn. rate consts., but for a given reaction criterion, yield values that are decreased by ∼35-80% relative to those obtained in the absence of intermol. HIs. Therefore, the neglect of intermol. HIs in previous BD simulation studies is likely to have contributed to the somewhat overestimated abs. rate consts. previously obtained. Consequently, intermol. HIs could be an important component to include in accurate modeling of the kinetics of macromol. assocn. events.
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491Emperador, A.; Sfriso, P.; Villarreal, M. A.; Gelpi, J. L.; Orozco, M. PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein Systems J. Chem. Theory Comput. 2015, 11, 5929– 5938 DOI: 10.1021/acs.jctc.5b00660491https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhvVSls7rK&md5=888a24ebc16fb2203176c246a8764d23PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein SystemsEmperador, Agusti; Sfriso, Pedro; Villarreal, Marcos Ariel; Gelpi, Josep Lluis; Orozco, ModestoJournal of Chemical Theory and Computation (2015), 11 (12), 5929-5938CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Mol. dynamics simulations of proteins are usually performed on a single mol., and coarse-grained protein models are calibrated using single-mol. simulations, therefore ignoring intermol. interactions. The authors present here a new coarse-grained force field for the study of many protein systems. The force field, which is implemented in the context of the discrete mol. dynamics algorithm, is able to reproduce the properties of folded and unfolded proteins, in both isolation, complexed forming well-defined quaternary structures, or aggregated, thanks to its proper evaluation of protein-protein interactions. The accuracy and computational efficiency of the method makes it a universal tool for the study of the structure, dynamics, and assocn./dissocn. of proteins.
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492May, A.; Pool, R.; van Dijk, E.; Bijlard, J.; Abeln, S.; Heringa, J.; Feenstra, K. A. Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins Bioinformatics 2014, 30, 326– 334 DOI: 10.1093/bioinformatics/btt675492https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1Cjt70%253D&md5=61540a9ae1e44fa047e85d7fb0d9892fCoarse-grained versus atomistic simulations: realistic interaction free energies for real proteinsMay, Ali; Pool, Rene; van Dijk, Erik; Bijlard, Jochem; Abeln, Sanne; Heringa, Jaap; Feenstra, K. AntonBioinformatics (2014), 30 (3), 326-334CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)Motivation: To assess whether two proteins will interact under physiol. conditions, information on the interaction free energy is needed. Statistical learning techniques and docking methods for predicting protein-protein interactions cannot quant. est. binding free energies. Full atomistic mol. simulation methods do have this potential, but are completely unfeasible for large-scale applications in terms of computational cost required. Here we investigate whether applying coarse-grained (CG) mol. dynamics simulations is a viable alternative for complexes of known structure. Results: We calc. the free energy barrier with respect to the bound state based on mol. dynamics simulations using both a full atomistic and a CG force field for the TCR-pMHC complex and the MP1-p14 scaffolding complex. We find that the free energy barriers from the CG simulations are of similar accuracy as those from the full atomistic ones, while achieving a speedup of >500-fold. We also observe that extensive sampling is extremely important to obtain accurate free energy barriers, which is only within reach for the CG models. Finally, we show that the CG model preserves biol. relevance of the interactions: (i) we observe a strong correlation between evolutionary likelihood of mutations and the impact on the free energy barrier with respect to the bound state; and (ii) we confirm the dominant role of the interface core in these interactions. Therefore, our results suggest that CG mol. simulations can realistically be used for the accurate prediction of protein-protein interaction strength.
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493Bastard, K.; Prevost, C.; Zacharias, M. Accounting for loop flexibility during protein-protein docking Proteins: Struct., Funct., Genet. 2006, 62, 956– 969 DOI: 10.1002/prot.20770There is no corresponding record for this reference.
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494Schneider, S.; Saladin, A.; Fiorucci, S.; Prevost, C.; Zacharias, M. ATTRACT and PTools: open source programs for protein-protein docking Methods Mol. Biol. 2012, 819, 221– 232 DOI: 10.1007/978-1-61779-465-0_15494https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFSjur7E&md5=94914ba8090379fd3b3f82587e70175cATTRACT and PTOOLS: open source programs for protein-protein dockingSchneider, Sebastian; Saladin, Adrien; Fiorucci, Sebastien; Prevost, Chantal; Zacharias, MartinMethods in Molecular Biology (New York, NY, United States) (2012), 819 (Computational Drug Discovery and Design), 221-232CODEN: MMBIED; ISSN:1064-3745. (Springer)The prediction of the structure of protein-protein complexes based on structures or structural models of isolated partners is of increasing importance for structural biol. and bioinformatics. The ATTRACT program can be used to perform systematic docking searches based on docking energy minimization. It is part of the object-oriented PTools library written in Python and C++. The library contains various routines to manipulate protein structures, to prep. and perform docking searches as well as analyzing docking results. It also intended to facilitate further methodol. developments in the area of macromol. docking that can be easily integrated. Here, we describe the application of PTools to perform systematic docking searches and to analyze the results. In addn., the possibility to perform multicomponent docking will also be presented.
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495Sacquin-Mora, S.; Laforet, E.; Lavery, R. Locating the active sites of enzymes using mechanical properties Proteins: Struct., Funct., Genet. 2007, 67, 350– 359 DOI: 10.1002/prot.21353There is no corresponding record for this reference.
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496Poulain, P.; Saladin, A.; Hartmann, B.; Prevost, C. Insights on protein-DNA recognition by coarse grain modelling J. Comput. Chem. 2008, 29, 2582– 2592 DOI: 10.1002/jcc.21014There is no corresponding record for this reference.
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497Saladin, A.; Amourda, C.; Poulain, P.; Ferey, N.; Baaden, M.; Zacharias, M.; Delalande, O.; Prevost, C. Modeling the early stage of DNA sequence recognition within RecA nucleoprotein filaments Nucleic Acids Res. 2010, 38, 6313– 6323 DOI: 10.1093/nar/gkq459There is no corresponding record for this reference.
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498Molza, A. E.; Ferey, N.; Czjzek, M.; Le Rumeur, E.; Hubert, J. F.; Tek, A.; Laurent, B.; Baaden, M.; Delalande, O. Innovative interactive flexible docking method for multi-scale reconstruction elucidates dystrophin molecular assembly Faraday Discuss. 2014, 169, 45– 62 DOI: 10.1039/C3FD00134BThere is no corresponding record for this reference.
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499Lensink, M. F.; Wodak, S. J. Docking, scoring, and affinity prediction in CAPRI Proteins: Struct., Funct., Genet. 2013, 81, 2082– 2095 DOI: 10.1002/prot.24428499https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1agurvL&md5=fd76a3201716b47f338ee29507d92ab5Docking, scoring, and affinity prediction in CAPRILensink, Marc F.; Wodak, Shoshana J.Proteins: Structure, Function, and Bioinformatics (2013), 81 (12), 2082-2095CODEN: PSFBAF ISSN:. (Wiley-Blackwell)We present the fifth evaluation of docking and related scoring methods used in the community-wide expt. on the Crit. Assessment of Predicted Interactions (CAPRI). The evaluation examd. predictions submitted for a total of 15 targets in eight CAPRI rounds held during the years 2010-2012. The targets represented one the most diverse set tackled by the CAPRI community so far. They included only 10 "classical" docking and scoring problems. In one of the classical targets, the new challenge was to predict the position of water mols. in the protein-protein interface. The remaining five targets represented other new challenges that involved estg. the relative binding affinity and the effect of point mutations on the stability of designed and natural protein-protein complexes. Although the 10 classical CAPRI targets included two difficult multicomponent systems, and a protein-oligosaccharide complex with which CAPRI participants had little experience, this evaluation indicates that the performance of docking and scoring methods has remained quite robust. More remarkably, we find that automatic docking servers exhibit a significantly improved performance, with some servers now performing on par with predictions done by humans. The performance of CAPRI participants in the new challenges, briefly reviewed here, was mediocre overall, but some groups did relatively well and their approaches suggested ways of improving methods for designing binders and for estg. the free energies of protein assemblies, which should impact the field of protein modeling and design as a whole.
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500Kozakov, D.; Beglov, D.; Bohnuud, T.; Mottarella, S. E.; Xia, B.; Hall, D. R.; Vajda, S. How good is automated protein docking? Proteins: Struct., Funct., Genet. 2013, 81, 2159– 2166 DOI: 10.1002/prot.24403500https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhs1agtrzJ&md5=b82ba81c585b0b514c4a94eb361cd962How good is automated protein docking?Kozakov, Dima; Beglov, Dmitri; Bohnuud, Tanggis; Mottarella, Scott E.; Xia, Bing; Hall, David R.; Vajda, SandorProteins: Structure, Function, and Bioinformatics (2013), 81 (12), 2159-2166CODEN: PSFBAF ISSN:. (Wiley-Blackwell)The protein docking server ClusPro has been participating in crit. assessment of prediction of interactions (CAPRI) since its introduction in 2004. This article evaluates the performance of ClusPro 2.0 for targets 46-58 in Rounds 22-27 of CAPRI. The anal. leads to a no. of important observations. First, ClusPro reliably yields acceptable or medium accuracy models for targets of moderate difficulty that have also been successfully predicted by other groups, and fails only for targets that have few acceptable models submitted. Second, the quality of automated docking by ClusPro is very close to that of the best human predictor groups, including our own submissions. This is very important, because servers have to submit results within 48 h and the predictions should be reproducible, whereas human predictors have several weeks and can use any type of information. Third, while we refined the ClusPro results for manual submission by running computationally costly Monte Carlo minimization simulations, we obsd. significant improvement in accuracy only for two of the six complexes correctly predicted by ClusPro. Fourth, new developments, not seen in previous rounds of CAPRI, are that the top ranked model provided by ClusPro was acceptable or better quality for all these six targets, and that the top ranked model was also the highest quality for five of the six, confirming that ranking models based on cluster size can reliably identify the best near-native conformations.
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501Vajda, S.; Kozakov, D. Convergence and combination of methods in protein-protein docking Curr. Opin. Struct. Biol. 2009, 19, 164– 170 DOI: 10.1016/j.sbi.2009.02.008501https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXkvVSqt7Y%253D&md5=412d42d11d31d7e656d0834405b4d2e6Convergence and combination of methods in protein-protein dockingVajda, Sandor; Kozakov, DimaCurrent Opinion in Structural Biology (2009), 19 (2), 164-170CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. The anal. of results from Crit. Assessment of Predicted Interactions (CAPRI), the first community-wide expt. devoted to protein docking, shows that all successful methods consist of multiple stages. The methods belong to 3 classes: global methods based on fast Fourier transforms (FFTs) or geometric matching, medium-range Monte Carlo methods, and the restraint-guided High Ambiguity Driven biomol. DOCKing (HADDOCK) program. Although these classes of methods require very different amts. of information in addn. to the structures of component proteins, they all share the same 4 computational steps: (1) simplified and/or rigid body search; (2) selecting the region(s) of interest; (3) refinement of docked structures; and (4) selecting the best models. Although each method is optimal for a specific class of docking problems, combining computational steps from different methods can improve the reliability and accuracy of results.
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502Huang, S. Y. Search strategies and evaluation in protein-protein docking: principles, advances and challenges Drug Discovery Today 2014, 19, 1081– 1096 DOI: 10.1016/j.drudis.2014.02.005502https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotFyhsb8%253D&md5=28d301e8e996ca34314ede2661938798Search strategies and evaluation in protein-protein docking: principles, advances and challengesHuang, Sheng-YouDrug Discovery Today (2014), 19 (8), 1081-1096CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)A review. Protein-protein docking is attracting increasing attention in drug discovery research targeting protein-protein interactions, owing to its potential in predicting protein-protein interactions and identifying 'hot spot' residues at the protein-protein interface. Given the relative lack of information about binding sites and the fact that proteins are generally larger than ligand, the search algorithms and evaluation methods for protein-protein docking differ somewhat from those for protein-ligand docking and, hence, require different research strategies. Here, we review the basic concepts, principles and advances of current search strategies and evaluation methods for protein-protein docking. We also discuss the current challenges and limitations, as well as future directions, of established approaches.
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503Huang, S. Y. Exploring the potential of global protein-protein docking: an overview and critical assessment of current programs for automatic ab initio docking Drug Discovery Today 2015, 20, 969– 977 DOI: 10.1016/j.drudis.2015.03.007503https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXltFCht70%253D&md5=b7924b6b5f797685bab4f077ec294acbExploring the potential of global protein-protein docking: an overview and critical assessment of current programs for automatic ab initio dockingHuang, Sheng-YouDrug Discovery Today (2015), 20 (8), 969-977CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)Protein-protein docking is an important computational tool for studying protein-protein interactions. A variety of docking programs with different sampling algorithms and scoring functions as well as computational efficiencies have been subsequently developed over the last decades. Here, we have reviewed the trend and performance of current global docking programs through a comprehensive assessment of the 18 docking/scoring protocols of 14 global docking programs on the latest protein docking benchmark 4.0. The effects of docking algorithms, interaction types, and conformational changes on the docking performance were investigated and discussed. The findings are expected to provide a general guideline for the choice of an appropriate docking protocol and offer insights into the optimization and development of docking and scoring algorithms.
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504Tuffery, P.; Derreumaux, P. Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approaches J. R. Soc., Interface 2012, 9, 20– 33 DOI: 10.1098/rsif.2011.0584504https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktFCns7w%253D&md5=559359a4fd0c00b6b6f2c825dc455540Flexibility and binding affinity in protein-ligand, protein-protein and multi-component protein interactions: limitations of current computational approachesTuffery, Pierre; Derreumaux, PhilippeJournal of the Royal Society, Interface (2012), 9 (66), 20-33CODEN: JRSICU; ISSN:1742-5689. (Royal Society)A review. The recognition process between a protein and a partner represents a significant theor. challenge. In silico structure-based drug design carried out with nothing more than the three-dimensional structure of the protein has led to the introduction of many compds. into clin. trials and numerous drug approvals. Central to guiding the discovery process is to recognize active among non-active compds. While large-scale computer simulations of compds. taken from a library (virtual screening) or designed de novo are highly desirable in the post-genomic area, many tech. problems remain to be adequately addressed. This article presents an overview and discusses the limits of current computational methods for predicting the correct binding pose and accurate binding affinity. It also presents the performances of the most popular algorithms for exploring binary and multi-body protein interactions.
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505Li, H.; Lu, L.; Chen, R.; Quan, L.; Xia, X.; Lu, Q. PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta PLoS One 2014, 9, e94769 DOI: 10.1371/journal.pone.0094769There is no corresponding record for this reference.
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506Wabik, J.; Kurcinski, M.; Kolinski, A. Coarse-Grained Modeling of Peptide Docking Associated with Large Conformation Transitions of the Binding Protein: Troponin I Fragment-Troponin C System Molecules 2015, 20, 10763– 10780 DOI: 10.3390/molecules200610763There is no corresponding record for this reference.
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507Ravikumar, K. M.; Huang, W.; Yang, S. Coarse-grained simulations of protein-protein association: an energy landscape perspective Biophys. J. 2012, 103, 837– 845 DOI: 10.1016/j.bpj.2012.07.013507https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1eku7nM&md5=8e27e21327fd69539751cf9911318937Coarse-Grained Simulations of Protein-Protein Association: An Energy Landscape PerspectiveRavikumar, Krishnakumar M.; Huang, Wei; Yang, SichunBiophysical Journal (2012), 103 (4), 837-845CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Understanding protein-protein assocn. is crucial in revealing the mol. basis of many biol. processes. Here, we describe a theor. simulation pipeline to study protein-protein assocn. from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via mol. dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examn. on mol. forces shows that the formation of assocd. protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein assocn. occurring in functional biomol. complexes.
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508Irback, A.; Jonsson, S. A. E.; Linnemann, N.; Linse, B.; Wallin, S. Aggregate geometry in amyloid fibril nucleation Phys. Rev. Lett. 2013, 110, 058101 DOI: 10.1103/PhysRevLett.110.058101There is no corresponding record for this reference.
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509Bieler, N. S.; Knowles, T. P.; Frenkel, D.; Vacha, R. Connecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulations PLoS Comput. Biol. 2012, 8, e1002692 DOI: 10.1371/journal.pcbi.1002692509https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFOrsLnM&md5=f1f53532587dfa379c6ec4ffecd895bbConnecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulationsBieler, Noah S.; Knowles, Tuomas P. J.; Frenkel, Daan; Vacha, RobertPLoS Computational Biology (2012), 8 (10), e1002692CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)The pre-fibrillar stages of amyloid formation have been implicated in cellular toxicity, but have proved to be challenging to study directly in expts. and simulations. Rational strategies to suppress the formation of toxic amyloid oligomers require a better understanding of the mechanisms by which they are generated. We report Dynamical Monte Carlo simulations that allow us to study the early stages of amyloid formation. We use a generic, coarse-grained model of an amyloidogenic peptide that has two internal states: the first one representing the sol. random coil structure and the second one the β-sheet conformation. We find that this system exhibits a propensity towards fibrillar self-assembly following the formation of a crit. nucleus. Our calcns. establish connections between the early nucleation events and the kinetic information available in the later stages of the aggregation process that are commonly probed in expts. We analyze the kinetic behavior in our simulations within the framework of the theory of classical nucleated polymn. and are able to connect the structural events at the early stages in amyloid growth with the resulting macroscopic observables such as the effective nucleus size. Furthermore, the free-energy landscapes that emerge from these simulations allow us to identify pertinent properties of the monomeric state that could be targeted to suppress oligomer formation.
