ACS Publications. Most Trusted. Most Cited. Most Read
Quick View

OR SEARCH CITATIONS

My Activity
Publications
CONTENT TYPES

Figure 1Loading Img
Download Hi-Res ImageDownload to MS-PowerPointCite This:ACS Omega 2021, 6, 23, 14748-14764
RETURN TO ISSUEPREVArticleNEXT

In Silico Repositioning of Dopamine Modulators with Possible Application to Schizophrenia: Pharmacophore Mapping, Molecular Docking and Molecular Dynamics Analysis

  • Melissa Mejia-Gutierrez*
    Melissa Mejia-Gutierrez
    Faculty of Natural and Exact Sciences, Department of Chemistry, and School of Basic Sciences, Department of Physiological Sciences, Faculty of Health, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia
    *Email: [email protected]. Phone: +57-2-3212100.
    More by Melissa Mejia-Gutierrez
    Orcidhttps://orcid.org/0000-0002-0372-4413
  • , 
  • Bryan D. Vásquez-Paz
    Bryan D. Vásquez-Paz
    Faculty of Natural and Exact Sciences, Department of Chemistry, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia
    More by Bryan D. Vásquez-Paz
    Orcidhttps://orcid.org/0000-0002-1253-3504
  • , 
  • Leonardo Fierro
    Leonardo Fierro
    Faculty of Health, School of Basic Sciences, Department of Physiological Sciencesh, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia
    More by Leonardo Fierro
  • , and 
  • Julio R. Maza
    Julio R. Maza
    Faculty of Basic Sciences, Department of Chemistry, Laboratory and Research group - Organic Chemistry and Biomedical Group, Universidad del Atlántico, 081001 Puerto Colombia, Colombia
    More by Julio R. Maza
    Orcidhttps://orcid.org/0000-0003-0334-1997
Cite this: ACS Omega 2021, 6, 23, 14748–14764
Publication Date (Web):June 1, 2021
https://doi.org/10.1021/acsomega.0c05984

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0.
  • Open Access

Article Views

5715

Altmetric

-

Citations

2
LEARN ABOUT THESE METRICS
PDF (8 MB)
Get e-Alerts
Supporting Info (2)»
SUBJECTS:

Abstract

High Resolution Image
Download MS PowerPoint Slide

We have performed theoretical calculations with 70 drugs that have been considered in 231 clinical trials as possible candidates to repurpose drugs for schizophrenia based on their interactions with the dopaminergic system. A hypothesis of shared pharmacophore features was formulated to support our calculations. To do so, we have used the crystal structure of the D2-like dopamine receptor in complex with risperidone, eticlopride, and nemonapride. Linagliptin, citalopram, flunarizine, sildenafil, minocycline, and duloxetine were the drugs that best fit with our model. Molecular docking calculations, molecular dynamics outcomes, blood-brain barrier penetration, and human intestinal absorption were studied and compared with the results. From the six drugs selected in the shared pharmacophore features input, flunarizine showed the best docking score with D2, D3, and D4 dopamine receptors and had high stability during molecular dynamics simulations. Flunarizine is a frequently used medication to treat migraines and vertigo. However, its antipsychotic properties have been previously hypothesized, particularly because of its possible ability to block the D2 dopamine receptors.

This publication is licensed under

CC-BY-NC-ND 4.0.
  • cc licence
  • by licence
  • nc licence
  • nd licence

Introduction

ARTICLE SECTIONS
Jump To
Drug repurposing (also known as drug repositioning, rediscovering, rescuing, or redirecting) investigates whether it is possible to develop new therapeutic applications for drugs currently in use. (1) It reduces time, production costs, and stages of development of new drugs, all of which usually take over 10–15 years and represent an investment of around several hundred million dollars. (2) Interestingly, psychopharmacology is one of the medical areas where drug repositioning has more potential to be applied. New therapeutic applications of some drugs and formulations currently in use were observed during their clinical administration to treat other diseases. This situation has occurred relatively frequently with medicaments used in neuropsychiatry, strengthening the approach to drug reuse in this field of medicine. (3)
Over the last years, schizophrenia patients have been markedly characterized, (4) and the analyses have been centered on one of the meaningful approaches, a sharp increase in presynaptic dopamine function. Therefore, targeting dopaminergic neurotransmission is continuously used for treating and approaching schizophrenia, aside from other mental disorders and psychiatric illnesses such as Tourette’s syndrome, Parkinsonian disorders, Huntington’s disease, attention deficit hyperactivity disorder (ADHD), and bipolar disorder. (5) The physiological cues of dopamine are intervened by five intimately related yet functionally distinct G protein-coupled receptors (GPCRs) that are sorted based on their sequence and pharmacological similitudes in two main subfamilies: the D1-class receptor (D1 and D5) and the D2-class receptor (D2, D3, and D4) receptors. (6) When dopamine (DA) is liberated from presynaptic axonal terminals, it might interact with D1-like receptors (D1Rs), which are positively linked to the production of cAMP and the stimulation of adenylyl cyclases, or with D2-like receptors (D2Rs), whose activation inhibits adenylyl cyclases and interrupt the generation of cAMP. Additionally, Ca2+ levels and several intracellular signaling processes are notably modulated by DRs. Neuronal activity and synaptic plasticity, for instance, are outstandingly affected by DA and in large part by its dopamine receptor (DR) binding.
The dopamine receptor dysfunction is, ostensibly, associated with human disorders in a vast number of multiple genetic studies. Variants in the D2, D3, and D4 dopamine receptor (DR) genes have been linked to schizophrenia or involved in the reaction to antipsychotic medications. These divergent variants have undeniably led to a more complex understanding of psychopharmacology. Haloperidol, for example, is relatively selective for dopamine D2, D3, and D4 receptors, whereas the pharmacology of olanzapine looks intricate. (6−8)
Schizophrenia is a neurodevelopmental disorder with pronounced disorders of thought, emotional disbalances, hallucinations, and mood changes. The annual prevalence is around 1.4 to 4.6 per 1000 inhabitants with an incidence between 0.16 and 0.42 cases per 1000 inhabitants. (9) The most prominent antipsychotic drugs used over the long term have been clozapine, aripiprazole, or olanzapine even though some of these drugs have little to null specificity with multiple side effects, and some could even contribute to a dramatic decline in the production of white blood cells. In addition, orthostatic hypotension, weight gain, and other extrapyramidal symptoms are commonly diagnosed in patients prescribed such medication. (10) Therefore, to address the gaps in the treatment, it is necessary to implement new drugs to minimize the known side effects and also to try to promote drug adherence. Evidence from systematic analysis has stated that patients with schizophrenia, generally, are over-sensitive to dopamine psychostimulants due to the considerable proportion of active D2-like dopamine receptors. As a result of this circumstance, psychotic reactions have been studied as an integrated state of D2 (high) dopamine supersensitivity. (11,12)
In some former reports, certain advancements have emerged in computational studies applied to drug repositioning in schizophrenia. Given the great value and the vast spectrum of the in silico tools used to understand drug design, it is not a coincidence that many new genome-wide associations, (13) machine learning approaches, (14) and interactome relations (15) are becoming so widespread in the later years. The central objective of the present study does open the door to far analysis of information, which is already conserved in one of the largest publicly available clinical trials databases (ClinicalTrials.gov, 18 January 2018 data freeze). The aim is to show how the clinical trials database information could be used and studied with cheminformatics techniques. In a recent revision of the abovementioned database, emerging data was collected and reviewed for about 88 repurposing candidates, stated across 231 clinical trials for their therapeutic actions in schizophrenia. (1) These compounds were tested and reported in terms of their pharmacological effects. They were included with at least one primary intervention using a regulatory-approved drug that is not already designated for schizophrenia but assessed in a target of schizophrenia. They were designed in categories depending on their therapeutic use in schizophrenia (nootropic agents 25%, hormonal agents 17%, monoamine neurotransmitters agents 15%, compounds that suppress inflammation 14%, compounds with anti-convulsant/mood disorders/sedative action 12%, metabolic/cardiovascular 11%, infectious disease 3%, and others 3%). The present study aims to perform computational calculations with 70 of these drugs (chosen for not being proteins or antibodies) interacting with D2-like receptors regarding the hypothesis of the dopaminergic system in schizophrenia.
The repurposing candidates were retrieved and then analyzed with different robust computational methodologies. To test and predict the conformations of the ligands when interacting with receptors, docking programs can mimic a similar structure to the one observed in crystallographic protein/ligand complexes. It was assumed that some limitations would arise from the attempt to rank these conformations as the top docking solutions in conjunction with the fact that it would promote an incomplete understanding of the pharmacology of dopamine receptors and human diseases. To tackle these issues, virtual screenings based on the best pharmacophore matching and molecular dynamics simulation were the leading centers of the present study. (16−19) A set of crystallographic ligands already bonded to DRs were inspected, and those certain frequent 3D shared pharmacophore features were grouped and then tested on the molecules identified as repurposing dopamine modulators. (20)
Selectively targeting DRs has been widely researched by computational methods such as molecular dynamics, pharmacophore model, molecular docking, and machine learning. (21−23) Molecular docking is guided by the target, where each compound is coupled and assessed against the characterized target structure (e.g., protein, DNA, RNA), whereas a pharmacophore model could be assembled whether or not in the presence of the biomolecular structure and by selecting the key points of the interaction, such as chemical, steric, and electronic features required on the compound. Each of these techniques has some attributes and scopes that make them profitable and correlative resources to search for molecules that inhibit or modulate different molecular targets in a disease. (24) One of the most highlighted merits of molecular dynamics is the possibility of examination of thermodynamic properties and other molecules that are determining on the free protein binding sites, as well as it would explain the evolution through the time of the system subjected to forces between atoms and molecules for a fixed period, to characterize at the atomic level, the ligand–target conformational and energetic landscapes.
Pharmacophore models coupled to molecular docking and molecular dynamics have been reported in many drug repositioning and targeting studies. (25−27) Kagami et al. (28) identified an inhibitor of a promising target of the human infection malaria, the purine nucleoside phosphorylase of Plasmodium falciparum, using these techniques. Two inhibitors were proposed and supported using molecular docking, shared pharmacophore features, and molecular dynamics simulation. In another study by Kumar et al., (29) the protein–ligand interactions of different complexes were applied to Alzheimer’s disease, and in silico repositioning of antipsychotic drugs was pointed out. Dilly et al. (30) conducted in silico studies of naproxen and its analogs to demonstrate that they could have antiviral activity against the influenza A virus. Teli and Rajanikant (31) performed in silico repositioning using drugs approved by the FDA as inhibitors of PHDs, which are compounds of the family of dioxygenases called HIF prolyl-4-hydroxylases. Other examples include computational methods, which have been increasing as the first strategies on the drug design process in pharmaceutical companies, making them almost mandatory during the procedure. (32−35)
Blood–brain barrier (BBB) penetration and gastrointestinal (GI) absorption are prime factors in neurological drugs, and these two properties are related to lipophilicity (WLOGP) and polarity (tPSA) molecular structure computation. (36) Since the in vitro and in vivo BBB tests are difficult, time-consuming, and low cost, both physicochemical features (WLOGP and tPSA) were calculated as predictive models to mimic the behavior of the drug within the human body, especially to determine a prediction of BBB penetration and possible side effects with the metabolism of the compounds tested. The following physicochemical-related structural properties are canonical and must be met by any new drug: (i) lipophilia; XLOGP3 [−0.7, +5.0], (ii) molecular weight [150–500] (g/mol), (iii) topological polar surface area (TPSA) [20, 130] Å2, (iv) solubility (log S) < 6, (v) carbons in sp3 hybridization >0.25, and (vi) flexibility <9 rotatable bonds. (104) The compounds that fall within the previously mentioned ranges will probably have good oral bioavailability, i.e., because of their structural configuration it will be easier for them to reach their therapeutic target (channels, transporters, receptors, or other protein macromolecules) in their active form.

Results and Discussion

ARTICLE SECTIONS
Jump To
The increase in new cases of schizophrenia and its strong complications have shown why it is classified among one of the leading causes of long-term disability. (37) Typically it emerges in late adolescence and late adulthood, which is why, although huge efforts have been overcome to prolong the life expectancy of people with schizophrenia, currently there is no effective way to prevent the cognitive impairments, and the causes are still unknown. Amid advancements in applied schizophrenia research, yet it is not well understood which should be the main focus, for example, environmental influences (e.g., obstetric complications) or genetic factors along with social factors (e.g., poverty) are strong connections and contributing factors. (38,39)
The pathogenic mechanisms underlying schizophrenia are unknown as well. One of the key factors that have been exhibited during the past years is that schizophrenia subjects have a notably higher amount of D2-like receptors compared to the control people. (40) Dopaminergic synapse and neuroactive ligand–receptor are some of the most representative and admitted pathways characterized in the illness, even though other pathways are being studied. (41,42)Figure 1 shows a brief overview of dopaminergic synapse, (43) in red are highlighted D2-like dopamine receptors. Dopamine receptors, also called G protein-coupled receptors or rhodopsin-like receptors, are distinctively characterized by having seven-transmembrane regions interconnected through three extracellular and intracellular loops. All DRs traverse the membrane seven times, and they are recognized as serpentine receptors because of how they wind back and forth across the membrane. (44) Due to the fact that DRs are considerably intervened by the activation of G proteins, most of their effects are acknowledged as G protein-coupled. In the context of drug therapy, drugs that block D2-like receptors are substantially recommended for the treatment of schizophrenia and other psychotic disorders; meanwhile, drugs that stimulate D1-like or D2-like receptors help with the motor symptoms that result from the decay of dopamine-related neurons of some diseases like Parkinson. (45)

Figure 1

Figure 1. Brief overview of the dopaminergic synapse pathway [KEEG copyright permission obtained: Material: Dopaminergic synapse, pathway map04728. (2021/ KEGG: Kyoto Encyclopedia of Genes and Genomes database resource/Bioinformatics Center, Institute for Chemical Research, Kyoto University and Human Genome Center, Institute of Medical Science, University of Tokyo). (105−107)

High Resolution Image
Download MS PowerPoint Slide
To analyze different binding modes of drugs reported as modulators of D2-like receptors and co-crystallized in with D2, D3, and D4 dopamine receptors, a 3D pharmacophore hypothesis was used to analyze the shared features in the binding site of the crystallographic ligands risperidone, eticlopride, and nemonapride bounded to D2, D3, and D4 protein receptors, respectively.
One widely used antipsychotic is risperidone. It is considered a second-generation antipsychotic and is one of the main drugs administrated during the treatment of schizophrenia. Risperidone has been recognized as one of the leader drugs due to its properties of reducing the overactivity of D2R receptors in the brain. (46,47) Eticlopride is sorted as a dopamine agent and neurotransmitter agent, and it is a substituted benzamide with a powerful affinity for D2-like but not D1-like receptors. (48) Nemonapride is another antipsychotic drug approved in Japan for schizophrenia, and it belongs to the benzamide class as well. It has a potent affinity to D2, D3, and D4 receptors. (49)
Figure 2 shows the pharmacophores established between the drugs risperidone, eticlopride, and nemonapride with D2, D3, and D4 receptors, respectively. Risperidone and the D2 dopamine receptor interact with three hydrophobic points: two owing to the 6-fluorobenzo[d]isoxazole region where the fluor is interacting with ALA89A, OLA6, PHE370A, and PHE165A and the phenyl group interacts with PHE378A, ALA89A, PHE165A, and TRP37A, while the third hydrophobic interaction occurs with the methyl group of the 4H-pyrido[1,2-a]pyrimidin-4-one. Additionally, risperidone presented one positive ionizable area located in the piperidine. Eticlopride interacts with the D3 receptor with four hydrophobic areas and one positive ionizable region. The hydrophobic interactions were in the 4-chloro-2-ethyl-5-methoxyphenol and the ethyl group bounded to pyrrolidine. The involved aminoacids in the hydrophobic interactions of eticlopride were VAL111A, PHE346A, ILE183A, VAL350A, VAL189A, PHE345A, TRP342A, TYR373A, and THR369A. The pyrrolidine ring of eticlopride interacts with ASP110A through one positive area due to the formation of a salt bridge between them. This is a result of the high likelihood of the pyrrolidine ring being charged at physiological pH. (50) Nemonapride interacts with the D4 dopamine receptor with three hydrophobic regions. The hydrophobic zones were located in the 1-benzyl, the 2-methyl bounded to pyrrolidine, and the 2-chloro-5-methoxy-N-methylaniline. The involved aminoacids in the hydrophobic interactions of nemonapride were LEU111A, PHE91A, VAL87A, TYR390A, THR386A, PHE362A, VAL116A, VAL193A, and LEU187A. Nemonapride presented two types of interaction with Asp115A,: a positive ionizable area with the pyrrolidine ring and a H-bond interaction with the formamide group. It is worth noting that all the presented drugs had at least three hydrophobic interactions and one positive ionizable feature into the established pharmacophore.

Figure 2

Figure 2. Established pharmacophore between (A) risperidone and D2 dopamine receptor (PDB: 6CM4-8NU), (B) eticlopride and D3 dopamine receptor (PDB: 3PBL-ETQ), and (C) nemonapride and D4 dopamine receptor (PDB: 5WIU-AQD).

High Resolution Image
Download MS PowerPoint Slide
The pharmacophore feature model was considered the first strategy to search into the database of 70 possible repurposing drugs (Table 1). The discovery and deeper understanding of such interactions presented a crucial starting point for this study.
Table 1. Information of Prospective Repurposing Drugs Selected for the Present Study
drug information
drug mechanism of action disease area indication
allopurinol xanthine dehydrogenase inhibitor rheumatology gout
citalopram serotonin transporter inhibitor neurology/psychiatry depression
clonidine adrenergic receptor alpha-2 agonist cardiology hypertension
cycloserine alanine racemase inhibitor infectious disease tuberculosis
cysteamine cystine hydrolytic enzyme metabolism cystinosis
dextroamphetamine dopamine transporter releasing agent neurology/psychiatry ADHD
dextromethorphan glutamate (NMDA) receptor subunit epsilon 1 antagonist pulmonary cough suppressant
dipyridamole 3′,5′-cyclic phosphodiesterase inhibitor cardiology coronary artery disease (CAD)
donepezil acetylcholinesterase inhibitor neurology/psychiatry Alzheimer’s disease
duloxetine serotonin transporter inhibitor neurology/psychiatry depression
esomeprazole potassium-transporting atpase inhibitor gastroenterology gastroesophageal reflux disease
estradiol estrogen receptor alpha agonist endocrinology contraceptive
eszopiclone GABA-A receptor; anion channel positive allosteric modulator neurology/psychiatry insomnia
famotidine histamine H2 receptor antagonist gastroenterology heartburn
fingolimod sphingosine 1-phosphate receptor agonist neurology/psychiatry multiple sclerosis
flunarizine voltage-gated T-type calcium channel blocker neurology/psychiatry migraine headache
fluvoxamine serotonin transporter inhibitor neurology/psychiatry obsessive–compulsive disorder (OCD)
gabapentin voltage-gated calcium channel modulator neurology/psychiatry epilepsy
galantamine acetylcholinesterase inhibitor neurology/psychiatry senile dementia
guanfacine adrenergic receptor alpha-2 agonist cardiology hypertension
isradipine voltage-gated L-type calcium channel blocker cardiology hypertension
lamotrigine sodium channel alpha subunit blocker neurology/psychiatry epilepsy
levetiracetam synaptic vesicle glycoprotein 2A modulator neurology/psychiatry epilepsy
levodopa dopamine D3 receptor agonist neurology/psychiatry Parkinson’s disease
linagliptin dipeptidyl peptidase IV inhibitor endocrinology diabetes mellitus
lorazepam GABA-A receptor; anion channel positive allosteric modulator neurology/psychiatry epilepsy
losartan type-1 angiotensin ii receptor antagonist cardiology hypertension
mecamylamine Nach receptor (a3/b4) negative allosteric modulator cardiology hypertension
meclofenamic acid arachidonate 5-lipoxygenase inhibitor rheumatology rheumatoid arthritis
memantine glutamate (NMDA) receptor negative allosteric modulator neurology/psychiatry Alzheimer’s disease
metformin 5′-AMP-activated protein kinase activator endocrinology diabetes mellitus
methotrexate dihydrofolate reductase inhibitor oncology acute lymphoblastic leukemia (ALL)
minocycline bacterial 70S ribosome inhibitor infectious disease respiratory tract infections
mirtazapine serotonin 2a (5-HT2a) receptor antagonist neurology/psychiatry depression
modafinil dopamine transporter inhibitor neurology/psychiatry shift work disorder (SWD)
nicotine Nach receptor (a4/b2) agonist neurology/psychiatry smoking cessation
nitroglycerin soluble guanylate cyclase activator cardiology angina pectoris
nitroprusside soluble guanylate cyclase activator cardiology hypertension
ondansetron serotonin 3a (5-HT3a) receptor antagonist gastroenterology nausea
oxcarbazepine sodium channel alpha subunit blocker neurology/psychiatry epilepsy
oxybate GABA-B receptor agonist neurology/psychiatry narcolepsy
papaverine phosphodiesterase 4 inhibitor cardiology myocardial infarction
pentosan polysulfate fibroblast growth factor 2 binder urology interstitial cystitis (IC)
pergolide dopamine receptor agonist neurology/psychiatry Parkinson’s disease
pramipexole D2-like dopamine receptor agonist neurology/psychiatry Parkinson’s disease
pravastatin HMG-coa reductase inhibitor endocrinology hypercholesterolemia
prednisolone glucocorticoid receptor agonist ophthalmology conjunctivitis
pregabalin voltage-gated calcium channel modulator neurology/psychiatry peripheral neuropathy
pregnenolone nuclear receptor subfamily 1 group I member 2 agonist rheumatology rheumatoid arthritis
progesterone progesterone receptor agonist obstetrics/gynecology infertility
pyrimethamine dihydrofolate reductase inhibitor infectious disease malaria
raloxifene estrogen receptor beta modulator orthopedics osteoporosis
ramelteon melatonin receptor agonist neurology/psychiatry insomnia
rasagiline monoamine oxidase B inhibitor neurology/psychiatry Parkinson’s disease
reboxetine norepinephrine transporter inhibitor neurology/psychiatry depression
riluzole sodium channel alpha subunit blocker neurology/psychiatry amyotrophic lateral sclerosis (ALS)
roflumilast phosphodiesterase 4 inhibitor pulmonary COPD
selegiline monoamine oxidase B inhibitor neurology/psychiatry Parkinson’s disease
sertraline serotonin transporter inhibitor neurology/psychiatry depression
sildenafil phosphodiesterase 5A inhibitor cardiology hypertension
simvastatin HMG-coa reductase inhibitor endocrinology hypercholesterolemia
tiagabine GABA transporter 1 inhibitor neurology/psychiatry epilepsy
tolcapone catechol O-methyltransferase inhibitor neurology/psychiatry Parkinson’s disease
topiramate GABA-A receptor; anion channel positive modulator neurology/psychiatry epilepsy
tropisetron serotonin 3a (5-HT3a) receptor antagonist gastroenterology nausea
valacyclovir human herpesvirus 1 DNA polymerase inhibitor infectious disease virus herpes simplex (HSV)
valproic acid 4-aminobutyrate aminotransferase inhibitor neurology/psychiatry epilepsy
varenicline Nach receptor (a4/b2) agonist neurology/psychiatry smoking cessation
vorinostat histone deacetylase 1 inhibitor oncology cutaneous T-cell lymphoma (CTCL)
vortioxetine serotonin 1a (5-HT1a) receptor agonist neurology/psychiatry depression
The creation of the shared feature pharmacophore was extracted by an alignment and interpolation of the merging pharmacophores of the native ligands with DRs. The model, which is presented in this research (Figure 3), only contains four features commonly aligned in the pharmacophore. The four-point pharmacophore model was selected as the input for the virtual screening against the 70 compounds of this research.

Figure 3

Figure 3. Construction of the pharmacophore-shared feature model. (A) Three hydrophobic interactions are represented by the yellow spheres and one positive ionizable area, which is represented as a blue astral center. (B) Four-point pharmacophore model based on shared features of the superposed structures 8NU-risperidone (red), ETQ-eticlopride (green), and AQD-nemonapride (magenta), crystallographic ligands of proteins 6CM4, 3PBL, and 5WIU.

High Resolution Image
Download MS PowerPoint Slide
The algorithm of screening, pharmacophore fit, retrieved a total of six structures as the best match of the pharmacophore model. All the selected structures had a minimum of three features located in the same disposition of the model. The selected compounds of the pharmacophore input were A - linagliptin, B - citalopram, C - flunarizine, D - sildenafil, E - minocycline, and F - duloxetine (Figure 4). Each of the six drugs has one positive ionizable area that is susceptible to protonation and two hydrophobic points positioning in the same conformation and 3D space the input pharmacophoric model. The atoms or groups classified as positive ionizable are susceptible to be protonated, such as the 3-amine-piperidine region in linagliptin, the 3-(dimethylamino)propyl group in citalopram, the piperazine group in flunarizine, the 1-methylpiperazine group in sildenafil, the 5-dimethylamino group in minocycline, the N-methylamine group in duloxetine. The hydrophobic areas were in the aromatic, saturated, unsaturated, and fluoridated regions. The physicochemical properties of the selected six drugs are shown in Table 2.

Figure 4

Figure 4. Pharmacophore screening results of the four-point shared pharmacophore. The selected compounds as a perfect match were (A) linagliptin, (B) citalopram, (C) flunarizine, (D) sildenafil, (E) minocycline, and (F) duloxetine. The yellow spheres represent the hydrophobic interactions, and the blue areas represent the positive ionizable areas.

High Resolution Image
Download MS PowerPoint Slide
Table 2. Structure and Physicochemical Properties of the Drugs Selected as the Best Match of the Pharmacophore Screeninga
a

XLOGP3: Octanol–Water Partition Coefficient Atomistic method, optimal range between −0.7 and +5.0. TPSA: Topological polar surface area, optimal range between 20 and 130 Å2. Ali LogS: Water solubility, implemented by the optimal range between. (104) Fraction Csp3: Saturation, the fraction of carbons in the sp3 hybridization not less than 0.25. Flexibility: Rotatable bonds, no more than 9 rotatable bonds.

To confront the results of the pharmacophore screening, molecular docking calculations with the D2, D3, and D4 dopamine receptors were conducted and they are shown in Table 3. The exactness and precision of the docking process during the simulation were validated by redocking analysis of the crystallographic ligands (Table 4). To avoid inexact results, the root-mean-square deviation (RMSD) was rooted in the threshold value of 2.0 Å: this process is termed “self-docking”. By self-docking it was shown that the binding sites had the optimal size and fidelity of the crystallographic complexes. These results show that the docking program, AutockVina, adopted an accurate binding pose during the whole simulation, and it has the potential to compute with confidence the computational ligand-binding affinities of 70 compounds to D2, D3, and D4 dopamine receptors.
Table 3. Molecular Docking Scores for Drugs with D2, D3, and D4 Receptorsb
a

Docking score (kcal/mol) calculated using AutoDock Vina.

b

GI absorption: High, PSA < 142 Å2 and log P between −2.3 and + 6.8. Low: outside the high GI range. BBB Permeant: Yes: PSA < 79 Å2 and log P between +0.4 to +6.0. No: outside the high BBB permeant range. The drugs selected in the pharmacophore screening are presented in bold (see the complete table in the Supporting Information).

Table 4. Self-Docking Results and RMSD of Crystallographic Ligands of the Proteins 6CM4, 3PBL, and 5WIU
dopamine receptor crystallographic ligand code RMSD (Å) docking score (kcal/mola)
D2 (6CM4) 8NU 1.244 –8.9
D3 (3PBL) ETQ 1.232 –4.9
D4 (5WIU) AQD 1.442 –6.9
a

Docking score (kcal/mol) calculated using AutoDock Vina.

Consequently, the key element of the drugs used to treat schizophrenia is the crossing of the blood–brain barrier. The study hereafter is guided into the selection of the repurposing molecules with the best docking scores and in conjunction with a high probability of being absorbed by the human intestine and a high possibility of penetration of the BBB. Predictive GI as well as BBB penetration were added at the bottom of Table 3. Interestingly, flunarizine showed better docking scores in comparison to crystallographic native ligands and the six drugs selected in the pharmacophore-based model. From the six pharmacophore matchings, both flunarizine and citalopram were simultaneously predicted with high GI absorption and BBB permeation. Flunarizine was coupled with −9.9, −9.2, and −11.0 kcal/mol, respectively, with D2, D3, and D4 dopamine receptors, and citalopram was coupled with −7.8, −7.2, and −8.2 kcal/mol to D2Rs. Although native ligands must have a high affinity to D2R targets, the docking scores exposed in Table 4 were not better than those accomplished by flunarizine.
Complexes of the docked structures of flunarizine with D2, D3, and D4 receptors are compared in Figure 5. Overall, the key components of flunarizine were the phenyl, 4-fluorobenzyl groups, and tertiary amine in the piperazine ring. In particular, this piperazine ring is plausible to be charged at physiological pH and it could form a salt bridge to the D2R. In accord with the shared pharmacophore input, the aforementioned groups established hydrophobic regions, polar contacts, and salt bridges with the three DRs. The main binding sites of flunarizine with the D2-like receptors are described in Figure 5, most of the contact residues in flunarizine were identical to the native ligands, and even some distances in those conserved amino acids are smaller in flunarizine than in risperidone, eticlopride, and nemonapride. (46,51) In general, hydrogen bonds are divided into a strong hydrogen bond when the involucrated atoms are N–H···O, N–H···N, and O–H···O, and when the hydrogen bond is built between, C–H···O, it is considered as a weak hydrogen bond. Although the type of involved atoms is a paramount factor of the hydrogen bonds, other aspects must be included as discrimination elements. The distance between acceptors and donor atoms is another aspect that is recommended to contemplate. For instance, weak hydrogen bonds are usually among 3.0–3.7 Å, and strong hydrogen bonds should measure over 2.0–3.9 Å. Besides those facts, hydrophobic interactions could be separated into five different classes, and they could be between carbon–carbon, carbon–halogen, or aromatic carbon–sulfur with distances slightly longer, usually ≤4.0 Å. Salt bridges are established with two regions of opposite charge, for instance, between a positively charged nitrogen and a negatively charged oxygen, and the average distance between is approximately 3.0–4.0 Å. (52)

Figure 5

Figure 5. Docked structures of the flunarizine and the native ligands with D2-like receptors. (A) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D2R (light blue), amino acids that were involucrated in the pharmacophore between the native ligand, risperidone (green), and D2R (lightblue). (B) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D3R (bright orange), amino acids that were involucrated in the pharmacophore between the native ligand, eticlopride (blue), and D3R (bright orange). (C) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D4R (light cyan), amino acids that were involucrated in the pharmacophore between the native ligand, nemonapride (brown), and D4R (light cyan).

High Resolution Image
Download MS PowerPoint Slide
Five key residues in the D2 dopamine receptor were selected to measure their distances to the ligands (Figure 5A): PHE-377, TRP-67, TYR 396, and PHE 377, which are aromatic amino acids, and ASP-81, which is negatively charged. Aspartic acid amino acid (ASP) is reported as one of the most frequent acceptors in weak hydrogen bond interactions, C–H···O interactions, (52) which had a reduction from 4.0 Å with risperidone to 3.8 Å with flunarizine. In terms of D3, six amino acids were chosen to analyze the ligand binding, and nonpolar, aromatic, and polar amino acids were compared (Figure 5B). VAL-86, a nonpolar amino acid, was markedly reduced to 3.2 Å, establishing a stable interaction of carbon-halogen type. (48) Representative binding amino acids of the binding pocket between the D4-flunarizine and D4-nemonapride (53) complexes were selected (Figure 5C). Some interactions slightly increased in the D4-flunarizine complex, for instance, ASP-115 increased from 3.0 to 3.4 Å and SER-196 increased from 3.4 to 4.1 Å. Yet, other interactions, especially those related to aromatic amino acids, were reduced (e.g., PHE-91 and PHE-363). So, hydrophobic interactions were the main driving force in flunarizine–D2Rs complexes.
To study the stability of the flunarizine and native ligands with the DRs, the protein–ligand complexes were analyzed by molecular dynamics simulations, and RMSD, RMSF, and radius of gyration (Rg) were examined (see Figure 6). The ligand topologies were generated using the CHARMM General Force Field due to the fact that it groups a huge scope of chemical groups presented in drug-like molecules, as well as many heterocyclic scaffolds. (54) The CHARMM36 force field was used to study the protein. (55−60) Another field, OPLS3e, has been studied by other authors to generate the protein field of DRs simulations, however, significant differences have not been reported between the two fields, and CHARMM36 has been primarily recommended. (61,62) Aiming to generate the first report of the molecular dynamic simulation of DRs with flunarizine and its comparison with the risperidone, eticlopride, and nemonapride, 30 ns was selected as the running time of the present simulations. Each parameter was adjusted to the final purpose of this article. To avoid the molecule becoming unstable and any error during the integration, it is recommended the use a short time step. Thus, selecting the time, time step, and the number of steps was a critical step of the present molecular dynamic study. Simulation time and the time step are linear in molecular dynamics simulation; for the specific objective of our study, the simulation time was 30,000 ps (30 ns) with 15,000,000 steps and a time step of 2 fs. (63,64)

Figure 6

Figure 6. Molecular dynamics simulations of DRs unbound and the protein complex with crystallographic ligands and flunarizine: (A) RMSD, (B) RMSF, and (C) radius of gyration plots.

High Resolution Image
Download MS PowerPoint Slide
To measure the difference between the backbone of a protein from an initial structure conformation to the final position, the RMSD analysis can be used. When a protein is unstable, its fluctuations in the RMSD protein are high. Regarding the atomic positions in the trajectory, root-mean-squared fluctuations (RMSF) may be used to calculate their mean square fluctuations, and the radius of gyration calculates the closeness of the protein structure from the start to the end of simulations. (65,66)
The RMSD analysis and tracing during the whole simulation with the selected compound, flunarizine, show that the RMSD value starts with an increasing trend with the three DRs (Figure 6A). The complex of flunarizine with the D2 (D2_FLUN) dopamine receptor had a low RMSD course in comparison to the risperidone complex during all the running times, showing that the flunarizine molecule binds more stably to the targeting site of the D2 receptor. The complex flunarizine–D3 dopamine receptor (D3_FLUN), at the initial stage of the molecular dynamics simulation, had a gradual decline until 1.25 ns and then a sightly increase up to 2.5 ns, which are not statistically significant, and the trend of the complex shows a lower RMSD in comparison to the complex with eticlopride (D3_EQT). Similarly, in the simulation of the D4 dopamine receptor, comparable trajectories were observed for the D4 dopamine receptor, in its unbounded manner, and complexes with flunarizine (D4_FLUN) and nemonapride (D4_ADQ), despite the fact that there was a peak increase in the RMSD between 15 and 20 ns for the complex D4_ADQ. In all cases, the binding of the compound flunarizine showed a better stabilization to the complexes than the native co-crystalized ligands.
The dynamic behavior of individual amino acid residues is shown in Figure 6B. The RMSF plots showed a matching pattern regarding the flexibility influence of the crystallographic compounds with the flunarizine at different levels. The regions of the DRs that are most susceptible to a 300 K temperature are the residues 50–75, 100–130, 140–160, 200–210, 215–250, 300–340, and 380–400 in the D2 dopamine receptor; residues 200–250, 275–300, and 325–375 in the D3 dopamine receptor; and residues 25–40, 50–60, 90–110, 140–160, 175–180, 220–260, 270–290, 300–325, and 360–380 in the D4 dopamine receptor. The radius of gyration showed a similar pattern with the complex during the simulation. The complex of flunarizine with the D2 dopamine receptor had a variation of radius of gyration between 2.8 and 3.0 nm during all the simulations. The complex of flunarizine with the D3 dopamine receptor had a variation of 2.4–3.0 nm, and the complex of flunarizine with the D4 dopamine receptor had a variation of 2.7–3.2 nm. These analyses evidenced that flunarizine had a similar pattern in the protein structure compactness with the three DRs. The RMSD analyses indicate a more stable complex between flunarizine with DRs in comparison to the crystallographic compounds, risperidone, eticlopride, or nemonapride.
To analyze a set of diverse conformations that resulted from the molecular dynamics simulations, snapshots from the 30,000 ps simulation (ignoring ions and water) at each 5000 ps intervals (Figures S1–S3) were created from the GROMACS simulation results. Figure S1 shows the structures of flunarizine–DRs complexes at different stages, beginning from 5000 to 30,000 ps, and each stage was generated with the gmx trajcon command of GROMACS. (67−70)
The main contacts of flunarizine were the phenyl, 4-fluorobenzyl, and tertiary amine in the piperazine ring as well as in the docked structures. Flunarizine, during the whole simulation, mainly interacts with nonpolar and aromatic amino acids and, in some frames, with established polar contacts with THR and CYS amino acids. Due to the fact that flunarizine has six rotatable bonds and four H-bond acceptors, it could adopt multiple shapes within the pocket.
Considering all the results, it is clear that flunarizine not only showed the greatest affinity energy and stability with the D2, D3, and D4 receptors in comparison to the native ligands risperidone, eticlopride, and nemonapride, but also the key features and distances were significantly ameliorated in flunarizine outcomes. The shown results of this study are supported by previous research where the clinical antipsychotic efficacy of flunarizine has been questioned, especially by its D2 blocking properties.
When it comes to how flunarizine has been involucrated into the schizophrenia spectrum, there is just one report of flunarizine with schizophrenia, and very promising results were retrieved although it was the first approach of the evaluation of its antipsychotic properties. Bisol et al. (71) emphasized that flunarizine could show good efficacy and tolerability for the treatment of schizophrenia with an uncommon profile. It was worth noting that the study scored the patients by PANSS (Positive and Negative Syndrome Scale), along with the Clinical Global Impressions-Improvement (CGI-I) scale and the Extrapyramidal Symptom Rating Scale (ESRS). The key points of the study were some facts such as the important reduction in the PANSS with the flunarizine group (21%) and compared to those using haloperidol (19%). Other motivators such as the long half-life (2–7 weeks), low cost, and low inference of extrapyramidal symptoms justified advanced investigation, particularly in psychiatric patients with low adherence to treatment. The present study is the first computational support of flunarizine as a possible treatment in schizophrenia by its high affinity and stability with DRs compared with antipsychotic drugs risperidone, eticlopride, and nemonapride, and the results presented here should be contrasted with more clinical trials and experimental data. (72−79) Further studies should be carried out to establish whether the possible antipsychotic effect of flunarizine is due to its interaction with D2 receptors or as a calcium channel antagonist or both.

Conclusions

ARTICLE SECTIONS
Jump To
An in silico drug repositioning study was conducted. Considering that D2-like receptors (D2, D3, and D4 receptors) are one of the main pharmacological targets for treating schizophrenia, a hypothesis of shared pharmacophore features was formulated for this study. The common features of risperidone, eticlopride, and nemonapride with DRs were studied and screened with a total of 70 promising compounds that are not currently indicated for schizophrenia. Linagliptin, citalopram, flunarizine, sildenafil, minocycline, and duloxetine were the drugs that perfectly matched the pharmacophore input. Blood–brain penetration and human intestinal absorption prediction results were analyzed and compared with the pharmacophore results. From the six drugs selected in the pharmacophore-share input, flunarizine showed the best docking score with the D2, D3, and D4 dopamine receptors (D2-like receptors) and high stability in comparison to all the tested ligands. Molecular docking and molecular dynamics simulations were used to corroborate the binding score and the complex stability of flunarizine–D2-like receptors. Flunarizine has been hypothesized in some previous studies by its D2-like dopamine blocking properties. These results are the first computational reports where it is supported that flunarizine should be studied as a D2-like dopamine blocker. Flunarizine has many advantages in comparison to other antipsychotics. Further studies must be performed with it in the field of psychopharmacology. Low induction of extrapyramidal symptoms, a long half-life (2–7 weeks), and low cost are some facts that justified further investigation, particularly in psychiatric patients with low adherence to other treatments.

Materials and Methods

ARTICLE SECTIONS
Jump To

Selection and Optimization of the Compounds

The suggested compounds in this study were selected using the following inclusion criteria: (1) having been tested in clinical studies (ClinicalTrials.gov) (1) with a pharmacological target approved for schizophrenia by the FDA but that had not yet been approved to treat schizophrenia and (2) have not been reported side effects, alone or in combination with other drugs. Thus, 70 (out of a group of 88 possible drugs reported in 231 clinical studies) were selected, which were the only nonprotein and non-antibody compounds (Table 1). The compounds’ 3D structures were downloaded from the PubChem database in “.sdf” format, and then they were submitted to quantum chemistry models, such as ab initio calculations with the DFT method with the B3LYP multiparameter functional and the 6-31G Gaussian basis set, using the program Gaussian 09. (80) The resulting optimized geometry was converted to “.mol2” format, and subsequently polar hydrogens, Gasteiger charges, and free bond rotation were incorporated to the molecules in “.pdbqt” format file using Open Babel 2.4.1. (81)

Selection and Optimization of the Targets

The selected pharmacological targets for schizophrenia were the dopamine receptors D2, D3, and D4. (53,82) The criteria of selection to crystallographic proteins were as follows: (1) organism, human as a source organism; (2) resolution at a minimum of 3.0 Å; (3) structures with identified and known binding sites with natural ligands of dopamine crystallographic receptors; and (4) wild type protein and without variants or mutations. (83)
The crystallographic structures of the used proteins in the present study were obtained from the Protein Data Bank, whose codes are PDB ID: 6CM4 (D2 receptor), 3PBL (D3 receptor), and 5WIU (D4 receptor). The 3D crystallographic structures of PDB proteins co-crystallized with the ligands 6CM4-8NU (risperidone), 3PBL-ETQ (eticlopride), 5WIU-AQD (nemonapride) were curated using the Swiss model web server to select reliable and complete three-dimensional protein structures without missing residues. (105−107) The 3D structures were optimized with the program UCSF Chimera, (84) which means the water molecules and other nonprotein ligands were removed and assigned AMBER force field charges as it is reported from the literature that it used a gradient convergence criteria of 0.005 kcal/mol. The structures were placed in their minimum energy conformation and were stored in “.pdbqt” format.

Pharmacophore Modeling and Screening

Crystal structures of complexes (D2 dopamine receptor with risperidone, D3 dopamine receptor with eticlopride, and D4 dopamine receptor with nemonapride) were superposed to create a shared feature pharmacophore using LiganScout 4.4. A four-point pharmacophore model was selected by combining all the original features and screened against 70 repurposing drug candidates, the algorithm of screening was the pharmacophore-fit scoring function, the conditions were a maximum number of omitted 1 feature, and the minimum required feature was 3. The screening mode was the matching of all query features and Multi-Thread execution mode. The interactions considered were hydrophobic interaction (represented as a yellow single sphere, distance constraint 1.0–5.9 Å), hydrogen bond donors (represented as a green dotted arrow, distance constraint 2.2–3.8 Å), a hydrogen bond acceptor (represented as a red dotted arrow, distance constraint 2.2–3.8 Å), positive ionizable interaction (represented as a blue astral center, distance constraints 1.5–5.5 Å with negative ionizable and 1.5–10.0 Å with aromatic ring), among others. (85)

Gastrointestinal Absorption and Blood–Brain Penetration Parameters

The SwissADME server and admetSAR online database were used to check ADME parameters of the drugs, absorption, distribution, metabolism, and excretion, along with some physicochemical properties. The blood–brain penetration and human intestinal absorption estimation were computed by the lipophilicity (WLOGP) and polarity (tPSA) of the molecules using the SwissADME web server. (36,86−88) This model is highly reliable because it is supported by a big library of molecules that were curated by the literature, patents, and database cross-checks. The guidelines for good absorption (89) are commonly accepted by a rectangular limit of log P between −2.3 and +6.8 with the PSA lower than 142 Å2. The molecules with a high possibility of ingress in the CNS had moderately polar (PSA < 79 Å2) and relatively lipophilic (log P from +0.4 to +6.0). (87,90−92)
The Combination of these predictive models had shown an accurate predictive model of molecules being absorbed by the human intestinal absorption (HIA) and blood–brain barrier (BBB), and it is of great support for lead optimization. (88,93−98)

Molecular Docking

With the ligands and proteins in “.pdbqt” format, molecular docking computation was performed in triplicate using AutoDock Vina, (24) the flexible side chains protocol, and an iterated local search global optimizer algorithm. Thus, flexible docking of the 70 compounds with each of the molecular targets (D2, D3, and D4) was automatically performed, through a bash script, running on a Precision 7920 workstation using a Linux Ubuntu 18.04. The docking site was selected upon the location of the co-crystalized ligands found in each PDB file: for the D2 receptor, the XYZ coordinates chosen to be the center of the grid box were 9.9, 5.8, and −9.5 Å, respectively; for the D3 receptor, the XYZ coordinates were 0.08, −14.8, and 10.4 Å, respectively; and for the D4 receptor, the XYZ coordinates were −17.4, 15.2, and −16.7 Å, respectively. For each docking, a grid box (that is, a grid or defined space large enough to allow the docked ligand to rotate freely) of x 25, y 25, and z 25 Å was constructed with a number of bonding modes equal to 20 and exhaustivity of 25. The pose with the most negative affinity (kcal/mol) was stored. Redocking estimates were studies as an accuracy process of the docking scores in the binding poses.

Molecular Dynamics Simulations

GROMACS 2018.1 was used for the molecular dynamics simulation of DR structures (PDB: 6CM4, 3PBL, 5WIU) and the ligands (8NU, ETQ, AQD, and flunarizine). (99−101) CHARMM36 force field was used for protein and ions, meanwhile the TIP3P model for water. (57,102) CHARMM General Force Field (CGenFF) (54) was used to retrieve the ligand parameters (legacy version 1.0.0). A dodecahedron box (103) and other periodic boundary conditions were optimized to perform the simulations. To solvate and neutralize the system, ions were added. A total of 5000 steps were performed in terms of energy minimization using the steep descent method of having a stable conformation. Canonical ensembles (NVT) and isobar isothermal ensembles (NPT) were performed, respectively, with a constant temperature of 300 K for 100 ps for NVT followed by a constant temperature of 300 K and a constant pressure of 1 atm per 100 ps for NPT. Molecular dynamics simulation was performed for 30,000 ps. The first step was minimized and then equilibrated with restraints on the ligand, its heavy atoms, and protein backbone atoms, followed by production runs. The Verlet cutoff scheme was used, a gid box with a nstlist of 10 was used, and rcoulomb and rvdw were fixed to 1.0 nm. The energies were saved every 10.0 ps with an update log file every 10.0 ps. The simulation covered 15 million steps with 30,000 ps (30 ns). Based on the average of these results, longer (100 ns) MD simulations should be employed in the following study. The RMSD, RMSF, and radius of gyration (Rg) were calculated by g-rmsd, g-rmsf, and g-Rg, respectively. Different snapshots were generated by the g-trjconv command, using 5000 ps intervals. The graphics for RMSD and RMSF were designed using the QtGrace v0.2.6 program.

Supporting Information

ARTICLE SECTIONS
Jump To

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.0c05984.

  • (Table S1) Molecular docking calculations of 70 promising drug repositioning candidates for schizophrenia with D2-like receptors and prediction of GI absorption - BBB permeation; (Table S2) physicochemical properties, lipophilicity, and drug likeness parameters of the drugs considered in this study; and (Figures S1–S3) representative snapshot from molecular dynamics trajectory of flunarizine with DRs (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

ARTICLE SECTIONS
Jump To
  • Corresponding Author
    • Melissa Mejia-Gutierrez - Faculty of Natural and Exact Sciences, Department of Chemistry, and School of Basic Sciences, Department of Physiological Sciences, Faculty of Health, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia;  Orcidhttps://orcid.org/0000-0002-0372-4413;  Email: [email protected]
  • Authors
    • Bryan D. Vásquez-Paz - Faculty of Natural and Exact Sciences, Department of Chemistry, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia;  Orcidhttps://orcid.org/0000-0002-1253-3504
    • Leonardo Fierro - Faculty of Health, School of Basic Sciences, Department of Physiological Sciencesh, Laboratory and Research group - Pharmacology Univalle Group, Universidad del Valle, 25360 Cali, Colombia
    • Julio R. Maza - Faculty of Basic Sciences, Department of Chemistry, Laboratory and Research group - Organic Chemistry and Biomedical Group, Universidad del Atlántico, 081001 Puerto Colombia, Colombia;  Orcidhttps://orcid.org/0000-0003-0334-1997
  • Funding

    This study was supported by financial sources of Universidad del Valle. The installations and the used computational capacity came from Universidad del Valle.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

ARTICLE SECTIONS
Jump To

All authors would like to thank the Laboratory and Research group “Pharmacology Univalle Group” for the technical help and deep discussion on these topics. We acknowledge our University “Universidad del Valle” for the various research facilities and for permission to use its computational resources.

Abbreviations

ARTICLE SECTIONS
Jump To
6CM4

structure of D2 dopamine Receptor
3PBL

structure of D3 dopamine Receptor
5WIU

structure of D4 dopamine Receptor
BBB

blood–brain barrier
GI absorption

gastrointestinal absorption
HBD

hydrogen bond donors
HBA

hydrogen bond acceptor
HIA

human intestinal absorption
NVT

moles (N), volume (V), and temperature (T)
NPT

moles (N), pressure (P), and temperature (T)
RMSD

root-mean-square deviation
RMSF

root-mean-square fluctuation
TPSA

topological polar surface area

References

ARTICLE SECTIONS
Jump To

This article references 107 other publications.