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510Li, M. S.; Klimov, D. K.; Straub, J. E.; Thirumalai, D. Probing the mechanisms of fibril formation using lattice models J. Chem. Phys. 2008, 129, 175101 DOI: 10.1063/1.2989981510https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlCksL%252FO&md5=6bc2eeaa868b4ddf622c34bffdf2cd8bProbing the mechanisms of fibril formation using lattice modelsLi, Mai Suan; Klimov, D. K.; Straub, J. E.; Thirumalai, D.Journal of Chemical Physics (2008), 129 (17), 175101/1-175101/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Using exhaustive Monte Carlo simulations we study the kinetics and mechanism of fibril formation using lattice models as a function of temp. (T) and the no. of chains (M). While these models are at best caricatures of peptides, we show that a no. of generic features thought to govern fibril assembly are captured by the toy model. The monomer, which contains eight beads made from three letters (hydrophobic, polar, and charged), adopts a compact conformation in the native state. In both the single-layered protofilament (seen for M≤10) and the two-layer fibril (M°10) structures, the monomers are arranged in an antiparallel fashion with the "strandlike" conformation that is perpendicular to the fibril axis. Partial unfolding of the folded monomer that populates an aggregation-prone conformation (N*) is required for ordered assembly. The contacts in the N* conformation, which is one of the four structures in the first "excited" state of the monomer, are also present in the native conformation. The time scale for fibril formation is a min. in the T-range when the conformation N* is substantially populated. The kinetics of fibril assembly occurs in three distinct stages. In each stage there is a cascade of events that transforms the monomers and oligomers to ordered structures. In the first "burst" stage, highly mobile oligomers of varying sizes form. The conversion to the N* conformation occurs within the oligomers during the second stage in which a vast no. of interchain contacts are established. As time progresses, a dominant cluster emerges that contains a majority of the chains. In the final stage, the aggregation of N* particles serve as a template onto which smaller oligomers or monomers can dock and undergo conversion to fibril structures. The overall time for growth in the latter stages is well described by the Lifshitz-Slyazov growth kinetics for crystn. from supersatd. solns. The detailed anal. shows that elements of the three popular models, namely, nucleation-growth (NG), templated assembly (TA), and nucleated conformational conversion (NCC) are present at various stages of fibril assembly. (c) 2008 American Institute of Physics.
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511Friedman, R.; Caflisch, A. Surfactant effects on amyloid aggregation kinetics J. Mol. Biol. 2011, 414, 303– 312 DOI: 10.1016/j.jmb.2011.10.011There is no corresponding record for this reference.
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512Bellesia, G.; Shea, J. E. Self-assembly of beta-sheet forming peptides into chiral fibrillar aggregates J. Chem. Phys. 2007, 126, 245104 DOI: 10.1063/1.2739547512https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXnsVOmsr4%253D&md5=368f791d0be49393a342fcbcbfc887b8Self-assembly of β-sheet forming peptides into chiral fibrillar aggregatesBellesia, Giovanni; Shea, Joan-EmmaJournal of Chemical Physics (2007), 126 (24), 245104/1-245104/11CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)The authors introduce a novel mid-resoln. off-lattice coarse-grained model to investigate the self-assembly of β-sheet-forming peptides. The model retains most of the peptide backbone degrees of freedom as well as one interaction center describing the side chains. The peptide consists of a core of alternating hydrophobic and hydrophilic residues, capped by two oppositely charged residues. Nonbonded interactions are described by Lennard-Jones and Coulombic terms. The influence of different levels of "hydrophobic" and "steric" forces between the side chains of the peptides on the thermodn. and kinetics of aggregation was investigated using Langevin dynamics. The model is simple enough to allow the simulation of systems consisting of hundreds of peptides, while remaining realistic enough to successfully lead to the formation of chiral, ordered β tapes, ribbons, and higher order fibrillar aggregates.
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513Carmichael, S. P.; Shell, M. S. A new multiscale algorithm and its application to coarse-grained peptide models for self-assembly J. Phys. Chem. B 2012, 116, 8383– 8393 DOI: 10.1021/jp2114994513https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1Oms7k%253D&md5=8a51350f45b075ad2d14609713917654A New Multiscale Algorithm and Its Application to Coarse-Grained Peptide Models for Self-AssemblyCarmichael, Scott P.; Shell, M. ScottJournal of Physical Chemistry B (2012), 116 (29), 8383-8393CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Peptide self-assembly plays a role in a no. of diseases, in pharmaceutical degrdn., and in emerging biomaterials. Here, we aim to develop an accurate mol.-scale picture of this process using a multiscale computational approach. We have reformulated this methodol. using a trajectory-reweighting and perturbation strategy that enables complex coarse-grained models with at least hundreds of parameters to be optimized efficiently. This new algorithm allows for complex peptide systems to be coarse-grained into much simpler models that nonetheless recapitulate many correct features of detailed all-atom ones. In particular, we present results for a polyalanine case study, with attention to both individual peptide folding and large-scale fibril assembly.
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514Cheon, M.; Chang, I.; Hall, C. K. Extending the PRIME model for protein aggregation to all 20 amino acids Proteins: Struct., Funct., Genet. 2010, 78, 2950– 2960 DOI: 10.1002/prot.22817514https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtFCrtrnL&md5=797a5b4c26ba155c516c0e689f306df8Extending the PRIME model for protein aggregation to all 20 amino acidsCheon, Mookyung; Chang, Iksoo; Hall, Carol K.Proteins: Structure, Function, and Bioinformatics (2010), 78 (14), 2950-2960CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)We extend PRIME, an intermediate-resoln. protein model previously used in simulations of the aggregation of polyalanine and polyglutamine, to the description of the geometry and energetics of peptides contg. all 20 amino acid residues. The 20 amino acid side chains are classified into 14 groups according to their hydrophobicity, polarity, size, charge, and potential for side chain hydrogen bonding. The parameters for extended PRIME, called PRIME 20, include hydrogen-bonding energies, side chain interaction range and energy, and excluded vol. The parameters are obtained by applying a perceptron-learning algorithm and a modified stochastic learning algorithm that optimizes the energy gap between 711 known native states from the PDB and decoy structures generated by gapless threading. The no. of independent pair interaction parameters is chosen to be small enough to be phys. meaningful yet large enough to give reasonably accurate results in discriminating decoys from native structures. The most phys. meaningful results are obtained with 19 energy parameters. Proteins 2010. © 2010 Wiley-Liss, Inc.
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515Uversky, V. N. Introduction to intrinsically disordered proteins (IDPs) Chem. Rev. 2014, 114, 6557– 6560 DOI: 10.1021/cr500288y515https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtV2js7zP&md5=9aa8ac1269cf374cd6447ae02dd63804Introduction to Intrinsically Disordered Proteins (IDPs)Uversky, Vladimir N.Chemical Reviews (Washington, DC, United States) (2014), 114 (13), 6557-6560CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review on proteins with intrinsically disordered structure, interest to which grows rapidly in recent years, their interaction with various biomols. and thermodn. aspects of the interactions.
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516Habchi, J.; Tompa, P.; Longhi, S.; Uversky, V. N. Introducing protein intrinsic disorder Chem. Rev. 2014, 114, 6561– 6588 DOI: 10.1021/cr400514h516https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtlygt7Y%253D&md5=56ee20777b53dabddad9fc22ddb2aed5Introducing protein intrinsic disorderHabchi, Johnny; Tompa, Peter; Longhi, Sonia; Uversky, Vladimir N.Chemical Reviews (Washington, DC, United States) (2014), 114 (13), 6561-6588CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)A review. This paper is intended as a general introduction to a series of thematic reviews on intrinsically disordered proteins (IDPs). Although IDPs possess no well-defined 3-dimensional structure but rather adapt an ensemble of conformations in soln., they are still functional. A literature review is provided by summarizing the main aspects of IDPs that have led to an exponential increase of interest in these proteins. Moreover, through the different parts of this review, biochem. and biophys. approaches that are frequently used to assess intrinsic disorder are detailed.
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517Mittag, T.; Kay, L. E.; Forman-Kay, J. D. Protein dynamics and conformational disorder in molecular recognition J. Mol. Recognit. 2009, 23, 105– 116 DOI: 10.1002/jmr.961There is no corresponding record for this reference.
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518Uversky, V. N.; Gillespie, J. R.; Fink, A. L. Why are “natively unfolded” proteins unstructured under physiologic conditions? Proteins: Struct., Funct., Genet. 2000, 41, 415– 427 DOI: 10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.3.CO;2-ZThere is no corresponding record for this reference.
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519Wright, P. E.; Dyson, H. J. Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm J. Mol. Biol. 1999, 293, 321– 331 DOI: 10.1006/jmbi.1999.3110519https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXms12rtbw%253D&md5=bf38ba52223ec01ee473b2891a713893Intrinsically Unstructured Proteins: Re-assessing the Protein Structure-Function ParadigmWright, Peter E.; Dyson, H. JaneJournal of Molecular Biology (1999), 293 (2), 321-331CODEN: JMOBAK; ISSN:0022-2836. (Academic Press)A review with 93 refs. A major challenge in the post-genome era will be detn. of the functions of the encoded protein sequences. Since it is generally assumed that the function of a protein is closely linked to its three-dimensional structure, prediction or exptl. detn. of the library of protein structures is a matter of high priority. However, a large proportion of gene sequences appear to code not for folded, globular proteins, but for long stretches of amino acids that are likely to be either unfolded in soln. or adopt non-globular structures of unknown conformation. Characterization of the conformational propensities and function of the non-globular protein sequences represents a major challenge. The high proportion of these sequences in the genomes of all organisms studied to date argues for important, as yet unknown functions, since there could be no other reason for their persistence throughout evolution. Clearly the assumption that a folded three-dimensional structure is necessary for function needs to be re-examd. Although the functions of many proteins are directly related to their three-dimensional structures, numerous proteins that lack intrinsic globular structure under physiol. conditions have now been recognized. Such proteins are frequently involved in some of the most important regulatory functions in the cell, and the lack of intrinsic structure in many cases is relieved when the protein binds to its target mol. The intrinsic lack of structure can confer functional advantages on a protein, including the ability to bind to several different targets. It also allows precise control over the thermodn. of the binding process and provides a simple mechanism for inducibility by phosphorylation or through interaction with other components of the cellular machinery. Numerous examples of domains that are unstructured in soln. but which become structured upon binding to the target have been noted in the areas of cell cycle control and both transcriptional and translational regulation, and unstructured domains are present in proteins that are targeted for rapid destruction. Since such proteins participate in crit. cellular control mechanisms, it appears likely that their rapid turnover, aided by their unstructured nature in the unbound state, provides a level of control that allows rapid and accurate responses of the cell to changing environmental conditions. (c) 1999 Academic Press.
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520Zhang, Y.; Stec, B.; Godzik, A. Between order and disorder in protein structures: analysis of ″dual personality″ fragments in proteins Structure 2007, 15, 1141– 1147 DOI: 10.1016/j.str.2007.07.012There is no corresponding record for this reference.
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521Eliezer, D. Biophysical characterization of intrinsically disordered proteins Curr. Opin. Struct. Biol. 2009, 19, 23– 30 DOI: 10.1016/j.sbi.2008.12.004521https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXit1OmsLs%253D&md5=4f813b15e8bae72fbde66ec7120a32b1Biophysical characterization of intrinsically disordered proteinsEliezer, DavidCurrent Opinion in Structural Biology (2009), 19 (1), 23-30CODEN: COSBEF; ISSN:0959-440X. (Elsevier B.V.)A review. The challenges assocd. with the structural characterization of disordered proteins have resulted in the application of a host of biophys. methods to such systems. NMR spectroscopy is perhaps the most readily suited technique for providing high-resoln. structural information on disordered protein states in soln. Optical methods, solid state NMR, ESR and X-ray scattering can also provide valuable information regarding the ensemble of conformations sampled by disordered states. Finally, computational studies have begun to assume an increasingly important role in interpreting and extending the impact of exptl. data obtained for such systems. This article discusses recent advances in the applications of these methods to intrinsically disordered proteins.
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522Rauscher, S.; Pomès, R. Molecular simulations of protein disorderThis paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular & Cellular Biology 52nd Annual Meeting — Protein Folding: Principles and Diseases” and has undergone the Journal’s usual peer review process Biochem. Cell Biol. 2010, 88, 269– 290 DOI: 10.1139/O09-169522https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXjs1egsbw%253D&md5=9be380bd6b6d5acde1ae415dc1331694Molecular simulations of protein disorderRauscher, Sarah; Pomes, RegisBiochemistry and Cell Biology (2010), 88 (2), 269-290CODEN: BCBIEQ; ISSN:0829-8211. (National Research Council of Canada)A review. Protein disorder is abundant in proteomes throughout all kingdoms of life and serves many biol. important roles. Disordered states of proteins are challenging to study exptl. due to their structural heterogeneity and tendency to aggregate. Computer simulations, which are not impeded by these properties, have recently emerged as a useful tool to characterize the conformational ensembles of intrinsically disordered proteins. In this review, we provide a survey of computational studies of protein disorder with an emphasis on the interdisciplinary nature of these studies. The application of simulation techniques to the study of disordered states is described in the context of exptl. and bioinformatics approaches. Exptl. data can be incorporated into simulations, and simulations can provide predictions for expt. In this way, simulations have been integrated into the existing methodologies for the study of disordered state ensembles. We provide recent examples of simulations of disordered states from the literature and our own work. Throughout the review, we emphasize important predictions and biophys. understanding made possible through the use of simulations. This review is intended as both an overview and a guide for structural biologists and theor. biophysicists seeking accurate, at.-level descriptions of disordered state ensembles.
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523Baker, C. M.; Best, R. B. Insights into the binding of intrinsically disordered proteins from molecular dynamics simulation Wires Comput. Mol. Sci. 2014, 4, 182– 198 DOI: 10.1002/wcms.1167523https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmtl2ju7w%253D&md5=0c269fbf7ac5d527d416a842dccbc0a3Insights into the binding of intrinsically disordered proteins from molecular dynamics simulationBaker, Christopher M.; Best, Robert B.Wiley Interdisciplinary Reviews: Computational Molecular Science (2014), 4 (3), 182-198CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)A review. Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no well-defined secondary or tertiary structure, existing instead as dynamic ensembles of conformations. They are biol. important, with approx. 20% of all eukaryotic proteins disordered, and found at the heart of many biochem. networks. To fulfil their biol. roles, many IDPs need to bind to proteins and/or nucleic acids. And although unstructured in soln., IDPs typically fold into a well-defined three-dimensional structure upon interaction with a binding partner. The flexibility and structural diversity inherent to IDPs makes this coupled folding and binding difficult to study at at. resoln. by expt. alone, and computer simulation currently offers perhaps the best opportunity to understand this process. But simulation of coupled folding and binding is itself extremely challenging; these mols. are large and highly flexible, and their binding partners, such as DNA or cyclins, are also often large. Therefore, their study requires either simplified representations, advanced enhanced sampling schemes, or both. It is not always clear that existing simulation techniques, optimized for studying folded proteins, are well suited to IDPs. In this article, we examine the progress that has been made in the study of coupled folding and binding using mol. dynamics simulation. We summarize what has been learnt, and examine the state of the art in terms of both methodologies and models. We also consider the lessons to be learnt from advances in other areas of simulation and highlight the issues that remain of be addressed.
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524David de, S.; Christopher, M. B.; Robert, B. B. In Computational Approaches to Protein Dynamics; CRC Press: Boca Raton, FL, 2014.There is no corresponding record for this reference.
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525Rauscher, S.; Gapsys, V.; Gajda, M. J.; Zweckstetter, M.; de Groot, B. L.; Grubmuller, H. Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment J. Chem. Theory Comput. 2015, 11, 5513– 5524 DOI: 10.1021/acs.jctc.5b00736525https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhs1ChsbvM&md5=0c38ce869b7b2bb569f59f9a77c19bedStructural ensembles of intrinsically disordered proteins depend strongly on force field: A comparison to experimentRauscher, Sarah; Gapsys, Vytautas; Gajda, Michal J.; Zweckstetter, Markus; de Groot, Bert L.; Grubmueller, HelmutJournal of Chemical Theory and Computation (2015), 11 (11), 5513-5524CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Intrinsically disordered proteins (IDPs) are notoriously challenging to study both exptl. and computationally. The structure of IDPs cannot be described by a single conformation but must instead be described as an ensemble of interconverting conformations. Atomistic simulations are increasingly used to obtain such IDP conformational ensembles. Here, the authors compared the IDP ensembles generated by 8 all-atom empirical force fields against primary SAXS and NMR data. Ensembles obtained with different force fields exhibited marked differences in chain dimensions, H-bonding, and secondary structure content. These differences were unexpectedly large: changing the force field was found to have a stronger effect on secondary structure content than changing the entire peptide sequence. The CHARMM 22* ensemble performed best in this force field comparison: it had the lowest error in chem. shifts and J-couplings and agreed well with the SAXS data. A high population of left-handed α-helix was present in the CHARMM 36 ensemble, which was inconsistent with measured scalar couplings. To eliminate inadequate sampling as a reason for differences between force fields, extensive simulations were carried out (0.964 ms in total); the remaining small sampling uncertainty was shown to be much smaller than the obsd. differences. The findings highlighted how IDPs, with their rugged energy landscapes, are highly sensitive test systems that are capable of revealing force field deficiencies and, therefore, contributing to force field development.
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526Sugase, K.; Dyson, H. J.; Wright, P. E. Mechanism of coupled folding and binding of an intrinsically disordered protein Nature 2007, 447, 1021– 1025 DOI: 10.1038/nature05858526https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXms1yqu7Y%253D&md5=e9be89311be0350df15c5dcfe6f86db7Mechanism of coupled folding and binding of an intrinsically disordered proteinSugase, Kenji; Dyson, H. Jane; Wright, Peter E.Nature (London, United Kingdom) (2007), 447 (7147), 1021-1025CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Protein folding and binding are analogous processes, in which the protein 'searches' for favorable intramol. or intermol. interactions on a funnelled energy landscape. Many eukaryotic proteins are disordered under physiol. conditions, and fold into ordered structures only on binding to their cellular targets. The mechanism by which folding is coupled to binding is poorly understood, but it has been hypothesized on theor. grounds that the binding kinetics may be enhanced by a 'fly-casting' effect, where the disordered protein binds weakly and non-specifically to its target and folds as it approaches the cognate binding site. Here we show, using NMR titrns. and 15N relaxation dispersion, that the phosphorylated kinase inducible activation domain (pKID) of the transcription factor CREB forms an ensemble of transient encounter complexes on binding to the KIX domain of the CREB binding protein. The encounter complexes are stabilized primarily by non-specific hydrophobic contacts, and evolve by way of an intermediate to the fully bound state without dissocn. from KIX. The carboxy-terminal helix of pKID is only partially folded in the intermediate, and becomes stabilized by intermol. interactions formed in the final bound state. Future applications of our method will provide new understanding of the mol. mechanisms by which intrinsically disordered proteins perform their diverse biol. functions.
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527Chen, H. F. Molecular dynamics simulation of phosphorylated KID post-translational modification. PLoS One 2009, 4, e6516 DOI: 10.1371/journal.pone.0006516527https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1MrjsFCktg%253D%253D&md5=aa0841aa09440c955cad15f190744a8aMolecular dynamics simulation of phosphorylated KID post-translational modificationChen Hai-FengPloS one (2009), 4 (8), e6516 ISSN:.BACKGROUND: Kinase-inducible domain (KID) as transcriptional activator can stimulate target gene expression in signal transduction by associating with KID interacting domain (KIX). NMR spectra suggest that apo-KID is an unstructured protein. After post-translational modification by phosphorylation, KID undergoes a transition from disordered to well folded protein upon binding to KIX. However, the mechanism of folding coupled to binding is poorly understood. METHODOLOGY: To get an insight into the mechanism, we have performed ten trajectories of explicit-solvent molecular dynamics (MD) for both bound and apo phosphorylated KID (pKID). Ten MD simulations are sufficient to capture the average properties in the protein folding and unfolding. CONCLUSIONS: Room-temperature MD simulations suggest that pKID becomes more rigid and stable upon the KIX-binding. Kinetic analysis of high-temperature MD simulations shows that bound pKID and apo-pKID unfold via a three-state and a two-state process, respectively. Both kinetics and free energy landscape analyses indicate that bound pKID folds in the order of KIX access, initiation of pKID tertiary folding, folding of helix alpha(B), folding of helix alpha(A), completion of pKID tertiary folding, and finalization of pKID-KIX binding. Our data show that the folding pathways of apo-pKID are different from the bound state: the foldings of helices alpha(A) and alpha(B) are swapped. Here we also show that Asn139, Asp140 and Leu141 with large Phi-values are key residues in the folding of bound pKID. Our results are in good agreement with NMR experimental observations and provide significant insight into the general mechanisms of binding induced protein folding and other conformational adjustment in post-translational modification.
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528Huang, Y.; Liu, Z. Kinetic Advantage of Intrinsically Disordered Proteins in Coupled Folding–Binding Process: A Critical Assessment of the “Fly-Casting” Mechanism J. Mol. Biol. 2009, 393, 1143– 1159 DOI: 10.1016/j.jmb.2009.09.010528https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlWhu7nJ&md5=cd30aaa9817e1fa8d28917a0e50e1c1bKinetic Advantage of Intrinsically Disordered Proteins in Coupled Folding-Binding Process: A Critical Assessment of the "Fly-Casting" MechanismHuang, Yongqi; Liu, ZhirongJournal of Molecular Biology (2009), 393 (5), 1143-1159CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)Intrinsically disordered proteins (IDPs) are recognized to play important roles in many biol. functions such as transcriptional and translational regulation, cellular signal transduction, protein phosphorylation, and mol. assemblies. The coupling of folding with binding through a "fly-casting" mechanism has been proposed to account for the fast binding kinetics of IDPs. In this article, exptl. data from the literature were collated to verify the kinetic advantages of IDPs, while mol. simulations were performed to clarify the origin of the kinetic advantages. The phosphorylated KID-kinase-inducible domain interacting domain (KIX) complex was used as an example in the simulations. By modifying a coarse-grained model with a native-centric Go-like potential, we were able to continuously tune the degree of disorder of the phosphorylated KID domain and thus investigate the intrinsic role of chain flexibility in binding kinetics. The simulations show that the "fly-casting" effect is not only due to the greater capture radii of IDPs. The coupling of folding with binding of IDPs leads to a significant redn. in binding free-energy barrier. Such a redn. accelerates the binding process. Although the greater capture radius has been regarded as the main factor in promoting the binding rate of IDPs, we found that this parameter will also lead to the slower translational diffusion of IDPs when compared with ordered proteins. As a result, the capture rate of IDPs was found to be slower than that of ordered proteins. The main origin of the faster binding for IDPs are the fewer encounter times required before the formation of the final binding complex. The roles of the interchain native contacts fraction (Qb) and the mass-center distance (ΔR) as reaction coordinates are also discussed.
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529Ganguly, D.; Chen, J. Topology-based modeling of intrinsically disordered proteins: Balancing intrinsic folding and intermolecular interactions Proteins: Struct., Funct., Genet. 2011, 79, 1251– 1266 DOI: 10.1002/prot.22960529https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvVWrsbc%253D&md5=c41eca538845eb9fddbf2b03ffa10a65Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactionsGanguly, Debabani; Chen, JianhanProteins: Structure, Function, and Bioinformatics (2011), 79 (4), 1251-1266CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topol.-based Go-like modeling as an effective tool for the mechanism of IDP recognition within the theor. framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Go-like models designed for folded proteins tend to over-est. the level of residual structures in unbound IDPs, whereas under-estg. the strength of intermol. interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topol.-derived models to balance intrinsic folding propensities and intermol. interactions, based on exptl. knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Go-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titrn. and relaxation dispersion study and provides a mol.-level interpretation of kinetic rates derived from dispersion curve anal. These case studies provide important insight into the applicability and potential pitfalls of topol.-based modeling for studying IDP folding and interaction in general.
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530Huang, Y.; Liu, Z. Nonnative interactions in coupled folding and binding processes of intrinsically disordered proteins PLoS One 2010, 5, e15375 DOI: 10.1371/journal.pone.0015375There is no corresponding record for this reference.
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531Turjanski, A. G.; Gutkind, J. S.; Best, R. B.; Hummer, G. Binding-induced folding of a natively unstructured transcription factor PLoS Comput. Biol. 2008, 4, e1000060 DOI: 10.1371/journal.pcbi.1000060531https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1c3ktlOksQ%253D%253D&md5=89af13cd7f9ef49b9a38a0887fd3dbdbBinding-induced folding of a natively unstructured transcription factorTurjanski Adrian Gustavo; Gutkind J Silvio; Best Robert B; Hummer GerhardPLoS computational biology (2008), 4 (4), e1000060 ISSN:.Transcription factors are central components of the intracellular regulatory networks that control gene expression. An increasingly recognized phenomenon among human transcription factors is the formation of structure upon target binding. Here, we study the folding and binding of the pKID domain of CREB to the KIX domain of the co-activator CBP. Our simulations of a topology-based Go-type model predict a coupled folding and binding mechanism, and the existence of partially bound intermediates. From transition-path and Phi-value analyses, we find that the binding transition state resembles the unstructured state in solution, implying that CREB becomes structured only after committing to binding. A change of structure following binding is reminiscent of an induced-fit mechanism and contrasts with models in which binding occurs to pre-structured conformations that exist in the unbound state at equilibrium. Interestingly, increasing the amount of structure in the unbound pKID reduces the rate of binding, suggesting a "fly-casting"-like process. We find that the inclusion of attractive non-native interactions results in the formation of non-specific encounter complexes that enhance the on-rate of binding, but do not significantly change the binding mechanism. Our study helps explain how being unstructured can confer an advantage in protein target recognition. The simulations are in general agreement with the results of a recently reported nuclear magnetic resonance study, and aid in the interpretation of the experimental binding kinetics.
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532Huang, Y.; Liu, Z. Smoothing molecular interactions: the ″kinetic buffer″ effect of intrinsically disordered proteins Proteins: Struct., Funct., Genet. 2010, 78, 3251– 3259 DOI: 10.1002/prot.22820There is no corresponding record for this reference.
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533Law, S. M.; Ahlstrom, L. S.; Panahi, A.; Brooks, C. L. Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins J. Phys. Chem. Lett. 2014, 5, 3441– 3444 DOI: 10.1021/jz501811k533https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsFOrtbfL&md5=7616e3be2deaf12bee951123850034a8Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered ProteinsLaw, Sean M.; Ahlstrom, Logan S.; Panahi, Afra; Brooks, Charles L.Journal of Physical Chemistry Letters (2014), 5 (19), 3441-3444CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)Mol. recognition by intrinsically disordered proteins (IDPs) plays a central role in many crit. cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here the authors employ the "Hamiltonian mapping" methodol., which is rooted in the weighted histogram anal. method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing ref. simulations on a given Hamiltonian, the authors illustrate for two model IDPs how this method can extrapolate thermodn. behavior under a range of modified Hamiltonians, in this case representing changes in the binding affinity (Kd) of the system. Given sufficient conformational sampling in a single trajectory, Hamiltonian mapping accurately reproduces Kd values from direct simulation. This method may be generally applied to systems beyond IDPs in force field optimization and in describing changes in thermodn. behavior as a function of external conditions for connection with expt.
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534Knott, M.; Best, R. B. Discriminating binding mechanisms of an intrinsically disordered protein via a multi-state coarse-grained model J. Chem. Phys. 2014, 140, 175102 DOI: 10.1063/1.4873710534https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXnsVertLk%253D&md5=a5d43d30da1f44ffad2a1a0384857247Discriminating binding mechanisms of an intrinsically disordered protein via a multi-state coarse-grained modelKnott, Michael; Best, Robert B.Journal of Chemical Physics (2014), 140 (17), 175102/1-175102/10CODEN: JCPSA6; ISSN:0021-9606. (American Institute of Physics)Many proteins undergo a conformational transition upon binding to their cognate binding partner, with intrinsically disordered proteins (IDPs) providing an extreme example in which a folding transition occurs. However, it is often not clear whether this occurs via an "induced fit" or "conformational selection" mechanism, or via some intermediate scenario. In the first case, transient encounters with the binding partner favor transitions to the bound structure before the two proteins dissoc., while in the second the bound structure must be selected from a subset of unbound structures which are in the correct state for binding, because transient encounters of the incorrect conformation with the binding partner are most likely to result in dissocn. A particularly interesting situation involves those intrinsically disordered proteins which can bind to different binding partners in different conformations. We have devised a multi-state coarse-grained simulation model which is able to capture the binding of IDPs in alternate conformations, and by applying it to the binding of nuclear coactivator binding domain (NCBD) to either ACTR or IRF-3 we are able to det. the binding mechanism. By all measures, the binding of NCBD to either binding partner appears to occur via an induced fit mechanism. Nonetheless, we also show how a scenario closer to conformational selection could arise by choosing an alternative non-binding structure for NCBD. (c) 2014 American Institute of Physics.
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535Rutter, G. O.; Brown, A. H.; Quigley, D.; Walsh, T. R.; Allen, M. P. Testing the transferability of a coarse-grained model to intrinsically disordered proteins Phys. Chem. Chem. Phys. 2015, 17, 31741– 31749 DOI: 10.1039/C5CP05652GThere is no corresponding record for this reference.
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536Terakawa, T.; Higo, J.; Takada, S. Multi-scale ensemble modeling of modular proteins with intrinsically disordered linker regions: application to p53 Biophys. J. 2014, 107, 721– 729 DOI: 10.1016/j.bpj.2014.06.026536https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXht12msrvP&md5=71999cdececfdc0716bf8799bcb71b6bMulti-scale Ensemble Modeling of Modular Proteins with Intrinsically Disordered Linker Regions: Application to p53Terakawa, Tsuyoshi; Higo, Junichi; Takada, ShojiBiophysical Journal (2014), 107 (3), 721-729CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)In eukaryotic proteins, intrinsically disordered regions (IDRs) are ubiquitous and often exist in linker regions that flank the functional domains of modular proteins, regulating their functions. For detailed structural ensemble modeling of IDRs, we propose a multiscale method for IDRs that possess significant long-range order in modular proteins and apply it to the eukaryotic transcription factor p53 as an example. First, we performed all-atom (AA) mol. dynamics (MD) simulations of the explicitly solvated p53 linker region, without exptl. restraint terms, finding fractional long-range contacts within the linker. Second, we fed this AA MD ensemble into a coarse-grained (CG) model, finding an optimal set of contact potentials. The optimized CG MD simulations reproduced the contact probability map from the AA MD simulations. Finally, we performed the CG MD simulation of the tetrameric p53 fragments including the core domains, the linker, and the tetramerization domain. Using the obtained ensemble, we theor. calcd. the small angle x-ray scattering (SAXS) profile of this fragment. The obtained SAXS profile agrees well with the expt. We also found that the long-range contacts in the p53 linker region are required to reproduce the exptl. SAXS profile. The developed framework in which we calc. the long-range contact probability map from the AA MD simulation and incorporate it to the CG model can be applied to broad range of IDRs.
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537Norgaard, A. B.; Ferkinghoff-Borg, J.; Lindorff-Larsen, K. Experimental Parameterization of an Energy Function for the Simulation of Unfolded Proteins Biophys. J. 2008, 94, 182– 192 DOI: 10.1529/biophysj.107.108241537https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXkvFY%253D&md5=1a76ebf781f80aada40e86d42a4cc6b1Experimental parameterization of an energy function for the simulation of unfolded proteinsNorgaard, Anders B.; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, KrestenBiophysical Journal (2008), 94 (1), 182-192CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The detn. of conformational preferences in unfolded and disordered proteins is an important challenge in structural biol. The authors here describe an algorithm to optimize energy functions for the simulation of unfolded proteins. The procedure is based on the max. likelihood principle and employs a fast and efficient gradient descent method to find the set of parameters of the energy function that best explain the exptl. data. The authors first validate the method by using synthetic ref. data, and subsequently apply the algorithms to data from NMR spin-labeling expts. on the Δ131Δ fragment of Staphylococcal nuclease. A significant strength of the procedure that the authors present is that it directly uses exptl. data to optimize the energy parameters, without relying on the availability of high resoln. structures. The procedure is fully general and can be applied to a range of exptl. data and energy functions including the force fields used in mol. dynamics simulations.
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538Amorós, D.; Ortega, A.; García de la Torre, J. Prediction of Hydrodynamic and Other Solution Properties of Partially Disordered Proteins with a Simple, Coarse-Grained Model J. Chem. Theory Comput. 2013, 9, 1678– 1685 DOI: 10.1021/ct300948u538https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXnvVGrsw%253D%253D&md5=5c4629fe843769e938d5a4b60328d09ePrediction of Hydrodynamic and Other Solution Properties of Partially Disordered Proteins with a Simple, Coarse-Grained ModelAmoros, D.; Ortega, A.; Garcia de la Torre, J.Journal of Chemical Theory and Computation (2013), 9 (3), 1678-1685CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The possibility of validating structures of intrinsically disordered proteins against soln. properties is a goal that would be most helpful in the understanding of their function. The authors have devised a scheme for the prediction of soln. properties of partially disordered proteins that comprise one or more ordered domains, along with flexible tails or linkers. A very simple, coarse-grained, residue-level model, which is easily parametrized using available structural information, along with previously developed tools for the simulation of soln. conformation and dynamics, allows the prediction of properties like sedimentation coeffs., relaxation times, and x-ray or neutron scattering. This is demonstrated for a variety of partially disordered proteins, for which well-characterized soln. properties are very accurately evaluated, with predictions falling in most cases within exptl. errors.