  1. 1
    Lago, S. G.; Bahn, S. Clinical Trials and Therapeutic Rationale for Drug Repurposing in Schizophrenia. ACS Chem. Neurosci. 2019, 10, 58– 78,  DOI: 10.1021/acschemneuro.8b00205
    Google Scholar
    1
    Clinical Trials and Therapeutic Rationale for Drug Repurposing in Schizophrenia
    Lago, Santiago G.; Bahn, Sabine
    ACS Chemical Neuroscience (2019), 10 (1), 58-78CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
    A review. There is a paucity of efficacious novel drugs to address high rates of treatment resistance and refractory symptoms in schizophrenia. The identification of novel therapeutic indications for approved drugs-drug repurposing-has the potential to expedite clin. trials and reduce the costly risk of failure which currently limits central nervous system drug discovery efforts. In the present Review we discuss the historical role of drug repurposing in schizophrenia drug discovery and review the main classes of repurposing candidates currently in clin. trials for schizophrenia in terms of their therapeutic rationale, mechanisms of action, and preliminary results from clin. trials. Subsequently we outline the challenges and limitations which face the clin. repurposing pipeline and how novel technologies might serve to address these.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtF2qsr7P&md5=38dcc54094733e1fea956d973cd5d615
  2. 2
    Saldívar-González, F.; Prieto-Martínez, F. D.; Medina-Franco, J. L. Descubrimiento y Desarrollo de Fármacos: Un Enfoque Computacional. Educ. Quim. 2017, 28, 51– 58,  DOI: 10.1016/j.eq.2016.06.002
    Google Scholar
    There is no corresponding record for this reference.
  3. 3
    Lee, H.-M.; Kim, Y. Drug Repurposing Is a New Opportunity for Developing Drugs against Neuropsychiatric Disorders. Schizophr. Res. Treat. 2016, 2016, 1,  DOI: 10.1155/2016/6378137
    Google Scholar
    There is no corresponding record for this reference.
  4. 4
    Lau, C.-I.; Wang, H.-C.; Hsu, J.-L.; Liu, M.-E. Does the Dopamine Hypothesis Explain Schizophrenia?. Rev. Neurosci. 2013, 24, 389– 400,  DOI: 10.1515/revneuro-2013-0011
    Google Scholar
    4
    Does the dopamine hypothesis explain schizophrenia?
    Lau, Chi-Ieong; Wang, Han-Cheng; Hsu, Jung-Lung; Liu, Mu-En
    Reviews in the Neurosciences (Berlin, Germany) (2013), 24 (4), 389-400CODEN: RNEUEO; ISSN:0334-1763. (Walter de Gruyter GmbH)
    A review. The dopamine hypothesis has been the cornerstone in the research and clin. practice of schizophrenia. With the initial emphasis on the role of excessive dopamine, the hypothesis has evolved to a concept of combining prefrontal hypodopaminergia and striatal hyperdopaminergia, and subsequently to the present aberrant salience hypothesis. This article provides a brief overview of the development and evidence of the dopamine hypothesis. It will argue that the current model of aberrant salience explains psychosis in schizophrenia and provides a plausible linkage between the pharmacol. and cognitive aspects of the disease. Despite the privileged role of dopamine hypothesis in psychosis, its pathophysiol. rather than etiol. basis, its limitations in defining symptoms other than psychosis, as well as the evidence of other neurotransmitters such as glutamate and adenosine, prompt us to a wider perspective of the disease. Finally, dopamine does explain the pathophysiol. of schizophrenia, but not necessarily the cause per se. Rather, dopamine acts as the common final pathway of a wide variety of predisposing factors, either environmental, genetic, or both, that lead to the disease. Other neurotransmitters, such as glutamate and adenosine, may also collaborate with dopamine to give rise to the entire picture of schizophrenia.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmslSqsbk%253D&md5=5eebc79abcee91d4045c849e8561bc70
  5. 5
    Beaulieu, J.-M.; Gainetdinov, R. R. The Physiology, Signaling, and Pharmacology of Dopamine Receptors. Pharmacol. Rev. 2011, 63, 182– 217,  DOI: 10.1124/pr.110.002642
    Google Scholar
    5
    The physiology, signaling, and pharmacology of dopamine receptors
    Beaulieu, Jean-Martin; Gainetdinov, Raul R.
    Pharmacological Reviews (2011), 63 (1), 182-217CODEN: PAREAQ; ISSN:0031-6997. (American Society for Pharmacology and Experimental Therapeutics)
    A review. G protein-coupled dopamine receptors (D1, D2, D3, D4, and D5) mediate all of the physiol. functions of the catecholaminergic neurotransmitter dopamine, ranging from voluntary movement and reward to hormonal regulation and hypertension. Pharmacol. agents targeting dopaminergic neurotransmission have been clin. used in the management of several neurol. and psychiatric disorders, including Parkinson's disease, schizophrenia, bipolar disorder, Huntington's disease, attention deficit hyperactivity disorder (ADHD1), and Tourette's syndrome. Numerous advances have occurred in understanding the general structural, biochem., and functional properties of dopamine receptors that have led to the development of multiple pharmacol. active compds. that directly target dopamine receptors, such as antiparkinson drugs and antipsychotics. Recent progress in understanding the complex biol. of dopamine receptor-related signal transduction mechanisms has revealed that, in addn. to their primary action on cAMP-mediated signaling, dopamine receptors can act through diverse signaling mechanisms that involve alternative G protein coupling or through G protein-independent mechanisms via interactions with ion channels or proteins that are characteristically implicated in receptor desensitization, such as β-arrestins. One of the future directions in managing dopamine-related pathol. conditions may involve a transition from the approaches that directly affect receptor function to a precise targeting of postreceptor intracellular signaling modalities either directly or through ligand-biased signaling pharmacol. In this comprehensive review, we discuss dopamine receptor classification, their basic structural and genetic organization, their distribution and functions in the brain and the periphery, and their regulation and signal transduction mechanisms. In addn., we discuss the abnormalities of dopamine receptor expression, function, and signaling that are documented in human disorders and the current pharmacol. and emerging trends in the development of novel therapeutic agents that act at dopamine receptors and/or on related signaling events.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXjslGis70%253D&md5=53e6841062c98abe60c732692109e498
  6. 6
    Parsons, M. J.; Mata, I.; Beperet, M.; Iribarren-Iriso, F.; Arroyo, B.; Sainz, R.; Arranz, M. J.; Kerwin, R. A Dopamine D2 Receptor Gene-Related Polymorphism Is Associated with Schizophrenia in a Spanish Population Isolate. Psychiatr. Genet. 2007, 17, 159– 163,  DOI: 10.1097/YPG.0b013e328017f8a4
    Google Scholar
    6
    A dopamine D2 receptor gene-related polymorphism is associated with schizophrenia in a Spanish population isolate
    Parsons Michael J; Mata Ignacio; Beperet Maria; Iribarren-Iriso Fernando; Arroyo Barbara; Sainz Ricardo; Arranz Maria J; Kerwin Robert
    Psychiatric genetics (2007), 17 (3), 159-63 ISSN:0955-8829.
    Numerous lines of evidence have highlighted the involvement of the dopamine system in the pathophysiology of schizophrenia. Association studies of dopaminergic genes such as the dopamine D2 receptor gene (DRD2), however, have produced contradictory results. To test the hypothesis that DRD2 polymorphisms are associated with schizophrenia, we investigated two DRD2-related polymorphisms (TaqI A1/A2 or rs1800497 and -141-C Ins/Del or rs1799732) in a Spanish population isolate from northern Spain consisting of 165 controls and 119 patients with schizophrenia. The TaqI A1 allele was less frequent in schizophrenic patients than in controls (P=0.002). A similar association was found for the TaqI A2/A2 genotype (P=0.0003). No association was found for the DRD2 -141-C Ins/Del polymorphism. The strong association between a potentially functional polymorphism, downstream of the DRD2 gene and schizophrenia, suggests that the direct or indirect functional effects of this polymorphism, acting on either the ANKK1 or DRD2 genes, may play a role in the pathophysiology of schizophrenia.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2s3htlGluw%253D%253D&md5=073be53eee6c5543dbc42e1fa22742a6
  7. 7
    Bertram, L. Genetic Research in Schizophrenia: New Tools and Future Perspectives. Schizophr. Bull. 2008, 34, 806– 812,  DOI: 10.1093/schbul/sbn079
    Google Scholar
    7
    Genetic research in schizophrenia: new tools and future perspectives
    Bertram Lars
    Schizophrenia bulletin (2008), 34 (5), 806-12 ISSN:0586-7614.
    Genetically, schizophrenia is a complex disease whose pathogenesis is likely governed by a number of different risk factors. While substantial efforts have been made to identify the underlying susceptibility alleles over the past 2 decades, they have been of only limited success. Each year, the field is enriched with nearly 150 additional genetic association studies, each of which either proposes or refutes the existence of certain schizophrenia genes. To facilitate the evaluation and interpretation of these findings, we have recently created a database for genetic association studies in schizophrenia ("SzGene"; available at http://www.szgene.org). In addition to systematically screening the scientific literature for eligible studies, SzGene also reports the results of allele-based meta-analyses for polymorphisms with sufficient genotype data. Currently, these meta-analyses highlight not only over 20 different potential schizophrenia genes, many of which represent the "usual suspects" (eg, various dopamine receptors and neuregulin 1), but also several that were never meta-analyzed previously. All the highlighted loci contain at least one variant showing modest (summary odds ratios approximately 1.20 [range 1.06-1.45]) but nominally significant risk effects. This review discusses some of the strengths and limitations of the SzGene database, which could become a useful bioinformatics tool within the schizophrenia research community.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1cnitFGrug%253D%253D&md5=d08d199281d7717b0dbeb68ff7e2a53f
  8. 8
    Rondou, P.; Haegeman, G.; Van Craenenbroeck, K. The Dopamine D4 Receptor: Biochemical and Signalling Properties. Cell. Mol. Life Sci. 2010, 67, 1971– 1986,  DOI: 10.1007/s00018-010-0293-y
    Google Scholar
    8
    The dopamine D4 receptor: biochemical and signalling properties
    Rondou, Pieter; Haegeman, Guy; Van Craenenbroeck, Kathleen
    Cellular and Molecular Life Sciences (2010), 67 (12), 1971-1986CODEN: CMLSFI; ISSN:1420-682X. (Birkhaeuser Verlag)
    A review. Dopamine is an important neurotransmitter that regulates several key functions in the brain, such as motor output, motivation and reward, learning and memory, and endocrine regulation. Dopamine does not mediate fast synaptic transmission, but rather modulates it by triggering slow-acting effects through the activation of dopamine receptors, which belong to the G-protein-coupled receptor superfamily. Besides activating different effectors through G-protein coupling, dopamine receptors also signal through interaction with a variety of proteins, collectively termed dopamine receptor-interacting proteins. We focus on the dopamine D4 receptor, which contains an important polymorphism in its third intracellular loop. This polymorphism has been the subject of numerous studies investigating links with several brain disorders, such as attention-deficit hyperactivity disorder and schizophrenia. We provide an overview of the structure, signaling properties and regulation of dopamine D4 receptors, and briefly discuss their physiol. and pathophysiol. role in the brain.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsFyrurY%253D&md5=ba05c503a292b3a300db61c76d394095
  9. 9
    Gómez-Restrepo, C. Guía de práctica clínica para el diagnóstico, tratamiento e inicio de la rehabilitación psicosocial de los adultos con esquizofrenia. Rev. Colomb. Psiquiatr. 2014, 44, 1– 2,  DOI: 10.1016/j.rcp.2015.05.014
    Google Scholar
    9
    Clinical Practice Guidelines for Diagnosis, Treatment and Beginning of Psychosocial Rehabilitation of Adults With Schizophrenia: "Do Well the Things That do Well"
    Gomez-Restrepo Carlos
    Revista colombiana de psiquiatria (2014), 44 Suppl 1 (), 1-2 ISSN:0034-7450.
    There is no expanded citation for this reference.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28vjvVaruw%253D%253D&md5=1a061db3900b4a39d08b1156b31fd0e8
  10. 10
    Goto, A.; Mouri, A.; Nagai, T.; Yoshimi, A.; Ukigai, M.; Tsubai, T.; Hida, H.; Ozaki, N.; Noda, Y. Involvement of the Histamine H4 Receptor in Clozapine-Induced Hematopoietic Toxicity: Vulnerability under Granulocytic Differentiation of HL-60 Cells. Toxicol. Appl. Pharmacol. 2016, 306, 8– 16,  DOI: 10.1016/j.taap.2016.06.028
    Google Scholar
    10
    Involvement of the histamine H4 receptor in clozapine-induced hematopoietic toxicity: Vulnerability under granulocytic differentiation of HL-60 cells
    Goto, Aya; Mouri, Akihiro; Nagai, Tomoko; Yoshimi, Akira; Ukigai, Mako; Tsubai, Tomomi; Hida, Hirotake; Ozaki, Norio; Noda, Yukihiro
    Toxicology and Applied Pharmacology (2016), 306 (), 8-16CODEN: TXAPA9; ISSN:0041-008X. (Elsevier Inc.)
    Clozapine is an effective antipsychotic for treatment-resistant schizophrenia, but can cause fatal hematopoietic toxicity as agranulocytosis. To elucidate the mechanism of hematopoietic toxicity induced by clozapine, we developed an in vitro assay system using HL-60 cells, and investigated the effect on hematopoiesis. HL-60 cells were differentiated by all-trans retinoic acid (ATRA) into three states according to the following hematopoietic process: undifferentiated HL-60 cells, those undergoing granulocytic ATRA-differentiation, and ATRA-differentiated granulocytic cells. Hematopoietic toxicity was evaluated by analyzing cell survival, cell proliferation, granulocytic differentiation, apoptosis, and necrosis. In undifferentiated HL-60 cells and ATRA-differentiated granulocytic cells, both clozapine (50 and 100 μM) and doxorubicin (0.2 μM) decreased the cell survival rate, but olanzapine (1-100 μM) did not. Under granulocytic differentiation for 5 days, clozapine, even at a concn. of 25 μM, decreased survival without affecting granulocytic differentiation, increased caspase activity, and caused apoptosis rather than necrosis. Histamine H4 receptor mRNA was expressed in HL-60 cells, whereas the expression decreased under granulocytic ATRA-differentiation little by little. Both thioperamide, a histamine H4 receptor antagonist, and DEVD-FMK, a caspase-3 inhibitor, exerted protection against clozapine-induced survival rate redn., but not of live cell counts. 4-Methylhistamine, a histamine H4 receptor agonist, decreased the survival rate and live cell counts, as did clozapine. HL-60 cells under granulocytic differentiation are vulnerable under in vitro assay conditions to hematopoietic toxicity induced by clozapine. Histamine H4 receptor is involved in the development of clozapine-induced hematopoietic toxicity through apoptosis, and may be a potential target for preventing its occurrence through granulocytic differentiation.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFams73P&md5=8e85539beabf52a04646e356d6ac1917
  11. 11
    Seeman, P.; Weinshenker, D.; Quirion, R.; Srivastava, L. K.; Bhardwaj, S. K.; Grandy, D. K.; Premont, R. T.; Sotnikova, T. D.; Boksa, P.; El-Ghundi, M. Dopamine Supersensitivity Correlates with D2High States, Implying Many Paths to Psychosis. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 3513– 3518,  DOI: 10.1073/pnas.0409766102
    Google Scholar
    11
    Dopamine supersensitivity correlates with D2High states, implying many paths to psychosis
    Seeman, Philip; Weinshenker, David; Quirion, Remi; Srivastava, Lalit K.; Bhardwaj, Sanjeev K.; Grandy, David K.; Premont, Richard T.; Sotnikova, Tatyana D.; Boksa, Patricia; El-Ghundi, Mufida; O'Dowd, Brian F.; George, Susan R.; Perreault, Melissa L.; Maennistoe, Pekka T.; Robinson, Siobhan; Palmiter, Richard D.; Tallerico, Teresa
    Proceedings of the National Academy of Sciences of the United States of America (2005), 102 (9), 3513-3518CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Dopamine supersensitivity occurs in schizophrenia and other psychoses, and after hippocampal lesions, antipsychotics, ethanol, amphetamine, phencyclidine, gene knockouts of Dbh (dopamine β-hydroxylase), Drd4 receptors, Gprk6 (G protein-coupled receptor kinase 6), Comt (catechol-O-methyltransferase), or Th-/-, DbhTh/+ (tyrosine hydroxylase), and in rats born by Cesarean-section. The functional state of D2, or the high-affinity state for dopamine (D2High), was measured in these supersensitive animal brain striata. Increased levels and higher proportions (40-900%) for D2High were found in all these tissues. If many types of brain impairment cause dopamine behavioral supersensitivity and a common increase in D2High states, it suggests that there are many pathways to psychosis, any one of which can be disrupted.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXitl2ksrk%253D&md5=3682a5e9a39d2eeda2ac383dc3c8e6da
  12. 12
    Seeman, P.; Ko, F.; Jack, E.; Greenstein, R.; Dean, B. Consistent with Dopamine Supersensitivity, RGS9 Expression Is Diminished in the Amphetamine-Treated Animal Model of Schizophrenia and in Postmortem Schizophrenia Brain. Synapse 2007, 61, 303– 309,  DOI: 10.1002/syn.20368
    Google Scholar
    12
    Consistent with dopamine supersensitivity, RGS9 expression is diminished in the amphetamine-treated animal model of schizophrenia and in postmortem schizophrenia brain
    Seeman, Philip; Ko, Francoise; Jack, Elaine; Greenstein, Rachel; Dean, Brian
    Synapse (Hoboken, NJ, United States) (2007), 61 (5), 303-309CODEN: SYNAET; ISSN:0887-4476. (Wiley-Liss, Inc.)
    It is known that RGS9-2 gene knockout mice show supersensitivity to DA and have a marked elevation in the proportion of DA D2 receptors in the high-affinity state for DA (D2High receptors). As this is a similar profile to that obsd. in the CNS from subjects with schizophrenia, we examd. whether postmortem CNS tissue from subjects with the disorder and brain striata from an animal model of psychosis or schizophrenia (the amphetamine-sensitized rat) had altered levels of RGS9-2. The mRNA for RGS9-2 in 29 control hippocampi was 0.185±0.015 fg per fg of β-glucuronidase mRNA (av. ± SE), while that in 29 schizophrenia hippocampi was 0.145±0.015 fg per fg of β-glucuronidase mRNA (av. ± SE), a redn. of 22%. Of the many receptor-regulating genes related to G proteins, and of 11 RGS genes, RGS9-2 was the most reduced in the amphetamine-sensitized rat striatum. The reduced levels of RGS9-2 expression in both an animal model of schizophrenia and a postmortem schizophrenia brain provide further evidence implicating RGS9-2 as a candidate gene in schizophrenia.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXjtlWjtbY%253D&md5=9354ccb04cb95001edbe634136ee2306
  13. 13
    Gaspar, H. A.; Breen, G. Drug Enrichment and Discovery from Schizophrenia Genome-Wide Association Results: An Analysis and Visualisation Approach. Sci. Rep. 2017, 7, 12460,  DOI: 10.1038/s41598-017-12325-3
    Google Scholar
    13
    Drug enrichment and discovery from schizophrenia genome-wide association results: an analysis and visualisation approach
    Gaspar H A; Breen G; Gaspar H A; Breen G
    Scientific reports (2017), 7 (1), 12460 ISSN:.
    Using successful genome-wide association results in psychiatry for drug repurposing is an ongoing challenge. Databases collecting drug targets and gene annotations are growing and can be harnessed to shed a new light on psychiatric disorders. We used genome-wide association study (GWAS) summary statistics from the Psychiatric Genetics Consortium (PGC) Schizophrenia working group to build a drug repositioning model for schizophrenia. As sample size increases, schizophrenia GWAS results show increasing enrichment for known antipsychotic drugs, selective calcium channel blockers, and antiepileptics. Each of these therapeutical classes targets different gene subnetworks. We identify 123 Bonferroni-significant druggable genes outside the MHC, and 128 FDR-significant biological pathways related to neurons, synapses, genic intolerance, membrane transport, epilepsy, and mental disorders. These results suggest that, in schizophrenia, current well-powered GWAS results can reliably detect known schizophrenia drugs and thus may hold considerable potential for the identification of new therapeutic leads. Moreover, antiepileptics and calcium channel blockers may provide repurposing opportunities. This study also reveals significant pathways in schizophrenia that were not identified previously, and provides a workflow for pathway analysis and drug repurposing using GWAS results.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1M%252FjvVKgtg%253D%253D&md5=b85b2cb96083a4683defa07536a9aab1
  14. 14
    Zhao, K.; So, H.-C. Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data. IEEE J. Biomed. Health Inf. 2019, 23, 1304– 1315,  DOI: 10.1109/JBHI.2018.2856535
    Google Scholar
    14
    Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data
    Zhao Kai; So Hon-Cheong
    IEEE journal of biomedical and health informatics (2019), 23 (3), 1304-1315 ISSN:.
    Development of new medications is a lengthy and costly process, and drug repositioning might help to shorten the development cycle. We present a machine learning (ML) workflow to drug discovery or repositioning by predicting indication for a particular disease based on drug expression profiles, with a focus on applications in psychiatry. Drugs that are not originally indicated for the disease but with high predicted probabilities serve as candidates for repurposing. This approach is widely applicable to any chemicals or drugs with expression profiles measured, even if drug targets are unknown. It is also highly flexible as virtually any supervised learning algorithms can be used. We employed the ML approach to identify repositioning opportunities for schizophrenia as well as depression and anxiety disorders. We applied various state-of-the-art ML approaches, including deep neural networks (DNNs), support vector machines (SVMs), elastic net regression, random forest, and gradient boosted trees. The predictive performance of the five approaches in cross validation did not differ substantially, with SVM slightly outperforming the others. However, other methods also reveal literature-supported repositioning candidates of different mechanisms of actions. As a further validation, we showed that the repositioning hits are enriched for psychiatric medications considered in clinical trials. We also examined the correlation between predicted probabilities of treatment potential and the number of related research articles, and found significant correlations for all methods, especially DNN. Finally, we propose that ML may provide a new avenue to exploring drug mechanisms via examining the variable importance of gene features.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3c%252FosVCgtw%253D%253D&md5=d19b972d8f957c5677a15af11c4d8e44
  15. 15
    Karunakaran, K. B.; Chaparala, S.; Ganapathiraju, M. K. Potentially Repurposable Drugs for Schizophrenia Identified from Its Interactome. Sci. Rep. 2019, 9, 12682,  DOI: 10.1038/s41598-019-48307-w
    Google Scholar
    15
    Potentially repurposable drugs for schizophrenia identified from its interactome
    Karunakaran Kalyani B; Chaparala Srilakshmi; Ganapathiraju Madhavi K; Ganapathiraju Madhavi K
    Scientific reports (2019), 9 (1), 12682 ISSN:.
    We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3MrkvVCnsg%253D%253D&md5=5a63e8a658a7dd64983aa7047a8d005b
  16. 16
    Lee, J. H.; Cho, S. J.; Kim, M.-H. Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening. Molecules 2018, 23, 2452,  DOI: 10.3390/molecules23102452
    Google Scholar
    There is no corresponding record for this reference.
  17. 17
    Lemos, A.; Melo, R.; Preto, A. J.; Almeida, J. G.; Moreira, I. S.; Dias Soeiro Cordeiro, M. N. In Silico Studies Targeting G-Protein Coupled Receptors for Drug Research Against Parkinson’s Disease. Curr. Neuropharmacol. 2018, 16, 786– 848,  DOI: 10.2174/1570159X16666180308161642
    Google Scholar
    17
    In Silico Studies Targeting G-protein Coupled Receptors for Drug Research Against Parkinson's Disease
    Lemos, Agostinho; Melo, Rita; Preto, Antonio Jose; Almeida, Jose Guilherme; Moreira, Irina Sousa; Dias Soeiro Cordeiro, Maria Natalia
    Current Neuropharmacology (2018), 16 (6), 786-848CODEN: CNUEAN; ISSN:1875-6190. (Bentham Science Publishers Ltd.)
    A review. Parkinson's Disease (PD) is a long-term neurodegenerative brain disorder that mainly affects the motor system. The causes are still unknown, and even though currently there is no cure, several therapeutic options are available to manage its symptoms. The development of novel antiparkinsonian agents and an understanding of their proper and optimal use are, indeed, highly demanding. For the last decades, L-3,4-DihydrOxyPhenylAlanine or levodopa (L-DOPA) has been the gold-std. therapy for the symptomatic treatment of motor dysfunctions assocd. to PD. However, the development of dyskinesias and motor fluctuations (wearing-off and on-off phenomena) assocd. with long-term L-DOPA replacement therapy have limited its antiparkinsonian efficacy. The investigation for non-dopaminergic therapies has been largely explored as an attempt to counteract the motor side effects assocd. with dopamine replacement therapy. Being one of the largest cell membrane protein families, G-Protein-Coupled Receptors (GPCRs) have become a relevant target for drug discovery focused on a wide range of therapeutic areas, including Central Nervous System (CNS) diseases. The modulation of specific GPCRs potentially implicated in PD, excluding dopamine receptors, may provide promising non-dopaminergic therapeutic alternatives for symptomatic treatment of PD. In this review, we focused on the impact of specific GPCR subclasses, including dopamine receptors, adenosine receptors, muscarinic acetylcholine receptors, metabotropic glutamate receptors, and 5-hydroxytryptamine receptors, on the pathophysiol. of PD and the importance of structure- and ligand-based in silico approaches for the development of small mols. to target these receptors.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFCjsb7M&md5=0408f396ca24d349682e712b3c68bb6a
  18. 18
    Ishiki, H. M.; Filho, J. M. B.; da Silva, M. S.; Scotti, M. T.; Scotti, L. Computer-Aided Drug Design Applied to Parkinson Targets. Curr. Neuropharmacol. 2018, 16, 865– 880,  DOI: 10.2174/1570159X15666171128145423
    Google Scholar
    18
    Computer-aided Drug Design Applied to Parkinson Targets
    Ishiki, Hamilton M.; Barbosa Filho, Jose Maria; da Silva, Marcelo S.; Scotti, Marcus T.; Scotti, Luciana
    Current Neuropharmacology (2018), 16 (6), 865-880CODEN: CNUEAN; ISSN:1875-6190. (Bentham Science Publishers Ltd.)
    Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by debilitating motor deficits, as well as autonomic problems, cognitive declines, changes in affect and sleep disturbances. Although the scientific community has performed great efforts in the study of PD, and from the most diverse points of view, the disease remains incurable. The exact mechanism underlying its progression is unclear, but oxidative stress, mitochondrial dysfunction and inflammation are thought to play major roles in the etiol. Objective: Current pharmacol. therapies for the treatment of Parkinson's disease are mostly inadequate, and new therapeutic agents are much needed. Methods: In this review, recent advances in computer-aided drug design for the rational design of new compds. against Parkinson disease; using methods such as Quant. Structure-Activity Relationships (QSAR), mol. docking, mol. dynamics and pharmacophore modeling are discussed. Results: In this review, four targets were selected: the enzyme monoamine oxidase, dopamine agonists, acetylcholine receptors, and adenosine receptors. Conclusion: Computer aided-drug design enables the creation of theor. models that can be used in a large database to virtually screen for and identify novel candidate mols.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFCjsb%252FE&md5=b6a5f7cd809bcadca64069bb831385e9
  19. 19
    Zhao, Y.; Lu, X.; Yang, C.-Y.; Huang, Z.; Fu, W.; Hou, T.; Zhang, J. Computational Modeling toward Understanding Agonist Binding on Dopamine 3. J. Chem. Inf. Model. 2010, 50, 1633– 1643,  DOI: 10.1021/ci1002119
    Google Scholar
    19
    Computational Modeling Toward Understanding Agonist Binding on Dopamine 3
    Zhao, Yaxue; Lu, Xuefeng; Yang, Chao-yie; Huang, Zhimin; Fu, Wei; Hou, Tingjun; Zhang, Jian
    Journal of Chemical Information and Modeling (2010), 50 (9), 1633-1643CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    The dopamine 3 (D3) receptor is a promising therapeutic target for the treatment of nervous system disorders, such as Parkinson's disease, and current research interests primarily focus on the discovery/design of potent D3 agonists. Herein, a well-designed computational protocol, which combines pharmacophore identification, homol. modeling, mol. docking, and mol. dynamics (MD) simulations, was employed to understand the agonist binding on D3 aiming to provide insights into the development of novel potent D3 agonists. We (1) identified the chem. features required in effective D3 agonists by pharmacophore modeling based upon 18 known diverse D3 agonists; (2) constructed the three-dimensional (3D) structure of D3 based on homol. modeling and the pharmacophore hypothesis; (3) identified the binding modes of the agonists to D3 by the correlation between the predicted binding free energies and the exptl. values; and (4) investigated the induced fit of D3 upon agonist binding through MD simulations. The pharmacophore models of the D3 agonists and the 3D structure of D3 can be used for either ligand- or receptor-based drug design. Furthermore, the MD simulations further give the insight that the long and flexible EL2 acts as a "door" for agonist binding, and the "ionic lock" at the bottom of TM3 and TM6 is essential to transduce the activation signal.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXpvVyltb0%253D&md5=081203310cb1e39f2710c70d50903c4d
  20. 20
    Kaserer, T.; Beck, K. R.; Akram, M.; Odermatt, A.; Schuster, D. Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases. Molecules 2015, 20, 22799– 22832,  DOI: 10.3390/molecules201219880
    Google Scholar
    20
    Pharmacophore models and pharmacophore-based virtual screening: concepts and applications exemplified on hydroxysteroid dehydrogenases
    Kaserer, Teresa; Beck, Katharina R.; Akram, Muhammad; Odermatt, Alex; Schuster, Daniela
    Molecules (2015), 20 (12), 22799-22832CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
    Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship anal. and selectivity profiling. In addn., compd.-target interactions assocd. with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are assocd. with specific pathol. conditions, and pharmacol. modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biol. functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XmtlKmtA%253D%253D&md5=b6492b9deafadc8dba3ad24eb54f2eb5
  21. 21
    Ferraro, M.; Decherchi, S.; De Simone, A.; Recanatini, M.; Cavalli, A.; Bottegoni, G. Multi-Target Dopamine D3 Receptor Modulators: Actionable Knowledge for Drug Design from Molecular Dynamics and Machine Learning. Eur. J. Med. Chem. 2020, 188, 111975,  DOI: 10.1016/j.ejmech.2019.111975
    Google Scholar
    21
    Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning
    Ferraro, Mariarosaria; Decherchi, Sergio; De Simone, Alessio; Recanatini, Maurizio; Cavalli, Andrea; Bottegoni, Giovanni
    European Journal of Medicinal Chemistry (2020), 188 (), 111975CODEN: EJMCA5; ISSN:0223-5234. (Elsevier Masson SAS)
    Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacol. profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, mol. dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we obsd. how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFCjtLk%253D&md5=706046edea065032891083a4afe8ccd0
  22. 22
    Bhargava, K.; Nath, R.; Seth, P. K.; Pant, K. K.; Dixit, R. K. Molecular Docking Studies of D2 Dopamine Receptor with Risperidone Derivatives. Bioinformation 2014, 10, 8– 12,  DOI: 10.6026/97320630010008
    Google Scholar
    22
    Molecular Docking studies of D2 Dopamine receptor with Risperidone derivatives
    Bhargava Kiran; Nath Rajendra; Pant Kamlesh Kumar; Dixit Rakesh Kumar; Seth Prahlad Kumar
    Bioinformation (2014), 10 (1), 8-12 ISSN:0973-2063.
    In this work, 3D model of D2 dopamine receptor was determined by comparative homology modeling program MODELLER. The computed model's energy was minimized and validated using PROCHECK and Errat tool to obtain a stable model structure and was submitted in Protein Model Database (PMDB-ID: PM0079251). Stable model was used for molecular docking against Risperidone and their 15 derivatives using AutoDock 4.2, which resulted in energy-based descriptors such as Binding Energy, Ligand Efficiency, Inhib Constant, Intermol energy, vdW + Hbond + desolv Energy, Electrostatic Energy, Total Internal Energy and Torsional Energy. After that, we have built quantitative structure activity relationship (QSAR) model, which was trained and tested on Risperidone and their 15 derivatives having activity value pKi in μM. For QSAR modeling, Multiple Linear Regression model was engendered using energy-based descriptors yielding correlation coefficient r2 of 0.513. To assess the predictive performance of QSAR models, different cross-validation procedures were adopted. Our results suggests that ligand-receptor binding interactions for D2 employing QSAR modeling seems to be a promising approach for prediction of pKi value of novel antagonists against D2 receptor.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cvkt1yhsg%253D%253D&md5=b6cd065fbd6fd72f510bbe90265c4c07
  23. 23
    Bueschbell, B.; Barreto, C. A. V.; Preto, A. J.; Schiedel, A. C.; Moreira, I. S. A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods. Molecules 2019, 24, 1196,  DOI: 10.3390/molecules24071196
    Google Scholar
    23
    A complete assessment of dopamine receptor- ligand interactions through computational methods
    Bueschbell, Beatriz; Barreto, Carlos A. V.; Preto, Antonio J.; Schiedel, Anke C.; Moreira, Irina S.
    Molecules (2019), 24 (7), 1196/1-1196/26CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
    Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a mol. basis has not been fully elucidated. Homol. modeling and mol. dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Residues of the arom. microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D1R-like selective ligands binding. This in silico approach was successful in showing known receptor-ligand interactions as well as in detg. unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXpt1Kqurk%253D&md5=ca3ad005e1b89b15daba57c3065a13b3
  24. 24
    Trott, O.; Olson, A. J. AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. J. Comput. Chem. 2010, 31, 455– 461,  DOI: 10.1002/jcc.21334
    Google Scholar
    24
    AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
    Trott, Oleg; Olson, Arthur J.
    Journal of Computational Chemistry (2010), 31 (2), 455-461CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    AutoDock Vina, a new program for mol. docking and virtual screening, is presented. AutoDock Vina achieves an approx. 2 orders of magnitude speed-up compared with the mol. docking software previously developed in the authors' lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by the authors' tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calcs. the grid maps and clusters the results in a way transparent to the user.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFGnur3O&md5=c6974af8a1235f7aa09918d3e6f70dc4
  25. 25
    Krautscheid, Y.; Senning, C. J. Å.; Sartori, S. B.; Singewald, N.; Schuster, D.; Stuppner, H. Pharmacophore Modeling, Virtual Screening, and in Vitro Testing Reveal Haloperidol, Eprazinone, and Fenbutrazate as Neurokinin Receptors Ligands. J. Chem. Inf. Model. 2014, 54, 1747– 1757,  DOI: 10.1021/ci500106z
    Google Scholar
    25
    Pharmacophore Modeling, Virtual Screening, and in Vitro Testing Reveal Haloperidol, Eprazinone, and Fenbutrazate as Neurokinin Receptors Ligands
    Krautscheid, Yvonne; Senning, Carl Johann Ake; Sartori, Simone B.; Singewald, Nicolas; Schuster, Daniela; Stuppner, Hermann
    Journal of Chemical Information and Modeling (2014), 54 (6), 1747-1757CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Neurokinin receptors (NKRs) have been shown to be involved in many physiol. processes, rendering them promising novel drug targets, but also making them the possible cause for side effects of several drugs. Aiming to answer the question whether the binding to NKRs could have a share in the side effects or even the desired effects of already licensed drugs, we generated a set of ligand-based common feature pharmacophore models based on the structural information about subtype-selective and nonselective NKR antagonists and screened an inhouse database mainly composed of licensed drugs. The prospective pharmacol. investigations of the virtual hits haloperidol, eprazinone, and fenbutrazate confirmed them to be NKR ligands in vitro. By the identification of licensed drugs as so far unknown NKR ligands, this study contributes to establishing an activity profile of the investigated compds. and confirms the presented pharmacophore models as useful tools for this purpose.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotlWiurc%253D&md5=b0524d52e6b4519f3c0b31c9407ebe19
  26. 26
    Patel, C. N.; Georrge, J. J.; Modi, K. M.; Narechania, M. B.; Patel, D. P.; Gonzalez, F. J.; Pandya, H. A. Pharmacophore-Based Virtual Screening of Catechol-o-Methyltransferase (COMT) Inhibitors to Combat Alzheimer’s Disease. J. Biomol. Struct. Dyn. 2018, 36, 3938– 3957,  DOI: 10.1080/07391102.2017.1404931
    Google Scholar
    26
    Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease
    Patel, Chirag N.; Georrge, John J.; Modi, Krunal M.; Narechania, Moksha B.; Patel, Daxesh P.; Gonzalez, Frank J.; Pandya, Himanshu A.
    Journal of Biomolecular Structure and Dynamics (2018), 36 (15), 3938-3957CODEN: JBSDD6; ISSN:0739-1102. (Taylor & Francis Ltd.)
    Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metab., excretion, and toxicity) filtering by using FAF-Drug-3 and 36 mols. were considered for mol. docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the mol. dynamics simulation anal. having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of mol.-level interactions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlejug%253D%253D&md5=1ed8fea8f07705061d975843721636ed
  27. 27
    Floresta, G.; Crocetti, L.; Giovannoni, M. P.; Biagini, P.; Cilibrizzi, A. Repurposing Strategies on Pyridazinone-Based Series by Pharmacophore- and Structure-Driven Screening. J. Enzyme Inhib. Med. Chem. 2020, 35, 1137– 1144,  DOI: 10.1080/14756366.2020.1760261
    Google Scholar
    27
    Repurposing strategies on pyridazinone-based series by pharmacophore- and structure-driven screening
    Floresta, Giuseppe; Crocetti, Letizia; Giovannoni, Maria Paola; Biagini, Pierfrancesco; Cilibrizzi, Agostino
    Journal of Enzyme Inhibition and Medicinal Chemistry (2020), 35 (1), 1137-1144CODEN: JEIMAZ; ISSN:1475-6366. (Taylor & Francis Ltd.)
    We report here in silico repurposing studies on 52 new pyridazinone-based small-mols. through inverse virtual screening (iVS) methodologies. These analogs were originally designed as formyl peptide receptor (FPR) ligands. As it is sometimes the case in drug discovery programs, subsequent biol. screening demonstrated the inefficacy of the mols. in binding FPRs, failing in the identification of new hits. Through a focussed drug-repurposing approach we have defined a variety of potential targets that are suitable to interact with this library of pyridazinone-based analogs. A two-step approach has been conducted for computational anal. Specifically, the mols. were initially processed through a pharmacophore-based screening. Secondly, the resulting features of binding were investigated by docking studies and following mol. dynamic simulations, in order to univocally confirm "pyridazinone-based ligand-target protein" interactions. Our findings propose aspartate aminotransferase as the most favorable repurposed target for this small-mol. series, worth of addnl. medicinal chem. investigations in the field.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtVShu7zE&md5=504be4c1ccc2329b87cc7fc7fe53d186
  28. 28
    Kagami, L. P.; das Neves, G. M.; Rodrigues, R. P.; da Silva, V. B.; Eifler-Lima, V. L.; Kawano, D. F. Identification of a Novel Putative Inhibitor of the Plasmodium Falciparum Purine Nucleoside Phosphorylase: Exploring the Purine Salvage Pathway to Design New Antimalarial Drugs. Mol. Diversity 2017, 21, 677– 695,  DOI: 10.1007/s11030-017-9745-8
    Google Scholar
    28