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539Qin, S.; Zhou, H.-X. Effects of Macromolecular Crowding on the Conformational Ensembles of Disordered Proteins J. Phys. Chem. Lett. 2013, 4, 3429– 3434 DOI: 10.1021/jz401817x539https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFWlurbL&md5=32eb5f746de4d8b82f3df03c4b94e202Effects of Macromolecular Crowding on the Conformational Ensembles of Disordered ProteinsQin, Sanbo; Zhou, Huan-XiangJournal of Physical Chemistry Letters (2013), 4 (20), 3429-3434CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)Due to their conformational malleability, intrinsically disordered proteins (IDPs) are particularly susceptible to influences of crowded cellular environments. Here we report a computational study of the effects of macromol. crowding on the conformational ensemble of a coarse-grained IDP model, by using two approaches. In one, the IDP is simulated along with the crowders; in the other, crowder-free simulations are postprocessed to predict the conformational ensembles under crowding. We found significant decreases in the radius of gyration of the IDP under crowding, and suggest repulsive interactions with crowders as a common cause for chain compaction in a no. of exptl. studies. The postprocessing approach accurately reproduced the conformational ensembles of the IDP in the direct simulations here, and holds enormous potential for realistic modeling of IDPs under crowding, by permitting thorough conformation sampling for the proteins even when they and the crowders are both represented at the all-atom level.
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540Wang, J.; Wang, Y.; Chu, X.; Hagen, S. J.; Han, W.; Wang, E. Multi-Scaled Explorations of Binding-Induced Folding of Intrinsically Disordered Protein Inhibitor IA3 to its Target Enzyme PLoS Comput. Biol. 2011, 7, e1001118 DOI: 10.1371/journal.pcbi.1001118540https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXltVWltLw%253D&md5=eb9f2910bd98103e585d1cd36bd97da1Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzymeWang, Jin; Wang, Yong; Chu, Xiakun; Hagen, Stephen J.; Han, Wei; Wang, ErkangPLoS Computational Biology (2011), 7 (4), e1001118CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Biomol. function is realized by recognition, and increasing evidence shows that recognition is detd. not only by structure but also by flexibility and dynamics. The authors explored a biomol. recognition process that involves a major conformational change - protein folding. In particular, the authors explore the binding-induced folding of IA3, an intrinsically disordered protein that blocks the active site cleft of the yeast aspartic proteinase saccharopepsin (YPrA) by folding its own N-terminal residues into an amphipathic alpha helix. The authors developed a multi-scaled approach that explores the underlying mechanism by combining structure-based mol. dynamics simulations at the residue level with a stochastic path method at the at. level. Both the free energy profile and the assocd. kinetic paths reveal a common scheme whereby IA3 binds to its target enzyme prior to folding itself into a helix. This theor. result is consistent with recent time-resolved expts. Furthermore, exploration of the detailed trajectories reveals the important roles of non-native interactions in the initial binding that occurs prior to IA3 folding. In contrast to the common view that non-native interactions contribute only to the roughness of landscapes and impede binding, the non-native interactions here facilitate binding by reducing significantly the entropic search space in the landscape. The information gained from multi-scaled simulations of the folding of this intrinsically disordered protein in the presence of its binding target may prove useful in the design of novel inhibitors of aspartic proteinases.
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541Stadler, A. M.; Stingaciu, L.; Radulescu, A.; Holderer, O.; Monkenbusch, M.; Biehl, R.; Richter, D. Internal Nanosecond Dynamics in the Intrinsically Disordered Myelin Basic Protein J. Am. Chem. Soc. 2014, 136, 6987– 6994 DOI: 10.1021/ja502343b541https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmslSqsr4%253D&md5=0e3b54caec9499f890643f5c62085046Internal nanosecond dynamics in the intrinsically disordered myelin basic proteinStadler, Andreas M.; Stingaciu, Laura; Radulescu, Aurel; Holderer, Olaf; Monkenbusch, Michael; Biehl, Ralf; Richter, DieterJournal of the American Chemical Society (2014), 136 (19), 6987-6994CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Intrinsically disordered proteins lack a well-defined folded structure and contain a high degree of structural freedom and conformational flexibility, which is expected to enhance binding to their physiol. targets. In soln. and in the lipid-free state, myelin basic protein (MBP) belongs to this class of proteins. Here, Using small-angle scattering, MBP was found to be structurally disordered similar to Gaussian chains. The combination of structural and hydrodynamic information revealed an intermediary compactness of the protein between globular proteins and random coil polymers. Modeling by a coarse-grained structural ensemble gave indications for a compact core with flexible ends. Neutron spin-echo (NSE) spectroscopy measurements revealed a large contribution of internal dynamics to the overall diffusion. The exptl. results showed a high flexibility of the structural ensemble. Displacement patterns along the 1st 2 normal modes demonstrated that collective stretching and bending motions dominated the internal modes. The obsd. dynamics represented nanosecond conformational fluctuations within the reconstructed coarse-grained structural ensemble, allowing the exploration of a large configurational space. In an alternative approach, the authors investigated if models from polymer theory, recently used for the interpretation of fluorescence spectroscopy expts. on disordered proteins, were suitable for the interpretation of the obsd. motions. Within the framework of the Zimm model with internal friction (ZIF), a large offset of 81.6 ns was needed as an addn. to all relaxation times due to intrachain friction sources. The ZIF model, however, showed small but systematic deviations from the measured data. The large value of the internal friction led to the breakdown of the Zimm model.
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542Yu, H.; Han, W.; Ma, W.; Schulten, K. Transient beta-hairpin formation in alpha-synuclein monomer revealed by coarse-grained molecular dynamics simulation J. Chem. Phys. 2015, 143, 243142 DOI: 10.1063/1.4936910There is no corresponding record for this reference.
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543Ghavami, A.; Veenhoff, L. M.; van der Giessen, E.; Onck, P. R. Probing the disordered domain of the nuclear pore complex through coarse-grained molecular dynamics simulations Biophys. J. 2014, 107, 1393– 1402 DOI: 10.1016/j.bpj.2014.07.060543https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsFags73O&md5=65a8bee4d1b11608c44609721832fba7Probing the Disordered Domain of the Nuclear Pore Complex through Coarse-Grained Molecular Dynamics SimulationsGhavami, Ali; Veenhoff, Liesbeth M.; van der Giessen, Erik; Onck, Patrick R.Biophysical Journal (2014), 107 (6), 1393-1402CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The distribution of disordered proteins (FG-nups) that line the transport channel of the nuclear pore complex (NPC) is investigated by means of coarse-grained mol. dynamics simulations. A one-bead-per-amino-acid model is presented that accounts for the hydrophobic/hydrophilic and electrostatic interactions between different amino acids, polarity of the solvent, and screening of free ions. The results indicate that the interaction of the FG-nups forms a high-d., doughnut-like distribution inside the NPC, which is rich in FG-repeats. We show that the obtained distribution is encoded in the amino-acid sequence of the FG-nups and is driven by both electrostatic and hydrophobic interactions. To explore the relation between structure and function, we have systematically removed different combinations of FG-nups from the pore to simulate inviable and viable NPCs that were previously studied exptl. The obtained d. distributions show that the max. d. of the FG-nups inside the pore does not exceed 185 mg/mL in the nonviable NPCs, whereas for the wild-type and viable NPCs, this value increases to 300 mg/mL. Interestingly, this max. d. is not correlated to the total mass of the FG-nups, but depends sensitively on the specific combination of essential Nups located in the central plane of the NPC.
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544Ahlstrom, L. S.; Law, S. M.; Dickson, A.; Brooks, C. L. Multiscale Modeling of a Conditionally Disordered pH-Sensing Chaperone J. Mol. Biol. 2015, 427, 1670– 1680 DOI: 10.1016/j.jmb.2015.01.002544https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtF2gs74%253D&md5=492c3d19e063027187c0edab01d4c76dMultiscale Modeling of a Conditionally Disordered pH-Sensing ChaperoneAhlstrom, Logan S.; Law, Sean M.; Dickson, Alex; Brooks, Charles L.Journal of Molecular Biology (2015), 427 (8), 1670-1680CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Ltd.)The pH-sensing chaperone HdeA promotes the survival of enteropathogenic bacteria during transit through the harshly acidic environment of the mammalian stomach. At low pH, HdeA transitions from an inactive, folded, dimer to chaperone-active, disordered, monomers to protect against the acid-induced aggregation of periplasmic proteins. Toward achieving a detailed mechanistic understanding of the pH response of HdeA, we develop a multiscale modeling approach to capture its pH-dependent thermodn. Our approach combines pKa (logarithmic acid dissocn. const.) calcns. from all-atom const. pH mol. dynamics simulations with coarse-grained modeling and yields new, at.-level, insights into HdeA chaperone function that can be directly tested by expt. "pH triggers" that significantly destabilize the dimer are each located near the N-terminus of a helix, suggesting that their neutralization at low pH destabilizes the helix macrodipole as a mechanism of monomer disordering. Moreover, we observe a non-monotonic change in the pH-dependent stability of HdeA, with maximal stability of the dimer near pH 5. This affect is attributed to the protonation Glu37, which exhibits an anomalously high pKa value and is located within the hydrophobic dimer interface. Finally, the pH-dependent binding pathway of HdeA comprises a partially unfolded, dimeric intermediate that becomes increasingly stable relative to the native dimer at lower pH values and displays key structural features for chaperone-substrate interaction. We anticipate that the insights from our model will help inform ongoing NMR and biochem. investigations.
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545Koehler Leman, J.; Ulmschneider, M. B.; Gray, J. J. Computational modeling of membrane proteins Proteins: Struct., Funct., Genet. 2015, 83, 1– 24 DOI: 10.1002/prot.24703545https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFeitrvO&md5=b1dc8d57d59832241025d99a9ba93855Computational modeling of membrane proteinsKoehler Leman, Julia; Ulmschneider, Martin B.; Gray, Jeffrey J.Proteins: Structure, Function, and Bioinformatics (2015), 83 (1), 1-24CODEN: PSFBAF ISSN:. (Wiley-Blackwell)A review. The detn. of membrane protein (MP) structures has always trailed that of sol. proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure detn. The percentage of MP structures in the protein databank (PDB) has been at a const. 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was exptl. elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topol. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and mol. dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.
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546Baker, M. Making membrane proteins for structures: a trillion tiny tweaks Nat. Methods 2010, 7, 429– 434 DOI: 10.1038/nmeth0610-429546https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsF2it7o%253D&md5=45cec959130da53eaf570f3767dd9087Making membrane proteins for structures: a trillion tiny tweaksBaker, MonyaNature Methods (2010), 7 (6), 429-434CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)A review on multiple means to get high-quality membrane proteins for x-ray crystallog. and NMR spectroscopy studies.
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547Marrink, S. J.; Mark, A. E. Molecular dynamics simulation of the formation, structure, and dynamics of small phospholipid vesicles J. Am. Chem. Soc. 2003, 125, 15233– 15242 DOI: 10.1021/ja0352092547https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXovVOhsbc%253D&md5=75693a417eba874efe843800d7a28069Molecular Dynamics Simulation of the Formation, Structure, and Dynamics of Small Phospholipid VesiclesMarrink, Siewert J.; Mark, Alan E.Journal of the American Chemical Society (2003), 125 (49), 15233-15242CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Here, we use coarse grained mol. dynamics (MD) simulations to study the spontaneous aggregation of dipalmitoylphosphatidylcholine (DPPC) lipids into small unilamellar vesicles. We show that the aggregation process occurs on a nanosecond time scale, with bicelles and cuplike vesicles formed at intermediate stages. Formation of hemifused vesicles is also obsd. at higher lipid concn. With either 25% dipalmitoylphosphatidylethanolamine (DPPE) or lysoPC mixed into the system, the final stages of the aggregation process occur significantly faster. The structure of the spontaneously formed vesicles is analyzed in detail. Microsecond simulations of isolated vesicles reveal significant differences in the packing of the lipids between the inner and outer monolayers, and between PC, PE, and lysoPC. Due to the small size of the vesicles they remain almost perfectly spherical, undergoing very limited shape fluctuations or bilayer undulations. The lipid lateral diffusion rate is found to be faster in the outer than in the inner monolayer. The water permeability coeff. of the pure DPPC vesicles is of the order of 10-3 cm s-1, in agreement with exptl. measurements.
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548Knecht, V.; Marrink, S. J. Molecular dynamics simulations of lipid vesicle fusion in atomic detail Biophys. J. 2007, 92, 4254– 4261 DOI: 10.1529/biophysj.106.103572548https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXmsFeksb4%253D&md5=996b9ea4dc0571b488541c38374f2acfMolecular dynamics simulations of lipid vesicle fusion in atomic detailKnecht, Volker; Marrink, Siewert-JanBiophysical Journal (2007), 92 (12), 4254-4261CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The fusion of a membrane-bonded vesicle with a target membrane is a key step in intracellular trafficking, exocytosis, and drug delivery. Mol. dynamics simulations have been used to study the fusion of small unilamellar vesicles composed of a dipalmitoyl-phosphatidylcholine (DPPC)/palmitic acid 1:2 mixt. in at. detail. The simulations were performed at 350-370 K and mimicked the temp.- and pH-induced fusion of DPPC/palmitic acid vesicles from expts. by others. To make the calcns. computationally feasible, a vesicle simulated at periodic boundary conditions was fused with its periodic image. Starting from a performed stalk between the outer leaflets of the vesicle and its periodic image, a hemifused state formed within 2 ns. In one out of six simulations, a transient pore formed close to the stalk, resulting in the mixing of DPPC lipids between the outer and the inner leaflet. The hemifused state was (meta)stable on a timescale of up to 11 ns. Forcing a single lipid into the interior of the hemifusion diaphragm induced the formation and expansion of a fusion pore on a nanosecond timescale. This work opens the perspective to study a wide variety of mesoscopic biol. processes in at. detail.
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549Bennett, W. F.; MacCallum, J. L.; Hinner, M. J.; Marrink, S. J.; Tieleman, D. P. Molecular view of cholesterol flip-flop and chemical potential in different membrane environments J. Am. Chem. Soc. 2009, 131, 12714– 12720 DOI: 10.1021/ja903529f549https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXpslahtb8%253D&md5=0ac4464b09d393f9a4d377c9cc2f2470Molecular View of Cholesterol Flip-Flop and Chemical Potential in Different Membrane EnvironmentsBennett, W. F. Drew; MacCallum, Justin L.; Hinner, Marlon J.; Marrink, Siewert J.; Tieleman, D. PeterJournal of the American Chemical Society (2009), 131 (35), 12714-12720CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The relative stability of cholesterol in cellular membranes and the thermodn. of fluctuations from equil. have important consequences for sterol trafficking and lateral domain formation. We used mol. dynamics computer simulations to investigate the partitioning of cholesterol in a systematic set of lipid bilayers. In addn. to atomistic simulations, we undertook a large set of coarse grained simulations, which allowed longer time and length scales to be sampled. Our results agree with recent expts. that the rate of cholesterol flip-flop can be fast on physiol. time scales, while extending our understanding of this process to a range of lipids. We predicted that the rate of flip-flop is strongly dependent on the compn. of the bilayer. In polyunsatd. bilayers, cholesterol undergoes flip-flop on a submicrosecond time scale, while flip-flop occurs in the second range in satd. bilayers with high cholesterol content. We also calcd. the free energy of cholesterol desorption, which can be equated to the excess chem. potential of cholesterol in the bilayer compared to water. The free energy of cholesterol desorption from a DPPC bilayer is 80 kJ/mol, compared to 67 kJ/mol for a DAPC bilayer. In general, cholesterol prefers more ordered and rigid bilayers and has the lowest affinity for bilayers with two polyunsatd. chains. Overall, the simulations provide a detailed mol. level thermodn. description of cholesterol interactions with lipid bilayers, of fundamental importance to eukaryotic life.
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550Ogushi, F.; Ishitsuka, R.; Kobayashi, T.; Sugita, Y. Rapid flip-flop motions of diacylglycerol and ceramide in phospholipid bilayers Chem. Phys. Lett. 2012, 522, 96 DOI: 10.1016/j.cplett.2011.11.057550https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XktFCjsQ%253D%253D&md5=ea07a981543f0037e086dff6c46f84e0Rapid flip-flop motions of diacylglycerol and ceramide in phospholipid bilayersOgushi, Fumiko; Ishitsuka, Reiko; Kobayashi, Toshihide; Sugita, YujiChemical Physics Letters (2012), 522 (), 96-102CODEN: CHPLBC; ISSN:0009-2614. (Elsevier B.V.)The authors investigated flip-flop motions of diacylglycerol and ceramide in phospholipid bilayers using coarse-grained mol. dynamics simulations. In the simulations, flip-flop motions of diacylglycerol and ceramide in the DAPC membrane were slower than cholesterol. The rates correlated with the no. of unsatd. bonds in the membrane phospholipids and hence with fluidity of membranes. These findings qual. agreed with corresponding exptl. data. Statistical anal. of the trajectories suggests that flip-flop could be approximated as a Poisson process. The rate of the transverse movement was influenced by depth of the polar head group in the membrane and extent of interaction with water.