    Identification of a novel putative inhibitor of the Plasmodium falciparum purine nucleoside phosphorylase: exploring the purine salvage pathway to design new antimalarial drugs
    Kagami, Luciano Porto; Machado das Neves, Gustavo; Rodrigues, Ricardo Pereira; Barreto da Silva, Vinicius; Eifler-Lima, Vera Lucia; Kawano, Daniel Fabio
    Molecular Diversity (2017), 21 (3), 677-695CODEN: MODIF4; ISSN:1381-1991. (Springer)
    Malaria, a tropical parasitic disease caused by Plasmodium spp., continues to place a heavy social burden, with almost 200 million cases and more than 580,000 deaths per yr. Plasmodium falciparum purine nucleoside phosphorylase (PfPNP) can be targeted for antimalarial drug design since its inhibition kills malaria parasites both in vitro and in vivo. Although the currently known inhibitors of PfPNP, immucillins, are orally available and of low toxicity to animals and humans, to the best of our knowledge, none of these compds. has entered clin. trials for the treatment of malaria. Using a pharmacophore-based virtual screening coupled to a consensual mol. docking approach, we identified 59 potential PfPNP inhibitors that are predicted to be orally absorbed in a Caco-2 cell model. Although most of these compds. are predicted to have high plasma protein binding levels, poor water soly. (except for compd. 25) and CYP3A4 metabolic stability (except for 4, 7 and 8), four structures (4, 7, 8 and 25) remain as potential leads because of their plausible interaction with a specific hydrophobic pocket of PfPNP, which would confer them higher selectivity for PfPNP over human PNP. Addnl., both predicted Gibbs free energies for binding and mol. dynamics suggest that compd. 4 may form a more stable complex with PfPNP than 5'-methylthio-immucillin-H, a potent and selective inhibitor of PfPNP.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXotVamur4%253D&md5=d6038621eb8d7b782460cac8ac1acb7c
  29. 29
    Kumar, S.; Chowdhury, S.; Kumar, S. In Silico Repurposing of Antipsychotic Drugs for Alzheimer’s Disease. BMC Neurosci. 2017, 18, 76,  DOI: 10.1186/s12868-017-0394-8
    Google Scholar
    29
    In silico repurposing of antipsychotic drugs for Alzheimer's disease
    Kumar, Shivani; Chowdhury, Suman; Kumar, Suresh
    BMC Neuroscience (2017), 18 (), 76/1-76/16CODEN: BNMEA6; ISSN:1471-2202. (BioMed Central Ltd.)
    Background: Alzheimer's disease (AD) is the most prevalent form of dementia and represents one of the highest unmet requirements in medicine today. There is shortage of novel mols. entering into market because of poor pharmacokinetic properties and safety issues. Drug repurposing offers an opportunity to reinvigorate the slowing drug discovery process by finding new uses for existing drugs. The major advantage of the drug repurposing approach is that the safety issues are already investigated in the clin. trials and the drugs are com. available in the marketplace. As this approach provides an effective soln. to hasten the process of providing new alternative drugs for AD, the current study shows the mol. interaction of already known antipsychotic drugs with the different protein targets implicated in AD using in silico studies. Result: A computational method based on ligand-protein interaction was adopted in present study to explore potential antipsychotic drugs for the treatment of AD. The screening of approx. 150 antipsychotic drugs was performed on five major protein targets (AChE, BuChE, BACE 1, MAO and NMDA) by mol. docking. In this study, for each protein target, the best drug was identified on the basis of dock score and glide energy. The top hits were then compared with the already known inhibitor of the resp. proteins. Some of the drugs showed relatively better docking score and binding energies as compared to the already known inhibitors of the resp. targets. Mol. descriptors like mol. wt., no. of hydrogen bond donors, acceptors, predicted octanol/water partition coeff. and percentage human oral absorption were also analyzed to det. the in silico ADME properties of these drugs and all were found in the acceptable range and follows Lipinski's rule. Conclusion: The present study have led to unravel the potential of leading antipsychotic drugs such as pimozide, bromperidol, melperone, anisoperidone, benperidol and anisopirol against multiple targets assocd. with AD. Benperidol was found to be the best candidate drug interacting with different target proteins involved in AD.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXlslGhsL0%253D&md5=977bad8bddde53997fd38addcf8c7207
  30. 30
    Dilly, S.; Fotso Fotso, A.; Lejal, N.; Zedda, G.; Chebbo, M.; Rahman, F.; Companys, S.; Bertrand, H. C.; Vidic, J.; Noiray, M. From Naproxen Repurposing to Naproxen Analogues and Their Antiviral Activity against Influenza A Virus. J. Med. Chem. 2018, 61, 7202– 7217,  DOI: 10.1021/acs.jmedchem.8b00557
    Google Scholar
    30
    From Naproxen Repurposing to Naproxen Analogues and Their Antiviral Activity against Influenza A Virus
    Dilly, Sebastien; Fotso Fotso, Aurelien; Lejal, Nathalie; Zedda, Gloria; Chebbo, Mohamad; Rahman, Fryad; Companys, Simon; Bertrand, Helene C.; Vidic, Jasmina; Noiray, Magali; Alessi, Marie-Christine; Tarus, Bogdan; Quideau, Stephane; Riteau, Beatrice; Slama-Schwok, Anny
    Journal of Medicinal Chemistry (2018), 61 (16), 7202-7217CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
    The nucleoprotein (NP) of influenza A virus (IAV) required for IAV replication is a promising target for new antivirals. The authors previously identified by in silico screening naproxen being a dual inhibitor of NP and cyclooxygenase COX2, thus combining antiviral and anti-inflammatory effects. However, the recently shown strong COX2 antiviral potential makes COX2 inhibition undesirable. Here the authors designed and synthesized two new series of naproxen analogs called derivs. 2, 3 (5-(4-aminophenoxy)-2-(6-methoxynaphthalen-2-yl)isophthalic acid), and 4 (4-(4-aminophenoxy)-2-(6-methoxynaphthalen-2-yl)isophthalic acid) targeting highly conserved residues of the RNA binding groove, stabilizing NP monomer without inhibiting COX2. Deriv. 2 presented improved antiviral effects in infected cells compared to that of naproxen and afforded a total protection of mice against a lethal viral challenge. Deriv. 4 also protected infected cells challenged with circulating 2009-pandemic and oseltamivir-resistant H1N1 virus. This improved antiviral effect likely results from derivs. 2 and 4 inhibiting NP-RNA and NP-polymerase acidic subunit PA N-terminal interactions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlGit7jI&md5=a3d21246bea09e82edd808d1e14a54ee
  31. 31
    Teli, M. K.; Rajanikant, G. K. Computational Repositioning and Experimental Validation of Approved Drugs for HIF-Prolyl Hydroxylase Inhibition. J. Chem. Inf. Model. 2013, 53, 1818– 1824,  DOI: 10.1021/ci400254a
    Google Scholar
    31
    Computational Repositioning and Experimental Validation of Approved Drugs for HIF-Prolyl Hydroxylase Inhibition
    Teli, Mahesh Kumar; G. K., Rajanikant
    Journal of Chemical Information and Modeling (2013), 53 (7), 1818-1824CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    HIF stability and activation are governed by a family of dioxygenases called HIF prolyl-4-hydroxylases (PHDs). It has been identified as a new target to augment the adaptive machinery that governs cytoprotection in disorders assocd. with ischemia/reperfusion, inflammation, and oxidative stress. In this sense, PHD inhibition has been proposed to mimic, at least in part, the protective effects of exposure to hypoxia. Exploiting drug polypharmacol. to identify novel modes of actions for drug repurposing has gained significant attention in the current era of weak drug pipelines. The present work plan aims at giving new purpose to some well-established FDA-approved drugs. Here, we propose that by combining the literature survey, docking, and manual interpretation altogether, we were able to perform virtual screening on FDA-approved drugs to identify potential PHD inhibitors. Upon screening of 1537 marketed drugs, a final set of six hits were selected for exptl. testing. All six drugs were divers, and immuno blotting was carried out to evaluate their ability to upregulate HIF in order to validate our hypothesis. Out of the six, three drugs showed significant upregulation of HIF possibly by inhibiting the PHD. It is believed that the appropriate use of the literature survey, docking, manual interpretation, and exptl. validation strategy in the drug design process should improve the ability to identify hits and confirm their potential to serve as basis for drug repurposing.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpvV2jt78%253D&md5=d5630c21fed2cb29d10050418fb8bcd7
  32. 32
    Macalino, S. J. Y.; Gosu, V.; Hong, S. Role of computer-aided drug design in modern drug discovery. Arch. Pharmacal Res. 2015, 38, 1686– 1701,  DOI: 10.1007/s12272-015-0640-5
    Google Scholar
    32
    Role of computer-aided drug design in modern drug discovery
    Macalino, Stephani Joy Y.; Gosu, Vijayakumar; Hong, Sunhye; Choi, Sun
    Archives of Pharmacal Research (2015), 38 (9), 1686-1701CODEN: APHRDQ; ISSN:0253-6269. (Pharmaceutical Society of Korea)
    A review. Drug discovery utilizes chem. biol. and computational drug design approaches for the efficient identification and optimization of lead compds. Chem. biol. is mostly involved in the elucidation of the biol. function of a target and the mechanism of action of a chem. modulator. Computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the detn. of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are crit. for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with exptl. routines, has a powerful impact on rational drug design. In this article, the authors give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXht1aktbzN&md5=9eeb85337b2d2d8261f062f726e8c46e
  33. 33
    Liu, X.; Shi, D.; Zhou, S.; Liu, H.; Liu, H.; Yao, X. Molecular Dynamics Simulations and Novel Drug Discovery. Expert Opin. Drug Discovery 2018, 13, 23– 37,  DOI: 10.1080/17460441.2018.1403419
    Google Scholar
    33
    Molecular dynamics simulations and novel drug discovery
    Liu, Xuewei; Shi, Danfeng; Zhou, Shuangyan; Liu, Hongli; Liu, Huanxiang; Yao, Xiaojun
    Expert Opinion on Drug Discovery (2018), 13 (1), 23-37CODEN: EODDBX; ISSN:1746-0441. (Taylor & Francis Ltd.)
    A review. Mol. dynamics (MD) simulations can provide not only plentiful dynamical structural information on biomacromols. but also a wealth of energetic information about protein and ligand interactions. Such information is very important to understanding the structure-function relationship of the target and the essence of protein-ligand interactions and to guiding the drug discovery and design process. Thus, MD simulations have been applied widely and successfully in each step of modern drug discovery.: In this review, the authors review the applications of MD simulations in novel drug discovery, including the pathogenic mechanisms of amyloidosis diseases, virtual screening and the interaction mechanisms between drugs and targets.: MD simulations have been used widely in investigating the pathogenic mechanisms of diseases caused by protein misfolding, in virtual screening, and in investigating drug resistance mechanisms caused by mutations of the target. These issues are very difficult to solve by exptl. methods alone. Thus, in the future, MD simulations will have wider application with the further improvement of computational capacity and the development of better sampling methods and more accurate force fields together with more efficient anal. methods.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhvVWmsb7J&md5=aad5a7f23a15e725d70a032399052191
  34. 34
    Do, P.-C.; Lee, E. H.; Le, L. Steered Molecular Dynamics Simulation in Rational Drug Design. J. Chem. Inf. Model. 2018, 58, 1473– 1482,  DOI: 10.1021/acs.jcim.8b00261
    Google Scholar
    34
    Steered Molecular Dynamics Simulation in Rational Drug Design
    Do, Phuc-Chau; Lee, Eric H.; Le, Ly
    Journal of Chemical Information and Modeling (2018), 58 (8), 1473-1482CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Conventional de novo drug design is time consuming, laborious, and resource intensive. In recent years, emerging in silico approaches have been proven to be crit. to accelerate the process of bringing drugs to market. Mol. dynamics (MD) simulations of single mol. and mol. complexes have been commonly applied to achieve accurate binding modes and binding energies of drug-receptor interactions. A deriv. of MD, namely, steered mol. dynamics (SMD), has been demonstrated as a promising tool for rational drug design. In this paper, we review various studies over the last 20 years using SMD simulations, thus paving the way to det. the relationship between protein structure and function. In addn., the paper highlights the use of SMD simulation for in silico drug design. We also aim to establish an understanding on the key interactions which play a crucial role in the stabilization of peptide-ligand interfaces, the binding and unbinding mechanism of the ligand-protein complex, the mechanism of ligand translocating via membrane, and the ranking of different ligands on receptors as therapeutic candidates.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1Klsr7O&md5=725ab4ae35861ece35c8ed56c12904b2
  35. 35
    Hodos, R. A.; Kidd, B. A.; Shameer, K.; Readhead, B. P.; Dudley, J. T. In Silico Methods for Drug Repurposing and Pharmacology. Wiley Interdiscip. Rev.: Syst. Biol. Med. 2016, 8, 186– 210,  DOI: 10.1002/wsbm.1337
    Google Scholar
    35
    In silico methods for drug repurposing and pharmacology
    Hodos Rachel A; Kidd Brian A; Shameer Khader; Readhead Ben P; Dudley Joel T; Hodos Rachel A
    Wiley interdisciplinary reviews. Systems biology and medicine (2016), 8 (3), 186-210 ISSN:.
    Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform these often complex and heterogeneous data into testable hypotheses and actionable insights. This is the aim of computational pharmacology, which uses in silico techniques to better understand and predict how drugs affect biological systems, which can in turn improve clinical use, avoid unwanted side effects, and guide selection and development of better treatments. One exciting application of computational pharmacology is drug repurposing-finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we argue that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action. WIREs Syst Biol Med 2016, 8:186-210. doi: 10.1002/wsbm.1337 For further resources related to this article, please visit the WIREs website.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28bgtFSruw%253D%253D&md5=625d7ef02f2c495031e62988ac98446f
  36. 36
    Daina, A.; Zoete, V. A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. ChemMedChem 2016, 11, 1117– 1121,  DOI: 10.1002/cmdc.201600182
    Google Scholar
    36
    A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules
    Daina, Antoine; Zoete, Vincent
    ChemMedChem (2016), 11 (11), 1117-1121CODEN: CHEMGX; ISSN:1860-7179. (Wiley-VCH Verlag GmbH & Co. KGaA)
    Apart from efficacy and toxicity, many drug development failures are imputable to poor pharmacokinetics and bioavailability. Gastrointestinal absorption and brain access are two pharmacokinetic behaviors crucial to est. at various stages of the drug discovery processes. To this end, the Brain Or IntestinaL Estd. permeation method (BOILED-Egg) is proposed as an accurate predictive model that works by computing the lipophilicity and polarity of small mols. Concomitant predictions for both brain and intestinal permeation are obtained from the same two physicochem. descriptors and straightforwardly translated into mol. design, owing to the speed, accuracy, conceptual simplicity and clear graphical output of the model. The BOILED-Egg can be applied in a variety of settings, from the filtering of chem. libraries at the early steps of drug discovery, to the evaluation of drug candidates for development.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XosFWit78%253D&md5=2cf19e6fe089ef1c0d8f38f0fdb528cc
  37. 37
    Tandon, R.; Keshavan, M. S.; Nasrallah, H. A. Schizophrenia, “Just the Facts”: What We Know in 2008 Part 1: Overview. Schizophr. Res. 2008, 100, 4– 19,  DOI: 10.1016/j.schres.2008.01.022
    Google Scholar
    37
    Schizophrenia, "Just the Facts": what we know in 2008 part 1: overview
    Tandon Rajiv; Keshavan Matcheri S; Nasrallah Henry A
    Schizophrenia research (2008), 100 (1-3), 4-19 ISSN:0920-9964.
    For every disorder, there is a set of established findings and accepted constructs upon which further understanding is built. The concept of schizophrenia as a disease entity has been with us for a little more than a century, although descriptions resembling this condition predate this conceptualization. In 1988, for the inaugural issue of Schizophrenia Research, at the invitation of the founding editors, a senior researcher, since deceased (RJ Wyatt) published a summary of generally accepted ideas about the disorder, which he termed "the facts" of schizophrenia. Ten years later, in conjunction with two of the authors (MSK, RT), he compiled a more extensive set of "facts" for the purpose of evaluating conceptual models or theoretical constructs developed to understand the nature of schizophrenia. On the 20th anniversary of this journal, we update and substantially expand our effort to periodically summarize the current body of information about schizophrenia. We compile a body of seventy-seven representative major findings and group them in terms of their specific relevance to schizophrenia -- etiologies, pathophysiology, clinical manifestations, and treatments. We rate each such "fact" on a 0-3 scale for measures of reproducibility, whether primary to schizophrenia, and durability over time. We also pose one or more critical questions with reference to each "fact", answers to which might help better elucidate the meaning of that finding for our understanding of schizophrenia. We intend to follow this paper with the submission to the journal of a series of topic-specific articles, critically reviewing the evidence.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1c7mvFSmtg%253D%253D&md5=81360c3f74b8b08c04b907d86b79ed00
  38. 38
    Gaebel, W.; Zielasek, J. Schizophrenia in 2020: Trends in Diagnosis and Therapy. Psychiatry Clin. Neurosci. 2015, 69, 661– 673,  DOI: 10.1111/pcn.12322
    Google Scholar
    38
    Schizophrenia in 2020: Trends in diagnosis and therapy
    Gaebel Wolfgang; Zielasek Jurgen; Gaebel Wolfgang; Zielasek Jurgen
    Psychiatry and clinical neurosciences (2015), 69 (11), 661-73 ISSN:.
    Schizophrenia research is providing an increasing number of studies and important insights into the condition's etiopathogenesis based on genetic, neuropsychological and cranial neuroimaging studies. However, research progress has not yet led to the incorporation of such findings into the revised classification criteria of mental disorders or everyday clinical practice. By 2020, schizophrenia will most likely still be a clinically defined primary psychotic disorder. While there is some hope that treatment will be improved with new antipsychotic drugs, drugs addressing negative symptoms, more refined psychotherapy approaches and the introduction of new treatment modalities like transcranial magnetic stimulation, an additional hope is to improve early detection and prevention. As the results of new research into the etiopathogenesis of schizophrenia are promising to improve diagnosis, classification and therapy in the future, a picture of complex brain dysfunction is currently emerging requiring sophisticated mathematical methods of analysis. The imminent clinical challenge will be to develop comprehensive diagnostic and treatment modules individually tailored to the time-variable needs of patients and their families.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MfntFGntg%253D%253D&md5=2c454cee2691b741060cf8b96316b856
  39. 39
    Seeman, P.; Kapur, S. Schizophrenia: More Dopamine, More D2 Receptors. Proc. Natl. Acad. Sci. U. S. A. 2000, 97, 7673– 7675,  DOI: 10.1073/pnas.97.14.7673
    Google Scholar
    39
    Schizophrenia: more dopamine, more D2 receptors
    Seeman, Philip; Kapur, Shitij
    Proceedings of the National Academy of Sciences of the United States of America (2000), 97 (14), 7673-7675CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    A polemic in response to A. Abi-Dargham (ibid. 8104).
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXkvFCntr8%253D&md5=258c7c70d64caf9035d9c322a6e1a61f
  40. 40
    Lee, T.; Seeman, P. Brain Dopamine Receptors In Schizophrenia; Usdin, E., Hanin, I. B. T.-B. M. in P. and N., Eds.; Pergamon , 1982; pp. 219– 226,  DOI: 10.1016/B978-0-08-027987-9.50027-5 .
    Google Scholar
    There is no corresponding record for this reference.
  41. 41
    Putnam, D. K.; Sun, J.; Zhao, Z. Exploring Schizophrenia Drug-Gene Interactions through Molecular Network and Pathway Modeling. AMIA . Annual Symposium proceedings. AMIA Annu. Symp. Proc. 2011, 2011, 1127– 1133
    Google Scholar
    41
    Exploring schizophrenia drug-gene interactions through molecular network and pathway modeling
    Putnam Daniel K; Sun Jingchun; Zhao Zhongming
    AMIA ... Annual Symposium proceedings. AMIA Symposium (2011), 2011 (), 1127-33 ISSN:.
    In this study, we retrieved 39 schizophrenia-related antipsychotic drugs from the DrugBank database. These drugs had interactions with 142 targets, whose corresponding genes were defined as drug targeted genes. To explore the complexity between these drugs and their related genes in schizophrenia, we constructed a drug-target gene network. These genes were overrepresented in several pathways including: neuroactive ligand-receptor pathways, glutamate metabolism, and glycine metabolism. Through integrating the pathway information into a drug-gene network, we revealed a few bridge genes connected the sub-networks of the drug-gene network: GRIN2A, GRIN3B, GRIN2C, GRIN2B, DRD1, and DRD2. These genes encode ionotropic glutamate receptors belonging to the NMDA receptor family and dopamine receptors. Haloperidol was the only drug to directly interact with these pathways and receptors and consequently may have a unique action at the drug-gene interaction level during the treatment of schizophrenia. This study represents the first systematic investigation of drug-gene interactions in psychosis.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38%252Fps1Onsw%253D%253D&md5=bf8ef4e18647e679530f273f7dbd4f26
  42. 42
    Kesby, J. P.; Eyles, D. W.; McGrath, J. J.; Scott, J. G. Dopamine, Psychosis and Schizophrenia: The Widening Gap between Basic and Clinical Neuroscience. Transl. Psychiatry 2018, 8, 30,  DOI: 10.1038/s41398-017-0071-9
    Google Scholar
    42
    Dopamine, psychosis and schizophrenia: the widening gap between basic and clinical neuroscience
    Kesby J P; Eyles D W; McGrath J J; Kesby J P; Scott J G; Eyles D W; McGrath J J; Scott J G; McGrath J J; Scott J G
    Translational psychiatry (2018), 8 (1), 30 ISSN:.
    The stagnation in drug development for schizophrenia highlights the need for better translation between basic and clinical research. Understanding the neurobiology of schizophrenia presents substantial challenges but a key feature continues to be the involvement of subcortical dopaminergic dysfunction in those with psychotic symptoms. Our contemporary knowledge regarding dopamine dysfunction has clarified where and when dopaminergic alterations may present in schizophrenia. For example, clinical studies have shown patients with schizophrenia show increased presynaptic dopamine function in the associative striatum, rather than the limbic striatum as previously presumed. Furthermore, subjects deemed at high risk of developing schizophrenia show similar presynaptic dopamine abnormalities in the associative striatum. Thus, our view of subcortical dopamine function in schizophrenia continues to evolve as we accommodate this newly acquired information. However, basic research in animal models has been slow to incorporate these clinical findings. For example, psychostimulant-induced locomotion, the commonly utilised phenotype for positive symptoms in rodents, is heavily associated with dopaminergic activation in the limbic striatum. This anatomical misalignment has brought into question how we assess positive symptoms in animal models and represents an opportunity for improved translation between basic and clinical research. The current review focuses on the role of subcortical dopamine dysfunction in psychosis and schizophrenia. We present and discuss alternative phenotypes that may provide a more translational approach to assess the neurobiology of positive symptoms in schizophrenia. Incorporation of recent clinical findings is essential if we are to develop meaningful translational animal models.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MvlsFylsw%253D%253D&md5=f9b6fb9d2f871a12b19cc4b67b3a9d09
  43. 43
    Laboratories, K. KEEG https://www.genome.jp/kegg/ (accessed Oct 26, 2020).
    Google Scholar
    There is no corresponding record for this reference.
  44. 44
    Sibley, D. R.; Neve, K. Dopamine Receptors; Enna, S. J., Bylund, D. B. B. T. T. C. P. R., Eds.; Elsevier: New York, 2007; pp. 1– 4,  DOI: 10.1016/B978-008055232-3.60151-5 .
    Google Scholar
    There is no corresponding record for this reference.
  45. 45
    Neve, K. A. Dopamine Receptors; Lennarz, W. J., Lane, M. D. B. T.-E. of B. C. (Second E., Eds.; Academic Press: Waltham, 2013; pp. 169– 173,  DOI: 10.1016/B978-0-12-378630-2.00326-1 .
    Google Scholar
    There is no corresponding record for this reference.
  46. 46
    Wang, S.; Che, T.; Levit, A.; Shoichet, B. K.; Wacker, D.; Roth, B. L. Structure of the D2 Dopamine Receptor Bound to the Atypical Antipsychotic Drug Risperidone. Nature 2018, 555, 269– 273,  DOI: 10.1038/nature25758
    Google Scholar
    46
    Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone
    Wang, Sheng; Che, Tao; Levit, Anat; Shoichet, Brian K.; Wacker, Daniel; Roth, Bryan L.
    Nature (London, United Kingdom) (2018), 555 (7695), 269-273CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
    Dopamine is a neurotransmitter that has been implicated in processes as diverse as reward, addiction, control of coordinated movement, metab. and hormonal secretion. Correspondingly, dysregulation of the dopaminergic system has been implicated in diseases such as schizophrenia, Parkinson's disease, depression, attention deficit hyperactivity disorder, and nausea and vomiting. The actions of dopamine are mediated by a family of five G-protein-coupled receptors. The D2 dopamine receptor (DRD2) is the primary target for both typical and atypical antipsychotic drugs, and for drugs used to treat Parkinson's disease. Unfortunately, many drugs that target DRD2 cause serious and potentially life-threatening side effects due to promiscuous activities against related receptors. Accordingly, a mol. understanding of the structure and function of DRD2 could provide a template for the design of safer and more effective medications. Here we report the crystal structure of DRD2 in complex with the widely prescribed atypical antipsychotic drug risperidone. The DRD2-risperidone structure reveals an unexpected mode of antipsychotic drug binding to dopamine receptors, and highlights structural determinants that are essential for the actions of risperidone and related drugs at DRD2.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXktFKqt7c%253D&md5=2842adc1893293ea8dbf98ae3270a1b2
  47. 47
    Corena-McLeod, M. Comparative Pharmacology of Risperidone and Paliperidone. Drugs R&D 2015, 15, 163– 174,  DOI: 10.1007/s40268-015-0092-x
    Google Scholar
    There is no corresponding record for this reference.
  48. 48
    Martelle, J. L.; Nader, M. A. A Review of the Discovery, Pharmacological Characterization, and Behavioral Effects of the Dopamine D2-like Receptor Antagonist Eticlopride. CNS Neurosci. Ther. 2008, 14, 248– 262,  DOI: 10.1111/j.1755-5949.2008.00047.x
    Google Scholar
    48
    A review of the discovery, pharmacological characterization, and behavioral effects of the dopamine D2-like receptor antagonist eticlopride
    Martelle, Jennifer L.; Nader, Michael A.
    CNS Neuroscience & Therapeutics (2008), 14 (3), 248-262CODEN: CNTNAB; ISSN:1755-5930. (Wiley-Blackwell)
    A review. Eticlopride is a substituted benzamide analog with high affinity and selectivity for dopamine (DA) D2-like receptors that was initially developed as a potential antipsychotic agent. A great deal of research has utilized this drug to better understand central DA receptor function, the role of D2-like receptors in behavior, and the influence of blockade of these receptors on several preclin. animal models. This review highlights research utilizing this drug and compares it to typical and atypical antipsychotics used clin. First, we describe structure-activity relationships as it relates to binding at DA receptors and the consequences on behavior. This is followed by a discussion of several imaging strategies including the use of eticlopride for in vivo, in vitro, and ex vivo examn. of DA D2-like receptor densities and function. Finally, we discuss the use of eticlopride in several behavioral models predictive of antipsychotic activity, extrapyramidal side effects (EPS), and learning and memory. While eticlopride is not used clin., it remains a viable research tool for understanding DA receptor function and behavior.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFentLjP&md5=cc9cec830ab1e3935901f6e3a9cabe66
  49. 49
    Miyamoto, S. Nemonapride BT - Encyclopedia of Psychopharmacology; Stolerman, I. P., Ed.; Springer Berlin Heidelberg: Berlin, Heidelberg, 2010; p 823,  DOI: 10.1007/978-3-540-68706-1_1840 .
    Google Scholar
    There is no corresponding record for this reference.
  50. 50
    Platania, C. B. M.; Salomone, S.; Leggio, G. M.; Drago, F.; Bucolo, C. Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation. PLoS One 2012, 7, e44316– e44316,  DOI: 10.1371/journal.pone.0044316
    Google Scholar
    50
    Homology modeling of dopamine D2 and D3 receptors: molecular dynamics refinement and docking evaluation
    Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio
    PLoS One (2012), 7 (9), e44316CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
    Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurol., psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homol. models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with mol. dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in mol. docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calcn. Robust correlation of computed and exptl. Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtlCitrrL&md5=50672aa14be2fa0cb33a4f43069937a3
  51. 51
    Chien, E. Y. T.; Liu, W.; Zhao, Q.; Katritch, V.; Han, G. W.; Hanson, M. A.; Shi, L.; Newman, A. H.; Javitch, J. A.; Cherezov, V.; Stevens, R. C. Structure of the human dopamine D3 receptor in complex with a D2/D3 selective antagonist. Science 2010, 330, 1091– 1095,  DOI: 10.1126/science.1197410
    Google Scholar
    51
    Structure of the Human Dopamine D3 Receptor in Complex with a D2/D3 Selective Antagonist
    Chien, Ellen Y. T.; Liu, Wei; Zhao, Qiang; Katritch, Vsevolod; Won Han, Gye; Hanson, Michael A.; Shi, Lei; Newman, Amy Hauck; Javitch, Jonathan A.; Cherezov, Vadim; Stevens, Raymond C.
    Science (Washington, DC, United States) (2010), 330 (6007), 1091-1095CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
    Dopamine modulates movement, cognition, and emotion through activation of dopamine G protein-coupled receptors in the brain. The crystal structure of the human dopamine D3 receptor (D3R) in complex with the small mol. D2R/D3R-specific antagonist eticlopride reveals important features of the ligand binding pocket and extracellular loops. On the intracellular side of the receptor, a locked conformation of the ionic lock and two distinctly different conformations of intracellular loop 2 are obsd. Docking of R-22, a D3R-selective antagonist, reveals an extracellular extension of the eticlopride binding site that comprises a second binding pocket for the aryl amide of R-22, which differs between the highly homologous D2R and D3R. This difference provides direction to the design of D3R-selective agents for treating drug abuse and other neuropsychiatric indications.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVahurvM&md5=12c6f343daea9fb14ca605a092f28533
  52. 52
    Ferreira de Freitas, R.; Schapira, M. A Systematic Analysis of Atomic Protein–Ligand Interactions in the PDB. MedChemComm 2017, 8, 1970– 1981,  DOI: 10.1039/C7MD00381A
    Google Scholar
    52
    A systematic analysis of atomic protein-ligand interactions in the PDB
    Ferreira de Freitas, Renato; Schapira, Matthieu
    MedChemComm (2017), 8 (10), 1970-1981CODEN: MCCEAY; ISSN:2040-2503. (Royal Society of Chemistry)
    As the protein databank (PDB) recently passed the cap of 123 456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biol. systems, but also to study the prevalence of structural patterns obsd. in a large body of unrelated structures, that may reflect rules governing protein folding or mol. recognition. Here, we compiled a list of 11 016 unique structures of small-mol. ligands bound to proteins - 6444 of which have exptl. binding affinity - representing 750 873 protein-ligand at. interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extd. from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high no. of C-H···O hydrogen bonds or the relatively frequent amide-p stacking between the backbone amide of proteins and arom. rings of ligands, uncover underused ligand design strategies.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhsFOiu7nE&md5=04688488e73253f76e4ea384456f89a8
  53. 53
    Wang, S.; Wacker, D.; Levit, A.; Che, T.; Betz, R. M.; McCorvy, J. D.; Venkatakrishnan, A. J.; Huang, X.-P.; Dror, R. O.; Shoichet, B. K.; Roth, B. L. D4 Dopamine Receptor High-Resolution Structures Enable the Discovery of Selective Agonists. Science 2017, 358, 381– 386,  DOI: 10.1126/science.aan5468
    Google Scholar
    53
    D4 dopamine receptor high-resolution structures enable the discovery of selective agonists
    Wang, Sheng; Wacker, Daniel; Levit, Anat; Che, Tao; Betz, Robin M.; McCorvy, John D.; Venkatakrishnan, A. J.; Huang, Xi-Ping; Dror, Ron O.; Shoichet, Brian K.; Roth, Bryan L.
    Science (Washington, DC, United States) (2017), 358 (6361), 381-386CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
    Dopamine receptors are implicated in the pathogenesis and treatment of nearly every neuropsychiatric disorder. Although thousands of drugs interact with these receptors, our mol. understanding of dopaminergic drug selectivity and design remains clouded. To illuminate dopamine receptor structure, function, and ligand recognition, we detd. crystal structures of the D4 dopamine receptor in its inactive state bound to the antipsychotic drug nemonapride, with resolns. up to 1.95 angstroms. These structures suggest a mechanism for the control of constitutive signaling, and their unusually high resoln. enabled a structure-based campaign for new agonists of the D4 dopamine receptor. The ability to efficiently exploit structure for specific probe discovery-rapidly moving from elucidating receptor structure to discovering previously unrecognized, selective agonists-testifies to the power of structure-based approaches.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhs1Kns73I&md5=0bbb93e6bcb33577f9d9b7459273d896
  54. 54
    Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A. D., Jr. CHARMM General Force Field: A Force Field for Drug-like Molecules Compatible with the CHARMM All-Atom Additive Biological Force Fields. J. Comput. Chem. 2010, 31, 671– 690,  DOI: 10.1002/jcc.21367
    Google Scholar
    54
    CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields
    Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A. D., Jr.
    Journal of Computational Chemistry (2010), 31 (4), 671-690CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like mols. is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chem. groups present in biomols. and drug-like mols., including a large no. of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concg. on an extensible force field. Statistics related to the quality of the parametrization with a focus on exptl. validation are presented. Addnl., the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethyl-pyrrolidine will allow users to readily extend the force field to chem. groups that are not explicitly covered in the force field as well as add functional groups to and link together mols. already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2010.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlentbc%253D&md5=26212e0e4f73bded0c89d4b411cd3833
  55. 55
    Jean, B.; Surratt, C. K.; Madura, J. D. Molecular Dynamics of Conformation-Specific Dopamine Transporter-Inhibitor Complexes. J. Mol. Graphics Modell. 2017, 76, 143– 151,  DOI: 10.1016/j.jmgm.2017.07.003
    Google Scholar
    55
    Molecular dynamics of conformation-specific dopamine transporter-inhibitor complexes
    Jean, Bernandie; Surratt, Christopher K.; Madura, Jeffry D.
    Journal of Molecular Graphics & Modelling (2017), 76 (), 143-151CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)
    The recreational psychostimulant cocaine inhibits dopamine reuptake from the synapse, resulting in excessive stimulation of postsynaptic dopamine receptors in brain areas assocd. with reward and addiction. Cocaine binds to and stabilizes the outward- (extracellular-) facing conformation of the dopamine transporter (DAT) protein, while the low abuse potential DAT inhibitor benztropine prefers the inward- (cytoplasmic-) facing conformation. A correlation has been previously postulated between psychostimulant abuse potential and preference for the outward-facing DAT conformation. The 3β-aryltropane cocaine analogs LX10 and LX11, however, differ only in stereochem. and share a preference for the outward-facing DAT, yet are reported to vary widely in abuse potential in an animal model. In search of the mol. basis for DAT conformation preference, complexes of cocaine, benztropine, LX10 or LX11 bound to each DAT conformation were subjected to 100 ns of all-atom mol. dynamics simulation. Results were consistent with previous findings from cysteine accessibility assays used to assess an inhibitor's DAT conformation preference. The resp. 2β- and 2α-substituted phenyltropanes of LX10 and LX11 interacted with hydrophobic regions of the DAT S1 binding site that were inaccessible to cocaine. Solvent accessibility measurements also revealed subtle differences in inhibitor positioning within a given DAT conformation. This work serves to advance our understanding of the conformational selectivity of DAT inhibitors and suggests that MD may be useful in antipsychostimulant therapeutic design.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXht1SjsLnN&md5=98a374f8b6d61d96ec9f979c02dedf64
  56. 56
    Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B. L.; Grubmüller, H.; MacKerell, A. D., Jr. CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nat. Methods 2017, 14, 71– 73,  DOI: 10.1038/nmeth.4067
    Google Scholar
    56
    CHARMM36m: an improved force field for folded and intrinsically disordered proteins
    Huang, Jing; Rauscher, Sarah; Nawrocki, Grzegorz; Ran, Ting; Feig, Michael; de Groot, Bert L.; Grubmuller, Helmut; MacKerell, Alexander D. Jr
    Nature Methods (2017), 14 (1), 71-73CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
    The all-atom additive CHARMM36 protein force field is widely used in mol. modeling and simulations. We present its refinement, CHARMM36m (http://mackerell.umaryland.edu/charmm_ff.shtml), with improved accuracy in generating polypeptide backbone conformational ensembles for intrinsically disordered peptides and proteins.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVSiu77I&md5=0aa151fbef2ee0b5e2cfb593c54330c2
  57. 57
    Nielsen, A. K.; Möller, I. R.; Wang, Y.; Rasmussen, S. G. F.; Lindorff-Larsen, K.; Rand, K. D.; Loland, C. J. Substrate-Induced Conformational Dynamics of the Dopamine Transporter. Nat. Commun. 2019, 10, 2714,  DOI: 10.1038/s41467-019-10449-w
    Google Scholar
    57
    Substrate-induced conformational dynamics of the dopamine transporter
    Nielsen Anne Kathrine; Moller Ingvar R; Loland Claus J; Nielsen Anne Kathrine; Moller Ingvar R; Rand Kasper D; Wang Yong; Lindorff-Larsen Kresten; Rasmussen Soren G F
    Nature communications (2019), 10 (1), 2714 ISSN:.
    The dopamine transporter is a member of the neurotransmitter:sodium symporters (NSSs), which are responsible for termination of neurotransmission through Na(+)-driven reuptake of neurotransmitter from the extracellular space. Experimental evidence elucidating the coordinated conformational rearrangements related to the transport mechanism has so far been limited. Here we probe the global Na(+)- and dopamine-induced conformational dynamics of the wild-type Drosophila melanogaster dopamine transporter using hydrogen-deuterium exchange mass spectrometry. We identify Na(+)- and dopamine-induced changes in specific regions of the transporter, suggesting their involvement in protein conformational transitions. Furthermore, we detect ligand-dependent slow cooperative fluctuations of helical stretches in several domains of the transporter, which could be a molecular mechanism that assists in the transporter function. Our results provide a framework for understanding the molecular mechanism underlying the function of NSSs by revealing detailed insight into the state-dependent conformational changes associated with the alternating access model of the dopamine transporter.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M3ptVWktw%253D%253D&md5=0d905c0a58496ad52714d0302e23e0f1