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551Esteban-Martin, S.; Risselada, H. J.; Salgado, J.; Marrink, S. J. Stability of asymmetric lipid bilayers assessed by molecular dynamics simulations J. Am. Chem. Soc. 2009, 131, 15194– 15202 DOI: 10.1021/ja904450t551https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXht1Sqt7%252FJ&md5=4b1f14269207a499e35e3c9766156ebfStability of Asymmetric Lipid Bilayers Assessed by Molecular Dynamics SimulationsEsteban-Martin, Santi; Risselada, H. Jelger; Salgado, Jesus; Marrink, Siewert J.Journal of the American Chemical Society (2009), 131 (42), 15194-15202CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The asym. insertion of amphiphiles into biol. membranes compromises the balance between the inner and outer monolayers. As a result, area expansion of the receiving leaflet and curvature strain may lead to membrane permeation, shape changes, or membrane fusion events. Both atomistic and coarse-grained mol. dynamics simulations of dipalmitoyl-phosphatidylcholine (DPPC) bilayers were conducted to study the effect of an asym. distribution of lipids between the two monolayers on membrane stability. Highly asym. lipid bilayers were found to be surprisingly stable within the sub-microsecond time span of the simulations. Even the limiting case of a monolayer immersed in water ruptured spontaneously only after at least 20 ns simulation. A thermal shock could destabilize these kinetically trapped states. Mixed systems composed of DPPC and short tail diC8PC lipids were also studied, showing that the presence of the cone-shaped short tail lipid facilitates the release of tension in the asym. systems via formation of a transmembrane pore. Thus, asym. area expansion and curvature stress cooperate to yield bilayer disruption. It appears that, although asym. area expansion destabilizes the bilayer structure, the activation energy for trans-monolayer lipid re-equilibration is increased. Such a large kinetic barrier can be reduced by lipids with pos. spontaneous curvature. These effects are important at the onset of bilayer destabilization phenomena, such as lipid pore formation and membrane fusion, and should be considered for the mechanism of induction of such processes by peptides and proteins.
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552Kasson, P. M.; Lindahl, E.; Pande, V. S. Atomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tails PLoS Comput. Biol. 2010, 6, e1000829 DOI: 10.1371/journal.pcbi.1000829552https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cnivVahtg%253D%253D&md5=fc4db798ffdd01d9c65400061156a2aaAtomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tailsKasson Peter M; Lindahl Erik; Pande Vijay SPLoS computational biology (2010), 6 (6), e1000829 ISSN:.Membrane fusion is essential to both cellular vesicle trafficking and infection by enveloped viruses. While the fusion protein assemblies that catalyze fusion are readily identifiable, the specific activities of the proteins involved and nature of the membrane changes they induce remain unknown. Here, we use many atomic-resolution simulations of vesicle fusion to examine the molecular mechanisms for fusion in detail. We employ committor analysis for these million-atom vesicle fusion simulations to identify a transition state for fusion stalk formation. In our simulations, this transition state occurs when the bulk properties of each lipid bilayer remain in a lamellar state but a few hydrophobic tails bulge into the hydrophilic interface layer and make contact to nucleate a stalk. Additional simulations of influenza fusion peptides in lipid bilayers show that the peptides promote similar local protrusion of lipid tails. Comparing these two sets of simulations, we obtain a common set of structural changes between the transition state for stalk formation and the local environment of peptides known to catalyze fusion. Our results thus suggest that the specific molecular properties of individual lipids are highly important to vesicle fusion and yield an explicit structural model that could help explain the mechanism of catalysis by fusion proteins.
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553Laganowsky, A.; Reading, E.; Allison, T. M.; Ulmschneider, M. B.; Degiacomi, M. T.; Baldwin, A. J.; Robinson, C. V. Membrane proteins bind lipids selectively to modulate their structure and function Nature 2014, 510, 172 DOI: 10.1038/nature13419553https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhtFygs7%252FF&md5=02119c92280671a8dea0e7b76ea0f857Membrane proteins bind lipids selectively to modulate their structure and functionLaganowsky, Arthur; Reading, Eamonn; Allison, Timothy M.; Ulmschneider, Martin B.; Degiacomi, Matteo T.; Baldwin, Andrew J.; Robinson, Carol V.Nature (London, United Kingdom) (2014), 510 (7503), 172-175CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to det. the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate (PI), in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin (CDL) imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar expts. identify AmtB as being highly selective for phosphatidylglycerol (PG), prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resoln. structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane protein structure and/or function. We anticipate that these findings will be important not only for defining the selectivity of membrane proteins towards lipids, but also for understanding the role of lipids in modulating protein function or drug binding.
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554Bond, P. J.; Sansom, M. S. Insertion and assembly of membrane proteins via simulation J. Am. Chem. Soc. 2006, 128, 2697– 2704 DOI: 10.1021/ja0569104554https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XhtVKjsr4%253D&md5=9c915e74b4a1223b9dd0183bdd2bee73Insertion and Assembly of Membrane Proteins via SimulationBond, Peter J.; Sansom, Mark S. P.Journal of the American Chemical Society (2006), 128 (8), 2697-2704CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)Interactions of lipids are central to the folding and stability of membrane proteins. Coarse-grained mol. dynamics simulations have been used to reveal the mechanisms of self-assembly of protein/membrane and protein/detergent complexes for representatives of two classes of membrane protein, namely, glycophorin (a simple α-helical bundle) and OmpA (a β-barrel). The accuracy of the coarse-grained simulations is established via comparison with the equiv. atomistic simulations of self-assembly of protein/detergent micelles. The simulation of OmpA/bilayer self-assembly reveals how a folded outer membrane protein can be inserted in a bilayer. The glycophorin/bilayer simulation supports the two-state model of membrane folding, in which transmembrane helix insertion precedes dimer self-assembly within a bilayer. The simulations also suggest that a dynamic equil. exists between the glycophorin helix monomer and dimer within a bilayer. The simulated glycophorin helix dimer is remarkably close in structure to that revealed by NMR. Thus, coarse-grained methods may help to define mechanisms of membrane protein (re)folding and will prove suitable for simulation of larger scale dynamic rearrangements of biol. membranes.
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555Hall, B. A.; Chetwynd, A. P.; Sansom, M. S. Exploring peptide-membrane interactions with coarse-grained MD simulations Biophys. J. 2011, 100, 1940– 1948 DOI: 10.1016/j.bpj.2011.02.041555https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXkvVKhsrc%253D&md5=d0d0312559a1a2da28a1b6b7e931bd35Exploring Peptide-Membrane Interactions with Coarse-Grained MD SimulationsHall, Benjamin A.; Chetwynd, Alan P.; Sansom, Mark S. P.Biophysical Journal (2011), 100 (8), 1940-1948CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)The interaction of α-helical peptides with lipid bilayers is central to our understanding of the physicochem. principles of biol. membrane organization and stability. Mutations that alter the position or orientation of an α-helix within a membrane, or that change the probability that the α-helix will insert into the membrane, can alter a range of membrane protein functions. We describe a comparative coarse-grained mol. dynamics simulation methodol., based on self-assembly of a lipid bilayer in the presence of an α-helical peptide, which allows us to model membrane transmembrane helix insertion. We validate this methodol. against available exptl. data for synthetic model peptides (WALP23 and LS3). Simulation-based ests. of apparent free energies of insertion into a bilayer of cystic fibrosis transmembrane regulator-derived helixes correlate well with published data for translocon-mediated insertion. Comparison of values of the apparent free energy of insertion from self-assembly simulations with those from coarse-grained mol. dynamics potentials of mean force for model peptides, and with translocon-mediated insertion of cystic fibrosis transmembrane regulator-derived peptides suggests a nonequil. model of helix insertion into bilayers.
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556Sobhanifar, S.; Schneider, B.; Lohr, F.; Gottstein, D.; Ikeya, T.; Mlynarczyk, K.; Pulawski, W.; Ghoshdastider, U.; Kolinski, M.; Filipek, S. Structural investigation of the C-terminal catalytic fragment of presenilin 1 Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 9644– 9649 DOI: 10.1073/pnas.1000778107There is no corresponding record for this reference.
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557Klingelhoefer, J. W.; Carpenter, T.; Sansom, M. S. Peptide nanopores and lipid bilayers: interactions by coarse-grained molecular-dynamics simulations Biophys. J. 2009, 96, 3519– 3528 DOI: 10.1016/j.bpj.2009.01.046557https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXnvVert74%253D&md5=10b6f8c757b2f4ed7bbdc8d380a98a1cPeptide nanopores and lipid bilayers: interactions by coarse-grained molecular-dynamics simulationsKlingelhoefer, Jochen W.; Carpenter, Timothy; Sansom, Mark S. P.Biophysical Journal (2009), 96 (9), 3519-3528CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)A set of 49 protein nanopore-lipid bilayer systems was explored by means of coarse-grained mol.-dynamics simulations to study the interactions between nanopores and the lipid bilayers in which they are embedded. The seven nanopore species investigated represent the two main structural classes of membrane proteins (α-helical and β-barrel), and the seven different bilayer systems range in thickness from ∼28 to ∼43 Å. The study focuses on the local effects of hydrophobic mismatch between the nanopore and the lipid bilayer. The effects of nanopore insertion on lipid bilayer thickness, the dependence between hydrophobic thickness and the obsd. nanopore tilt angle, and the local distribution of lipid types around a nanopore in mixed-lipid bilayers are all analyzed. Different behavior for nanopores of similar hydrophobic length but different geometry is obsd. The local lipid bilayer perturbation caused by the inserted nanopores suggests possible mechanisms for both lipid bilayer-induced protein sorting and protein-induced lipid sorting. A correlation between smaller lipid bilayer thickness (larger hydrophobic mismatch) and larger nanopore tilt angle is obsd. and, in the case of larger hydrophobic mismatches, the simulated tilt angle distribution seems to broaden. Furthermore, both nanopore size and key residue types (e.g., tryptophan) seem to influence the level of protein tilt, emphasizing the reciprocal nature of nanopore-lipid bilayer interactions.
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558Balali-Mood, K.; Bond, P. J.; Sansom, M. S. Interaction of monotopic membrane enzymes with a lipid bilayer: a coarse-grained MD simulation study Biochemistry 2009, 48, 2135– 2145 DOI: 10.1021/bi8017398558https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXit1Wgtbw%253D&md5=7d24e712ae6651696a102ae60cd9eb2dInteraction of Monotopic Membrane Enzymes with a Lipid Bilayer: A Coarse-Grained MD Simulation StudyBalali-Mood, Kia; Bond, Peter J.; Sansom, Mark S. P.Biochemistry (2009), 48 (10), 2135-2145CODEN: BICHAW; ISSN:0006-2960. (American Chemical Society)Monotopic membrane proteins bind tightly to cell membranes but do not generally span the lipid bilayer. Their interactions with lipid bilayers may be studied via coarse-grained mol. dynamics (CG-MD) simulations. Understanding such interactions is important as monotopic enzymes frequently act on hydrophobic substrates, while x-ray structures rarely provide direct information about their interactions with membranes. CG-MD self-assembly simulations enable prediction of the orientation and depth of insertion into a lipid bilayer of a monotopic protein, and also of the interactions of individual protein residues with lipid mols. The CG-MD method has been evaluated via comparison with extended (>30 ns) atomistic simulations of monoamine oxidase, revealing good agreement between the results of coarse-grained and atomistic simulations. CG-MD simulations have been applied to a set of 11 monotopic proteins for which three-dimensional structures are available. These proteins may be divided into two groups on the basis of the results of the simulations. One group consists of those proteins which are inserted into the lipid bilayer to a limited extent, interacting mainly at the phospholipid-water interface. The second group consists of those which are inserted more deeply into the bilayer. Those monotopic proteins which are inserted more deeply cause significant local perturbation of bilayer properties such as bilayer thickness. Deeper insertion seems to correlate with a greater no. of basic residues in the "foot" whereby a monotopic protein interacts with the membrane.
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559Sansom, M. S.; Scott, K. A.; Bond, P. J. Coarse-grained simulation: a high-throughput computational approach to membrane proteins Biochem. Soc. Trans. 2008, 36, 27– 32 DOI: 10.1042/BST0360027559https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1ajtb0%253D&md5=424f251326616431102765093ba07a84Coarse-grained simulation: a high-throughput computational approach to membrane proteinsSansom, Mark S. P.; Scott, Kathryn A.; Bond, Peter J.Biochemical Society Transactions (2008), 36 (1), 27-32CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)A review. An understanding of the interactions of membrane proteins with a lipid bilayer environment is central to relating their structure to their function and stability. A high-throughput approach to prediction of membrane protein interactions with a lipid bilayer based on coarse-grained Mol. Dynamics simulations is described. This method has been used to develop a database of CG simulations (coarse-grained simulations) of membrane proteins. Comparison of CG simulations and AT simulations (atomistic simulations) of lactose permease reveals good agreement between the two methods in terms of predicted lipid headgroup contacts. Both CG and AT simulations predict considerable local bilayer deformation by the voltage sensor domain of the potassium channel KvAP.
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560Dominguez, L.; Meredith, S. C.; Straub, J. E.; Thirumalai, D. Transmembrane fragment structures of amyloid precursor protein depend on membrane surface curvature J. Am. Chem. Soc. 2014, 136, 854– 857 DOI: 10.1021/ja410958j560https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvFOnsbjP&md5=9f9a6c85d62696895fdedb7da53492f4Transmembrane Fragment Structures of Amyloid Precursor Protein Depend on Membrane Surface CurvatureDominguez, Laura; Meredith, Stephen C.; Straub, John E.; Thirumalai, DavidJournal of the American Chemical Society (2014), 136 (3), 854-857CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The amyloid β (Aβ) peptide assocd. with Alzheimer's disease results from processing of the amyloid precursor protein (APP) by secretases. Cleavage of APP by β-secretase produces a 99 amino acid C-terminal fragment of APP (C99) consisting of a single transmembrane (TM) helix. Simulations of C99 congeners and structural studies of C99 in surfactant micelles and lipid vesicles have shown that a key peptide structural motif is a prominent "GG-kink," centered at two glycines dividing the TM helix. The flexibility of the GG-kink is important in the processing of C99 by γ-secretase. We performed multiscale simulations of C9915-55 in a DPC surfactant micelle and POPC lipid bilayer in order to elucidate the role of membrane surface curvature in modulating the peptide structure. C9915-55 in a DPC surfactant micelle possesses a "GG-kink," in the TM domain near the dynamic hinge located at G37/G38. Such a kink is not obsd. in C9915-55 in a POPC lipid bilayer. Intramol. interaction between the extracellular and TM domains of C9915-55 is enhanced in the micelle environment, influencing helical stability, TM helix extension, exposure to water, and depth of insertion in the lipophilic region. Our results show that the fluctuations of the structural ensemble of APP are strongly influenced by membrane surface curvature.
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561Long, S. B.; Tao, X.; Campbell, E. B.; MacKinnon, R. Atomic structure of a voltage-dependent K+ channel in a lipid membrane-like environment Nature 2007, 450, 376– U373 DOI: 10.1038/nature06265561https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtlajs7%252FN&md5=45593aca2f588a16cc49bbddcc20a4e3Atomic structure of a voltage-dependent K+ channel in a lipid membrane-like environmentLong, Stephen B.; Tao, Xiao; Campbell, Ernest B.; MacKinnon, RoderickNature (London, United Kingdom) (2007), 450 (7168), 376-382CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Voltage-dependent K+ (Kv) channels repolarize the action potential in neurons and muscle. This type of channel is gated directly by membrane voltage through protein domains known as voltage sensors, which are mol. voltmeters that read the membrane voltage and regulate the pore. Here we describe the structure of a chimeric voltage-dependent K+ channel, which we call the 'paddle-chimera channel', in which the voltage-sensor paddle has been transferred from Kv2.1 to Kv1.2. Crystd. in complex with lipids, the complete structure at 2.4 angstroem resoln. reveals the pore and voltage sensors embedded in a membrane-like arrangement of lipid mols. The detailed structure, which can be compared directly to a large body of functional data, explains charge stabilization within the membrane and suggests a mechanism for voltage-sensor movements and pore gating.
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562Sengupta, D.; Chattopadhyay, A. Identification of cholesterol binding sites in the serotonin1A receptor J. Phys. Chem. B 2012, 116, 12991– 12996 DOI: 10.1021/jp309888u562https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFWks77O&md5=7d6baa0a1397fc7d0ad6119d4865295bIdentification of cholesterol binding sites in the serotonin1A receptorSengupta, Durba; Chattopadhyay, AmitabhaJournal of Physical Chemistry B (2012), 116 (43), 12991-12996CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)The serotonin1A receptor is a representative member of the G protein-coupled receptor (GPCR) superfamily and serves as an important drug target in the development of therapeutic agents for neuropsychiatric disorders. Previous work has shown the requirement of membrane cholesterol in the organization, dynamics, and function of the serotonin1A receptor. Here, the authors show that membrane cholesterol binds preferentially to certain sites on the serotonin1A receptor by performing multiple, long time scale MARTINI coarse-grain mol. dynamics simulations. Interestingly, these results identified the highly conserved cholesterol recognition/interaction amino acid consensus (CRAC) motif on transmembrane helix V as one of the sites with high cholesterol occupancy, thereby confirming its role as a putative cholesterol binding motif. These results represent the 1st direct evidence for membrane cholesterol binding to specific sites on the serotonin1A receptor and represent an important step in the overall understanding of GPCR function in health and disease.
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563Koivuniemi, A.; Vuorela, T.; Kovanen, P. T.; Vattulainen, I.; Hyvonen, M. T. Lipid exchange mechanism of the cholesteryl ester transfer protein clarified by atomistic and coarse-grained simulations PLoS Comput. Biol. 2012, 8, e1002299 DOI: 10.1371/journal.pcbi.1002299563https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFSqu7k%253D&md5=13185165cb3d37e76faacc2d8a7cd895Lipid exchange mechanism of the cholesteryl ester transfer protein clarified by atomistic and coarse-grained simulationsKoivuniemi, Artturi; Vuorela, Timo; Kovanen, Petri T.; Vattulainen, Ilpo; Hyvonen, Marja T.PLoS Computational Biology (2012), 8 (1), e1002299CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Cholesteryl ester transfer protein (CETP) transports cholesteryl esters, triglycerides, and phospholipids between different lipoprotein fractions in blood plasma. The inhibition of CETP has been shown to be a sound strategy to prevent and treat the development of coronary heart disease. We employed mol. dynamics simulations to unravel the mechanisms assocd. with the CETP-mediated lipid exchange. To this end we used both atomistic and coarse-grained models whose results were consistent with each other. We found CETP to bind to the surface of high d. lipoprotein (HDL)-like lipid droplets through its charged and tryptophan residues. Upon binding, CETP rapidly (in about 10 ns) induced the formation of a small hydrophobic patch to the phospholipid surface of the droplet, opening a route from the core of the lipid droplet to the binding pocket of CETP. This was followed by a conformational change of helix X of CETP to an open state, in which we found the accessibility of cholesteryl esters to the C-terminal tunnel opening of CETP to increase. Furthermore, in the absence of helix X, cholesteryl esters rapidly diffused into CETP through the C-terminal opening. The results provide compelling evidence that helix X acts as a lid which conducts lipid exchange by alternating the open and closed states. The findings have potential for the design of novel mol. agents to inhibit the activity of CETP.
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564Pleskot, R.; Pejchar, P.; Zarsky, V.; Staiger, C. J.; Potocky, M. Structural insights into the inhibition of actin-capping protein by interactions with phosphatidic acid and phosphatidylinositol (4,5)-bisphosphate PLoS Comput. Biol. 2012, 8, e1002765 DOI: 10.1371/journal.pcbi.1002765There is no corresponding record for this reference.
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565Stansfeld, P. J.; Hopkinson, R.; Ashcroft, F. M.; Sansom, M. S. PIP(2)-binding site in Kir channels: definition by multiscale biomolecular simulations Biochemistry 2009, 48, 10926– 10933 DOI: 10.1021/bi9013193There is no corresponding record for this reference.
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566Yin, F.; Kindt, J. T. Hydrophobic mismatch and lipid sorting near OmpA in mixed bilayers: atomistic and coarse-grained simulations Biophys. J. 2012, 102, 2279– 2287 DOI: 10.1016/j.bpj.2012.04.005There is no corresponding record for this reference.
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567Arnarez, C.; Mazat, J. P.; Elezgaray, J.; Marrink, S. J.; Periole, X. Evidence for cardiolipin binding sites on the membrane-exposed surface of the cytochrome bc1 J. Am. Chem. Soc. 2013, 135, 3112– 3120 DOI: 10.1021/ja310577u567https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhvVCjt7o%253D&md5=8b88191b2e174b337c8efdffca93b008Evidence for Cardiolipin Binding Sites on the Membrane-Exposed Surface of the Cytochrome bc1Arnarez, Clement; Mazat, Jean-Pierre; Elezgaray, Juan; Marrink, Siewert-J.; Periole, XavierJournal of the American Chemical Society (2013), 135 (8), 3112-3120CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The respiratory chain is located in the inner membrane of mitochondria and produces the major part of the ATP used by a cell. Cardiolipin (CL), a doubly-charged phospholipid composing ∼10-20% of the mitochondrial membrane, plays an important role in the function and supramol. organization of the respiratory chain complexes. We present an extensive set of coarse-grain mol. dynamics (CGMD) simulations aiming at the detn. of the preferential interfaces of CLs on the respiratory chain complex III (cytochrome bc1, CIII). Six CL binding sites are identified, including the CL binding sites known from earlier structural studies and buried in protein cavities. The simulations revealed the importance of two subunits of CIII (G and K in bovine heart) for the structural integrity of these internal CL binding sites. In addn., new binding sites are found on the membrane-exposed protein surface. The reproducibility of these binding sites over two species (bovine heart and yeast mitochondria) points to an important role for the function of the respiratory chain. Interestingly, the membrane-exposed CL binding sites are located on the matrix side of CIII in the inner membrane, and thus may provide localized sources of protons ready for uptake by CIII. Furthermore, we found that CLs bound to those membrane-exposed sites bridge the proteins during their assembly into supercomplexes by sharing the binding sites.
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568Weingarth, M.; Prokofyev, A.; van der Cruijsen, E. A.; Nand, D.; Bonvin, A. M.; Pongs, O.; Baldus, M. Structural determinants of specific lipid binding to potassium channels J. Am. Chem. Soc. 2013, 135, 3983– 3988 DOI: 10.1021/ja3119114568https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXivVyjtbs%253D&md5=8c667335f5f765a293dec730163cf341Structural Determinants of Specific Lipid Binding to Potassium ChannelsWeingarth, Markus; Prokofyev, Alexander; van der Cruijsen, Elwin A. W.; Nand, Deepak; Bonvin, Alexandre M. J. J.; Pongs, Olaf; Baldus, MarcJournal of the American Chemical Society (2013), 135 (10), 3983-3988CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)We have investigated specific lipid binding to the pore domain of potassium channels KcsA and chimeric KcsA-Kv1.3 on the structural and functional level using extensive coarse-grained and atomistic mol. dynamics (MD) simulations, solid-state NMR, and single channel measurements. We show that while KcsA activity is critically modulated by the specific and cooperative binding of anionic nonannular lipids close to the channel's selectivity filter, the influence of nonannular lipid binding on KcsA-Kv1.3 is much reduced. The diminished impact of specific lipid binding on KcsA-Kv1.3 results from a point-mutation at the corresponding nonannular lipid binding site leading to a salt-bridge between adjacent KcsA-Kv1.3 subunits, which is conserved in many voltage-gated potassium channels and prevents strong nonannular lipid binding to the pore domain. Our findings elucidate how protein-lipid and protein-protein interactions modulate K+ channel activity. The combination of MD, NMR, and functional studies as shown here may help to dissect the structural and dynamical processes that are crit. for the functioning of larger membrane proteins, including Kv channels in a membrane setting.
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569Sharma, S.; Juffer, A. H. An atomistic model for assembly of transmembrane domain of T cell receptor complex J. Am. Chem. Soc. 2013, 135, 2188– 2197 DOI: 10.1021/ja308413eThere is no corresponding record for this reference.
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570Dominguez, L.; Foster, L.; Meredith, S. C.; Straub, J. E.; Thirumalai, D. Structural heterogeneity in transmembrane amyloid precursor protein homodimer is a consequence of environmental selection J. Am. Chem. Soc. 2014, 136, 9619– 9626 DOI: 10.1021/ja503150x570https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXpslegt74%253D&md5=34f02544624e8b0be212ab89c2cda440Structural heterogeneity in transmembrane amyloid precursor protein homodimer is a consequence of environmental selectionDominguez, Laura; Foster, Leigh; Meredith, Stephen C.; Straub, John E.; Thirumalai, D.Journal of the American Chemical Society (2014), 136 (27), 9619-9626CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)The 99-residue C-terminal fragment of amyloid precursor protein (C99), consisting of a single transmembrane (TM) helix, is known to form homodimers. Homodimers can be processed by γ-secretase to produce amyloid-β (Aβ) protein, which is implicated in Alzheimer's disease (AD). While knowledge of the structure of C99 homodimers is of great importance, exptl. NMR studies and simulations have produced varying structural models, including right-handed and left-handed coiled-coils. In order to investigate the structure of this crit. protein complex, simulations of the C9915-55 homodimer in POPC membrane bilayer and dodecylphosphocholine (DPC) surfactant micelle environments were performed using a multiscale approach that blends atomistic and coarse-grained models. The C9915-55 homodimer adopted a dominant right-handed coiled-coil topol. consisting of 3 characteristic structural states in a bilayer, only one of which was dominant in the micelle. This structural study, which provides a self-consistent framework for understanding a no. of expts., showed that the energy landscape of the C99 homodimer supported a variety of slowly interconverting structural states. The relative importance of any given state could be modulated through environmental selection realized by altering the membrane or micelle characteristics.
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571Carpenter, T.; Bond, P. J.; Khalid, S.; Sansom, M. S. Self-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channel Biophys. J. 2008, 95, 3790– 3801 DOI: 10.1529/biophysj.108.131078571https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXht1eksr3L&md5=ae97377b16d555433a7de894577a910aSelf-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channelCarpenter, Timothy; Bond, Peter J.; Khalid, Syma; Sansom, Mark S. P.Biophysical Journal (2008), 95 (8), 3790-3801CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of α-helixes and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained mol. dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helixes during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helixes. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 × 5 μs) were used to study the tetramerization of inserted M2 helixes. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This anal. reveals that the M2 tetramer has 2 × rotationally sym. packing of the helixes. The helixes form a left-handed bundle, with a helix tilt angle of ∼16°. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundle's stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.
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572Provasi, D.; Boz, M. B.; Johnston, J. M.; Filizola, M. Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-association PLoS Comput. Biol. 2015, 11, e1004148 DOI: 10.1371/journal.pcbi.1004148572https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xpt12msLk%253D&md5=42f9876cca764097f69ea7ba9c4b6a37Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-associationProvasi, Davide; Boz, Mustafa Burak; Johnston, Jennifer M.; Filizola, MartaPLoS Computational Biology (2015), 11 (3), e1004148/1-e1004148/21CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Substantial evidence in support of the formation of opioid receptor (OR) di-/oligomers suggests previously unknown mechanisms used by these proteins to exert their biol. functions. In an attempt to guide exptl. assessment of the identity of the minimal signaling unit for ORs, we conducted extensive coarse-grained (CG) mol. dynamics (MD) simulations of different combinations of the three major OR subtypes, i.e., μ-OR, δ-OR, and κ-OR, in an explicit lipid bilayer. Specifically, we ran multiple, independent MD simulations of each homomeric μ-OR/μ-OR, δ-OR/δ-OR, and κ-OR/κ-OR complex, as well as two of the most studied heteromeric complexes, i.e., δ-OR/μ-OR and δ-OR/κ-OR, to derive the preferred supramol. organization and dimer interfaces of ORs in a cell membrane model. These simulations yielded over 250 μs of accumulated data, which correspond to approx. 1 ms of effective simulated dynamics according to established scaling factors of the CG model we employed. Anal. of these data indicates similar preferred supramol. organization and dimer interfaces of ORs across the different receptor subtypes, but also important differences in the kinetics of receptor assocn. at specific dimer interfaces. We also investigated the kinetic properties of interfacial lipids, and explored their possible role in modulating the rate of receptor assocn. and in promoting the formation of filiform aggregates, thus supporting a distinctive role of the membrane in OR oligomerization and, possibly, signaling.
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573Johnston, J. M.; Wang, H.; Provasi, D.; Filizola, M. Assessing the relative stability of dimer interfaces in g protein-coupled receptors PLoS Comput. Biol. 2012, 8, e1002649 DOI: 10.1371/journal.pcbi.1002649573https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xht1CnsLjE&md5=c28c9e997026a1f11fef3a717e94e167Assessing the relative stability of dimer interfaces in G protein-coupled receptorsJohnston, Jennifer M.; Wang, Hao; Provasi, Davide; Filizola, MartaPLoS Computational Biology (2012), 8 (8), e1002649CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Considerable evidence has accumulated in recent years suggesting that G protein-coupled receptors (GPCRs) assoc. in the plasma membrane to form homo- and/or heteromers. Nevertheless, the stoichiometry, fraction and lifetime of such receptor complexes in living cells remain topics of intense debate. Motivated by exptl. data suggesting differing stabilities for homomers of the cognate human β1- and β2-adrenergic receptors, we have carried out approx. 160 μs of biased mol. dynamics simulations to calc. the dimerization free energy of crystal structure-based models of these receptors, interacting at two interfaces that have often been implicated in GPCR assocn. under physiol. conditions. Specifically, results are presented for simulations of coarse-grained (MARTINI-based) and atomistic representations of each receptor, in homodimeric configurations with either transmembrane helixes TM1/H8 or TM4/3 at the interface, in an explicit lipid bilayer. Our results support a definite contribution to the relative stability of GPCR dimers from both interface sequence and configuration. We conclude that β1- and β2-adrenergic receptor homodimers with TM1/H8 at the interface are more stable than those involving TM4/3 and that this might be reconciled with exptl. studies by considering a model of oligomerization in which more stable TM1 homodimers diffuse through the membrane, transiently interacting with other protomers at interfaces involving other TM helixes.
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574Ayton, G. S.; Voth, G. A. Multiscale simulation of protein mediated membrane remodeling Semin. Cell Dev. Biol. 2010, 21, 357– 362 DOI: 10.1016/j.semcdb.2009.11.011574https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXkvFKrt78%253D&md5=278f7c0439def895bf49a1fcf6d6f018Multiscale simulation of protein mediated membrane remodelingAyton, Gary S.; Voth, Gregory A.Seminars in Cell & Developmental Biology (2010), 21 (4), 357-362CODEN: SCDBFX; ISSN:1084-9521. (Elsevier Ltd.)A review. Proteins interacting with membranes can result in substantial membrane deformations and curvatures. This effect is known in its broadest terms as membrane remodeling. This review article will survey current multiscale simulation methodologies that have been employed to examine protein mediated membrane remodeling.
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575Genheden, S.; Essex, J. W. A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes J. Chem. Theory Comput. 2015, 11, 4749– 4759 DOI: 10.1021/acs.jctc.5b00469575https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhtlymsbvL&md5=bbe0cddc06d9c83f0007e997029c871fA Simple and Transferable All-Atom/Coarse-Grained Hybrid Model to Study Membrane ProcessesGenheden, Samuel; Essex, Jonathan W.Journal of Chemical Theory and Computation (2015), 11 (10), 4749-4759CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)An efficient all-atom/coarse-grained hybrid model is presented and applied to study membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, the efficiency is improved by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different time steps. Furthermore, the interaction between the atoms and the coarse-grained beads is fine-tuned by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calcn. of small-mol. partition coeffs. Finally, the model is applied to membrane peptides. The tilt angle is studied of the Walp23 and Kalp23 helixes in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent mols. or tabulated potentials, thus offering a novel, simple approach to study membrane processes.
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576Vorobyov, I.; Kim, I.; Chu, Z. T.; Warshel, A. Refining the treatment of membrane proteins by coarse-grained models Proteins: Struct., Funct., Genet. 2016, 84, 92– 117 DOI: 10.1002/prot.24958There is no corresponding record for this reference.
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577Kessel, A.; Shental-Bechor, D.; Haliloglu, T.; Ben-Tal, N. Interactions of hydrophobic peptides with lipid bilayers: Monte Carlo simulations with M2delta Biophys. J. 2003, 85, 3431– 3444 DOI: 10.1016/S0006-3495(03)74765-1There is no corresponding record for this reference.
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578Maddox, M. W.; Longo, M. L. A Monte Carlo study of peptide insertion into lipid bilayers: equilibrium conformations and insertion mechanisms Biophys. J. 2002, 82, 244– 263 DOI: 10.1016/S0006-3495(02)75391-5There is no corresponding record for this reference.
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579Milik, M.; Skolnick, J. Insertion of peptide chains into lipid membranes: an off-lattice Monte Carlo dynamics model Proteins: Struct., Funct., Genet. 1993, 15, 10– 25 DOI: 10.1002/prot.340150104There is no corresponding record for this reference.
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580Baumgartner, A. Insertion and hairpin formation of membrane proteins: a Monte Carlo study Biophys. J. 1996, 71, 1248– 1255 DOI: 10.1016/S0006-3495(96)79324-4There is no corresponding record for this reference.