  58. 58
    Klauda, J. B.; Venable, R. M.; Freites, J. A.; O’Connor, J. W.; Tobias, D. J.; Mondragon-Ramirez, C.; Vorobyov, I.; MacKerell, A. D., Jr.; Pastor, R. W. Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 2010, 114, 7830– 7843,  DOI: 10.1021/jp101759q
    Google Scholar
    58
    Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types
    Klauda, Jeffery B.; Venable, Richard M.; Freites, J. Alfredo; O'Connor, Joseph W.; Tobias, Douglas J.; Mondragon-Ramirez, Carlos; Vorobyov, Igor; MacKerell, Alexander D., Jr.; Pastor, Richard W.
    Journal of Physical Chemistry B (2010), 114 (23), 7830-7843CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)
    A significant modification to the additive all-atom CHARMM lipid force field (FF) is developed and applied to phospholipid bilayers with both choline and ethanolamine contg. head groups and with both satd. and unsatd. aliph. chains. Motivated by the current CHARMM lipid FF (C27 and C27r) systematically yielding values of the surface area per lipid that are smaller than exptl. ests. and gel-like structures of bilayers well above the gel transition temp., selected torsional, Lennard-Jones and partial at. charge parameters were modified by targeting both quantum mech. (QM) and exptl. data. QM calcns. ranging from high-level ab initio calcns. on small mols. to semiempirical QM studies on a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer in combination with exptl. thermodn. data were used as target data for parameter optimization. These changes were tested with simulations of pure bilayers at high hydration of the following six lipids: DPPC, 1,2-dimyristoyl-sn-phosphatidylcholine (DMPC), 1,2-dilauroyl-sn-phosphatidylcholine (DLPC), 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine (POPC), 1,2-dioleoyl-sn-phosphatidylcholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine (POPE); simulations of a low hydration DOPC bilayer were also performed. Agreement with exptl. surface area is on av. within 2%, and the d. profiles agree well with neutron and x-ray diffraction expts. NMR deuterium order parameters (SCD) are well predicted with the new FF, including proper splitting of the SCD for the aliph. carbon adjacent to the carbonyl for DPPC, POPE, and POPC bilayers. The area compressibility modulus and frequency dependence of 13C NMR relaxation rates of DPPC and the water distribution of low hydration DOPC bilayers also agree well with expt. Accordingly, the presented lipid FF, referred to as C36, allows for mol. dynamics simulations to be run in the tensionless ensemble (NPT), and is anticipated to be of utility for simulations of pure lipid systems as well as heterogeneous systems including membrane proteins.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsVGjtrk%253D&md5=04c4d3aa1a59740190994d7df80cbb71
  59. 59
    Vanommeslaeghe, K.; MacKerell, A. D., Jr. Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 2012, 52, 3144– 3154,  DOI: 10.1021/ci300363c
    Google Scholar
    59
    Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing
    Vanommeslaeghe, K.; MacKerell, A. D.
    Journal of Chemical Information and Modeling (2012), 52 (12), 3144-3154CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug-like mols. alone or interacting with biol. systems. In simulations involving biol. macromols., the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and charges is required. In the present article, which is part I of a series of two, we present the algorithms for bond perception and atom typing for the CHARMM General Force Field (CGenFF). The CGenFF atom typer first assocs. attributes to the atoms and bonds in a mol., such as valence, bond order, and ring membership among others. Of note are a no. of features that are specifically required for CGenFF. This information is then used by the atom typing routine to assign CGenFF atom types based on a programmable decision tree. This allows for straight-forward implementation of CGenFF's complicated atom typing rules and for equally straight-forward updating of the atom typing scheme as the force field grows. The presented atom typer was validated by assigning correct atom types on 477 model compds. including in the training set as well as 126 test-set mols. that were constructed to specifically verify its different components. The program may be utilized via an online implementation at https://www.paramchem.org/.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1Gns7fL&md5=c6679293f4a2501f2bcadf2020ca1473
  60. 60
    Best, R. B.; Zhu, X.; Shim, J.; Lopes, P. E. M.; Mittal, J.; Feig, M.; Mackerell, A. D., Jr. Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone φ, ψ and Side-Chain χ(1) and χ(2) Dihedral Angles. J. Chem. Theory Comput. 2012, 8, 3257– 3273,  DOI: 10.1021/ct300400x
    Google Scholar
    60
    Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone .vphi., ψ and Side-Chain χ1 and χ2 Dihedral Angles
    Best, Robert B.; Zhu, Xiao; Shim, Jihyun; Lopes, Pedro E. M.; Mittal, Jeetain; Feig, Michael; MacKerell, Alexander D.
    Journal of Chemical Theory and Computation (2012), 8 (9), 3257-3273CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
    While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large no. of applications, limitations in the model with respect to the equil. between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non-Gly, -Pro) backbone CMAP potential has been refined against exptl. soln. NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mech. energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mech. energy surfaces, followed by addnl. empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against a collection of exptl. data: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equil. folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for modeling and simulation studies of proteins, including studies of protein folding, assembly, and functionally relevant conformational changes.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKqurfP&md5=9a48a0c5770fb1e887c3bb34d45b1354
  61. 61
    Lane, J. R.; Abramyan, A. M.; Adhikari, P.; Keen, A. C.; Lee, K.-H.; Sanchez, J.; Verma, R. K.; Lim, H. D.; Yano, H.; Javitch, J. A.; Shi, L. Distinct Inactive Conformations of the Dopamine D2 and D3 Receptors Correspond to Different Extents of Inverse Agonism. eLife 2020, 9, e52189  DOI: 10.7554/eLife.52189
    Google Scholar
    61
    Distinct inactive conformations of the dopamine D2 and D3 receptors correspond to different extents of inverse agonism
    Lane, J. Robert; Abramyan, Ara M.; Adhikari, Pramisha; Keen, Alastair C.; Lee, Kuo-Hao; Sanchez, Julie; Verma, Ravi Kumar; Lim, Herman D.; Yano, Hideaki; Javitch, Jonathan A.; Shi, Lei
    eLife (2020), 9 (), e52189CODEN: ELIFA8; ISSN:2050-084X. (eLife Sciences Publications Ltd.)
    By analyzing and simulating inactive conformations of the highly homologous dopamine D2 and D3 receptors (D2R and D3R), we find that eticlopride binds D2R in a pose very similar to that in the D3R/eticlopride structure but incompatible with the D2R/risperidone structure. In addn., risperidone occupies a sub-pocket near the Na+ binding site, whereas eticlopride does not. Based on these findings and our exptl. results, we propose that the divergent receptor conformations stabilized by Na+ -sensitive eticlopride and Na+ -insensitive risperidone correspond to different degrees of inverse agonism. Moreover, our simulations reveal that the extracellular loops are highly dynamic, with spontaneous transitions of extracellular loop 2 from the helical conformation in the D2R/risperidone structure to an extended conformation similar to that in the D3R/eticlopride structure. Our results reveal previously unappreciated diversity and dynamics in the inactive conformations of D2R. These findings are crit. for rational drug discovery, as limiting a virtual screen to a single conformation will miss relevant ligands.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlarsb7O&md5=e282f1721292b10c6a1ac5cfc44a98c4
  62. 62
    MacKerell, A. D., Jr.; Feig, M.; Brooks, C. L. Improved Treatment of the Protein Backbone in Empirical Force Fields. J. Am. Chem. Soc. 2004, 126, 698– 699,  DOI: 10.1021/ja036959e
    Google Scholar
    62
    Improved treatment of the protein backbone in empirical force fields
    MacKerell, Alexander D., Jr.; Feig, Michael; Brooks, Charles L., III
    Journal of the American Chemical Society (2004), 126 (3), 698-699CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
    Empirical force field-based calcns. of proteins, including protein-folding studies, have improved our understanding of the relationship of their structure to their biol. function. However, limitations in the accuracy of empirical force fields in the treatment of the peptide backbone exist. Presented is a grid correction approach to improve the treatment of the peptide backbone φ/ψ conformational energies. Inclusion of this correction with the CHARMM22 all-atom protein force field is shown to lead to significant improvement in the treatment of the conformational energies of both the peptide model compd., the alanine dipeptide, and of proteins in their crystal environment. The developed approach is suggested to lead to significant improvements in the accuracy of empirical force fields to treat peptides and proteins.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXhtVWisb7F&md5=a1426b50784d4eca888dc270643ef947
  63. 63
    Jo, J. C.; Kim, B. C. Determination of Proper Time Step for Molecular Dynamics Simulation. Bull. Korean Chem. Soc. 2000, 21, 419
    Google Scholar
    There is no corresponding record for this reference.
  64. 64
    Hollingsworth, S. A.; Dror, R. O. Molecular Dynamics Simulation for All. Neuron 2018, 99, 1129– 1143,  DOI: 10.1016/j.neuron.2018.08.011
    Google Scholar
    64
    Molecular Dynamics Simulation for All
    Hollingsworth, Scott A.; Dror, Ron O.
    Neuron (2018), 99 (6), 1129-1143CODEN: NERNET; ISSN:0896-6273. (Cell Press)
    A review. The impact of mol. dynamics (MD) simulations in mol. biol. and drug discovery has expanded dramatically in recent years. These simulations capture the behavior of proteins and other biomols. in full at. detail and at very fine temporal resoln. Major improvements in simulation speed, accuracy, and accessibility, together with the proliferation of exptl. structural data, have increased the appeal of biomol. simulation to experimentalists-a trend particularly noticeable in, although certainly not limited to, neuroscience. Simulations have proven valuable in deciphering functional mechanisms of proteins and other biomols., in uncovering the structural basis for disease, and in the design and optimization of small mols., peptides, and proteins. Here we describe, in practical terms, the types of information MD simulations can provide and the ways in which they typically motivate further exptl. work.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhslGltLzL&md5=35e14022763288ed45c2a605cc900f61
  65. 65
    Lobanov, M. Y.; Bogatyreva, N. S.; Galzitskaya, O. V. Radius of Gyration as an Indicator of Protein Structure Compactness. Mol. Biol. 2008, 42, 623– 628,  DOI: 10.1134/S0026893308040195
    Google Scholar
    65
    Radius of gyration as an indicator of protein structure compactness
    Lobanov, M. Yu.; Bogatyreva, N. S.; Galzitskaya, O. V.
    Molecular Biology (Moscow, Russian Federation, English Edition) (2008), 42 (4), 623-628CODEN: MOLBBJ; ISSN:0026-8933. (Pleiades Publishing, Ltd.)
    Identification and study of the main principles underlying the kinetics and thermodn. of protein folding generate new insights into the factors that control this process. Statistical anal. of the radius of gyration for 3769 protein domains of four major classes (α, β, α/β, and α + β) showed that each class has a characteristic radius of gyration that dets. the protein's structural compactness. For instance, α proteins have the highest radius of gyration throughout the protein size range considered, suggesting a less tight packing as compared with β- and (α + β)-proteins. The lowest radius of gyration and, accordingly, the tightest packing are characteristic of α/β-proteins. The protein radius of gyration normalized by the radius of gyration of a ball with the same vol. is independent of the protein size, in contrast to compactness and the no. of contacts per residue.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXps1ahtrc%253D&md5=2eca54d4bb83f4cc3843bc2506fdd1a1
  66. 66
    Falsafi-Zadeh, S.; Karimi, Z.; Galehdari, H. VMD DisRg: New User-Friendly Implement for Calculation Distance and Radius of Gyration in VMD Program. Bioinformation 2012, 8, 341– 343,  DOI: 10.6026/97320630008341
    Google Scholar
    66
    VMD DisRg: New User-Friendly Implement for calculation distance and radius of gyration in VMD program
    Falsafi-Zadeh Sajad; Karimi Zahra; Galehdari Hamid
    Bioinformation (2012), 8 (7), 341-3 ISSN:.
    UNLABELLED: Molecular dynamic simulation is a practical and powerful technique for analysis of protein structure. Several programs have been developed to facilitate the mentioned investigation, under them the visual molecular dynamic or VMD is the most frequently used programs. One of the beneficial properties of the VMD is its ability to be extendable by designing new plug-in. We introduce here a new facility of the VMD for distance analysis and radius of gyration of biopolymers such as protein and DNA. AVAILABILITY: The database is available for free at http://trc.ajums.ac.ir/HomePage.aspx/?TabID/=12618/&Site/=trc.ajums.ac/&Lang/=fa-IR.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38rpvFOhsg%253D%253D&md5=f235c8036e531f2540a1e08ed92e7dc5
  67. 67
    Shao, J.; Tanner, S. W.; Thompson, N.; Cheatham, T. E. Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms. J. Chem. Theory Comput. 2007, 3, 2312– 2334,  DOI: 10.1021/ct700119m
    Google Scholar
    67
    Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms
    Shao, Jianyin; Tanner, Stephen W.; Thompson, Nephi; Cheatham, Thomas E., III
    Journal of Chemical Theory and Computation (2007), 3 (6), 2312-2334CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
    Mol. dynamics simulation methods produce trajectories of at. positions (and optionally velocities and energies) as a function of time and provide a representation of the sampling of a given mol.'s energetically accessible conformational ensemble. As simulations on the 10-100 ns time scale become routine, with sampled configurations stored on the picosecond time scale, such trajectories contain large amts. of data. Data-mining techniques, like clustering, provide one means to group and make sense of the information in the trajectory. In this work, several clustering algorithms were implemented, compared, and utilized to understand MD trajectory data. The development of the algorithms into a freely available C code library, and their application to a simple test example of random (or systematically placed) points in a 2D plane (where the pairwise metric is the distance between points) provide a means to understand the relative performance. Eleven different clustering algorithms were developed, ranging from top-down splitting (hierarchical) and bottom-up aggregating (including single-linkage edge joining, centroid-linkage, av.-linkage, complete-linkage, centripetal, and centripetal-complete) to various refinement (means, Bayesian, and self-organizing maps) and tree (COBWEB) algorithms. Systematic testing in the context of MD simulation of various DNA systems (including DNA single strands and the interaction of a minor groove binding drug DB226 with a DNA hairpin) allows a more direct assessment of the relative merits of the distinct clustering algorithms. Addnl., means to assess the relative performance and differences between the algorithms, to dynamically select the initial cluster count, and to achieve faster data mining by "sieved clustering" were evaluated. Overall, it was found that there is no one perfect "one size fits all" algorithm for clustering MD trajectories and that the results strongly depend on the choice of atoms for the pairwise comparison. Some algorithms tend to produce homogeneously sized clusters, whereas others have a tendency to produce singleton clusters. Issues related to the choice of a pairwise metric, clustering metrics, which atom selection is used for the comparison, and about the relative performance are discussed. Overall, the best performance was obsd. with the av.-linkage, means, and SOM algorithms. If the cluster count is not known in advance, the hierarchical or av.-linkage clustering algorithms are recommended. Although these algorithms perform well, it is important to be aware of the limitations or weaknesses of each algorithm, specifically the high sensitivity to outliers with hierarchical, the tendency to generate homogenously sized clusters with means, and the tendency to produce small or singleton clusters with av.-linkage.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtFaqsLzE&md5=668cff11c29736325a4788379cc43def
  68. 68
    Wu, X.; Wang, S. Self-Guided Molecular Dynamics Simulation for Efficient Conformational Search. J. Phys. Chem. B 1998, 102, 7238– 7250,  DOI: 10.1021/jp9817372
    Google Scholar
    68
    Self-Guided Molecular Dynamics Simulation for Efficient Conformational Search
    Wu, Xiongwu; Wang, Shaomeng
    Journal of Physical Chemistry B (1998), 102 (37), 7238-7250CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)
    Conformational searching is a basic approach in theor. and computational chem., and mol. dynamics [MD] simulation is a powerful computational tool to study structural, thermodn., and kinetic properties of mol. systems. In this paper, we report a new MD simulation method with the primary goal of improving dramatically the conformational searching efficiency in an MD simulation in order to study slow events in physics, chem., and biol. This new MD simulation method was based upon a new equation of motion in which a guiding force was introduced, in addn. to the instantaneous force, to accelerate the systematic motion. This guiding force may be calcd. as a time av. of the instantaneous force from the trajectory obtained from the very same MD simulation. Bonded substructures were defined for mol. systems in order to enhance effectively both the inter- and intramol. systematic motions. The improvement of the overall conformational searching efficiency and the possible alterations of ensemble properties and the conformational distribution of the system were investigated through comparative simulations of two peptide systems, an alanine dipeptide and a 16-residue synthetic peptide, both in vacuum and in explicit water. We demonstrated that the self-guided MD simulation method improved conformational searching efficiency but did not significantly alter the ensemble av. properties and the conformational distributions of the systems. The successful helix-folding simulations of the 16-residue synthetic peptide both in vacuum and in explicit water clearly showed that the self-guided MD simulations achieved a dramatic enhancement in the conformational searching efficiency and showed an extraordinary ability to overcome energy barriers, as compared to the conventional MD simulations. Our results suggest that this new MD simulation method may be used as a powerful tool to study many important yet slow events or processes in physics, chem., and biol.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXltlyhsLk%253D&md5=1365a5c8317e7418764214230507ffbc
  69. 69
    Wu, X.; Brooks, B. R. Beta-Hairpin Folding Mechanism of a Nine-Residue Peptide Revealed from Molecular Dynamics Simulations in Explicit Water. Biophys. J. 2004, 86, 1946– 1958,  DOI: 10.1016/S0006-3495(04)74258-7
    Google Scholar
    69
    β-hairpin folding mechanism of a nine-residue peptide revealed from molecular dynamics simulations in explicit water
    Wu, Xiongwu; Brooks, Bernard R.
    Biophysical Journal (2004), 86 (4), 1946-1958CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)
    The β-hairpin fold mechanism of a nine-residue peptide, which is modified from the β-hairpin of α-amylase inhibitor tendamistat (residues 15-23), is studied through direct folding simulations in explicit water at native folding conditions. Three 300-ns self-guided mol. dynamics (SGMD) simulations have revealed a series of β-hairpin folding events. During these simulations, the peptide folds repeatedly into a major cluster of β-hairpin structures, which agree well with NMR exptl. observations. This major cluster is found to have the min. conformational free energy among all sampled conformations. This peptide also folds into many other β-hairpin structures, which represent some local free energy min. states. In the unfolded state, the N-terminal residues of the peptide, Tyr-1, Gln-2, and Asn-3, have a confined conformational distribution. This confinement makes β-hairpin the only energetically favored structure to fold. The unfolded state of this peptide is populated with conformations with non-native intrapeptide interactions. This peptide goes through fully hydrated conformations to eliminate non-native interactions before folding into a β-hairpin. The folding of a β-hairpin starts with side-chain interactions, which bring two strands together to form interstrand hydrogen bonds. The unfolding of the β-hairpin is not simply the reverse of the folding process. Comparing unfolding simulations using MD and SGMD methods demonstrate that SGMD simulations can qual. reproduce the kinetics of the peptide system.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXivF2ns74%253D&md5=791be954834d05a48fcbf12fee8c11de
  70. 70
    Wu, X.; Wang, S. Helix Folding of an Alanine-Based Peptide in Explicit Water. J. Phys. Chem. B 2001, 105, 2227– 2235,  DOI: 10.1021/jp004048a
    Google Scholar
    70
    Helix folding of an alanine-based peptide in explicit water
    Wu, Xiongwu; Wang, Shaomeng
    Journal of Physical Chemistry B (2001), 105 (11), 2227-2235CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)
    Computer simulations using full at. representations for both the peptide and water mols. were performed to study the folding of a 16-residue alanine-based helical peptide in aq. soln. Using a recently developed self-guided mol. dynamics (SGMD) method, which was shown to improve the conformational searching efficiency significantly as compared to conventional MD simulation method, reversible folding (folding, unfolding and refolding) of a 16-residue alanine-based synthetic peptide in explicit water at 274 K was successfully accomplished. Consistent with exptl. results, the helix was found to be the major secondary structural element in aq. soln., and among different helix forms, the α-helix is the dominant form. Conformational anal. of our simulation results showed that turns and 310-helixes play an essential role in the folding of α-helix. Interestingly, our results showed that the propagation of a helix segment is more frequent at the C-end than at the N-end. In most helix conformations, the backbone carbonyl groups of the peptide prefer to simultaneously form intramol. hydrogen bonds with the backbone amide groups of the peptide and intermol. hydrogen bonds with water mols., indicating water accessibility to the backbone carbonyl groups is crucial for helix formation in water. Therefore, the helical propensities of amino acids may be related to the water accessibility of their backbone groups in helical conformation. Water mols. also function as hydrogen bonding bridges linking helical residue pairs (i, i + n, with n = 3, 4, 5), suggesting a role of water bridges in helix folding.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXhtFynur4%253D&md5=b73d2957b2e487a5e39aa6a3d168c732
  71. 71
    Bisol, L. W.; Brunstein, M. G.; Ottoni, G. L.; Ramos, F. L. P.; Borba, D. L.; Daltio, C. S.; de Oliveira, R. V.; Paz, G. E. G.; de Souza, S. E.; Bressan, R. A.; Lara, D. R. Is Flunarizine a Long-Acting Oral Atypical Antipsychotic? A Randomized Clinical Trial versus Haloperidol for the Treatment of Schizophrenia. J. Clin. Psychiatry 2008, 69, 1572– 1579,  DOI: 10.4088/jcp.v69n1007
    Google Scholar
    71
    Is flunarizine a long-acting oral atypical antipsychotic? A randomized clinical trial versus haloperidol for the treatment of schizophrenia
    Bisol, Luisa W.; Brunstein, Miriam G.; Ottoni, Gustavo L.; Ramos, Fernanda L. P.; Borba, Daniela L.; Daltio, Claudiane S.; de Oliveira, Ricardo V.; Paz, Gisele E. G.; de Souza, Sayuri E.; Bressan, Rodrigo A.; Lara, Diogo R.
    Journal of Clinical Psychiatry (Memphis, TN, United States) (2008), 69 (10), 1572-1579CODEN: JCLPDE; ISSN:0160-6689. (Physicians Postgraduate Press, Inc.)
    Background: Flunarizine is known as a non-specific calcium channel blocker that has been used for decades for the treatment of migraine, vertigo, and cognitive deficits related to cerebro-vascular disorders. Flunarizine also has dopamine D2 receptor blocking properties and was effective in animal models of predictive validity for antipsychotics. However, its clin. antipsychotic efficacy has never been investigated. Objective: To evaluate the therapeutic efficacy and tolerability of flunarizine compared to haloperidol in outpatients with stable and chronic DSM-IV-defined schizophrenia and schizoaffective disorder. Method: Seventy patients from 2 centers were randomly assigned and participated in a double-blind, parallel-group, flexible-dose study comparing flunarizine (10-50 mg/day) and haloperidol (2.5-12.5 mg/day) for 12 wk. Patients were assessed with the Pos. and Neg. Syndrome Scale (PANSS), the Clin. Global Impressions-Improvement (CGI-I), scale, the Extrapyramidal Symptom Rating Scale (ESRS), a battery for cognitive performance, and lab. examns. The study was conducted from Sept. 2004 to May 2007. Results: Mean doses at endpoint were 29.7 mg/day for flunarizine and 6.4 mg/day for haloperidol. Both groups showed significant symptom improvement during the study, with a redn. of 21% in the flunarizine group and 19% in the haloperidol group in PANSS total scores (p < .05). There were no significant differences in PANSS overall score and all subscales, CGI-I score, or cognitive performance. Dropout rates, ESRS scores, and prolactin levels were not different between groups, but significantly more patients reported emergence of akathisia in the haloperidol group (p = .04), and wt. gain was significantly higher with flunarizine (1.2 kg) than with haloperidol (-0.8 kg) (p < .05). Conclusion: This is the first study evaluating the antipsychotic properties of flunarizine, which showed good efficacy and tolerability for the treatment of schizophrenia, with a possible atypical profile. Its unique pharmacokinetic profiles as an oral drug with long half-life (2-7 wk), low cost, and low induction of extrapyramidal symptoms warrants further investigation, particularly in psychiatric patients with low adherence to treatment.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlClu7jI&md5=9df07aa8c8d61e93e0f173fda4071c33
  72. 72
    Ambrosio, C.; Stefanini, E. Interaction of Flunarizine with Dopamine D2 and D1 Receptors. Eur. J. Pharmacol. 1991, 197, 221– 223,  DOI: 10.1016/0014-2999(91)90526-v
    Google Scholar
    72
    Interaction of flunarizine with dopamine D2 and D1 receptors
    Ambrosio, Caterina; Stefanini, Ennio
    European Journal of Pharmacology (1991), 197 (2-3), 221-3CODEN: EJPHAZ; ISSN:0014-2999.
    Flunarizine dose dependently inhibits the binding of both [3H]spiperone and [3H]SCH 23390 with Ki values of 112 and 532 nM, resp. The inhibition of [3H]spiperone binding by flunarizine was competitive as revealed by the Schild plot. The results indicate that flunarizine is a fairly potent dopamine D2 receptor antagonist and offer a possible explanation for the extrapyramidal side-effects obsd. in patients treated with the drug.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3MXks1ClsLk%253D&md5=c7f29f3592474b0d91738106a67c5470
  73. 73
    Wöber, C.; Brücke, T.; Wöber-Bingöl, C.; Asenbaum, S.; Wessely, P.; Podreka, I. Dopamine D2 Receptor Blockade and Antimigraine Action of Flunarizine. Cephalalgia 1994, 14, 235– 240,  DOI: 10.1046/j.1468-2982.1994.014003235.x
    Google Scholar
    73
    Dopamine D2 receptor blockade and antimigraine action of flunarizine
    Wober C; Brucke T; Wober-Bingol C; Asenbaum S; Wessely P; Podreka I
    Cephalalgia : an international journal of headache (1994), 14 (3), 235-40 ISSN:0333-1024.
    We studied in vivo the influence of flunarizine on dopamine D2 receptors and investigated whether dopamine D2 receptor blockade is involved in its antimigraine action. Eleven migraine patients, treated with flunarizine, 10 mg per day, underwent single photon emission computer tomography (SPECT) using [123I] labeled iodobenzamide, a ligand with high affinity and high specificity for D2 receptors. There was a reduction of the dopamine D2 receptor binding potential in all patients compared to age-matched controls. The efficacy of flunarizine in migraine prophylaxis failed to correlate with the degree of the dopamine D2 receptor blockade. The antimigraine action of flunarizine may not involve antidopaminergic mechanisms.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADyaK2M%252Fkt1KksA%253D%253D&md5=b47a181903189786358c99422fcd22aa
  74. 74
    Yan, Y.; Pan, J.; Chen, Y.; Xing, W.; Li, Q.; Wang, D.; Zhou, X.; Xie, J.; Miao, C.; Yuan, Y.; Zeng, W.; Chen, D. Increased Dopamine and Its Receptor Dopamine Receptor D1 Promote Tumor Growth in Human Hepatocellular Carcinoma. Cancer Commun. 2020, 694,  DOI: 10.1002/cac2.12103
    Google Scholar
    74
    Increased dopamine and its receptor dopamine receptor D1 promote tumor growth in human hepatocellular carcinoma
    Yan Yan; Pan Jiahao; Xing Wei; Li Qiang; Wang Dongyin; Zhou Xiaoshuang; Xie Jingdun; Zeng Weian; Chen Dongtai; Yan Yan; Chen Yonghua; Miao Changhong; Yuan Yunfei
    Cancer communications (London, England) (2020), 40 (12), 694-710 ISSN:.
    BACKGROUND: Dopamine and dopamine receptor D1 (DRD1), a member of the dopamine receptor family, have been indicated to play important roles in cancer progression, but dopamine secretion in hepatocellular carcinoma (HCC) and the effects of DRD1 on HCC remain unclear. This study was designed to explore the contribution of the dopaminergic system to HCC and determine the relationship between DRD1 and prognosis in HCC patients. METHODS: The dopamine metabolic system was monitored using enzyme-linked immunosorbent assays (ELISAs). The expression of DRD1 was detected by microarray analysis, immunohistochemistry (IHC), and quantitative real-time PCR (qRT-PCR). Stable DRD1 knockout and overexpression cell lines were established for investigation. Transwell, colony formation, and Cell Counting Kit 8 (CCK8) assays were performed to assess the malignant behaviors of cancer cells. The cAMP/PI3K/AKT/ cAMP response element-binding (CREB) signaling pathway was evaluated by Western blot. This pathway, which is agitated by DRD1 in striatal neurons, had been proven to participate in tumor progression. Xenograft HCC tumors were generated for in vivo experiments. RESULTS: Dopamine secretion increased locally in HCC due to an imbalance in dopamine metabolism, including the upregulation of dopa decarboxylase (DDC) and the downregulation of monoamine oxidase A (MAOA). Dopamine promoted the proliferation and metastasis of HCC. DRD1 was highly expressed in HCC tissues and positive DRD1 expression was related to a poor prognosis in HCC patients. The upregulation of DRD1 agitated malignant activities, including proliferation and metastasis in HCC by regulating the cAMP/PI3K/AKT/CREB pathway, and the downregulation of DRD1 had opposing effects. The effects of dopamine on HCC was reversed by depleting DRD1. SCH23390, a selective DRD1 antagonist, inhibited the proliferation and metastasis of HCC cells both in vitro and in vivo. CONCLUSION: Dopamine secretion was locally increased in HCC and promoted HCC cell proliferation and metastasis. DRD1 was found to exert positive effects on HCC progression and play a vital role in the dopamine system, and could be a potential therapeutic target and prognostic biomarker for HCC.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3s%252FnsFyrtg%253D%253D&md5=ebb589ca4c6414c523621969d7c1b7c4
  75. 75
    Kafka, S. H.; Corbett, R. Selective Adenosine A2A Receptor/Dopamine D2 Receptor Interactions in Animal Models of Schizophrenia. Eur. J. Pharmacol. 1996, 295, 147– 154,  DOI: 10.1016/0014-2999(95)00668-0
    Google Scholar
    75
    Selective adenosine A2A receptor/dopamine D2 receptor interactions in animal models of schizophrenia
    Kafka, Sharon H.; Corbett, Roy
    European Journal of Pharmacology (1996), 295 (2/3), 147-54CODEN: EJPHAZ; ISSN:0014-2999. (Elsevier)
    In the apomorphine-induced climbing mouse assay, the potencies of the selective adenosine A1 receptor agonist, N6-cyclohexyladenosine (CHA), and the selective A2A adenosine receptor agonist, 2-p-(2-carboxyethyl) phenethylamino 5'-N-ethylcarboxamidoadenosine (CGS 21680), and various dopamine receptor antagonists were as follows: SCH 23390 = haloperidol > raclopride > CHA = CGS 21680. While in catalepsy, their potencies were SCH 23390 > haloperidol > raclopride > CGS 21680. CHA failed to induce catalepsy due to significant sedation/ataxia. The combined administration of the ED15 dose of CHA failed to potentiate the ED50 value of SCH 23390, raclopride, or haloperidol in the apomorphine-induced climbing mouse assay. However, the combined administration of the ED15 dose of CGS 21680 significantly decreased the ED50 of raclopride by 8.0-fold and haloperidol by 35-fold. The adenosine A2A receptor antagonist, 1,3,7-trimethyl-8-(3-chlorostyryl)xanthine (CSC), significantly decreased catalepsy induced by raclopride and haloperidol, while the adenosine A1 receptor antagonist, 1,3-dimethyl-8-phenylxanthine (8-PT), was ineffective. The present results show that in behavioral assays predictive for antipsychotic activity, adenosine receptor agonists block behaviors in a similar manner to dopamine receptor antagonists.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XjtVaruw%253D%253D&md5=4a9693816110c9f5625661786e74fd27
  76. 76
    Belforte, J. E.; Magariños-Azcone, C.; Armando, I.; Buño, W.; Pazo, J. H. Pharmacological Involvement of the Calcium Channel Blocker Flunarizine in Dopamine Transmission at the Striatum. Parkinsonism Relat. Disord. 2001, 8, 33– 40,  DOI: 10.1016/s1353-8020(01)00006-2
    Google Scholar
    76
    Pharmacological involvement of the calcium channel blocker flunarizine in dopamine transmission at the striatum
    Belforte J E; Magarinos-Azcone C; Armando I; Buno W; Pazo J H
    Parkinsonism & related disorders (2001), 8 (1), 33-40 ISSN:1353-8020.
    Single intrastriatal microinjections of 25, 50 and 100nmol/microl of flunarizine in normal rats produced a dose-dependent turning behavior toward the injected side when they were challenged with apomorphine (1mg/kg, s.c). This effect was seen at 1, 3 and 7 days following administration of the high dose of flunarizine, but had subsided by 24h after administration of the intermediate dose; the low dose was ineffective. However, intrastriatal injection of the high dose of flunarizine resulted in a local lesion and thereafter this dose was not used. A similar dose-response relationship was determined for nifedipine, an L-type calcium channel antagonist. Injection of this antagonist did not result in apomorphine-elicited rotational behavior, reflecting its lack of antidopaminergic action. Intrastriatal injections of haloperidol (5microg/microl), an antagonist of dopamine D(2) receptors, or the sodium channel blocker lidocaine (40microg/microl), were given in order to compare their effects to those observed with flunarizine. Intracerebral injection of haloperidol produced ipsilateral turning in response to systemic administration of apomorphine given 60min after. The same response was obtained with the injection of apomorphine 10min after the injection of intracerebral lidocaine. This effect was no longer apparent 24h after the microinjection of haloperidol and 60min after the injection of lidocaine. In rats rendered hemiparkinsionian by lesioning the nigrostriatal pathway with 6OHDA, intrastriatal microinjection of flunarizine (50nmol/microl) significantly reduced apomorphine (0.2mg/kg, s.c.)-elicited turning behavior towards the non-lesioned side. These results suggest an antidopaminergic effect of flunarizine mediated by antagonistic action of post-synaptic striatal dopamine receptors. However, an action of the drug on sodium channels may not be ruled out. These studies offer additional supporting evidence for the induction or aggravation of extrapyramidal side-effects in patients receiving flunarizine.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD38zgt1Khtg%253D%253D&md5=a6280d94b5b4e6e313debfbe5abf26d4
  77. 77
    Karsan, N.; Palethorpe, D.; Rattanawong, W.; Marin, J. C.; Bhola, R.; Goadsby, P. J. Flunarizine in Migraine-Related Headache Prevention: Results from 200 Patients Treated in the UK. Eur. J. Neurol. 2018, 25, 811– 817,  DOI: 10.1111/ene.13621
    Google Scholar
    77
    Flunarizine in migraine-related headache prevention: results from 200 patients treated in the UK
    Karsan N; Palethorpe D; Rattanawong W; Marin J C; Bhola R; Goadsby P J; Karsan N; Palethorpe D; Rattanawong W; Marin J C; Bhola R; Goadsby P J
    European journal of neurology (2018), 25 (6), 811-817 ISSN:.
    BACKGROUND AND PURPOSE: For over 20 years, as a group we have been using flunarizine in primary headache disorders. Flunarizine is widely used in Europe, but not licensed in the UK. In September 2014, the National Institute for Clinical Excellence published supportive guidelines for flunarizine use in migraine, based on randomized controlled evidence that it is as effective as propranolol and topiramate in adults. METHODS: We reviewed a cohort of adult patients (n = 200) treated with flunarizine from our practice. The clinical information of these patients, i.e. diagnosis, dose, efficacy, side effects and duration of treatment, was collected. RESULTS: The most common indication for flunarizine use was chronic migraine, followed by migraine with aura, sporadic hemiplegic migraine, familial hemiplegic migraine and new daily persistent headache with migrainous features. Flunarizine was generally effective, with only 24% (n = 47) of patients reporting no clinical effect. The most common dose used was 10 mg per day. Duration of treatment information was available for 39% (n = 78) of patients. Of these patients, 64% (n = 50) continued treatment for more than 1 year. Doses up to 15 mg were generally well tolerated, with only 10.5% (n = 21) of patients stopping treatment due to adverse effects. The most common adverse events were tiredness, mood change and weight gain. CONCLUSION: The data provide supportive evidence from tertiary headache practice in the UK for the use of flunarizine in migraine. The data encourages development of future guidance regarding flunarizine use in headache centres in countries where its use is not routine.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MrosFSkug%253D%253D&md5=dbd9bce6300fd702d4689846c737ca12
  78. 78
    Amery, W. K.; Caers, L. I.; Aerts, T. J. L. Flunarizine, a Calcium Entry Blocker in Migraine Prophylaxis. J. Headache Pain 1985, 25, 249– 254,  DOI: 10.1111/j.1526-4610.1985.hed2505249.x
    Google Scholar
    There is no corresponding record for this reference.
  79. 79
    Piccini, P.; Nuti, A.; Paoletti, A. M.; Napolitano, A.; Melis, G. B.; Bonuccelli, U. Possible Involvement of Dopaminergic Mechanisms in the Antimigraine Action of Flunarizine. Cephalalgia 1990, 10, 3– 8,  DOI: 10.1046/j.1468-2982.1990.1001003.x
    Google Scholar
    79
    Possible involvement of dopaminergic mechanisms in the antimigraine action of flunarizine
    Piccini P; Nuti A; Paoletti A M; Napolitano A; Melis G B; Bonuccelli U
    Cephalalgia : an international journal of headache (1990), 10 (1), 3-8 ISSN:0333-1024.
    Flunarizine, a calcium antagonist widely used in the prophylactic treatment of migraine, may interfere with dopaminergic systems. Flunarizine therapy can in fact induce extrapyramidal side effects and can increase basal as well as stimulated prolactin levels. To better define the mechanism of flunarizine action in migraine, we studied prolactin and growth hormone responses to thyrotropin releasing hormone and sulpiride in 13 female migraineurs before and after 60 days of flunarizine therapy. The treatment did not modify basal prolactin and growth hormone levels, but prolactin response to thyrotropin releasing hormone was enhanced. A paradoxical increase of growth hormone to thyrotropin releasing hormone observed before therapy was blunted after flunarizine treatment. These data indicate a modulatory action of flunarizine on dopaminergic systems which might to some extent explain the antimigraine action of this drug.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADyaK3c7pvFyntg%253D%253D&md5=feb337ba996ec12e6fc463edbb5789a3