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581Lopez, C. F.; Nielsen, S. O.; Srinivas, G.; Degrado, W. F.; Klein, M. L. Probing Membrane Insertion Activity of Antimicrobial Polymers via Coarse-grain Molecular Dynamics J. Chem. Theory Comput. 2006, 2, 649– 655 DOI: 10.1021/ct050298p581https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28XislCjt70%253D&md5=b8298b5565fe9160a797c73d67ed383fProbing Membrane Insertion Activity of Antimicrobial Polymers via Coarse-Grain Molecular DynamicsLopez, Carlos F.; Nielsen, Steven O.; Srinivas, Goundla; DeGrado, William F.; Klein, Michael L.Journal of Chemical Theory and Computation (2006), 2 (3), 649-655CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Knowledge of the mechanism of action of antimicrobial agents is crucial for the development of new compds. to combat microbial pathogens. To this end, computational studies on the interaction of known membrane-active antimicrobial polymers with phospholipid bilayers reveal spontaneous membrane insertion and cooperative action at low and high concns., resp. In late-stage attack, antimicrobials cross the membrane core and occasionally align to provide a stepping-stone pathway for water permeation; this suggests a possible new mode of action that does not depend on pore formation for transport to and across the inner leaflet. The computations rationalize the obsd. activity of a new class of antimicrobial compds.
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582Dryga, A.; Chakrabarty, S.; Vicatos, S.; Warshel, A. Realistic simulation of the activation of voltage-gated ion channels Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 3335– 3340 DOI: 10.1073/pnas.1121094109There is no corresponding record for this reference.
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583Kim, I.; Warshel, A. Coarse-grained simulations of the gating current in the voltage-activated Kv1.2 channel Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 2128– 2133 DOI: 10.1073/pnas.1324014111583https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXisFyis7Y%253D&md5=310e4cde327b90015d5a87e2a69714f1Coarse-grained simulations of the gating current in the voltage-activated Kv1.2 channelKim, Ilsoo; Warshel, AriehProceedings of the National Academy of Sciences of the United States of America (2014), 111 (6), 2128-2133CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)Quant. structure-based modeling of voltage activation of ion channels is very challenging. For example, it is very hard to reach converging results, by microscopic simulations while macroscopic treatments involve major uncertainties regarding key features. The current work overcomes some of the above challenges by using our recently developed coarse-grained (CG) model in simulating the activation of the Kv1.2 channel. The CG model has allowed us to explore problems that cannot be fully addressed at present by microscopic simulations, while providing insights on some features that are not usually considered in continuum models, including the distribution of the electrolytes between the membrane and the electrodes during the activation process and thus the phys. nature of the gating current. Here, we demonstrate that the CG model yields realistic gating charges and free energy landscapes that allow us to simulate the fluctuating gating current in the activation processes. Our ability to simulate the time dependence of the fast gating current allows us to reproduce the obsd. trend and provides a clear description of its relationship to the landscape involved in the activation process.
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584Rychkova, A.; Vicatos, S.; Warshel, A. On the energetics of translocon-assisted insertion of charged transmembrane helices into membranes Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 17598– 17603 DOI: 10.1073/pnas.1012207107584https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlartbrL&md5=8138efcd04f563ae9dbe13388e271ba2On the energetics of translocon-assisted insertion of charged transmembrane helices into membranesRychkova, Anna; Vicatos, Spyridon; Warshel, AriehProceedings of the National Academy of Sciences of the United States of America (2010), 107 (41), 17598-17603, S17598/1-S17598/5CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)The understanding of the mechanism of insertion of transmembrane (TM) helixes through the translocon presents a major open challenge. Although the exptl. information about the partition of the inserted helixes between the membrane and the soln. contains crucial information about this process, it is not clear how to ext. this information. In particular, it is not clear how to rationalize the small apparent insertion energy, ΔGapp, of an ionized residue in the center of a TM helix. Here we explore the nature of the insertion energies, asking what should be the value of these parameters if their measurements represent equil. conditions. This is done using a coarse-grained model with advanced electrostatic treatment. Estg. the energetics of ionized arginine of a TM helix in the presence of neighboring helixes or the translocon provides a rationale for the obsd. ΔGapp of ionized residues. It is concluded that the apparent insertion free energy of TM with charged residues reflects probably more than just the free energy of moving the isolate single helix from water into the membrane. The present approach should be effective not only in exploring the mechanism of the operation of the translocon but also for studies of other membrane proteins.
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585Alford, R. F.; Koehler Leman, J.; Weitzner, B. D.; Duran, A. M.; Tilley, D. C.; Elazar, A.; Gray, J. J. An Integrated Framework Advancing Membrane Protein Modeling and Design PLoS Comput. Biol. 2015, 11, e1004398 DOI: 10.1371/journal.pcbi.1004398585https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XkvVKit7o%253D&md5=4618d6db56c18c04a5dd63dd694241b9An integrated framework advancing membrane protein modeling and designAlford, Rebecca F.; Leman, Julia Koehler; Weitzner, Brian D.; Duran, Amanda M.; Tgilley, Drew C.; Elazar, Assaf; Gray, Jeffrey J.PLoS Computational Biology (2015), 11 (9), e1004398/1-e1004398/23CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)Membrane proteins are crit. functional mols. in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to det. their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resoln. structural refinement; (3) protein-protein docking; and (4) assembly of sym. protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.
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586Xu, X.; Yan, C.; Wohlhueter, R.; Ivanov, I. Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic Resolution Comput. Struct. Biotechnol. J. 2015, 13, 492– 503 DOI: 10.1016/j.csbj.2015.08.005586https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFOlsbvK&md5=e7eeba75dfdaf67a6e41ea26cd3c8f19Integrative Modeling of Macromolecular Assemblies from Low to Near-Atomic ResolutionXu, Xiaojun; Yan, Chunli; Wohlhueter, Robert; Ivanov, IvayloComputational and Structural Biotechnology Journal (2015), 13 (), 492-503CODEN: CSBJAC; ISSN:2001-0370. (Elsevier B.V.)While conventional high-resoln. techniques in structural biol. are challenged by the size and flexibility of many biol. assemblies, recent advances in low-resoln. techniques such as cryo-electron microscopy (cryo-EM) and small angle X-ray scattering (SAXS) have opened up new avenues to define the structures of such assemblies. By systematically combining various sources of structural, biochem. and biophys. information, integrative modeling approaches aim to provide a unified structural description of such assemblies, starting from high-resoln. structures of the individual components and integrating all available information from low-resoln. exptl. methods. In this review, we describe integrative modeling approaches, which use complementary data from either cryo-EM or SAXS. Specifically, we focus on the popular mol. dynamics flexible fitting (MDFF) method, which has been widely used for flexible fitting into cryo-EM maps. Second, we describe hybrid mol. dynamics, Rosetta Monte-Carlo and min. ensemble search (MES) methods that can be used to incorporate SAXS into pseudoat. structural models. We present concise descriptions of the two methods and their most popular alternatives, along with select illustrative applications to protein/nucleic acid assemblies involved in DNA replication and repair.
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587Latek, D.; Kolinski, A. CABS-NMR--De novo tool for rapid global fold determination from chemical shifts, residual dipolar couplings and sparse methyl-methyl NOEs J. Comput. Chem. 2011, 32, 536– 544 DOI: 10.1002/jcc.21640There is no corresponding record for this reference.
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588van der Schot, G.; Bonvin, A. M. Performance of the WeNMR CS-Rosetta3 web server in CASD-NMR J. Biomol. NMR 2015, 62, 497– 502 DOI: 10.1007/s10858-015-9942-7There is no corresponding record for this reference.
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589Rossi, P.; Shi, L.; Liu, G.; Barbieri, C. M.; Lee, H. W.; Grant, T. D.; Luft, J. R.; Xiao, R.; Acton, T. B.; Snell, E. H. A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta Proteins: Struct., Funct., Genet. 2015, 83, 309– 317 DOI: 10.1002/prot.24719There is no corresponding record for this reference.
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590Jang, R.; Wang, Y.; Xue, Z. D.; Zhang, Y. NMR data-driven structure determination using NMR-I-TASSER in the CASD-NMR experiment J. Biomol. NMR 2015, 62, 511– 525 DOI: 10.1007/s10858-015-9914-yThere is no corresponding record for this reference.
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591Zheng, W. Accurate flexible fitting of high-resolution protein structures into cryo-electron microscopy maps using coarse-grained pseudo-energy minimization Biophys. J. 2011, 100, 478– 488 DOI: 10.1016/j.bpj.2010.12.3680591https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXmsVGmtQ%253D%253D&md5=5ea50acf9c5eaeca1b8ee88e629333d9Accurate Flexible Fitting of High-Resolution Protein Structures into Cryo-Electron Microscopy Maps Using Coarse-Grained Pseudo-Energy MinimizationZheng, WenjunBiophysical Journal (2011), 100 (2), 478-488CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)Cryo-electron microscopy (cryo-EM) has been widely used to explore conformational states of large biomol. assemblies. The detailed interpretation of cryo-EM data requires the flexible fitting of a known high-resoln. protein structure into a low-resoln. cryo-EM map. To this end, we have developed what we believe is a new method based on a two-bead-per-residue protein representation, and a modified form of the elastic network model that allows large-scale conformational changes while maintaining pseudobonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified elastic network model energy with a cryo-EM-fitting score and a collision energy that penalizes steric collisions. Unlike previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled. We have validated our method for a diverse set of 10 pairs of protein structures using simulated cryo-EM maps with a range of resolns. and in the absence/presence of random noise. We have shown that our method is both accurate and efficient compared with alternative techniques, and its performance is robust to the addn. of random noise. Our method is also shown to be useful for the flexible fitting of three exptl. cryo-EM maps.
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592Grubisic, I.; Shokhirev, M. N.; Orzechowski, M.; Miyashita, O.; Tama, F. Biased coarse-grained molecular dynamics simulation approach for flexible fitting of X-ray structure into cryo electron microscopy maps J. Struct. Biol. 2010, 169, 95– 105 DOI: 10.1016/j.jsb.2009.09.010There is no corresponding record for this reference.
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593Zhang, J.; Baker, M. L.; Schroder, G. F.; Douglas, N. R.; Reissmann, S.; Jakana, J.; Dougherty, M.; Fu, C. J.; Levitt, M.; Ludtke, S. J. Mechanism of folding chamber closure in a group II chaperonin Nature 2010, 463, 379– 383 DOI: 10.1038/nature08701593https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXovVGgtQ%253D%253D&md5=ac6c036c116db4a4b4abdefceb2ed091Mechanism of folding chamber closure in a group II chaperoninZhang, Junjie; Baker, Matthew L.; Schroeder, Gunnar F.; Douglas, Nicholai R.; Reissmann, Stefanie; Jakana, Joanita; Dougherty, Matthew; Fu, Caroline J.; Levitt, Michael; Ludtke, Steven J.; Frydman, Judith; Chiu, WahNature (London, United Kingdom) (2010), 463 (7279), 379-383CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)Group II chaperonins are essential mediators of cellular protein folding in eukaryotes and archaea. These oligomeric protein machines, ∼1 megadalton, consist of two back-to-back rings encompassing a central cavity that accommodates polypeptide substrates. Chaperonin-mediated protein folding is critically dependent on the closure of a built-in lid, which is triggered by ATP hydrolysis. The structural rearrangements and mol. events leading to lid closure are still unknown. Here we report four single particle cryo-electron microscopy (cryo-EM) structures of Mm-cpn, an archaeal group II chaperonin, in the nucleotide-free (open) and nucleotide-induced (closed) states. The 4.3 Å resoln. of the closed conformation allowed construction of the first ever at. model directly from the single particle cryo-EM d. map, in which we were able to visualize the nucleotide and more than 70% of the side chains. The model of the open conformation was obtained by using the deformable elastic network modeling with the 8 Å resoln. open-state cryo-EM d. restraints. Together, the open and closed structures show how local conformational changes triggered by ATP hydrolysis lead to an alteration of intersubunit contacts within and across the rings, ultimately causing a rocking motion that closes the ring. Our analyses show that there is an intricate and unforeseen set of interactions controlling allosteric communication and inter-ring signaling, driving the conformational cycle of group II chaperonins. Beyond this, we anticipate that our methodol. of combining single particle cryo-EM and computational modeling will become a powerful tool in the detn. of at. details involved in the dynamic processes of macromol. machines in soln.
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594DiMaio, F.; Song, Y.; Li, X.; Brunner, M. J.; Xu, C.; Conticello, V.; Egelman, E.; Marlovits, T. C.; Cheng, Y.; Baker, D. Atomic-accuracy models from 4.5-A cryo-electron microscopy data with density-guided iterative local refinement Nat. Methods 2015, 12, 361– 365 DOI: 10.1038/nmeth.3286594https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MrnslOksA%253D%253D&md5=a019ca4dd689f2321c103867d74db255Atomic-accuracy models from 4.5-ÅA cryo-electron microscopy data with density-guided iterative local refinementDiMaio Frank; Song Yifan; Baker David; Song Yifan; Li Xueming; Cheng Yifan; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Brunner Matthias J; Marlovits Thomas; Xu Chunfu; Conticello Vincent; Egelman Edward; Baker DavidNature methods (2015), 12 (4), 361-365 ISSN:.We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-ÅA resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.
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595Demers, J. P.; Habenstein, B.; Loquet, A.; Kumar Vasa, S.; Giller, K.; Becker, S.; Baker, D.; Lange, A.; Sgourakis, N. G. High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy Nat. Commun. 2014, 5, 4976 DOI: 10.1038/ncomms5976595https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXksVeqsr8%253D&md5=6a65afb2807b2b58e2eb04b3780cae35High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopyDemers, Jean-Philippe; Habenstein, Birgit; Loquet, Antoine; Kumar Vasa, Suresh; Giller, Karin; Becker, Stefan; Baker, David; Lange, Adam; Sgourakis, Nikolaos G.Nature Communications (2014), 5 (), 4976CODEN: NCAOBW; ISSN:2041-1723. (Nature Publishing Group)We introduce a general hybrid approach for detg. the structures of supramol. assemblies. Cryo-electron microscopy (cryo-EM) data define the overall envelope of the assembly and rigid-body orientation of the subunits while solid-state NMR (ssNMR) chem. shifts and distance constraints define the local secondary structure, protein fold and inter-subunit interactions. Finally, Rosetta structure calcns. provide a general framework to integrate the different sources of structural information. Combining a 7.7-Å cryo-EM d. map and 996 ssNMR distance constraints, the structure of the type-III secretion system needle of Shigella flexneri is detd. to a precision of 0.4 Å. The calcd. structures are cross-validated using an independent data set of 691 ssNMR constraints and scanning transmission electron microscopy measurements. The hybrid model resolves the conformation of the non-conserved N terminus, which occupies a protrusion in the cryo-EM d., and reveals conserved pore residues forming a continuous pattern of electrostatic interactions, thereby suggesting a mechanism for effector protein translocation.
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596Esquivel-Rodriguez, J.; Kihara, D. Computational methods for constructing protein structure models from 3D electron microscopy maps J. Struct. Biol. 2013, 184, 93– 102 DOI: 10.1016/j.jsb.2013.06.008There is no corresponding record for this reference.
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597Shrestha, R.; Berenger, F.; Zhang, K. Y. Accelerating ab initio phasing with de novo models Acta Crystallogr., Sect. D: Biol. Crystallogr. 2011, 67, 804– 812 DOI: 10.1107/S090744491102779XThere is no corresponding record for this reference.
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598Shrestha, R.; Simoncini, D.; Zhang, K. Y. Error-estimation-guided rebuilding of de novo models increases the success rate of ab initio phasing Acta Crystallogr., Sect. D: Biol. Crystallogr. 2012, 68, 1522– 1534 DOI: 10.1107/S0907444912037961There is no corresponding record for this reference.
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599Yang, S.; Park, S.; Makowski, L.; Roux, B. A rapid coarse residue-based computational method for x-ray solution scattering characterization of protein folds and multiple conformational states of large protein complexes Biophys. J. 2009, 96, 4449– 4463 DOI: 10.1016/j.bpj.2009.03.036599https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXpsFOrtrg%253D&md5=a84231b3eabd6b83a079a492099ecf81A rapid coarse residue-based computational method for X-ray solution scattering characterization of protein folds and multiple conformational states of large protein complexesYang, Sichun; Park, Sanghyun; Makowski, Lee; Roux, BenoitBiophysical Journal (2009), 96 (11), 4449-4463CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)We present a coarse residue-based computational method to rapidly compute the soln. scattering profile from a protein with dynamical fluctuations. The method is built upon a coarse-grained (CG) representation of the protein. This CG representation takes advantage of the intrinsic low-resoln. and CG nature of soln. scattering data. It allows rapid scattering detn. from a large no. of conformations that can be extd. from CG simulations to obtain scattering characterization of protein conformations. The method includes several important elements, effective residue structure factors derived from the Protein Data Bank, explicit treatment of water mols. in the hydration layer at the surface of the protein, and an ensemble av. of scattering from a variety of appropriate conformations to account for macromol. flexibility. This simplified method is calibrated and illustrated to accurately reproduce the exptl. scattering curve of Hen egg white lysozyme. We then illustrated the applications of this CG method by computing the soln. scattering patterns of several representative protein folds and multiple conformational states. The results suggest that soln. scattering data, when combined with the reliable computational method that we developed, show great potential for a better structural description of multidomain complexes in different functional states, and for recognizing structural folds when sequence similarity to a protein of known structure is low.