  80. 80
    Frisch, M. J. Gaussian 09, Revision B.01, Gaussian, Inc. 2009.
    Google Scholar
    There is no corresponding record for this reference.
  81. 81
    O’Boyle, N. M.; Banck, M.; James, C. A.; Morley, C.; Vandermeersch, T.; Hutchison, G. R. Open Babel: An Open Chemical Toolbox. J. Cheminf. 2011, 3, 33,  DOI: 10.1186/1758-2946-3-33
    Google Scholar
    81
    Open Babel: an open chemical toolbox
    O'Boyle, Noel M.; Banck, Michael; James, Craig A.; Morley, Chris; Vandermeersch, Tim; Hutchison, Geoffrey R.
    Journal of Cheminformatics (2011), 3 (), 33CODEN: JCOHB3; ISSN:1758-2946. (Chemistry Central Ltd.)
    Background: A frequent problem in computational modeling is the interconversion of chem. structures between different formats. While std. interchange formats exist (for example, Chem. Markup Language) and de facto stds. have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chem. data, differences in the data stored by different formats (0D vs. 3D, for example), and competition between software along with a lack of vendor-neutral formats. Results: We discuss, for the first time, Open Babel, an open-source chem. toolbox that speaks the many languages of chem. data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chem. and mol. data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Conclusions: Open Babel presents a soln. to the proliferation of multiple chem. file formats. In addn., it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chem. data in areas such as org. chem., drug design, materials science, and computational chem. It is freely available under an open-source license.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVWjurbF&md5=74e4f19b7f87417f916d57f7abcfb761
  82. 82
    Jaiteh, M.; Rodríguez-Espigares, I.; Selent, J.; Carlsson, J. Performance of Virtual Screening against GPCR Homology Models: Impact of Template Selection and Treatment of Binding Site Plasticity. PLoS Comput. Biol. 2020, 16, e1007680– e1007680,  DOI: 10.1371/journal.pcbi.1007680
    Google Scholar
    82
    Performance of virtual screening against GPCR homology models: impact of template selection and treatment of binding site plasticity
    Jaiteh, Mariama; Rodriguez-Espigares, Ismael; Selent, Jana; Carlsson, Jens
    PLoS Computational Biology (2020), 16 (3), e1007680/1-e1007680/25CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)
    Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small no. of available at. resoln. structures. We assessed the use of homol. modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Comparison of the homol. models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. Mol. docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Mol. dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homol. models. These results provide guide-lines for successful application of structure-based ligand discovery using GPCR homol. models.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXps1Wrtrk%253D&md5=a39e9cd1e6a711f8f8765ce7fd347f36
  83. 83
    Morris, G. M.; Lim-Wilby, M. Molecular Docking. Methods Mol. Biol. 2008, 443, 365– 382,  DOI: 10.1007/978-1-59745-177-2_19
    Google Scholar
    83
    Molecular docking
    Morris, Garrett M.; Lim-Wilby, Marguerita
    Methods in Molecular Biology (Totowa, NJ, United States) (2008), 443 (Molecular Modeling of Proteins), 365-382CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)
    A review. Mol. docking is a key tool in structural mol. biol. and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compds., rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of mol. docking software, and covers the usage of some of the most-cited docking software.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXktFCis74%253D&md5=3125f282b5fc4d65f9828445a5eb46bb
  84. 84
    Pettersen, E. F.; Goddard, T. D.; Huang, C. C.; Couch, G. S.; Greenblatt, D. M.; Meng, E. C.; Ferrin, T. E. UCSF Chimera--a Visualization System for Exploratory Research and Analysis. J. Comput. Chem. 2004, 25, 1605– 1612,  DOI: 10.1002/jcc.20084
    Google Scholar
    84
    UCSF Chimera-A visualization system for exploratory research and analysis
    Pettersen, Eric F.; Goddard, Thomas D.; Huang, Conrad C.; Couch, Gregory S.; Greenblatt, Daniel M.; Meng, Elaine C.; Ferrin, Thomas E.
    Journal of Computational Chemistry (2004), 25 (13), 1605-1612CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale mol. assemblies such as viral coats, and Collab., which allows researchers to share a Chimera session interactively despite being at sep. locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and assocd. structures; ViewDock, for screening docked ligand orientations; Movie, for replaying mol. dynamics trajectories; and Vol. Viewer, for display and anal. of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXmvVOhsbs%253D&md5=944b175f440c1ff323705987cf937ee7
  85. 85
    Guner, O.; Clement, O.; Kurogi, Y. Pharmacophore Modeling and Three Dimensional Database Searching for Drug Design Using Catalyst: Recent Advances. Curr. Med. Chem. 2004, 11, 2991– 3005,  DOI: 10.2174/0929867043364036
    Google Scholar
    85
    Pharmacophore modeling and three dimensional database searching for drug design using catalyst: recent advances
    Guner Osman; Clement Omoshile; Kurogi Yasuhisa
    Current medicinal chemistry (2004), 11 (22), 2991-3005 ISSN:0929-8673.
    Perceiving a pharmacophore is the first essential step towards understanding the interaction between a receptor and a ligand. Once a pharmacophore is established, a beneficial use of it is 3D database searching to retrieve novel compounds that would match the pharmacophore. As the 3D searching technology has evolved over the years, it has been effectively used for lead optimization, combinatorial library focusing, as well as virtual high-throughput screening. This paper is an update to the original paper published in this journal earlier: Kurogi, Y, and Guner, O. F. "Pharmacophore Modeling and Three-Dimensional Database Searching for Drug Design Using Catalyst," in Current Medicinal Chemistry, 2001, 8(9), 1035-1055.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2crnt1eiuw%253D%253D&md5=2a9b7d5a86415bad0959dcd9e737f934
  86. 86
    Cheng, F.; Li, W.; Zhou, Y.; Shen, J.; Wu, Z.; Liu, G.; Lee, P. W.; Tang, Y. AdmetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. J. Chem. Inf. Model. 2012, 52, 3099– 3105,  DOI: 10.1021/ci300367a
    Google Scholar
    86
    admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties
    Cheng, Feixiong; Li, Weihua; Zhou, Yadi; Shen, Jie; Wu, Zengrui; Liu, Guixia; Lee, Philip W.; Tang, Yun
    Journal of Chemical Information and Modeling (2012), 52 (11), 3099-3105CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    A review. Absorption, distribution, metab., excretion, and toxicity (ADMET) properties play key roles in the discovery/development of drugs, pesticides, food additives, consumer products, and industrial chems. This information is esp. useful when to conduct environmental and human hazard assessment. The most crit. rate limiting step in the chem. safety assessment workflow is the availability of high quality data. This paper describes an ADMET structure-activity relationship database, abbreviated as admetSAR. It is an open source, text and structure searchable, and continually updated database that collects, curates, and manages available ADMET-assocd. properties data from the published literature. In admetSAR, over 210 000 ADMET annotated data points for more than 96,000 unique compds. with 45 kinds of ADMET-assocd. properties, proteins, species, or organisms have been carefully curated from a large no. of diverse literatures. The database provides a user-friendly interface to query a specific chem. profile, using either CAS registry no., common name, or structure similarity. In addn., the database includes 22 qual. classification and 5 quant. regression models with highly predictive accuracy, allowing to est. ecol./mammalian ADMET properties for novel chems. AdmetSAR is accessible free of charge at http://www.admetexp.org.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFGmtbnJ&md5=93b02a243f5b50a8d457880ef867007b
  87. 87
    Anbu, V.; Karthick, T.; Vijayalakshmi, K. A. Combined Experimental and Computational Approach for the Vibrational Characteristics and Theoretical Evaluation of Binding Activities and ADME Descriptors of 2,6-Di-Tert-Butyl-p-Cresol. Polycyclic Aromat. Compd. 2020, 1– 17,  DOI: 10.1080/10406638.2020.1768567
    Google Scholar
    There is no corresponding record for this reference.
  88. 88
    Newby, D.; Freitas, A. A.; Ghafourian, T. Decision Trees to Characterise the Roles of Permeability and Solubility on the Prediction of Oral Absorption. Eur. J. Med. Chem. 2015, 90, 751– 765,  DOI: 10.1016/j.ejmech.2014.12.006
    Google Scholar
    88
    Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption
    Newby, Danielle; Freitas, Alex A.; Ghafourian, Taravat
    European Journal of Medicinal Chemistry (2015), 90 (), 751-765CODEN: EJMCA5; ISSN:0223-5234. (Elsevier Masson SAS)
    Oral absorption of compds. depends on many physiol., physiochem. and formulation factors. Two important properties that govern oral absorption are in vitro permeability and soly., which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aq. soly., m.p., and max. dose for the same compds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a soly.-related parameter such as exptl. or predicted soly., or the m.p. based absorption potential (MPbAP), along with structural mol. descriptors were developed and validated to predict oral absorption class. The decision trees were able to det. the individual roles of permeability and soly. in oral absorption process. Poorly permeable compds. with high soly. show low intestinal absorption, whereas poorly water sol. compds. with high or low permeability may have high intestinal absorption provided that they have certain mol. characteristics such as a small polar surface or specific topol.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVyksrvM&md5=b7904ecbe359d31b61e298b23afb4cf9
  89. 89
    Ursu, O.; Rayan, A.; Goldblum, A.; Oprea, T. I. Understanding Drug-Likeness. WIREs Comput. Mol. Sci. 2011, 1, 760– 781,  DOI: 10.1002/wcms.52
    Google Scholar
    89
    Understanding drug-likeness
    Ursu, Oleg; Rayan, Anwar; Goldblum, Amiram; Oprea, Tudor I.
    Wiley Interdisciplinary Reviews: Computational Molecular Science (2011), 1 (5), 760-781CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)
    A review. "Drug-likeness", a qual. property of chems. assigned by experts committee vote, is wedely integrated into the early stages of lead and drug discovery. Its conceptual evolution paralleled work related to Pfizer's "rule of five" and lead-likeness, and is placed within this framework. The discrimination between "drugs" (represented by a collection of pharmaceutically relevant small mols., some of which are marketed drugs) and "nondrugs" (typically, chem. reagents) is possible using a wide variety of statistical tools and chem. descriptor systems. Here we summarize 18 papers focused on drug-likeness, and provide a comprehensive overview of progress in the field. Tools that est. drug-likeness are valuable in the early stages of lead discovery, and can be used to filter out compds. with undersirable properties from screening libraries and to prioritize hits from primary screens. As the goal is, most often, to develop orally available drugs, it is also useful to optimize drug-like pharmacokinetic properties. We examine tools that evaluate drug-likeness and some of their shortcomings, challenges facing these tools, and address the following issues: What is the definition of drug-likeness and how can it be utilized to reduce attrition rate in drug discovery. How difficult is it to distinguish drugs from nondrugs. Are nondrug datasets reliable. Can we est. oral drug-likeness. We discuss a drug-like filter and recent advances in the prediction of oral drug-likeness. The heuristic aspect of drug-likeness is also addressed.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFWrtrbO&md5=3cd46a7a7a082d6d3730e6bbf16712d2
  90. 90
    Rankovic, Z. CNS Drug Design: Balancing Physicochemical Properties for Optimal Brain Exposure. J. Med. Chem. 2015, 58, 2584– 2608,  DOI: 10.1021/jm501535r
    Google Scholar
    90
    CNS Drug Design: Balancing Physicochemical Properties for Optimal Brain Exposure
    Rankovic, Zoran
    Journal of Medicinal Chemistry (2015), 58 (6), 2584-2608CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
    A review. The human brain is a uniquely complex organ, which has evolved a sophisticated protection system to prevent injury from external insults and toxins. Designing mols. that can overcome this protection system and achieve optimal concn. at the desired therapeutic target in the brain is a specific and major challenge for medicinal chemists working in CNS drug discovery. Analogous to the now widely accepted rule of 5 in the design of oral drugs, the physicochem. properties required for optimal brain exposure have been extensively studied in an attempt to similarly define the attributes of successful CNS drugs and drug candidates. This body of work is systematically reviewed here, with a particular emphasis on the interplay between the most crit. physicochem. and pharmacokinetic parameters of CNS drugs as well as their impact on medicinal chem. strategies toward mols. with optimal brain exposure. A summary of modern CNS pharmacokinetic concepts and methods is also provided.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVyhsrrP&md5=f01e3f2dc4e2eff7b0618124277a5cf8
  91. 91
    Ghose, A. K.; Herbertz, T.; Hudkins, R. L.; Dorsey, B. D.; Mallamo, J. P. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery. ACS Chem. Neurosci. 2012, 3, 50– 68,  DOI: 10.1021/cn200100h
    Google Scholar
    91
    Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery
    Ghose, Arup K.; Herbertz, Torsten; Hudkins, Robert L.; Dorsey, Bruce D.; Mallamo, John P.
    ACS Chemical Neuroscience (2012), 3 (1), 50-68CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
    The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochem. and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compds., we analyzed the physicochem. property and the chem. structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined anal. provided the following guidelines for designing high-quality CNS drugs: (i) topol. mol. polar surface area of <76 Å2 (25-60 Å2), (ii) at least one (one or two, including one aliph. amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) vol. of 740-970 Å3, (vi) solvent accessible surface area of 460-580 Å2, and (vii) pos. QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The chemoinformatics approaches for graphically analyzing multiple properties efficiently are presented.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVSit7rO&md5=4c20ba34c3d5397170b50242975ce25d
  92. 92
    Zafar, F.; Gupta, A.; Thangavel, K.; Khatana, K.; Sani, A. A.; Ghosal, A.; Tandon, P.; Nishat, N. Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives. ACS Omega 2020, 5, 6021– 6030,  DOI: 10.1021/acsomega.9b04398
    Google Scholar
    92
    Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives
    Zafar, Fahmina; Gupta, Anjali; Thangavel, Karthick; Khatana, Kavita; Sani, Ali Alhaji; Ghosal, Anujit; Tandon, Poonam; Nishat, Nahid
    ACS Omega (2020), 5 (11), 6021-6030CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
    Anacardic acid (AA) and its derivs. are well-known for their therapeutic applications ranging from antitumor, antibacterial, antioxidant, anticancer, and so forth. However, their poor pharmacokinetic and safety properties create significant hurdles in the formulation of the final drug mol. As a part of our endeavor to enhance the potential and exploration of the anticancer activities, a detailed study on the properties of selected AA derivs. was performed in this work. A comprehensive anal. of the drug-like properties of 100 naturally occurring AA derivs. was performed, and the results were compared with certain marketed anticancer drugs. The work focused on the understanding of the interplay among eight physicochem. properties. The relationships between the physicochem. properties, absorption, distribution, metab., and excretion attributes, and the in silico toxicity profile for the set of AA derivs. were established. The ligand efficacy of the finally scrutinized 17 AA derivs. on the basis of pharmacokinetic properties and toxicity parameters was further subjected to dock against the potential anticancer target cyclin-dependent kinase 2 (PDB ID: 1W98). In the docked complex, the ligand mols. (AA derivs.) selectively bind with the target residues, and a high binding affinity of the ligand mols. was ensured by the full fitness score using the SwissDock Web server. The BOILED-Egg model shows that out of 17 scrutinized mols., 3 mols. exhibit gastrointestinal absorption capability and 14 mols. exhibit permeability through the blood-brain barrier penetration. The anal. can also provide some useful insights to chemists to modify the existing natural scaffolds in designing new anacardic anticancer drugs. The increased probability of success may lead to the identification of drug-like candidates with favorable safety profiles after further clin. evaluation.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXkslemsr0%253D&md5=9f1d51d83ba9c30498a508229afafaa4
  93. 93
    Singh, N.; Kumar, N.; Rathee, G.; Sood, D.; Singh, A.; Tomar, V.; Dass, S. K.; Chandra, R. Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches. ACS Omega 2020, 5, 2267– 2279,  DOI: 10.1021/acsomega.9b03479
    Google Scholar
    93
    Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches
    Singh, Nidhi; Kumar, Neeraj; Rathee, Garima; Sood, Damini; Singh, Aarushi; Tomar, Vartika; Dass, Sujata K.; Chandra, Ramesh
    ACS Omega (2020), 5 (5), 2267-2279CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
    Chalcone, a privileged structure, is considered as an effective template in the field of medicinal chem. for potent drug discovery. In the present study, a privileged template chalcone was designed, synthesized, and characterized by various spectroscopic techniques (NMR, high-resoln. mass spectrometry, Fourier transform IR (FT-IR) spectroscopy, UV spectroscopy, and single-crystal X-ray diffraction). The mechanism of binding of chalcone with bovine serum albumin (BSA) was detd. by multispectroscopic techniques and computational methods. Steady-state fluorescence spectroscopy suggests that the intrinsic fluorescence of BSA was quenched upon the addn. of chalcone by the combined dynamic and static quenching mechanism. Time-resolved spectroscopy confirms complex formation. FT-IR and CD spectroscopy suggested the presence of chalcone in the BSA mol. microenvironment and also the possibility of rearrangement of the native structure of BSA. Moreover, mol. docking studies confirm the moderate binding of chalcone with BSA and the mol. dynamics simulation anal. shows the stability of the BSA-drug complex system with minimal deformability fluctuations and potential interaction by the covariance matrix. Moreover, pharmacodynamics and pharmacol. anal. show good results through Lipinski rules, with no toxicity profile and high gastrointestinal absorptions by boiled egg permeation assays. This study elucidates the mechanistic profile of the privileged chalcone scaffold to be used in therapeutic applications.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhs1Smtbs%253D&md5=7b683aaf8be2e0760e619929e1a2b845
  94. 94
    Al-Blewi, F.; Rezki, N.; Naqvi, A.; Qutb Uddin, H.; Al-Sodies, S.; Messali, M.; Aouad, M. R.; Bardaweel, S. A Profile of the In Vitro Anti-Tumor Activity and In Silico ADME Predictions of Novel Benzothiazole Amide-Functionalized Imidazolium Ionic Liquids. Int. J. Mol. Sci. 2019, 20, 2865,  DOI: 10.3390/ijms20122865
    Google Scholar
    94
    A profile of the in vitro anti-tumor activity and in silico ADME predictions of novel benzothiazole amide-functionalized imidazolium ionic liquids
    Al-Blewi, Fawzia; Rezki, Nadjet; Naqvi, Arshi; Uddin, Husna Qutb; Al-Sodies, Salsabeel; Messali, Mouslim; Aouad, Mohamed Reda; Bardaweel, Sanaa
    International Journal of Molecular Sciences (2019), 20 (12), 2865CODEN: IJMCFK; ISSN:1422-0067. (MDPI AG)
    A focused array of green imidazolium ionic liqs. (ILs) encompassing benzothiazole ring and amide linkage were designed and synthesized using quaternization and metathesis protocols. The synthesized ILs have been fully characterized by usual spectroscopic methods and screened for their anticancer activities against human cancer cell lines originating from breast and colon cancers. Collectively, our biol. data demonstrate that the newly synthesized series has variable anticancer activities in the examd. cancer types. The synthesized ILs 8, 10 and 21-29 comprising the Me and Me sulfonyl benzothiazole ring emerged as the most potent compds. with promising antiproliferative activities relative to their benzothiazole ring counterparts. Furthermore, the mechanism underlying the obsd. anticancer activity was investigated. The most active compd. 22 appears to exert its anticancer effect through apoptosis dependent pathway in breast cancer cells. Interestingly, compd. 22 has also shown good in silico absorption (81.75%) along with high gastro-intestinal absorption as per ADME predictions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFGrs7c%253D&md5=4ea3bb4d9142d32a6248248dd27dc96c
  95. 95
    Ahmad, S. S.; Sinha, M.; Ahmad, K.; Khalid, M.; Choi, I. Study of Caspase 8 Inhibition for the Management of Alzheimer’s Disease: A Molecular Docking and Dynamics Simulation. Molecules 2020, 25, 2071,  DOI: 10.3390/molecules25092071
    Google Scholar
    95
    Study of caspase 8 inhibition for the management of Alzheimer's disease: A Molecular Docking and Dynamics Simulation
    Ahmad, Syed Sayeed; Sinha, Meetali; Ahmad, Khurshid; Khalid, Mohammad; Choi, Inho
    Molecules (2020), 25 (9), 2071CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
    Alzheimer's disease (AD) is the most common type of dementia and usually manifests as diminished episodic memory and cognitive functions. Caspases are crucial mediators of neuronal death in a no. of neurodegenerative diseases, and caspase 8 is considered a major therapeutic target in the context of AD. In the present study, we performed a virtual screening of 200 natural compds. by mol. docking with respect to their abilities to bind with caspase 8. Among them, rutaecarpine was found to have the highest (neg.) binding energy (-6.5 kcal/mol) and was further subjected to mol. dynamics (MD) simulation anal. Caspase 8 was detd. to interact with rutaecarpine through five amino acid residues, specifically Thr337, Lys353, Val354, Phe355, and Phe356, and two hydrogen bonds (ligand: H35-A: LYS353:O and A:PHE355: N-ligand: N5). Furthermore, a 50 ns MD simulation was conducted to optimize the interaction, to predict complex flexibility, and to investigate the stability of the caspase 8-rutaecarpine complex, which appeared to be quite stable. The obtained results propose that rutaecarpine could be a lead compd. that bears remarkable anti-Alzheimer's potential against caspase 8.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFWgurfN&md5=42c8668c9347e7077ec9ac18edb4b0b8
  96. 96
    Loureiro, D. R. P.; Soares, J. X.; Costa, J. C.; Magalhães, Á. F.; Azevedo, C. M. G.; Pinto, M. M. M.; Afonso, C. M. M. Structures, Activities and Drug-Likeness of Anti-Infective Xanthone Derivatives Isolated from the Marine Environment: A Review. Molecules 2019, 24, 243,  DOI: 10.3390/molecules24020243
    Google Scholar
    96
    Structures, activities and drug-likeness of anti-infective xanthone derivatives isolated from the marine environment: a review
    Loureiro, Daniela R. P.; Soares, Jose X.; Costa, Joana C.; Magalhaes, Alvaro F.; Azevedo, Carlos M. G.; Pinto, Madalena M. M.; Afonso, Carlos M. M.
    Molecules (2019), 24 (2), 243/1-243/23CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
    Marine organisms represent almost half of total biodiversity and are a very important source of new bioactive substances. Within the varied biol. activities found in marine products, their antimicrobial activity is one of the most relevant. Infectious diseases are responsible for high levels of morbidity and mortality and many antimicrobials lose their effectiveness with time due to the development of resistance. These facts justify the high importance of finding new, effective and safe anti-infective agents. Among the variety of biol. activities of marine xanthone derivs., one that must be highlighted is their anti-infective properties. In this work, a literature review of marine xanthones with anti-infective activity, namely antibacterial, antifungal, antiparasitic and antiviral, is presented. Their structures, biol. activity, sources and the methods used for bioactivity evaluation are described. The xanthone derivs. are grouped in three sets: xanthones, hydroxanthones and glycosylated derivs. Moreover, mol. descriptors, biophysico-chem. properties, and pharmacokinetic parameters were calcd., and the chem. space occupied by marine xanthone derivs. is recognized. The chem. space was compared with marketed drugs and framed accordingly to the drug-likeness concept in order to profile the pharmacokinetic of anti-infective marine xanthone derivs.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXnvVWksro%253D&md5=5af03f519089965e4f182ae4656dda3b
  97. 97
    Kehinde, I.; Ramharack, P.; Nlooto, M.; Gordon, M. The Pharmacokinetic Properties of HIV-1 Protease Inhibitors: A Computational Perspective on Herbal Phytochemicals. Heliyon 2019, 5, e02565– e02565,  DOI: 10.1016/j.heliyon.2019.e02565
    Google Scholar
    There is no corresponding record for this reference.
  98. 98
    Garg, P.; Verma, J.; Roy, N. In Silico Modeling for Blood—Brain Barrier Permeability Predictions. Drug Absorpt. Stud. 2008, 510– 556,  DOI: 10.1007/978-0-387-74901-3_22
    Google Scholar
    There is no corresponding record for this reference.
  99. 99
    Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R. GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. Comput. Phys. Commun. 1995, 91, 43– 56,  DOI: 10.1016/0010-4655(95)00042-E
    Google Scholar
    99
    GROMACS: A message-passing parallel molecular dynamics implementation
    Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R.
    Computer Physics Communications (1995), 91 (1-3), 43-56CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier)
    A parallel message-passing implementation of a mol. dynamics (MD) program that is useful for bio(macro)mols. in aq. environment is described. The software has been developed for a custom-designed 32-processor ring GROMACS (Groningen MAchine for Chem. Simulation) with communication to and from left and right neighbors, but can run on any parallel system onto which a a ring of processors can be mapped and which supports PVM-like block send and receive calls. The GROMACS software consists of a preprocessor, a parallel MD and energy minimization program that can use an arbitrary no. of processors (including one), an optional monitor, and several anal. tools. The programs are written in ANSI C and available by ftp (information: [email protected]). The functionality is based on the GROMOS (Groningen Mol. Simulation) package (van Gunsteren and Berendsen, 1987; BIOMOS B.V., Nijenborgh 4, 9747 AG Groningen). Conversion programs between GROMOS and GROMACS formats are included.The MD program can handle rectangular periodic boundary conditions with temp. and pressure scaling. The interactions that can be handled without modification are variable non-bonded pair interactions with Coulomb and Lennard-Jones or Buckingham potentials, using a twin-range cut-off based on charge groups, and fixed bonded interactions of either harmonic or constraint type for bonds and bond angles and either periodic or cosine power series interactions for dihedral angles. Special forces can be added to groups of particles (for non-equil. dynamics or for position restraining) or between particles (for distance restraints). The parallelism is based on particle decompn. Interprocessor communication is largely limited to position and force distribution over the ring once per time step.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXps1Wrtr0%253D&md5=04d823aeab28ca374efb86839c705179
  100. 100
    Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435– 447,  DOI: 10.1021/ct700301q
    Google Scholar
    100
    GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
    Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik
    Journal of Chemical Theory and Computation (2008), 4 (3), 435-447CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
    Mol. simulation is an extremely useful, but computationally very expensive tool for studies of chem. and biomol. systems. Here, we present a new implementation of our mol. simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decompn. algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addn. used a Multiple-Program, Multiple-Data approach, with sep. node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest nos. of std. cluster nodes.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVSqurc%253D&md5=d53c94901386260221792ea30f151c5f
  101. 101
    van der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. GROMACS: Fast, Flexible, and Free. J. Comput. Chem. 2005, 26, 1701– 1718,  DOI: 10.1002/jcc.20291
    Google Scholar
    101
    GROMACS: Fast, flexible, and free
    Van 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.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1SlsbbO&md5=4aa71b1dc0b5b4978a88b0568245a265
  102. 102
    Michino, M.; Boateng, C. A.; Donthamsetti, P.; Yano, H.; Bakare, O. M.; Bonifazi, A.; Ellenberger, M. P.; Keck, T. M.; Kumar, V.; Zhu, C.; Verma, R.; Deschamps, J. R.; Javitch, J. A.; Newman, A. H.; Shi, L. Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor. J. Med. Chem. 2017, 60, 580– 593,  DOI: 10.1021/acs.jmedchem.6b01148
    Google Scholar
    102
    Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor
    Michino, Mayako; Boateng, Comfort A.; Donthamsetti, Prashant; Yano, Hideaki; Bakare, Oluyomi M.; Bonifazi, Alessandro; Ellenberger, Michael P.; Keck, Thomas M.; Kumar, Vivek; Zhu, Clare; Verma, Ravi; Deschamps, Jeffrey R.; Javitch, Jonathan A.; Newman, Amy Hauck; Shi, Lei
    Journal of Medicinal Chemistry (2017), 60 (2), 580-593CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
    Both dopamine D3 receptor (D3R) partial agonists and antagonists have been implicated as potential medications for substance use disorders. In contrast to antagonists, partial agonists may cause fewer side effects since they maintain some dopaminergic tone and may be less disruptive to normal neuronal functions. Here, the authors report three sets of 4-phenylpiperazine stereoisomers that differ considerably in efficacy: the (R)-enantiomers are antagonists/weak partial agonists, whereas the (S)-enantiomers are much more efficacious. To investigate the structural basis of partial agonism, the authors performed comparative microsecond-scale mol. dynamics simulations starting from the inactive state of D3R in complex with these enantiomers. Anal. of the simulation results reveals common structural rearrangements near the ligand binding site induced by the bound (S)-enantiomers, but not by the (R)-enantiomers, that are features of partially activated receptor conformations. These receptor models bound with partial agonists may be useful for structure-based design of compds. with tailored efficacy profiles.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitFSgu7nK&md5=91e378048c5dfd4c44fb54746a2e1df2
  103. 103
    Wassenaar, T. A.; Mark, A. E. The Effect of Box Shape on the Dynamic Properties of Proteins Simulated under Periodic Boundary Conditions. J. Comput. Chem. 2006, 27, 316– 325,  DOI: 10.1002/jcc.20341
    Google Scholar
    103
    The effect of box shape on the dynamic properties of proteins simulated under periodic boundary conditions
    Wassenaar, Tsjerk A.; Mark, Alan E.
    Journal of Computational Chemistry (2006), 27 (3), 316-325CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    The effect of the box shape on the dynamic behavior of proteins simulated under periodic boundary conditions is evaluated. In particular, the influence of simulation boxes defined by the near-densest lattice packing (NDLP) in conjunction with rotational constraints is compared to that of std. box types without these constraints. Three different proteins of varying size, shape, and secondary structure content were examd. in the study. The statistical significance of differences in RMSD, radius of gyration, solvent-accessible surface, no. of hydrogen bonds, and secondary structure content between proteins, box types, and the application or not of rotational constraints has been assessed. Furthermore, the differences in the collective modes for each protein between different boxes and the application or not of rotational constraints have been examd. In total 105 simulations were performed, and the results compared using a three-way multivariate anal. of variance (MANOVA) for properties derived from the trajectories and a three-way univariate anal. of variance (ANOVA) for collective modes. It is shown that application of roto-translational constraints does not have a statistically significant effect on the results obtained from the different simulations. However, the choice of simulation box was found to have a small (5-10%), but statistically significant effect on the behavior of two of the three proteins included in the study.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht12qtL8%253D&md5=88830b82651ff8ea52559687a503a00c
  104. 104
    Ali, J.; Camilleri, P.; Brown, M. B.; Hutt, A. J.; Kirton, S. B. In Silico Prediction of Aqueous Solubility Using Simple QSPR Models: The Importance of Phenol and Phenol-like Moieties. J. Chem. Inf. Model. 2012, 52, 2950– 2957,  DOI: 10.1021/ci300447c
    Google Scholar
    104
    In Silico Prediction of Aqueous Solubility Using Simple QSPR Models: The Importance of Phenol and Phenol-like Moieties
    Ali, Jogoth; Camilleri, Patrick; Brown, Marc B.; Hutt, Andrew J.; Kirton, Stewart B.
    Journal of Chemical Information and Modeling (2012), 52 (11), 2950-2957CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Recently the authors published a robust QSPR model of aq. soly. which exploited the computationally derived mol. descriptor topog. polar surface area (TPSA) alongside exptl. detd. m.p. and logP. This model (the "TPSA model") is able to accurately predict to within ± one log unit the aq. soly. of 87% of the compds. in a chem. diverse data set of 1265 mols. This is comparable to results achieved for established models of aq. soly. e.g. ESOL (79%) and the General Soly. Equation (81%). Hierarchical clustering of this data set according to chem. similarity shows that a significant no. of mols. with phenolic and/or phenol-like moieties are poorly predicted by these equations. Modification of the TPSA model to addnl. incorporate a descriptor pertaining to a simple count of phenol and phenol-like moieties improves the predictive ability within ± one log unit to 89% for the full data set (1265 compds. -8.48 < logS < 1.58) and 82% for a reduced data set (1160 compds. 6.00 < logS < 0.00) which excludes compds. at the sparsely populated extremities of the data range. This improvement can be rationalized as the addnl. descriptor in the model acting as a correction factor which acknowledges the effect of phenolic substituents on the electronic characteristics of arom. mols. i.e. the generally pos. contribution to aq. soly. made by phenolic moieties.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFOlsbjE&md5=b16631526dbac405a0840b6e57667cc8
  105. 105
    Okuda, S.; Yamada, T.; Hamajima, M.; Itoh, M.; Katayama, T.; Bork, P.; Goto, S.; Kanehisa, M. KEGG Atlas Mapping for Global Analysis of Metabolic Pathways. Nucleic Acids Res. 2008, 36, W423– W426,  DOI: 10.1093/nar/gkn282
    Google Scholar
    105
    KEGG Atlas mapping for global analysis of metabolic pathways
    Okuda, Shujiro; Yamada, Takuji; Hamajima, Masami; Itoh, Masumi; Katayama, Toshiaki; Bork, Peer; Goto, Susumu; Kanehisa, Minoru
    Nucleic Acids Research (2008), 36 (Web Server), W423-W426CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    KEGG Atlas is a new graphical interface to the KEGG suite of databases, esp. to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an assocd. viewer for metab., covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technol. The mapping of high-throughput exptl. data onto the global map is the main use of KEGG Atlas. In the global metab. map, the node (circle) is a chem. compd. and the edge (line) is a set of reactions linked to a set of KEGG Orthol. (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K no. identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chem. compds. are converted to the C no. identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXptlKku7Y%253D&md5=4f2397c5ebc8c0cddb5a922e339bfea4
  106. 106
    Kanehisa, M.; Goto, S.; Sato, Y.; Furumichi, M.; Tanabe, M. KEGG for Integration and Interpretation of Large-Scale Molecular Data Sets. Nucleic Acids Res. 2012, 40, D109– D114,  DOI: 10.1093/nar/gkr988
    Google Scholar
    106
    KEGG for integration and interpretation of large-scale molecular data sets
    Kanehisa, Minoru; Goto, Susumu; Sato, Yoko; Furumichi, Miho; Tanabe, Mao
    Nucleic Acids Research (2012), 40 (D1), D109-D114CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/ or http://www.kegg.jp/) is a database resource that integrates genomic, chem. and systemic functional information. In particular, gene catalogs from completely sequenced genomes are linked to higher-level systemic functions of the cell, the organism and the ecosystem. Major efforts have been undertaken to manually create a knowledge base for such systemic functions by capturing and organizing exptl. knowledge in computable forms; namely, in the forms of KEGG pathway maps, BRITE functional hierarchies and KEGG modules. Continuous efforts have also been made to develop and improve the cross-species annotation procedure for linking genomes to the mol. networks through the KEGG Orthol. system. Here we report KEGG Mapper, a collection of tools for KEGG PATHWAY, BRITE and MODULE mapping, enabling integration and interpretation of large-scale data sets. We also report a variant of the KEGG mapping procedure to extend the knowledge base, where different types of data and knowledge, such as disease genes and drug targets, are integrated as part of the KEGG mol. networks. Finally, we describe recent enhancements to the KEGG content, esp. the incorporation of disease and drug information used in practice and in society, to support translational bioinformatics.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhs12htbrO&md5=d234c2f8945fbec1d3767e11fa96710b
  107. 107
    Kanehisa, M.; Goto, S.; Furumichi, M.; Tanabe, M.; Hirakawa, M. KEGG for Representation and Analysis of Molecular Networks Involving Diseases and Drugs. Nucleic Acids Res. 2010, 38, D355– D360,  DOI: 10.1093/nar/gkp896
    Google Scholar
    107
    KEGG for representation and analysis of molecular networks involving diseases and drugs
    Kanehisa, Minoru; Goto, Susumu; Furumichi, Miho; Tanabe, Mao; Hirakawa, Mika
    Nucleic Acids Research (2010), 38 (Database Iss), D355-D360CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
    Most human diseases are complex multi-factorial diseases resulting from the combination of various genetic and environmental factors. In the KEGG database resource (http://www.genome.jp/kegg/), diseases are viewed as perturbed states of the mol. system, and drugs as perturbants to the mol. system. Disease information is computerized in two forms: pathway maps and gene/mol. lists. The KEGG PATHWAY database contains pathway maps for the mol. systems in both normal and perturbed states. In the KEGG DISEASE database, each disease is represented by a list of known disease genes, any known environmental factors at the mol. level, diagnostic markers and therapeutic drugs, which may reflect the underlying mol. system. The KEGG DRUG database contains chem. structures and/or chem. components of all drugs in Japan, including crude drugs and TCM (Traditional Chinese Medicine) formulas, and drugs in the USA and Europe. This database also captures knowledge about two types of mol. networks: the interaction network with target mols., metabolizing enzymes, other drugs, etc. and the chem. structure transformation network in the history of drug development. The new disease/drug information resource named KEGG MEDICUS can be used as a ref. knowledge base for computational anal. of mol. networks, esp., by integrating large-scale exptl. datasets.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXktlygtg%253D%253D&md5=925b12b2f02668850a855f4606cce2a0