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600Stovgaard, K.; Andreetta, C.; Ferkinghoff-Borg, J.; Hamelryck, T. Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models BMC Bioinf. 2010, 11, 429 DOI: 10.1186/1471-2105-11-429600https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC3cjosl2rsQ%253D%253D&md5=ef71c9a203195bb3ce614b39e7cb55f3Calculation of accurate small angle X-ray scattering curves from coarse-grained protein modelsStovgaard Kasper; Andreetta Christian; Ferkinghoff-Borg Jesper; Hamelryck ThomasBMC bioinformatics (2010), 11 (), 429 ISSN:.BACKGROUND: Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS) is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. RESULTS: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. CONCLUSION: We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data.
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601Hagita, K.; McGreevy, R. L.; Arai, T.; Inui, M.; Matsuda, K.; Tamura, K. First example of multi-scale reverse Monte Carlo modeling for small-angle scattering experimental data using reverse mapping from coarse-grained particles to atoms J. Phys.: Condens. Matter 2010, 22, 404215 DOI: 10.1088/0953-8984/22/40/404215601https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlGls7vP&md5=9188c5d853dba7a768075eced225957dFirst example of multi-scale reverse Monte Carlo modeling for small-angle scattering experimental data using reverse mapping from coarse-grained particles to atomsHagita, K.; McGreevy, R. L.; Arai, T.; Inui, M.; Matsuda, K.; Tamura, K.Journal of Physics: Condensed Matter (2010), 22 (40), 404215/1-404215/11CODEN: JCOMEL; ISSN:0953-8984. (Institute of Physics Publishing)We propose a new method for multi-scale reverse Monte Carlo (RMC) modeling of small-angle scattering data using reverse mapping from coarse-grained particles to atoms in cases where scale sepn. cannot be assumed. For efficient RMC anal. for small-angle scattering data, it is important to det. a large scale structure with the lowest possible computing cost. In order to find this large scale structure, a method using coarse-grained particles instead of atoms is suitable. As our first example, we examine the structure of expanded fluid Hg near the crit. point. For this system, small-angle x-ray scattering (SAXS) data and wide-angle x-ray diffraction data (XRD) are obsd. in the same thermodn. state. First, RMC anal. using coarse-grained particles for SAXS data is performed. Second, RMC anal. for SAXS and XRD data is performed with the replacement of a coarse-grained particle by an ad hoc cluster of several Hg atoms. In the present study, we have detd. that the size of one coarse-grained particle corresponds to ten Hg atoms. The no. d. for the coarse-grained particles is set to one-tenth the actual no. d. of atoms and the cutoff length is three times (6.9 Å) that of Hg atoms (2.3 Å). As a result, this approach is found to be successful and the computing cost of RMC anal. can be reduced.
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602Haxton, T. K. High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained Sites J. Chem. Theory Comput. 2015, 11, 1244– 1254 DOI: 10.1021/ct500881x602https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXitlKksbw%253D&md5=be0d6906322d0c0dc6ab026ab5e8d8f2High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained SitesHaxton, Thomas K.Journal of Chemical Theory and Computation (2015), 11 (3), 1244-1254CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)We introduce a method to bring nearly atomistic resoln. to coarse-grained models, and we apply the method to proteins. Using a small no. of coarse-grained sites (about one per eight atoms) but assigning an independent three-dimensional orientation to each site, we preferentially integrate out stiff degrees of freedom (bond lengths and angles, as well as dihedral angles in rings) that are accurately approximated by their av. values, while retaining soft degrees of freedom (unconstrained dihedral angles) mostly responsible for conformational variability. We demonstrate that our scheme retains nearly atomistic resoln. by mapping all exptl. protein configurations in the Protein Data Bank onto coarse-grained configurations and then anal. backmapping those configurations back to all-atom configurations. This roundtrip mapping throws away all information assocd. with the eliminated (stiff) degrees of freedom except for their av. values, which we use to construct optimal backmapping functions. Despite the 4:1 redn. in the no. of degrees of freedom, we find that heavy atoms move only 0.051 Å on av. during the roundtrip mapping, while hydrogens move 0.179 Å on av., an unprecedented combination of efficiency and accuracy among coarse-grained protein models. We discuss the advantages of such a high-resoln. model for parametrizing effective interactions and accurately calcg. observables through direct or multiscale simulations.
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603Kang, M.; Roberts, C.; Cheng, Y.; Chang, C. E. Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 Protease J. Chem. Theory Comput. 2011, 7, 3438– 3446 DOI: 10.1021/ct2004885603https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFOitLfE&md5=38bd8818a7ec33b4fbb6ff9f86018972Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 ProteaseKang, Myungshim; Roberts, Christopher; Cheng, Yuhui; Chang, Chia-en A.Journal of Chemical Theory and Computation (2011), 7 (10), 3438-3446CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)Most biol. processes are initiated or mediated by the assocn. of ligands and proteins. This work studies multistep, ligand-protein assocn. processes by Brownian dynamics simulations with coarse-grained models for HIV-1 protease (HIVp) and its neutral ligands. We report the av. assocn. times when the ligand concn. is 100 μM. The influence of crowding on the simulated binding time was also studied. HIVp has flexible loops that serve as a gate during the ligand binding processes. It is believed that the flaps are partially closed most of the time in its free state. To accelerate our simulations, we fixed a part of the HIVp and reparameterized our coarse-grained model, using atomistic mol. dynamics simulations, to reproduce the "gating" motions of HIVp. HIVp-ligand interactions changed the gating behavior of HIVp and helped ligands diffuse on HIVp surface to accelerate binding. The structural adjustment of the ligand toward its final stable state was the limiting step in the binding processes, which is highly system dependent. The intermol. attraction between the ligands and crowder proteins contributes the most to the crowding effects. The results highlight broader implications in recognition pathways under more complex environment that considers mol. dynamics and conformational changes. This work brings insights into ligand-protein assocns. and is helpful in the design of targeted ligands.
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604Negami, T.; Shimizu, K.; Terada, T. Protein-Ligand Binding Simulation with the Martini Coarse-Grained Force Field. Biophys. J. 2014, 106, 609a. DOI: 10.1016/j.bpj.2013.11.3370There is no corresponding record for this reference.
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605Ruiz-Herrero, T.; Estrada, J.; Guantes, R.; Miguez, D. G. A tunable coarse-grained model for ligand-receptor interaction PLoS Comput. Biol. 2013, 9, e1003274 DOI: 10.1371/journal.pcbi.1003274There is no corresponding record for this reference.
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606de Jong, D. H.; Baoukina, S.; Ingolfsson, H. I.; Marrink, S. J. Martini straight: Boosting performance using a shorter cutoff and GPUs Comput. Phys. Commun. 2016, 199, 1– 7 DOI: 10.1016/j.cpc.2015.09.014606https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhs1Krtb%252FJ&md5=9bb06db6dbe3171eb07bf7509105fc67Martini straight: Boosting performance using a shorter cutoff and GPUsde Jong, Djurre H.; Baoukina, Svetlana; Ingolfsson, Helgi I.; Marrink, Siewert J.Computer Physics Communications (2016), 199 (), 1-7CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier B.V.)In mol. dynamics simulations, sufficient sampling is of key importance and a continuous challenge in the field. The coarse grain Martini force field has been widely used to enhance sampling. In its original implementation, this force field applied a shifted Lennard-Jones potential for the non-bonded van der Waals interactions, to avoid problems related to a relatively short cutoff. Here we investigate the use of a straight cutoff Lennard-Jones potential with potential modifiers. Together with a Verlet neighbor search algorithm, the modified potential allows the use of GPUs to accelerate the computations in Gromacs. We find that this alternative potential has little influence on most of the properties studied, including partitioning free energies, bulk liq. properties and bilayer properties. At the same time, energy conservation is kept within reasonable bounds. We conclude that the newly proposed straight cutoff approach is a viable alternative to the std. shifted potentials used in Martini, offering significant speedup even in the absence of GPUs.
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607Lettieri, S.; Zuckerman, D. M. Accelerating molecular Monte Carlo simulations using distance and orientation-dependent energy tables: tuning from atomistic accuracy to smoothed ″coarse-grained″ models J. Comput. Chem. 2012, 33, 268– 275 DOI: 10.1002/jcc.21970There is no corresponding record for this reference.
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608Tunbridge, I.; Best, R. B.; Gain, J.; Kuttel, M. M. Simulation of Coarse-Grained Protein-Protein Interactions with Graphics Processing Units J. Chem. Theory Comput. 2010, 6, 3588– 3600 DOI: 10.1021/ct1003884608https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXht1CmtLnE&md5=25836ea416b8414aab7135646358e849Simulation of Coarse-Grained Protein-Protein Interactions with Graphics Processing UnitsTunbridge, Ian; Best, Robert B.; Gain, James; Kuttel, Michelle M.Journal of Chemical Theory and Computation (2010), 6 (11), 3588-3600CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors report a hybrid parallel central and graphics processing units (CPU-GPU) implementation of a coarse-grained model for replica exchange Monte Carlo (REMC) simulations of protein assemblies. The authors describe the design, optimization, validation, and benchmarking of their algorithms, particularly the parallelization strategy, which is specific to the requirements of GPU hardware. Performance evaluation of the authors' hybrid implementation shows scaled speedup as compared to a single-core CPU; ref. simulations of small 100 residue proteins have a modest speedup of 4, while large simulations with thousands of residues are up to 1400 times faster. Importantly, the combination of coarse-grained models with highly parallel GPU hardware vastly increases the length- and time-scales accessible for protein simulation, making it possible to simulate much larger systems of interacting proteins than have previously been attempted. As a first step toward the simulation of the assembly of an entire viral capsid, the authors have demonstrated that the chosen coarse-grained model, together with REMC sampling, is capable of identifying the correctly bound structure, for a pair of fragments from the human hepatitis B virus capsid. The authors' parallel soln. can easily be generalized to other interaction functions and other types of macromols. and has implications for the parallelization of similar N-body problems that require random access lookups.
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609Czaplewski, C.; Liwo, A.; Makowski, M.; Oldziej, S.; Scheraga, H. A. Coarse-Grained Models of Proteins: Theory and Applications Multiscale Approaches to Protein Modeling 2011, 35– 83 DOI: 10.1007/978-1-4419-6889-0_3There is no corresponding record for this reference.
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610Thorpe, I. F.; Goldenberg, D. P.; Voth, G. A. Exploration of transferability in multiscale coarse-grained peptide models J. Phys. Chem. B 2011, 115, 11911– 11926 DOI: 10.1021/jp204455gThere is no corresponding record for this reference.
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611Potoyan, D. A.; Savelyev, A.; Papoian, G. A. Recent successes in coarse-grained modeling of DNA Wires Comput. Mol. Sci. 2013, 3, 69– 83 DOI: 10.1002/wcms.1114There is no corresponding record for this reference.
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612Boniecki, M. J.; Lach, G.; Dawson, W. K.; Tomala, K.; Lukasz, P.; Soltysinski, T.; Rother, K. M.; Bujnicki, J. M. SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction Nucleic Acids Res. 2016, 44, e63 DOI: 10.1093/nar/gkv1479612https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhs12qt73P&md5=f791ee4418e04676d97866fae0e6214aSimRNA: a coarse-grained method for RNA folding simulations and 3D structure predictionBoniecki, Michal J.; Lach, Grzegorz; Dawson, Wayne K.; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M.; Bujnicki, Janusz M.Nucleic Acids Research (2016), 44 (7), e63/1-e63/12CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)RNA mols. play fundamental roles in cellular processes. Their function and interactions with other biomols. are dependent on the ability to form complex three-dimensional (3D) structures. However, exptl. detn. of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approx. the energy and identify conformations that correspond to biol. relevant structures. SimRNA can fold RNA mols. using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use addnl. restraints, derived from exptl. or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures.
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613Hyeon, C.; Denesyuk, N. A.; Thirumalai, D. Development and Applications of Coarse-Grained Models for RNA Isr. J. Chem. 2014, 54, 1358– 1373 DOI: 10.1002/ijch.201400029613https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhsVSnurrN&md5=ffd7c390b827112b614cfb1dad168c05Development and Applications of Coarse-Grained Models for RNAHyeon, Changbong; Denesyuk, Natalia A.; Thirumalai, D.Israel Journal of Chemistry (2014), 54 (8-9), 1358-1373CODEN: ISJCAT; ISSN:0021-2148. (Wiley-VCH Verlag GmbH & Co. KGaA)A review. In contrast to proteins, much less attention has been focused on the development of computational models for describing RNA mols., which are being recognized as playing key roles in many cellular functions. Current atomically detailed force fields are not accurate enough to capture the properties of even simple nucleic acid constructs. In this article, we review our efforts to develop coarse-grained (CG) models that capture the underlying physics for the particular length scale of interest. Two models are discussed. One of them is the three interaction site (TIS) model, in which each nucleotide is represented by three beads corresponding to sugar, phosphate, and base. The other is the self-organized polymer (SOP) model, in which each nucleotide is represented as a single interaction center. Applications of the TIS model to study the complexity of hairpin formation and the effects of crowding in a shifting equil. between two conformations in human telomerase pseudoknot are described. The work on crowding illustrates a direct link to the activity of telomerase. We use the SOP model to describe the response of the Tetrahymena ribozyme to force. The simulated unfolding pathways agree well with single mol. pulling expts. We also review predictions for the unfolding pathways for the Azoarcus ribozyme. The success of the CG applications to describe dynamics in RNA gives hope that more complex processes involving RNA-protein interactions can be tackled using variants of the proposed models.
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614Lopez, C. A.; Rzepiela, A. J.; de Vries, A. H.; Dijkhuizen, L.; Hunenberger, P. H.; Marrink, S. J.; Martini Coarse-Grained Force Field: Extension to Carbohydrates J. Chem. Theory Comput. 2009, 5, 3195– 3210 DOI: 10.1021/ct900313w614https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhtlChur%252FF&md5=e358a3bd8f010d95846c94836af9cc54Martini Coarse-Grained Force Field: Extension to CarbohydratesLopez, Cesar A.; Rzepiela, Andrzej J.; de Vries, Alex H.; Dijkhuizen, Lubbert; Hunenberger, Philippe H.; Marrink, Siewert J.Journal of Chemical Theory and Computation (2009), 5 (12), 3195-3210CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)The authors present an extension of the Martini coarse-grained force field to carbohydrates. The parametrization follows the same philosophy as was used previously for lipids and proteins, focusing on the reprodn. of partitioning free energies of small compds. between polar and nonpolar phases. The carbohydrate building blocks considered are the monosaccharides glucose and fructose and the disaccharides sucrose, trehalose, maltose, cellobiose, nigerose, laminarabiose, kojibiose, and sophorose. Bonded parameters for these saccharides are optimized by comparison to conformations sampled with an atomistic force field, in particular with respect to the representation of the most populated rotameric state for the glycosidic bond. Application of the new coarse-grained carbohydrate model to the oligosaccharides amylose and Curdlan shows a preservation of the main structural properties with 3 orders of magnitude more efficient sampling than the atomistic counterpart. Finally, the authors investigate the cryo- and anhydro-protective effect of glucose and trehalose on a lipid bilayer and find a strong decrease of the melting temp., in good agreement with both exptl. findings and atomistic simulation studies.
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615Lopez, C. A.; Bellesia, G.; Redondo, A.; Langan, P.; Chundawat, S. P. S.; Dale, B. E.; Marrink, S. J.; Gnanakaran, S. MARTINI Coarse-Grained Model for Crystalline Cellulose Microfibers J. Phys. Chem. B 2015, 119, 465– 473 DOI: 10.1021/jp5105938615https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhvFOjs7bI&md5=4cbec8abad57d8fe1ac7db96a932d50aMARTINI Coarse-Grained Model for Crystalline Cellulose MicrofibersLopez, Cesar A.; Bellesia, Giovanni; Redondo, Antonio; Langan, Paul; Chundawat, Shishir P. S.; Dale, Bruce E.; Marrink, Siewert J.; Gnanakaran, S.Journal of Physical Chemistry B (2015), 119 (2), 465-473CODEN: JPCBFK; ISSN:1520-5207. (American Chemical Society)Com.-scale biofuel prodn. requires a deep understanding of the structure and dynamics of its principal target: cellulose. However, an accurate description and modeling of this carbohydrate structure at the mesoscale remains elusive, particularly because of its overwhelming length scale and configurational complexity. We have derived a set of MARTINI coarse-grained force field parameters for the simulation of cryst. cellulose fibers. The model is adapted to reproduce different physicochem. and mech. properties of native cellulose Iβ. The model is able not only to handle a transition from cellulose Iβ to another cellulose allomorph, cellulose IIII, but also to capture the phys. response to temp. and mech. bending of longer cellulose nanofibers. By developing the MARTINI model of a solid cellulose cryst. fiber from the building blocks of a sol. cellobiose coarse-grained model, we have provided a systematic way to build MARTINI models for other cryst. biopolymers.
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Supporting Information
The authors declare no competing financial interest.
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