Cited By

ARTICLE SECTIONS
Jump To

This article is cited by 2 publications.

  1. Simona De Vita, Ester Colarusso, Maria Giovanna Chini, Giuseppe Bifulco, Gianluigi Lauro. PharmaCore: The Automatic Generation of 3D Structure-Based Pharmacophore Models from Protein/Ligand Complexes. Journal of Chemical Information and Modeling 2024, Article ASAP.
  2. Ali H. Alharbi. Bio-Computational Evaluation of Compounds of Bacopa Monnieri as a Potential Treatment for Schizophrenia. Molecules 2022, 27 (20) , 7050. https://doi.org/10.3390/molecules27207050
Download PDF

  • Abstract

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 1

    Figure 1. Brief overview of the dopaminergic synapse pathway [KEEG copyright permission obtained: Material: Dopaminergic synapse, pathway map04728. (2021/ KEGG: Kyoto Encyclopedia of Genes and Genomes database resource/Bioinformatics Center, Institute for Chemical Research, Kyoto University and Human Genome Center, Institute of Medical Science, University of Tokyo). (105−107)

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 2

    Figure 2. Established pharmacophore between (A) risperidone and D2 dopamine receptor (PDB: 6CM4-8NU), (B) eticlopride and D3 dopamine receptor (PDB: 3PBL-ETQ), and (C) nemonapride and D4 dopamine receptor (PDB: 5WIU-AQD).

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 3

    Figure 3. Construction of the pharmacophore-shared feature model. (A) Three hydrophobic interactions are represented by the yellow spheres and one positive ionizable area, which is represented as a blue astral center. (B) Four-point pharmacophore model based on shared features of the superposed structures 8NU-risperidone (red), ETQ-eticlopride (green), and AQD-nemonapride (magenta), crystallographic ligands of proteins 6CM4, 3PBL, and 5WIU.

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 4

    Figure 4. Pharmacophore screening results of the four-point shared pharmacophore. The selected compounds as a perfect match were (A) linagliptin, (B) citalopram, (C) flunarizine, (D) sildenafil, (E) minocycline, and (F) duloxetine. The yellow spheres represent the hydrophobic interactions, and the blue areas represent the positive ionizable areas.

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 5

    Figure 5. Docked structures of the flunarizine and the native ligands with D2-like receptors. (A) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D2R (light blue), amino acids that were involucrated in the pharmacophore between the native ligand, risperidone (green), and D2R (lightblue). (B) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D3R (bright orange), amino acids that were involucrated in the pharmacophore between the native ligand, eticlopride (blue), and D3R (bright orange). (C) Amino acids that were involucrated in the pharmacophore between flunarizine (deep purple) and D4R (light cyan), amino acids that were involucrated in the pharmacophore between the native ligand, nemonapride (brown), and D4R (light cyan).

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 6

    Figure 6. Molecular dynamics simulations of DRs unbound and the protein complex with crystallographic ligands and flunarizine: (A) RMSD, (B) RMSF, and (C) radius of gyration plots.

    High Resolution Image
    Download MS PowerPoint Slide

  • References

    ARTICLE SECTIONS
    Jump To

    This article references 107 other publications.

    1. 1
      Lago, S. G.; Bahn, S. Clinical Trials and Therapeutic Rationale for Drug Repurposing in Schizophrenia. ACS Chem. Neurosci. 2019, 10, 58– 78,  DOI: 10.1021/acschemneuro.8b00205
      1
      Clinical Trials and Therapeutic Rationale for Drug Repurposing in Schizophrenia
      Lago, Santiago G.; Bahn, Sabine
      ACS Chemical Neuroscience (2019), 10 (1), 58-78CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
      A review. There is a paucity of efficacious novel drugs to address high rates of treatment resistance and refractory symptoms in schizophrenia. The identification of novel therapeutic indications for approved drugs-drug repurposing-has the potential to expedite clin. trials and reduce the costly risk of failure which currently limits central nervous system drug discovery efforts. In the present Review we discuss the historical role of drug repurposing in schizophrenia drug discovery and review the main classes of repurposing candidates currently in clin. trials for schizophrenia in terms of their therapeutic rationale, mechanisms of action, and preliminary results from clin. trials. Subsequently we outline the challenges and limitations which face the clin. repurposing pipeline and how novel technologies might serve to address these.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtF2qsr7P&md5=38dcc54094733e1fea956d973cd5d615
    2. 2
      Saldívar-González, F.; Prieto-Martínez, F. D.; Medina-Franco, J. L. Descubrimiento y Desarrollo de Fármacos: Un Enfoque Computacional. Educ. Quim. 2017, 28, 51– 58,  DOI: 10.1016/j.eq.2016.06.002
      There is no corresponding record for this reference.
    3. 3
      Lee, H.-M.; Kim, Y. Drug Repurposing Is a New Opportunity for Developing Drugs against Neuropsychiatric Disorders. Schizophr. Res. Treat. 2016, 2016, 1,  DOI: 10.1155/2016/6378137
      There is no corresponding record for this reference.
    4. 4
      Lau, C.-I.; Wang, H.-C.; Hsu, J.-L.; Liu, M.-E. Does the Dopamine Hypothesis Explain Schizophrenia?. Rev. Neurosci. 2013, 24, 389– 400,  DOI: 10.1515/revneuro-2013-0011
      4
      Does the dopamine hypothesis explain schizophrenia?
      Lau, Chi-Ieong; Wang, Han-Cheng; Hsu, Jung-Lung; Liu, Mu-En
      Reviews in the Neurosciences (Berlin, Germany) (2013), 24 (4), 389-400CODEN: RNEUEO; ISSN:0334-1763. (Walter de Gruyter GmbH)
      A review. The dopamine hypothesis has been the cornerstone in the research and clin. practice of schizophrenia. With the initial emphasis on the role of excessive dopamine, the hypothesis has evolved to a concept of combining prefrontal hypodopaminergia and striatal hyperdopaminergia, and subsequently to the present aberrant salience hypothesis. This article provides a brief overview of the development and evidence of the dopamine hypothesis. It will argue that the current model of aberrant salience explains psychosis in schizophrenia and provides a plausible linkage between the pharmacol. and cognitive aspects of the disease. Despite the privileged role of dopamine hypothesis in psychosis, its pathophysiol. rather than etiol. basis, its limitations in defining symptoms other than psychosis, as well as the evidence of other neurotransmitters such as glutamate and adenosine, prompt us to a wider perspective of the disease. Finally, dopamine does explain the pathophysiol. of schizophrenia, but not necessarily the cause per se. Rather, dopamine acts as the common final pathway of a wide variety of predisposing factors, either environmental, genetic, or both, that lead to the disease. Other neurotransmitters, such as glutamate and adenosine, may also collaborate with dopamine to give rise to the entire picture of schizophrenia.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXmslSqsbk%253D&md5=5eebc79abcee91d4045c849e8561bc70
    5. 5
      Beaulieu, J.-M.; Gainetdinov, R. R. The Physiology, Signaling, and Pharmacology of Dopamine Receptors. Pharmacol. Rev. 2011, 63, 182– 217,  DOI: 10.1124/pr.110.002642
      5
      The physiology, signaling, and pharmacology of dopamine receptors
      Beaulieu, Jean-Martin; Gainetdinov, Raul R.
      Pharmacological Reviews (2011), 63 (1), 182-217CODEN: PAREAQ; ISSN:0031-6997. (American Society for Pharmacology and Experimental Therapeutics)
      A review. G protein-coupled dopamine receptors (D1, D2, D3, D4, and D5) mediate all of the physiol. functions of the catecholaminergic neurotransmitter dopamine, ranging from voluntary movement and reward to hormonal regulation and hypertension. Pharmacol. agents targeting dopaminergic neurotransmission have been clin. used in the management of several neurol. and psychiatric disorders, including Parkinson's disease, schizophrenia, bipolar disorder, Huntington's disease, attention deficit hyperactivity disorder (ADHD1), and Tourette's syndrome. Numerous advances have occurred in understanding the general structural, biochem., and functional properties of dopamine receptors that have led to the development of multiple pharmacol. active compds. that directly target dopamine receptors, such as antiparkinson drugs and antipsychotics. Recent progress in understanding the complex biol. of dopamine receptor-related signal transduction mechanisms has revealed that, in addn. to their primary action on cAMP-mediated signaling, dopamine receptors can act through diverse signaling mechanisms that involve alternative G protein coupling or through G protein-independent mechanisms via interactions with ion channels or proteins that are characteristically implicated in receptor desensitization, such as β-arrestins. One of the future directions in managing dopamine-related pathol. conditions may involve a transition from the approaches that directly affect receptor function to a precise targeting of postreceptor intracellular signaling modalities either directly or through ligand-biased signaling pharmacol. In this comprehensive review, we discuss dopamine receptor classification, their basic structural and genetic organization, their distribution and functions in the brain and the periphery, and their regulation and signal transduction mechanisms. In addn., we discuss the abnormalities of dopamine receptor expression, function, and signaling that are documented in human disorders and the current pharmacol. and emerging trends in the development of novel therapeutic agents that act at dopamine receptors and/or on related signaling events.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXjslGis70%253D&md5=53e6841062c98abe60c732692109e498
    6. 6
      Parsons, M. J.; Mata, I.; Beperet, M.; Iribarren-Iriso, F.; Arroyo, B.; Sainz, R.; Arranz, M. J.; Kerwin, R. A Dopamine D2 Receptor Gene-Related Polymorphism Is Associated with Schizophrenia in a Spanish Population Isolate. Psychiatr. Genet. 2007, 17, 159– 163,  DOI: 10.1097/YPG.0b013e328017f8a4
      6
      A dopamine D2 receptor gene-related polymorphism is associated with schizophrenia in a Spanish population isolate
      Parsons Michael J; Mata Ignacio; Beperet Maria; Iribarren-Iriso Fernando; Arroyo Barbara; Sainz Ricardo; Arranz Maria J; Kerwin Robert
      Psychiatric genetics (2007), 17 (3), 159-63 ISSN:0955-8829.
      Numerous lines of evidence have highlighted the involvement of the dopamine system in the pathophysiology of schizophrenia. Association studies of dopaminergic genes such as the dopamine D2 receptor gene (DRD2), however, have produced contradictory results. To test the hypothesis that DRD2 polymorphisms are associated with schizophrenia, we investigated two DRD2-related polymorphisms (TaqI A1/A2 or rs1800497 and -141-C Ins/Del or rs1799732) in a Spanish population isolate from northern Spain consisting of 165 controls and 119 patients with schizophrenia. The TaqI A1 allele was less frequent in schizophrenic patients than in controls (P=0.002). A similar association was found for the TaqI A2/A2 genotype (P=0.0003). No association was found for the DRD2 -141-C Ins/Del polymorphism. The strong association between a potentially functional polymorphism, downstream of the DRD2 gene and schizophrenia, suggests that the direct or indirect functional effects of this polymorphism, acting on either the ANKK1 or DRD2 genes, may play a role in the pathophysiology of schizophrenia.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2s3htlGluw%253D%253D&md5=073be53eee6c5543dbc42e1fa22742a6
    7. 7
      Bertram, L. Genetic Research in Schizophrenia: New Tools and Future Perspectives. Schizophr. Bull. 2008, 34, 806– 812,  DOI: 10.1093/schbul/sbn079
      7
      Genetic research in schizophrenia: new tools and future perspectives
      Bertram Lars
      Schizophrenia bulletin (2008), 34 (5), 806-12 ISSN:0586-7614.
      Genetically, schizophrenia is a complex disease whose pathogenesis is likely governed by a number of different risk factors. While substantial efforts have been made to identify the underlying susceptibility alleles over the past 2 decades, they have been of only limited success. Each year, the field is enriched with nearly 150 additional genetic association studies, each of which either proposes or refutes the existence of certain schizophrenia genes. To facilitate the evaluation and interpretation of these findings, we have recently created a database for genetic association studies in schizophrenia ("SzGene"; available at http://www.szgene.org). In addition to systematically screening the scientific literature for eligible studies, SzGene also reports the results of allele-based meta-analyses for polymorphisms with sufficient genotype data. Currently, these meta-analyses highlight not only over 20 different potential schizophrenia genes, many of which represent the "usual suspects" (eg, various dopamine receptors and neuregulin 1), but also several that were never meta-analyzed previously. All the highlighted loci contain at least one variant showing modest (summary odds ratios approximately 1.20 [range 1.06-1.45]) but nominally significant risk effects. This review discusses some of the strengths and limitations of the SzGene database, which could become a useful bioinformatics tool within the schizophrenia research community.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1cnitFGrug%253D%253D&md5=d08d199281d7717b0dbeb68ff7e2a53f
    8. 8
      Rondou, P.; Haegeman, G.; Van Craenenbroeck, K. The Dopamine D4 Receptor: Biochemical and Signalling Properties. Cell. Mol. Life Sci. 2010, 67, 1971– 1986,  DOI: 10.1007/s00018-010-0293-y
      8
      The dopamine D4 receptor: biochemical and signalling properties
      Rondou, Pieter; Haegeman, Guy; Van Craenenbroeck, Kathleen
      Cellular and Molecular Life Sciences (2010), 67 (12), 1971-1986CODEN: CMLSFI; ISSN:1420-682X. (Birkhaeuser Verlag)
      A review. Dopamine is an important neurotransmitter that regulates several key functions in the brain, such as motor output, motivation and reward, learning and memory, and endocrine regulation. Dopamine does not mediate fast synaptic transmission, but rather modulates it by triggering slow-acting effects through the activation of dopamine receptors, which belong to the G-protein-coupled receptor superfamily. Besides activating different effectors through G-protein coupling, dopamine receptors also signal through interaction with a variety of proteins, collectively termed dopamine receptor-interacting proteins. We focus on the dopamine D4 receptor, which contains an important polymorphism in its third intracellular loop. This polymorphism has been the subject of numerous studies investigating links with several brain disorders, such as attention-deficit hyperactivity disorder and schizophrenia. We provide an overview of the structure, signaling properties and regulation of dopamine D4 receptors, and briefly discuss their physiol. and pathophysiol. role in the brain.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsFyrurY%253D&md5=ba05c503a292b3a300db61c76d394095
    9. 9
      Gómez-Restrepo, C. Guía de práctica clínica para el diagnóstico, tratamiento e inicio de la rehabilitación psicosocial de los adultos con esquizofrenia. Rev. Colomb. Psiquiatr. 2014, 44, 1– 2,  DOI: 10.1016/j.rcp.2015.05.014
      9
      Clinical Practice Guidelines for Diagnosis, Treatment and Beginning of Psychosocial Rehabilitation of Adults With Schizophrenia: "Do Well the Things That do Well"
      Gomez-Restrepo Carlos
      Revista colombiana de psiquiatria (2014), 44 Suppl 1 (), 1-2 ISSN:0034-7450.
      There is no expanded citation for this reference.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28vjvVaruw%253D%253D&md5=1a061db3900b4a39d08b1156b31fd0e8
    10. 10
      Goto, A.; Mouri, A.; Nagai, T.; Yoshimi, A.; Ukigai, M.; Tsubai, T.; Hida, H.; Ozaki, N.; Noda, Y. Involvement of the Histamine H4 Receptor in Clozapine-Induced Hematopoietic Toxicity: Vulnerability under Granulocytic Differentiation of HL-60 Cells. Toxicol. Appl. Pharmacol. 2016, 306, 8– 16,  DOI: 10.1016/j.taap.2016.06.028
      10
      Involvement of the histamine H4 receptor in clozapine-induced hematopoietic toxicity: Vulnerability under granulocytic differentiation of HL-60 cells
      Goto, Aya; Mouri, Akihiro; Nagai, Tomoko; Yoshimi, Akira; Ukigai, Mako; Tsubai, Tomomi; Hida, Hirotake; Ozaki, Norio; Noda, Yukihiro
      Toxicology and Applied Pharmacology (2016), 306 (), 8-16CODEN: TXAPA9; ISSN:0041-008X. (Elsevier Inc.)
      Clozapine is an effective antipsychotic for treatment-resistant schizophrenia, but can cause fatal hematopoietic toxicity as agranulocytosis. To elucidate the mechanism of hematopoietic toxicity induced by clozapine, we developed an in vitro assay system using HL-60 cells, and investigated the effect on hematopoiesis. HL-60 cells were differentiated by all-trans retinoic acid (ATRA) into three states according to the following hematopoietic process: undifferentiated HL-60 cells, those undergoing granulocytic ATRA-differentiation, and ATRA-differentiated granulocytic cells. Hematopoietic toxicity was evaluated by analyzing cell survival, cell proliferation, granulocytic differentiation, apoptosis, and necrosis. In undifferentiated HL-60 cells and ATRA-differentiated granulocytic cells, both clozapine (50 and 100 μM) and doxorubicin (0.2 μM) decreased the cell survival rate, but olanzapine (1-100 μM) did not. Under granulocytic differentiation for 5 days, clozapine, even at a concn. of 25 μM, decreased survival without affecting granulocytic differentiation, increased caspase activity, and caused apoptosis rather than necrosis. Histamine H4 receptor mRNA was expressed in HL-60 cells, whereas the expression decreased under granulocytic ATRA-differentiation little by little. Both thioperamide, a histamine H4 receptor antagonist, and DEVD-FMK, a caspase-3 inhibitor, exerted protection against clozapine-induced survival rate redn., but not of live cell counts. 4-Methylhistamine, a histamine H4 receptor agonist, decreased the survival rate and live cell counts, as did clozapine. HL-60 cells under granulocytic differentiation are vulnerable under in vitro assay conditions to hematopoietic toxicity induced by clozapine. Histamine H4 receptor is involved in the development of clozapine-induced hematopoietic toxicity through apoptosis, and may be a potential target for preventing its occurrence through granulocytic differentiation.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhtFams73P&md5=8e85539beabf52a04646e356d6ac1917
    11. 11
      Seeman, P.; Weinshenker, D.; Quirion, R.; Srivastava, L. K.; Bhardwaj, S. K.; Grandy, D. K.; Premont, R. T.; Sotnikova, T. D.; Boksa, P.; El-Ghundi, M. Dopamine Supersensitivity Correlates with D2High States, Implying Many Paths to Psychosis. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 3513– 3518,  DOI: 10.1073/pnas.0409766102
      11
      Dopamine supersensitivity correlates with D2High states, implying many paths to psychosis
      Seeman, Philip; Weinshenker, David; Quirion, Remi; Srivastava, Lalit K.; Bhardwaj, Sanjeev K.; Grandy, David K.; Premont, Richard T.; Sotnikova, Tatyana D.; Boksa, Patricia; El-Ghundi, Mufida; O'Dowd, Brian F.; George, Susan R.; Perreault, Melissa L.; Maennistoe, Pekka T.; Robinson, Siobhan; Palmiter, Richard D.; Tallerico, Teresa
      Proceedings of the National Academy of Sciences of the United States of America (2005), 102 (9), 3513-3518CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Dopamine supersensitivity occurs in schizophrenia and other psychoses, and after hippocampal lesions, antipsychotics, ethanol, amphetamine, phencyclidine, gene knockouts of Dbh (dopamine β-hydroxylase), Drd4 receptors, Gprk6 (G protein-coupled receptor kinase 6), Comt (catechol-O-methyltransferase), or Th-/-, DbhTh/+ (tyrosine hydroxylase), and in rats born by Cesarean-section. The functional state of D2, or the high-affinity state for dopamine (D2High), was measured in these supersensitive animal brain striata. Increased levels and higher proportions (40-900%) for D2High were found in all these tissues. If many types of brain impairment cause dopamine behavioral supersensitivity and a common increase in D2High states, it suggests that there are many pathways to psychosis, any one of which can be disrupted.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXitl2ksrk%253D&md5=3682a5e9a39d2eeda2ac383dc3c8e6da
    12. 12
      Seeman, P.; Ko, F.; Jack, E.; Greenstein, R.; Dean, B. Consistent with Dopamine Supersensitivity, RGS9 Expression Is Diminished in the Amphetamine-Treated Animal Model of Schizophrenia and in Postmortem Schizophrenia Brain. Synapse 2007, 61, 303– 309,  DOI: 10.1002/syn.20368
      12
      Consistent with dopamine supersensitivity, RGS9 expression is diminished in the amphetamine-treated animal model of schizophrenia and in postmortem schizophrenia brain
      Seeman, Philip; Ko, Francoise; Jack, Elaine; Greenstein, Rachel; Dean, Brian
      Synapse (Hoboken, NJ, United States) (2007), 61 (5), 303-309CODEN: SYNAET; ISSN:0887-4476. (Wiley-Liss, Inc.)
      It is known that RGS9-2 gene knockout mice show supersensitivity to DA and have a marked elevation in the proportion of DA D2 receptors in the high-affinity state for DA (D2High receptors). As this is a similar profile to that obsd. in the CNS from subjects with schizophrenia, we examd. whether postmortem CNS tissue from subjects with the disorder and brain striata from an animal model of psychosis or schizophrenia (the amphetamine-sensitized rat) had altered levels of RGS9-2. The mRNA for RGS9-2 in 29 control hippocampi was 0.185±0.015 fg per fg of β-glucuronidase mRNA (av. ± SE), while that in 29 schizophrenia hippocampi was 0.145±0.015 fg per fg of β-glucuronidase mRNA (av. ± SE), a redn. of 22%. Of the many receptor-regulating genes related to G proteins, and of 11 RGS genes, RGS9-2 was the most reduced in the amphetamine-sensitized rat striatum. The reduced levels of RGS9-2 expression in both an animal model of schizophrenia and a postmortem schizophrenia brain provide further evidence implicating RGS9-2 as a candidate gene in schizophrenia.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXjtlWjtbY%253D&md5=9354ccb04cb95001edbe634136ee2306
    13. 13
      Gaspar, H. A.; Breen, G. Drug Enrichment and Discovery from Schizophrenia Genome-Wide Association Results: An Analysis and Visualisation Approach. Sci. Rep. 2017, 7, 12460,  DOI: 10.1038/s41598-017-12325-3
      13
      Drug enrichment and discovery from schizophrenia genome-wide association results: an analysis and visualisation approach
      Gaspar H A; Breen G; Gaspar H A; Breen G
      Scientific reports (2017), 7 (1), 12460 ISSN:.
      Using successful genome-wide association results in psychiatry for drug repurposing is an ongoing challenge. Databases collecting drug targets and gene annotations are growing and can be harnessed to shed a new light on psychiatric disorders. We used genome-wide association study (GWAS) summary statistics from the Psychiatric Genetics Consortium (PGC) Schizophrenia working group to build a drug repositioning model for schizophrenia. As sample size increases, schizophrenia GWAS results show increasing enrichment for known antipsychotic drugs, selective calcium channel blockers, and antiepileptics. Each of these therapeutical classes targets different gene subnetworks. We identify 123 Bonferroni-significant druggable genes outside the MHC, and 128 FDR-significant biological pathways related to neurons, synapses, genic intolerance, membrane transport, epilepsy, and mental disorders. These results suggest that, in schizophrenia, current well-powered GWAS results can reliably detect known schizophrenia drugs and thus may hold considerable potential for the identification of new therapeutic leads. Moreover, antiepileptics and calcium channel blockers may provide repurposing opportunities. This study also reveals significant pathways in schizophrenia that were not identified previously, and provides a workflow for pathway analysis and drug repurposing using GWAS results.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1M%252FjvVKgtg%253D%253D&md5=b85b2cb96083a4683defa07536a9aab1
    14. 14
      Zhao, K.; So, H.-C. Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data. IEEE J. Biomed. Health Inf. 2019, 23, 1304– 1315,  DOI: 10.1109/JBHI.2018.2856535
      14
      Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data
      Zhao Kai; So Hon-Cheong
      IEEE journal of biomedical and health informatics (2019), 23 (3), 1304-1315 ISSN:.
      Development of new medications is a lengthy and costly process, and drug repositioning might help to shorten the development cycle. We present a machine learning (ML) workflow to drug discovery or repositioning by predicting indication for a particular disease based on drug expression profiles, with a focus on applications in psychiatry. Drugs that are not originally indicated for the disease but with high predicted probabilities serve as candidates for repurposing. This approach is widely applicable to any chemicals or drugs with expression profiles measured, even if drug targets are unknown. It is also highly flexible as virtually any supervised learning algorithms can be used. We employed the ML approach to identify repositioning opportunities for schizophrenia as well as depression and anxiety disorders. We applied various state-of-the-art ML approaches, including deep neural networks (DNNs), support vector machines (SVMs), elastic net regression, random forest, and gradient boosted trees. The predictive performance of the five approaches in cross validation did not differ substantially, with SVM slightly outperforming the others. However, other methods also reveal literature-supported repositioning candidates of different mechanisms of actions. As a further validation, we showed that the repositioning hits are enriched for psychiatric medications considered in clinical trials. We also examined the correlation between predicted probabilities of treatment potential and the number of related research articles, and found significant correlations for all methods, especially DNN. Finally, we propose that ML may provide a new avenue to exploring drug mechanisms via examining the variable importance of gene features.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3c%252FosVCgtw%253D%253D&md5=d19b972d8f957c5677a15af11c4d8e44
    15. 15
      Karunakaran, K. B.; Chaparala, S.; Ganapathiraju, M. K. Potentially Repurposable Drugs for Schizophrenia Identified from Its Interactome. Sci. Rep. 2019, 9, 12682,  DOI: 10.1038/s41598-019-48307-w
      15
      Potentially repurposable drugs for schizophrenia identified from its interactome
      Karunakaran Kalyani B; Chaparala Srilakshmi; Ganapathiraju Madhavi K; Ganapathiraju Madhavi K
      Scientific reports (2019), 9 (1), 12682 ISSN:.
      We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3MrkvVCnsg%253D%253D&md5=5a63e8a658a7dd64983aa7047a8d005b
    16. 16
      Lee, J. H.; Cho, S. J.; Kim, M.-H. Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening. Molecules 2018, 23, 2452,  DOI: 10.3390/molecules23102452
      There is no corresponding record for this reference.
    17. 17
      Lemos, A.; Melo, R.; Preto, A. J.; Almeida, J. G.; Moreira, I. S.; Dias Soeiro Cordeiro, M. N. In Silico Studies Targeting G-Protein Coupled Receptors for Drug Research Against Parkinson’s Disease. Curr. Neuropharmacol. 2018, 16, 786– 848,  DOI: 10.2174/1570159X16666180308161642
      17
      In Silico Studies Targeting G-protein Coupled Receptors for Drug Research Against Parkinson's Disease
      Lemos, Agostinho; Melo, Rita; Preto, Antonio Jose; Almeida, Jose Guilherme; Moreira, Irina Sousa; Dias Soeiro Cordeiro, Maria Natalia
      Current Neuropharmacology (2018), 16 (6), 786-848CODEN: CNUEAN; ISSN:1875-6190. (Bentham Science Publishers Ltd.)
      A review. Parkinson's Disease (PD) is a long-term neurodegenerative brain disorder that mainly affects the motor system. The causes are still unknown, and even though currently there is no cure, several therapeutic options are available to manage its symptoms. The development of novel antiparkinsonian agents and an understanding of their proper and optimal use are, indeed, highly demanding. For the last decades, L-3,4-DihydrOxyPhenylAlanine or levodopa (L-DOPA) has been the gold-std. therapy for the symptomatic treatment of motor dysfunctions assocd. to PD. However, the development of dyskinesias and motor fluctuations (wearing-off and on-off phenomena) assocd. with long-term L-DOPA replacement therapy have limited its antiparkinsonian efficacy. The investigation for non-dopaminergic therapies has been largely explored as an attempt to counteract the motor side effects assocd. with dopamine replacement therapy. Being one of the largest cell membrane protein families, G-Protein-Coupled Receptors (GPCRs) have become a relevant target for drug discovery focused on a wide range of therapeutic areas, including Central Nervous System (CNS) diseases. The modulation of specific GPCRs potentially implicated in PD, excluding dopamine receptors, may provide promising non-dopaminergic therapeutic alternatives for symptomatic treatment of PD. In this review, we focused on the impact of specific GPCR subclasses, including dopamine receptors, adenosine receptors, muscarinic acetylcholine receptors, metabotropic glutamate receptors, and 5-hydroxytryptamine receptors, on the pathophysiol. of PD and the importance of structure- and ligand-based in silico approaches for the development of small mols. to target these receptors.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFCjsb7M&md5=0408f396ca24d349682e712b3c68bb6a
    18. 18
      Ishiki, H. M.; Filho, J. M. B.; da Silva, M. S.; Scotti, M. T.; Scotti, L. Computer-Aided Drug Design Applied to Parkinson Targets. Curr. Neuropharmacol. 2018, 16, 865– 880,  DOI: 10.2174/1570159X15666171128145423
      18
      Computer-aided Drug Design Applied to Parkinson Targets
      Ishiki, Hamilton M.; Barbosa Filho, Jose Maria; da Silva, Marcelo S.; Scotti, Marcus T.; Scotti, Luciana
      Current Neuropharmacology (2018), 16 (6), 865-880CODEN: CNUEAN; ISSN:1875-6190. (Bentham Science Publishers Ltd.)
      Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by debilitating motor deficits, as well as autonomic problems, cognitive declines, changes in affect and sleep disturbances. Although the scientific community has performed great efforts in the study of PD, and from the most diverse points of view, the disease remains incurable. The exact mechanism underlying its progression is unclear, but oxidative stress, mitochondrial dysfunction and inflammation are thought to play major roles in the etiol. Objective: Current pharmacol. therapies for the treatment of Parkinson's disease are mostly inadequate, and new therapeutic agents are much needed. Methods: In this review, recent advances in computer-aided drug design for the rational design of new compds. against Parkinson disease; using methods such as Quant. Structure-Activity Relationships (QSAR), mol. docking, mol. dynamics and pharmacophore modeling are discussed. Results: In this review, four targets were selected: the enzyme monoamine oxidase, dopamine agonists, acetylcholine receptors, and adenosine receptors. Conclusion: Computer aided-drug design enables the creation of theor. models that can be used in a large database to virtually screen for and identify novel candidate mols.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtFCjsb%252FE&md5=b6a5f7cd809bcadca64069bb831385e9
    19. 19
      Zhao, Y.; Lu, X.; Yang, C.-Y.; Huang, Z.; Fu, W.; Hou, T.; Zhang, J. Computational Modeling toward Understanding Agonist Binding on Dopamine 3. J. Chem. Inf. Model. 2010, 50, 1633– 1643,  DOI: 10.1021/ci1002119
      19
      Computational Modeling Toward Understanding Agonist Binding on Dopamine 3
      Zhao, Yaxue; Lu, Xuefeng; Yang, Chao-yie; Huang, Zhimin; Fu, Wei; Hou, Tingjun; Zhang, Jian
      Journal of Chemical Information and Modeling (2010), 50 (9), 1633-1643CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      The dopamine 3 (D3) receptor is a promising therapeutic target for the treatment of nervous system disorders, such as Parkinson's disease, and current research interests primarily focus on the discovery/design of potent D3 agonists. Herein, a well-designed computational protocol, which combines pharmacophore identification, homol. modeling, mol. docking, and mol. dynamics (MD) simulations, was employed to understand the agonist binding on D3 aiming to provide insights into the development of novel potent D3 agonists. We (1) identified the chem. features required in effective D3 agonists by pharmacophore modeling based upon 18 known diverse D3 agonists; (2) constructed the three-dimensional (3D) structure of D3 based on homol. modeling and the pharmacophore hypothesis; (3) identified the binding modes of the agonists to D3 by the correlation between the predicted binding free energies and the exptl. values; and (4) investigated the induced fit of D3 upon agonist binding through MD simulations. The pharmacophore models of the D3 agonists and the 3D structure of D3 can be used for either ligand- or receptor-based drug design. Furthermore, the MD simulations further give the insight that the long and flexible EL2 acts as a "door" for agonist binding, and the "ionic lock" at the bottom of TM3 and TM6 is essential to transduce the activation signal.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXpvVyltb0%253D&md5=081203310cb1e39f2710c70d50903c4d
    20. 20
      Kaserer, T.; Beck, K. R.; Akram, M.; Odermatt, A.; Schuster, D. Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases. Molecules 2015, 20, 22799– 22832,  DOI: 10.3390/molecules201219880
      20
      Pharmacophore models and pharmacophore-based virtual screening: concepts and applications exemplified on hydroxysteroid dehydrogenases
      Kaserer, Teresa; Beck, Katharina R.; Akram, Muhammad; Odermatt, Alex; Schuster, Daniela
      Molecules (2015), 20 (12), 22799-22832CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
      Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship anal. and selectivity profiling. In addn., compd.-target interactions assocd. with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are assocd. with specific pathol. conditions, and pharmacol. modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biol. functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XmtlKmtA%253D%253D&md5=b6492b9deafadc8dba3ad24eb54f2eb5
    21. 21
      Ferraro, M.; Decherchi, S.; De Simone, A.; Recanatini, M.; Cavalli, A.; Bottegoni, G. Multi-Target Dopamine D3 Receptor Modulators: Actionable Knowledge for Drug Design from Molecular Dynamics and Machine Learning. Eur. J. Med. Chem. 2020, 188, 111975,  DOI: 10.1016/j.ejmech.2019.111975
      21
      Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning
      Ferraro, Mariarosaria; Decherchi, Sergio; De Simone, Alessio; Recanatini, Maurizio; Cavalli, Andrea; Bottegoni, Giovanni
      European Journal of Medicinal Chemistry (2020), 188 (), 111975CODEN: EJMCA5; ISSN:0223-5234. (Elsevier Masson SAS)
      Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacol. profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, mol. dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we obsd. how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFCjtLk%253D&md5=706046edea065032891083a4afe8ccd0
    22. 22
      Bhargava, K.; Nath, R.; Seth, P. K.; Pant, K. K.; Dixit, R. K. Molecular Docking Studies of D2 Dopamine Receptor with Risperidone Derivatives. Bioinformation 2014, 10, 8– 12,  DOI: 10.6026/97320630010008
      22
      Molecular Docking studies of D2 Dopamine receptor with Risperidone derivatives
      Bhargava Kiran; Nath Rajendra; Pant Kamlesh Kumar; Dixit Rakesh Kumar; Seth Prahlad Kumar
      Bioinformation (2014), 10 (1), 8-12 ISSN:0973-2063.
      In this work, 3D model of D2 dopamine receptor was determined by comparative homology modeling program MODELLER. The computed model's energy was minimized and validated using PROCHECK and Errat tool to obtain a stable model structure and was submitted in Protein Model Database (PMDB-ID: PM0079251). Stable model was used for molecular docking against Risperidone and their 15 derivatives using AutoDock 4.2, which resulted in energy-based descriptors such as Binding Energy, Ligand Efficiency, Inhib Constant, Intermol energy, vdW + Hbond + desolv Energy, Electrostatic Energy, Total Internal Energy and Torsional Energy. After that, we have built quantitative structure activity relationship (QSAR) model, which was trained and tested on Risperidone and their 15 derivatives having activity value pKi in μM. For QSAR modeling, Multiple Linear Regression model was engendered using energy-based descriptors yielding correlation coefficient r2 of 0.513. To assess the predictive performance of QSAR models, different cross-validation procedures were adopted. Our results suggests that ligand-receptor binding interactions for D2 employing QSAR modeling seems to be a promising approach for prediction of pKi value of novel antagonists against D2 receptor.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cvkt1yhsg%253D%253D&md5=b6cd065fbd6fd72f510bbe90265c4c07
    23. 23
      Bueschbell, B.; Barreto, C. A. V.; Preto, A. J.; Schiedel, A. C.; Moreira, I. S. A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods. Molecules 2019, 24, 1196,  DOI: 10.3390/molecules24071196
      23
      A complete assessment of dopamine receptor- ligand interactions through computational methods
      Bueschbell, Beatriz; Barreto, Carlos A. V.; Preto, Antonio J.; Schiedel, Anke C.; Moreira, Irina S.
      Molecules (2019), 24 (7), 1196/1-1196/26CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
      Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a mol. basis has not been fully elucidated. Homol. modeling and mol. dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D1-like and D2-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Residues of the arom. microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D1R-like selective ligands binding. This in silico approach was successful in showing known receptor-ligand interactions as well as in detg. unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXpt1Kqurk%253D&md5=ca3ad005e1b89b15daba57c3065a13b3
    24. 24
      Trott, O.; Olson, A. J. AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. J. Comput. Chem. 2010, 31, 455– 461,  DOI: 10.1002/jcc.21334
      24
      AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
      Trott, Oleg; Olson, Arthur J.
      Journal of Computational Chemistry (2010), 31 (2), 455-461CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      AutoDock Vina, a new program for mol. docking and virtual screening, is presented. AutoDock Vina achieves an approx. 2 orders of magnitude speed-up compared with the mol. docking software previously developed in the authors' lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by the authors' tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calcs. the grid maps and clusters the results in a way transparent to the user.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFGnur3O&md5=c6974af8a1235f7aa09918d3e6f70dc4
    25. 25
      Krautscheid, Y.; Senning, C. J. Å.; Sartori, S. B.; Singewald, N.; Schuster, D.; Stuppner, H. Pharmacophore Modeling, Virtual Screening, and in Vitro Testing Reveal Haloperidol, Eprazinone, and Fenbutrazate as Neurokinin Receptors Ligands. J. Chem. Inf. Model. 2014, 54, 1747– 1757,  DOI: 10.1021/ci500106z
      25
      Pharmacophore Modeling, Virtual Screening, and in Vitro Testing Reveal Haloperidol, Eprazinone, and Fenbutrazate as Neurokinin Receptors Ligands
      Krautscheid, Yvonne; Senning, Carl Johann Ake; Sartori, Simone B.; Singewald, Nicolas; Schuster, Daniela; Stuppner, Hermann
      Journal of Chemical Information and Modeling (2014), 54 (6), 1747-1757CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Neurokinin receptors (NKRs) have been shown to be involved in many physiol. processes, rendering them promising novel drug targets, but also making them the possible cause for side effects of several drugs. Aiming to answer the question whether the binding to NKRs could have a share in the side effects or even the desired effects of already licensed drugs, we generated a set of ligand-based common feature pharmacophore models based on the structural information about subtype-selective and nonselective NKR antagonists and screened an inhouse database mainly composed of licensed drugs. The prospective pharmacol. investigations of the virtual hits haloperidol, eprazinone, and fenbutrazate confirmed them to be NKR ligands in vitro. By the identification of licensed drugs as so far unknown NKR ligands, this study contributes to establishing an activity profile of the investigated compds. and confirms the presented pharmacophore models as useful tools for this purpose.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXotlWiurc%253D&md5=b0524d52e6b4519f3c0b31c9407ebe19
    26. 26
      Patel, C. N.; Georrge, J. J.; Modi, K. M.; Narechania, M. B.; Patel, D. P.; Gonzalez, F. J.; Pandya, H. A. Pharmacophore-Based Virtual Screening of Catechol-o-Methyltransferase (COMT) Inhibitors to Combat Alzheimer’s Disease. J. Biomol. Struct. Dyn. 2018, 36, 3938– 3957,  DOI: 10.1080/07391102.2017.1404931
      26
      Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease
      Patel, Chirag N.; Georrge, John J.; Modi, Krunal M.; Narechania, Moksha B.; Patel, Daxesh P.; Gonzalez, Frank J.; Pandya, Himanshu A.
      Journal of Biomolecular Structure and Dynamics (2018), 36 (15), 3938-3957CODEN: JBSDD6; ISSN:0739-1102. (Taylor & Francis Ltd.)
      Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metab., excretion, and toxicity) filtering by using FAF-Drug-3 and 36 mols. were considered for mol. docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the mol. dynamics simulation anal. having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of mol.-level interactions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlejug%253D%253D&md5=1ed8fea8f07705061d975843721636ed
    27. 27
      Floresta, G.; Crocetti, L.; Giovannoni, M. P.; Biagini, P.; Cilibrizzi, A. Repurposing Strategies on Pyridazinone-Based Series by Pharmacophore- and Structure-Driven Screening. J. Enzyme Inhib. Med. Chem. 2020, 35, 1137– 1144,  DOI: 10.1080/14756366.2020.1760261
      27
      Repurposing strategies on pyridazinone-based series by pharmacophore- and structure-driven screening
      Floresta, Giuseppe; Crocetti, Letizia; Giovannoni, Maria Paola; Biagini, Pierfrancesco; Cilibrizzi, Agostino
      Journal of Enzyme Inhibition and Medicinal Chemistry (2020), 35 (1), 1137-1144CODEN: JEIMAZ; ISSN:1475-6366. (Taylor & Francis Ltd.)
      We report here in silico repurposing studies on 52 new pyridazinone-based small-mols. through inverse virtual screening (iVS) methodologies. These analogs were originally designed as formyl peptide receptor (FPR) ligands. As it is sometimes the case in drug discovery programs, subsequent biol. screening demonstrated the inefficacy of the mols. in binding FPRs, failing in the identification of new hits. Through a focussed drug-repurposing approach we have defined a variety of potential targets that are suitable to interact with this library of pyridazinone-based analogs. A two-step approach has been conducted for computational anal. Specifically, the mols. were initially processed through a pharmacophore-based screening. Secondly, the resulting features of binding were investigated by docking studies and following mol. dynamic simulations, in order to univocally confirm "pyridazinone-based ligand-target protein" interactions. Our findings propose aspartate aminotransferase as the most favorable repurposed target for this small-mol. series, worth of addnl. medicinal chem. investigations in the field.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtVShu7zE&md5=504be4c1ccc2329b87cc7fc7fe53d186
    28. 28
      Kagami, L. P.; das Neves, G. M.; Rodrigues, R. P.; da Silva, V. B.; Eifler-Lima, V. L.; Kawano, D. F. Identification of a Novel Putative Inhibitor of the Plasmodium Falciparum Purine Nucleoside Phosphorylase: Exploring the Purine Salvage Pathway to Design New Antimalarial Drugs. Mol. Diversity 2017, 21, 677– 695,  DOI: 10.1007/s11030-017-9745-8
      28
      Identification of a novel putative inhibitor of the Plasmodium falciparum purine nucleoside phosphorylase: exploring the purine salvage pathway to design new antimalarial drugs
      Kagami, Luciano Porto; Machado das Neves, Gustavo; Rodrigues, Ricardo Pereira; Barreto da Silva, Vinicius; Eifler-Lima, Vera Lucia; Kawano, Daniel Fabio
      Molecular Diversity (2017), 21 (3), 677-695CODEN: MODIF4; ISSN:1381-1991. (Springer)
      Malaria, a tropical parasitic disease caused by Plasmodium spp., continues to place a heavy social burden, with almost 200 million cases and more than 580,000 deaths per yr. Plasmodium falciparum purine nucleoside phosphorylase (PfPNP) can be targeted for antimalarial drug design since its inhibition kills malaria parasites both in vitro and in vivo. Although the currently known inhibitors of PfPNP, immucillins, are orally available and of low toxicity to animals and humans, to the best of our knowledge, none of these compds. has entered clin. trials for the treatment of malaria. Using a pharmacophore-based virtual screening coupled to a consensual mol. docking approach, we identified 59 potential PfPNP inhibitors that are predicted to be orally absorbed in a Caco-2 cell model. Although most of these compds. are predicted to have high plasma protein binding levels, poor water soly. (except for compd. 25) and CYP3A4 metabolic stability (except for 4, 7 and 8), four structures (4, 7, 8 and 25) remain as potential leads because of their plausible interaction with a specific hydrophobic pocket of PfPNP, which would confer them higher selectivity for PfPNP over human PNP. Addnl., both predicted Gibbs free energies for binding and mol. dynamics suggest that compd. 4 may form a more stable complex with PfPNP than 5'-methylthio-immucillin-H, a potent and selective inhibitor of PfPNP.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXotVamur4%253D&md5=d6038621eb8d7b782460cac8ac1acb7c
    29. 29
      Kumar, S.; Chowdhury, S.; Kumar, S. In Silico Repurposing of Antipsychotic Drugs for Alzheimer’s Disease. BMC Neurosci. 2017, 18, 76,  DOI: 10.1186/s12868-017-0394-8
      29
      In silico repurposing of antipsychotic drugs for Alzheimer's disease
      Kumar, Shivani; Chowdhury, Suman; Kumar, Suresh
      BMC Neuroscience (2017), 18 (), 76/1-76/16CODEN: BNMEA6; ISSN:1471-2202. (BioMed Central Ltd.)
      Background: Alzheimer's disease (AD) is the most prevalent form of dementia and represents one of the highest unmet requirements in medicine today. There is shortage of novel mols. entering into market because of poor pharmacokinetic properties and safety issues. Drug repurposing offers an opportunity to reinvigorate the slowing drug discovery process by finding new uses for existing drugs. The major advantage of the drug repurposing approach is that the safety issues are already investigated in the clin. trials and the drugs are com. available in the marketplace. As this approach provides an effective soln. to hasten the process of providing new alternative drugs for AD, the current study shows the mol. interaction of already known antipsychotic drugs with the different protein targets implicated in AD using in silico studies. Result: A computational method based on ligand-protein interaction was adopted in present study to explore potential antipsychotic drugs for the treatment of AD. The screening of approx. 150 antipsychotic drugs was performed on five major protein targets (AChE, BuChE, BACE 1, MAO and NMDA) by mol. docking. In this study, for each protein target, the best drug was identified on the basis of dock score and glide energy. The top hits were then compared with the already known inhibitor of the resp. proteins. Some of the drugs showed relatively better docking score and binding energies as compared to the already known inhibitors of the resp. targets. Mol. descriptors like mol. wt., no. of hydrogen bond donors, acceptors, predicted octanol/water partition coeff. and percentage human oral absorption were also analyzed to det. the in silico ADME properties of these drugs and all were found in the acceptable range and follows Lipinski's rule. Conclusion: The present study have led to unravel the potential of leading antipsychotic drugs such as pimozide, bromperidol, melperone, anisoperidone, benperidol and anisopirol against multiple targets assocd. with AD. Benperidol was found to be the best candidate drug interacting with different target proteins involved in AD.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXlslGhsL0%253D&md5=977bad8bddde53997fd38addcf8c7207
    30. 30
      Dilly, S.; Fotso Fotso, A.; Lejal, N.; Zedda, G.; Chebbo, M.; Rahman, F.; Companys, S.; Bertrand, H. C.; Vidic, J.; Noiray, M. From Naproxen Repurposing to Naproxen Analogues and Their Antiviral Activity against Influenza A Virus. J. Med. Chem. 2018, 61, 7202– 7217,  DOI: 10.1021/acs.jmedchem.8b00557
      30
      From Naproxen Repurposing to Naproxen Analogues and Their Antiviral Activity against Influenza A Virus
      Dilly, Sebastien; Fotso Fotso, Aurelien; Lejal, Nathalie; Zedda, Gloria; Chebbo, Mohamad; Rahman, Fryad; Companys, Simon; Bertrand, Helene C.; Vidic, Jasmina; Noiray, Magali; Alessi, Marie-Christine; Tarus, Bogdan; Quideau, Stephane; Riteau, Beatrice; Slama-Schwok, Anny
      Journal of Medicinal Chemistry (2018), 61 (16), 7202-7217CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      The nucleoprotein (NP) of influenza A virus (IAV) required for IAV replication is a promising target for new antivirals. The authors previously identified by in silico screening naproxen being a dual inhibitor of NP and cyclooxygenase COX2, thus combining antiviral and anti-inflammatory effects. However, the recently shown strong COX2 antiviral potential makes COX2 inhibition undesirable. Here the authors designed and synthesized two new series of naproxen analogs called derivs. 2, 3 (5-(4-aminophenoxy)-2-(6-methoxynaphthalen-2-yl)isophthalic acid), and 4 (4-(4-aminophenoxy)-2-(6-methoxynaphthalen-2-yl)isophthalic acid) targeting highly conserved residues of the RNA binding groove, stabilizing NP monomer without inhibiting COX2. Deriv. 2 presented improved antiviral effects in infected cells compared to that of naproxen and afforded a total protection of mice against a lethal viral challenge. Deriv. 4 also protected infected cells challenged with circulating 2009-pandemic and oseltamivir-resistant H1N1 virus. This improved antiviral effect likely results from derivs. 2 and 4 inhibiting NP-RNA and NP-polymerase acidic subunit PA N-terminal interactions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhtlGit7jI&md5=a3d21246bea09e82edd808d1e14a54ee
    31. 31
      Teli, M. K.; Rajanikant, G. K. Computational Repositioning and Experimental Validation of Approved Drugs for HIF-Prolyl Hydroxylase Inhibition. J. Chem. Inf. Model. 2013, 53, 1818– 1824,  DOI: 10.1021/ci400254a
      31
      Computational Repositioning and Experimental Validation of Approved Drugs for HIF-Prolyl Hydroxylase Inhibition
      Teli, Mahesh Kumar; G. K., Rajanikant
      Journal of Chemical Information and Modeling (2013), 53 (7), 1818-1824CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      HIF stability and activation are governed by a family of dioxygenases called HIF prolyl-4-hydroxylases (PHDs). It has been identified as a new target to augment the adaptive machinery that governs cytoprotection in disorders assocd. with ischemia/reperfusion, inflammation, and oxidative stress. In this sense, PHD inhibition has been proposed to mimic, at least in part, the protective effects of exposure to hypoxia. Exploiting drug polypharmacol. to identify novel modes of actions for drug repurposing has gained significant attention in the current era of weak drug pipelines. The present work plan aims at giving new purpose to some well-established FDA-approved drugs. Here, we propose that by combining the literature survey, docking, and manual interpretation altogether, we were able to perform virtual screening on FDA-approved drugs to identify potential PHD inhibitors. Upon screening of 1537 marketed drugs, a final set of six hits were selected for exptl. testing. All six drugs were divers, and immuno blotting was carried out to evaluate their ability to upregulate HIF in order to validate our hypothesis. Out of the six, three drugs showed significant upregulation of HIF possibly by inhibiting the PHD. It is believed that the appropriate use of the literature survey, docking, manual interpretation, and exptl. validation strategy in the drug design process should improve the ability to identify hits and confirm their potential to serve as basis for drug repurposing.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXpvV2jt78%253D&md5=d5630c21fed2cb29d10050418fb8bcd7
    32. 32
      Macalino, S. J. Y.; Gosu, V.; Hong, S. Role of computer-aided drug design in modern drug discovery. Arch. Pharmacal Res. 2015, 38, 1686– 1701,  DOI: 10.1007/s12272-015-0640-5
      32
      Role of computer-aided drug design in modern drug discovery
      Macalino, Stephani Joy Y.; Gosu, Vijayakumar; Hong, Sunhye; Choi, Sun
      Archives of Pharmacal Research (2015), 38 (9), 1686-1701CODEN: APHRDQ; ISSN:0253-6269. (Pharmaceutical Society of Korea)
      A review. Drug discovery utilizes chem. biol. and computational drug design approaches for the efficient identification and optimization of lead compds. Chem. biol. is mostly involved in the elucidation of the biol. function of a target and the mechanism of action of a chem. modulator. Computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the detn. of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are crit. for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with exptl. routines, has a powerful impact on rational drug design. In this article, the authors give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXht1aktbzN&md5=9eeb85337b2d2d8261f062f726e8c46e
    33. 33
      Liu, X.; Shi, D.; Zhou, S.; Liu, H.; Liu, H.; Yao, X. Molecular Dynamics Simulations and Novel Drug Discovery. Expert Opin. Drug Discovery 2018, 13, 23– 37,  DOI: 10.1080/17460441.2018.1403419
      33
      Molecular dynamics simulations and novel drug discovery
      Liu, Xuewei; Shi, Danfeng; Zhou, Shuangyan; Liu, Hongli; Liu, Huanxiang; Yao, Xiaojun
      Expert Opinion on Drug Discovery (2018), 13 (1), 23-37CODEN: EODDBX; ISSN:1746-0441. (Taylor & Francis Ltd.)
      A review. Mol. dynamics (MD) simulations can provide not only plentiful dynamical structural information on biomacromols. but also a wealth of energetic information about protein and ligand interactions. Such information is very important to understanding the structure-function relationship of the target and the essence of protein-ligand interactions and to guiding the drug discovery and design process. Thus, MD simulations have been applied widely and successfully in each step of modern drug discovery.: In this review, the authors review the applications of MD simulations in novel drug discovery, including the pathogenic mechanisms of amyloidosis diseases, virtual screening and the interaction mechanisms between drugs and targets.: MD simulations have been used widely in investigating the pathogenic mechanisms of diseases caused by protein misfolding, in virtual screening, and in investigating drug resistance mechanisms caused by mutations of the target. These issues are very difficult to solve by exptl. methods alone. Thus, in the future, MD simulations will have wider application with the further improvement of computational capacity and the development of better sampling methods and more accurate force fields together with more efficient anal. methods.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhvVWmsb7J&md5=aad5a7f23a15e725d70a032399052191
    34. 34
      Do, P.-C.; Lee, E. H.; Le, L. Steered Molecular Dynamics Simulation in Rational Drug Design. J. Chem. Inf. Model. 2018, 58, 1473– 1482,  DOI: 10.1021/acs.jcim.8b00261
      34
      Steered Molecular Dynamics Simulation in Rational Drug Design
      Do, Phuc-Chau; Lee, Eric H.; Le, Ly
      Journal of Chemical Information and Modeling (2018), 58 (8), 1473-1482CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Conventional de novo drug design is time consuming, laborious, and resource intensive. In recent years, emerging in silico approaches have been proven to be crit. to accelerate the process of bringing drugs to market. Mol. dynamics (MD) simulations of single mol. and mol. complexes have been commonly applied to achieve accurate binding modes and binding energies of drug-receptor interactions. A deriv. of MD, namely, steered mol. dynamics (SMD), has been demonstrated as a promising tool for rational drug design. In this paper, we review various studies over the last 20 years using SMD simulations, thus paving the way to det. the relationship between protein structure and function. In addn., the paper highlights the use of SMD simulation for in silico drug design. We also aim to establish an understanding on the key interactions which play a crucial role in the stabilization of peptide-ligand interfaces, the binding and unbinding mechanism of the ligand-protein complex, the mechanism of ligand translocating via membrane, and the ranking of different ligands on receptors as therapeutic candidates.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXht1Klsr7O&md5=725ab4ae35861ece35c8ed56c12904b2
    35. 35
      Hodos, R. A.; Kidd, B. A.; Shameer, K.; Readhead, B. P.; Dudley, J. T. In Silico Methods for Drug Repurposing and Pharmacology. Wiley Interdiscip. Rev.: Syst. Biol. Med. 2016, 8, 186– 210,  DOI: 10.1002/wsbm.1337
      35
      In silico methods for drug repurposing and pharmacology
      Hodos Rachel A; Kidd Brian A; Shameer Khader; Readhead Ben P; Dudley Joel T; Hodos Rachel A
      Wiley interdisciplinary reviews. Systems biology and medicine (2016), 8 (3), 186-210 ISSN:.
      Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform these often complex and heterogeneous data into testable hypotheses and actionable insights. This is the aim of computational pharmacology, which uses in silico techniques to better understand and predict how drugs affect biological systems, which can in turn improve clinical use, avoid unwanted side effects, and guide selection and development of better treatments. One exciting application of computational pharmacology is drug repurposing-finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we argue that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action. WIREs Syst Biol Med 2016, 8:186-210. doi: 10.1002/wsbm.1337 For further resources related to this article, please visit the WIREs website.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC28bgtFSruw%253D%253D&md5=625d7ef02f2c495031e62988ac98446f
    36. 36
      Daina, A.; Zoete, V. A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. ChemMedChem 2016, 11, 1117– 1121,  DOI: 10.1002/cmdc.201600182
      36
      A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules
      Daina, Antoine; Zoete, Vincent
      ChemMedChem (2016), 11 (11), 1117-1121CODEN: CHEMGX; ISSN:1860-7179. (Wiley-VCH Verlag GmbH & Co. KGaA)
      Apart from efficacy and toxicity, many drug development failures are imputable to poor pharmacokinetics and bioavailability. Gastrointestinal absorption and brain access are two pharmacokinetic behaviors crucial to est. at various stages of the drug discovery processes. To this end, the Brain Or IntestinaL Estd. permeation method (BOILED-Egg) is proposed as an accurate predictive model that works by computing the lipophilicity and polarity of small mols. Concomitant predictions for both brain and intestinal permeation are obtained from the same two physicochem. descriptors and straightforwardly translated into mol. design, owing to the speed, accuracy, conceptual simplicity and clear graphical output of the model. The BOILED-Egg can be applied in a variety of settings, from the filtering of chem. libraries at the early steps of drug discovery, to the evaluation of drug candidates for development.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XosFWit78%253D&md5=2cf19e6fe089ef1c0d8f38f0fdb528cc
    37. 37
      Tandon, R.; Keshavan, M. S.; Nasrallah, H. A. Schizophrenia, “Just the Facts”: What We Know in 2008 Part 1: Overview. Schizophr. Res. 2008, 100, 4– 19,  DOI: 10.1016/j.schres.2008.01.022
      37
      Schizophrenia, "Just the Facts": what we know in 2008 part 1: overview
      Tandon Rajiv; Keshavan Matcheri S; Nasrallah Henry A
      Schizophrenia research (2008), 100 (1-3), 4-19 ISSN:0920-9964.
      For every disorder, there is a set of established findings and accepted constructs upon which further understanding is built. The concept of schizophrenia as a disease entity has been with us for a little more than a century, although descriptions resembling this condition predate this conceptualization. In 1988, for the inaugural issue of Schizophrenia Research, at the invitation of the founding editors, a senior researcher, since deceased (RJ Wyatt) published a summary of generally accepted ideas about the disorder, which he termed "the facts" of schizophrenia. Ten years later, in conjunction with two of the authors (MSK, RT), he compiled a more extensive set of "facts" for the purpose of evaluating conceptual models or theoretical constructs developed to understand the nature of schizophrenia. On the 20th anniversary of this journal, we update and substantially expand our effort to periodically summarize the current body of information about schizophrenia. We compile a body of seventy-seven representative major findings and group them in terms of their specific relevance to schizophrenia -- etiologies, pathophysiology, clinical manifestations, and treatments. We rate each such "fact" on a 0-3 scale for measures of reproducibility, whether primary to schizophrenia, and durability over time. We also pose one or more critical questions with reference to each "fact", answers to which might help better elucidate the meaning of that finding for our understanding of schizophrenia. We intend to follow this paper with the submission to the journal of a series of topic-specific articles, critically reviewing the evidence.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD1c7mvFSmtg%253D%253D&md5=81360c3f74b8b08c04b907d86b79ed00
    38. 38
      Gaebel, W.; Zielasek, J. Schizophrenia in 2020: Trends in Diagnosis and Therapy. Psychiatry Clin. Neurosci. 2015, 69, 661– 673,  DOI: 10.1111/pcn.12322
      38
      Schizophrenia in 2020: Trends in diagnosis and therapy
      Gaebel Wolfgang; Zielasek Jurgen; Gaebel Wolfgang; Zielasek Jurgen
      Psychiatry and clinical neurosciences (2015), 69 (11), 661-73 ISSN:.
      Schizophrenia research is providing an increasing number of studies and important insights into the condition's etiopathogenesis based on genetic, neuropsychological and cranial neuroimaging studies. However, research progress has not yet led to the incorporation of such findings into the revised classification criteria of mental disorders or everyday clinical practice. By 2020, schizophrenia will most likely still be a clinically defined primary psychotic disorder. While there is some hope that treatment will be improved with new antipsychotic drugs, drugs addressing negative symptoms, more refined psychotherapy approaches and the introduction of new treatment modalities like transcranial magnetic stimulation, an additional hope is to improve early detection and prevention. As the results of new research into the etiopathogenesis of schizophrenia are promising to improve diagnosis, classification and therapy in the future, a picture of complex brain dysfunction is currently emerging requiring sophisticated mathematical methods of analysis. The imminent clinical challenge will be to develop comprehensive diagnostic and treatment modules individually tailored to the time-variable needs of patients and their families.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2MfntFGntg%253D%253D&md5=2c454cee2691b741060cf8b96316b856
    39. 39
      Seeman, P.; Kapur, S. Schizophrenia: More Dopamine, More D2 Receptors. Proc. Natl. Acad. Sci. U. S. A. 2000, 97, 7673– 7675,  DOI: 10.1073/pnas.97.14.7673
      39
      Schizophrenia: more dopamine, more D2 receptors
      Seeman, Philip; Kapur, Shitij
      Proceedings of the National Academy of Sciences of the United States of America (2000), 97 (14), 7673-7675CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      A polemic in response to A. Abi-Dargham (ibid. 8104).
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXkvFCntr8%253D&md5=258c7c70d64caf9035d9c322a6e1a61f
    40. 40
      Lee, T.; Seeman, P. Brain Dopamine Receptors In Schizophrenia; Usdin, E., Hanin, I. B. T.-B. M. in P. and N., Eds.; Pergamon , 1982; pp. 219– 226,  DOI: 10.1016/B978-0-08-027987-9.50027-5 .
      There is no corresponding record for this reference.
    41. 41
      Putnam, D. K.; Sun, J.; Zhao, Z. Exploring Schizophrenia Drug-Gene Interactions through Molecular Network and Pathway Modeling. AMIA . Annual Symposium proceedings. AMIA Annu. Symp. Proc. 2011, 2011, 1127– 1133
      41
      Exploring schizophrenia drug-gene interactions through molecular network and pathway modeling
      Putnam Daniel K; Sun Jingchun; Zhao Zhongming
      AMIA ... Annual Symposium proceedings. AMIA Symposium (2011), 2011 (), 1127-33 ISSN:.
      In this study, we retrieved 39 schizophrenia-related antipsychotic drugs from the DrugBank database. These drugs had interactions with 142 targets, whose corresponding genes were defined as drug targeted genes. To explore the complexity between these drugs and their related genes in schizophrenia, we constructed a drug-target gene network. These genes were overrepresented in several pathways including: neuroactive ligand-receptor pathways, glutamate metabolism, and glycine metabolism. Through integrating the pathway information into a drug-gene network, we revealed a few bridge genes connected the sub-networks of the drug-gene network: GRIN2A, GRIN3B, GRIN2C, GRIN2B, DRD1, and DRD2. These genes encode ionotropic glutamate receptors belonging to the NMDA receptor family and dopamine receptors. Haloperidol was the only drug to directly interact with these pathways and receptors and consequently may have a unique action at the drug-gene interaction level during the treatment of schizophrenia. This study represents the first systematic investigation of drug-gene interactions in psychosis.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38%252Fps1Onsw%253D%253D&md5=bf8ef4e18647e679530f273f7dbd4f26
    42. 42
      Kesby, J. P.; Eyles, D. W.; McGrath, J. J.; Scott, J. G. Dopamine, Psychosis and Schizophrenia: The Widening Gap between Basic and Clinical Neuroscience. Transl. Psychiatry 2018, 8, 30,  DOI: 10.1038/s41398-017-0071-9
      42
      Dopamine, psychosis and schizophrenia: the widening gap between basic and clinical neuroscience
      Kesby J P; Eyles D W; McGrath J J; Kesby J P; Scott J G; Eyles D W; McGrath J J; Scott J G; McGrath J J; Scott J G
      Translational psychiatry (2018), 8 (1), 30 ISSN:.
      The stagnation in drug development for schizophrenia highlights the need for better translation between basic and clinical research. Understanding the neurobiology of schizophrenia presents substantial challenges but a key feature continues to be the involvement of subcortical dopaminergic dysfunction in those with psychotic symptoms. Our contemporary knowledge regarding dopamine dysfunction has clarified where and when dopaminergic alterations may present in schizophrenia. For example, clinical studies have shown patients with schizophrenia show increased presynaptic dopamine function in the associative striatum, rather than the limbic striatum as previously presumed. Furthermore, subjects deemed at high risk of developing schizophrenia show similar presynaptic dopamine abnormalities in the associative striatum. Thus, our view of subcortical dopamine function in schizophrenia continues to evolve as we accommodate this newly acquired information. However, basic research in animal models has been slow to incorporate these clinical findings. For example, psychostimulant-induced locomotion, the commonly utilised phenotype for positive symptoms in rodents, is heavily associated with dopaminergic activation in the limbic striatum. This anatomical misalignment has brought into question how we assess positive symptoms in animal models and represents an opportunity for improved translation between basic and clinical research. The current review focuses on the role of subcortical dopamine dysfunction in psychosis and schizophrenia. We present and discuss alternative phenotypes that may provide a more translational approach to assess the neurobiology of positive symptoms in schizophrenia. Incorporation of recent clinical findings is essential if we are to develop meaningful translational animal models.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MvlsFylsw%253D%253D&md5=f9b6fb9d2f871a12b19cc4b67b3a9d09
    43. 43
      Laboratories, K. KEEG https://www.genome.jp/kegg/ (accessed Oct 26, 2020).
      There is no corresponding record for this reference.
    44. 44
      Sibley, D. R.; Neve, K. Dopamine Receptors; Enna, S. J., Bylund, D. B. B. T. T. C. P. R., Eds.; Elsevier: New York, 2007; pp. 1– 4,  DOI: 10.1016/B978-008055232-3.60151-5 .
      There is no corresponding record for this reference.
    45. 45
      Neve, K. A. Dopamine Receptors; Lennarz, W. J., Lane, M. D. B. T.-E. of B. C. (Second E., Eds.; Academic Press: Waltham, 2013; pp. 169– 173,  DOI: 10.1016/B978-0-12-378630-2.00326-1 .
      There is no corresponding record for this reference.
    46. 46
      Wang, S.; Che, T.; Levit, A.; Shoichet, B. K.; Wacker, D.; Roth, B. L. Structure of the D2 Dopamine Receptor Bound to the Atypical Antipsychotic Drug Risperidone. Nature 2018, 555, 269– 273,  DOI: 10.1038/nature25758
      46
      Structure of the D2 dopamine receptor bound to the atypical antipsychotic drug risperidone
      Wang, Sheng; Che, Tao; Levit, Anat; Shoichet, Brian K.; Wacker, Daniel; Roth, Bryan L.
      Nature (London, United Kingdom) (2018), 555 (7695), 269-273CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
      Dopamine is a neurotransmitter that has been implicated in processes as diverse as reward, addiction, control of coordinated movement, metab. and hormonal secretion. Correspondingly, dysregulation of the dopaminergic system has been implicated in diseases such as schizophrenia, Parkinson's disease, depression, attention deficit hyperactivity disorder, and nausea and vomiting. The actions of dopamine are mediated by a family of five G-protein-coupled receptors. The D2 dopamine receptor (DRD2) is the primary target for both typical and atypical antipsychotic drugs, and for drugs used to treat Parkinson's disease. Unfortunately, many drugs that target DRD2 cause serious and potentially life-threatening side effects due to promiscuous activities against related receptors. Accordingly, a mol. understanding of the structure and function of DRD2 could provide a template for the design of safer and more effective medications. Here we report the crystal structure of DRD2 in complex with the widely prescribed atypical antipsychotic drug risperidone. The DRD2-risperidone structure reveals an unexpected mode of antipsychotic drug binding to dopamine receptors, and highlights structural determinants that are essential for the actions of risperidone and related drugs at DRD2.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXktFKqt7c%253D&md5=2842adc1893293ea8dbf98ae3270a1b2
    47. 47
      Corena-McLeod, M. Comparative Pharmacology of Risperidone and Paliperidone. Drugs R&D 2015, 15, 163– 174,  DOI: 10.1007/s40268-015-0092-x
      There is no corresponding record for this reference.
    48. 48
      Martelle, J. L.; Nader, M. A. A Review of the Discovery, Pharmacological Characterization, and Behavioral Effects of the Dopamine D2-like Receptor Antagonist Eticlopride. CNS Neurosci. Ther. 2008, 14, 248– 262,  DOI: 10.1111/j.1755-5949.2008.00047.x
      48
      A review of the discovery, pharmacological characterization, and behavioral effects of the dopamine D2-like receptor antagonist eticlopride
      Martelle, Jennifer L.; Nader, Michael A.
      CNS Neuroscience & Therapeutics (2008), 14 (3), 248-262CODEN: CNTNAB; ISSN:1755-5930. (Wiley-Blackwell)
      A review. Eticlopride is a substituted benzamide analog with high affinity and selectivity for dopamine (DA) D2-like receptors that was initially developed as a potential antipsychotic agent. A great deal of research has utilized this drug to better understand central DA receptor function, the role of D2-like receptors in behavior, and the influence of blockade of these receptors on several preclin. animal models. This review highlights research utilizing this drug and compares it to typical and atypical antipsychotics used clin. First, we describe structure-activity relationships as it relates to binding at DA receptors and the consequences on behavior. This is followed by a discussion of several imaging strategies including the use of eticlopride for in vivo, in vitro, and ex vivo examn. of DA D2-like receptor densities and function. Finally, we discuss the use of eticlopride in several behavioral models predictive of antipsychotic activity, extrapyramidal side effects (EPS), and learning and memory. While eticlopride is not used clin., it remains a viable research tool for understanding DA receptor function and behavior.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFentLjP&md5=cc9cec830ab1e3935901f6e3a9cabe66
    49. 49
      Miyamoto, S. Nemonapride BT - Encyclopedia of Psychopharmacology; Stolerman, I. P., Ed.; Springer Berlin Heidelberg: Berlin, Heidelberg, 2010; p 823,  DOI: 10.1007/978-3-540-68706-1_1840 .
      There is no corresponding record for this reference.
    50. 50
      Platania, C. B. M.; Salomone, S.; Leggio, G. M.; Drago, F.; Bucolo, C. Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation. PLoS One 2012, 7, e44316– e44316,  DOI: 10.1371/journal.pone.0044316
      50
      Homology modeling of dopamine D2 and D3 receptors: molecular dynamics refinement and docking evaluation
      Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio
      PLoS One (2012), 7 (9), e44316CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
      Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurol., psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homol. models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with mol. dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in mol. docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calcn. Robust correlation of computed and exptl. Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtlCitrrL&md5=50672aa14be2fa0cb33a4f43069937a3
    51. 51
      Chien, E. Y. T.; Liu, W.; Zhao, Q.; Katritch, V.; Han, G. W.; Hanson, M. A.; Shi, L.; Newman, A. H.; Javitch, J. A.; Cherezov, V.; Stevens, R. C. Structure of the human dopamine D3 receptor in complex with a D2/D3 selective antagonist. Science 2010, 330, 1091– 1095,  DOI: 10.1126/science.1197410
      51
      Structure of the Human Dopamine D3 Receptor in Complex with a D2/D3 Selective Antagonist
      Chien, Ellen Y. T.; Liu, Wei; Zhao, Qiang; Katritch, Vsevolod; Won Han, Gye; Hanson, Michael A.; Shi, Lei; Newman, Amy Hauck; Javitch, Jonathan A.; Cherezov, Vadim; Stevens, Raymond C.
      Science (Washington, DC, United States) (2010), 330 (6007), 1091-1095CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
      Dopamine modulates movement, cognition, and emotion through activation of dopamine G protein-coupled receptors in the brain. The crystal structure of the human dopamine D3 receptor (D3R) in complex with the small mol. D2R/D3R-specific antagonist eticlopride reveals important features of the ligand binding pocket and extracellular loops. On the intracellular side of the receptor, a locked conformation of the ionic lock and two distinctly different conformations of intracellular loop 2 are obsd. Docking of R-22, a D3R-selective antagonist, reveals an extracellular extension of the eticlopride binding site that comprises a second binding pocket for the aryl amide of R-22, which differs between the highly homologous D2R and D3R. This difference provides direction to the design of D3R-selective agents for treating drug abuse and other neuropsychiatric indications.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhsVahurvM&md5=12c6f343daea9fb14ca605a092f28533
    52. 52
      Ferreira de Freitas, R.; Schapira, M. A Systematic Analysis of Atomic Protein–Ligand Interactions in the PDB. MedChemComm 2017, 8, 1970– 1981,  DOI: 10.1039/C7MD00381A
      52
      A systematic analysis of atomic protein-ligand interactions in the PDB
      Ferreira de Freitas, Renato; Schapira, Matthieu
      MedChemComm (2017), 8 (10), 1970-1981CODEN: MCCEAY; ISSN:2040-2503. (Royal Society of Chemistry)
      As the protein databank (PDB) recently passed the cap of 123 456 structures, it stands more than ever as an important resource not only to analyze structural features of specific biol. systems, but also to study the prevalence of structural patterns obsd. in a large body of unrelated structures, that may reflect rules governing protein folding or mol. recognition. Here, we compiled a list of 11 016 unique structures of small-mol. ligands bound to proteins - 6444 of which have exptl. binding affinity - representing 750 873 protein-ligand at. interactions, and analyzed the frequency, geometry and impact of each interaction type. We find that hydrophobic interactions are generally enriched in high-efficiency ligands, but polar interactions are over-represented in fragment inhibitors. While most observations extd. from the PDB will be familiar to seasoned medicinal chemists, less expected findings, such as the high no. of C-H···O hydrogen bonds or the relatively frequent amide-p stacking between the backbone amide of proteins and arom. rings of ligands, uncover underused ligand design strategies.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhsFOiu7nE&md5=04688488e73253f76e4ea384456f89a8
    53. 53
      Wang, S.; Wacker, D.; Levit, A.; Che, T.; Betz, R. M.; McCorvy, J. D.; Venkatakrishnan, A. J.; Huang, X.-P.; Dror, R. O.; Shoichet, B. K.; Roth, B. L. D4 Dopamine Receptor High-Resolution Structures Enable the Discovery of Selective Agonists. Science 2017, 358, 381– 386,  DOI: 10.1126/science.aan5468
      53
      D4 dopamine receptor high-resolution structures enable the discovery of selective agonists
      Wang, Sheng; Wacker, Daniel; Levit, Anat; Che, Tao; Betz, Robin M.; McCorvy, John D.; Venkatakrishnan, A. J.; Huang, Xi-Ping; Dror, Ron O.; Shoichet, Brian K.; Roth, Bryan L.
      Science (Washington, DC, United States) (2017), 358 (6361), 381-386CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
      Dopamine receptors are implicated in the pathogenesis and treatment of nearly every neuropsychiatric disorder. Although thousands of drugs interact with these receptors, our mol. understanding of dopaminergic drug selectivity and design remains clouded. To illuminate dopamine receptor structure, function, and ligand recognition, we detd. crystal structures of the D4 dopamine receptor in its inactive state bound to the antipsychotic drug nemonapride, with resolns. up to 1.95 angstroms. These structures suggest a mechanism for the control of constitutive signaling, and their unusually high resoln. enabled a structure-based campaign for new agonists of the D4 dopamine receptor. The ability to efficiently exploit structure for specific probe discovery-rapidly moving from elucidating receptor structure to discovering previously unrecognized, selective agonists-testifies to the power of structure-based approaches.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhs1Kns73I&md5=0bbb93e6bcb33577f9d9b7459273d896
    54. 54
      Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A. D., Jr. CHARMM General Force Field: A Force Field for Drug-like Molecules Compatible with the CHARMM All-Atom Additive Biological Force Fields. J. Comput. Chem. 2010, 31, 671– 690,  DOI: 10.1002/jcc.21367
      54
      CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields
      Vanommeslaeghe, K.; Hatcher, E.; Acharya, C.; Kundu, S.; Zhong, S.; Shim, J.; Darian, E.; Guvench, O.; Lopes, P.; Vorobyov, I.; Mackerell, A. D., Jr.
      Journal of Computational Chemistry (2010), 31 (4), 671-690CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like mols. is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chem. groups present in biomols. and drug-like mols., including a large no. of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concg. on an extensible force field. Statistics related to the quality of the parametrization with a focus on exptl. validation are presented. Addnl., the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethyl-pyrrolidine will allow users to readily extend the force field to chem. groups that are not explicitly covered in the force field as well as add functional groups to and link together mols. already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2010.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXhtlentbc%253D&md5=26212e0e4f73bded0c89d4b411cd3833
    55. 55
      Jean, B.; Surratt, C. K.; Madura, J. D. Molecular Dynamics of Conformation-Specific Dopamine Transporter-Inhibitor Complexes. J. Mol. Graphics Modell. 2017, 76, 143– 151,  DOI: 10.1016/j.jmgm.2017.07.003
      55
      Molecular dynamics of conformation-specific dopamine transporter-inhibitor complexes
      Jean, Bernandie; Surratt, Christopher K.; Madura, Jeffry D.
      Journal of Molecular Graphics & Modelling (2017), 76 (), 143-151CODEN: JMGMFI; ISSN:1093-3263. (Elsevier Ltd.)
      The recreational psychostimulant cocaine inhibits dopamine reuptake from the synapse, resulting in excessive stimulation of postsynaptic dopamine receptors in brain areas assocd. with reward and addiction. Cocaine binds to and stabilizes the outward- (extracellular-) facing conformation of the dopamine transporter (DAT) protein, while the low abuse potential DAT inhibitor benztropine prefers the inward- (cytoplasmic-) facing conformation. A correlation has been previously postulated between psychostimulant abuse potential and preference for the outward-facing DAT conformation. The 3β-aryltropane cocaine analogs LX10 and LX11, however, differ only in stereochem. and share a preference for the outward-facing DAT, yet are reported to vary widely in abuse potential in an animal model. In search of the mol. basis for DAT conformation preference, complexes of cocaine, benztropine, LX10 or LX11 bound to each DAT conformation were subjected to 100 ns of all-atom mol. dynamics simulation. Results were consistent with previous findings from cysteine accessibility assays used to assess an inhibitor's DAT conformation preference. The resp. 2β- and 2α-substituted phenyltropanes of LX10 and LX11 interacted with hydrophobic regions of the DAT S1 binding site that were inaccessible to cocaine. Solvent accessibility measurements also revealed subtle differences in inhibitor positioning within a given DAT conformation. This work serves to advance our understanding of the conformational selectivity of DAT inhibitors and suggests that MD may be useful in antipsychostimulant therapeutic design.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXht1SjsLnN&md5=98a374f8b6d61d96ec9f979c02dedf64
    56. 56
      Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B. L.; Grubmüller, H.; MacKerell, A. D., Jr. CHARMM36m: An Improved Force Field for Folded and Intrinsically Disordered Proteins. Nat. Methods 2017, 14, 71– 73,  DOI: 10.1038/nmeth.4067
      56
      CHARMM36m: an improved force field for folded and intrinsically disordered proteins
      Huang, Jing; Rauscher, Sarah; Nawrocki, Grzegorz; Ran, Ting; Feig, Michael; de Groot, Bert L.; Grubmuller, Helmut; MacKerell, Alexander D. Jr
      Nature Methods (2017), 14 (1), 71-73CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)
      The all-atom additive CHARMM36 protein force field is widely used in mol. modeling and simulations. We present its refinement, CHARMM36m (http://mackerell.umaryland.edu/charmm_ff.shtml), with improved accuracy in generating polypeptide backbone conformational ensembles for intrinsically disordered peptides and proteins.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvVSiu77I&md5=0aa151fbef2ee0b5e2cfb593c54330c2
    57. 57
      Nielsen, A. K.; Möller, I. R.; Wang, Y.; Rasmussen, S. G. F.; Lindorff-Larsen, K.; Rand, K. D.; Loland, C. J. Substrate-Induced Conformational Dynamics of the Dopamine Transporter. Nat. Commun. 2019, 10, 2714,  DOI: 10.1038/s41467-019-10449-w
      57
      Substrate-induced conformational dynamics of the dopamine transporter
      Nielsen Anne Kathrine; Moller Ingvar R; Loland Claus J; Nielsen Anne Kathrine; Moller Ingvar R; Rand Kasper D; Wang Yong; Lindorff-Larsen Kresten; Rasmussen Soren G F
      Nature communications (2019), 10 (1), 2714 ISSN:.
      The dopamine transporter is a member of the neurotransmitter:sodium symporters (NSSs), which are responsible for termination of neurotransmission through Na(+)-driven reuptake of neurotransmitter from the extracellular space. Experimental evidence elucidating the coordinated conformational rearrangements related to the transport mechanism has so far been limited. Here we probe the global Na(+)- and dopamine-induced conformational dynamics of the wild-type Drosophila melanogaster dopamine transporter using hydrogen-deuterium exchange mass spectrometry. We identify Na(+)- and dopamine-induced changes in specific regions of the transporter, suggesting their involvement in protein conformational transitions. Furthermore, we detect ligand-dependent slow cooperative fluctuations of helical stretches in several domains of the transporter, which could be a molecular mechanism that assists in the transporter function. Our results provide a framework for understanding the molecular mechanism underlying the function of NSSs by revealing detailed insight into the state-dependent conformational changes associated with the alternating access model of the dopamine transporter.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3M3ptVWktw%253D%253D&md5=0d905c0a58496ad52714d0302e23e0f1
    58. 58
      Klauda, J. B.; Venable, R. M.; Freites, J. A.; O’Connor, J. W.; Tobias, D. J.; Mondragon-Ramirez, C.; Vorobyov, I.; MacKerell, A. D., Jr.; Pastor, R. W. Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 2010, 114, 7830– 7843,  DOI: 10.1021/jp101759q
      58
      Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types
      Klauda, Jeffery B.; Venable, Richard M.; Freites, J. Alfredo; O'Connor, Joseph W.; Tobias, Douglas J.; Mondragon-Ramirez, Carlos; Vorobyov, Igor; MacKerell, Alexander D., Jr.; Pastor, Richard W.
      Journal of Physical Chemistry B (2010), 114 (23), 7830-7843CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)
      A significant modification to the additive all-atom CHARMM lipid force field (FF) is developed and applied to phospholipid bilayers with both choline and ethanolamine contg. head groups and with both satd. and unsatd. aliph. chains. Motivated by the current CHARMM lipid FF (C27 and C27r) systematically yielding values of the surface area per lipid that are smaller than exptl. ests. and gel-like structures of bilayers well above the gel transition temp., selected torsional, Lennard-Jones and partial at. charge parameters were modified by targeting both quantum mech. (QM) and exptl. data. QM calcns. ranging from high-level ab initio calcns. on small mols. to semiempirical QM studies on a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer in combination with exptl. thermodn. data were used as target data for parameter optimization. These changes were tested with simulations of pure bilayers at high hydration of the following six lipids: DPPC, 1,2-dimyristoyl-sn-phosphatidylcholine (DMPC), 1,2-dilauroyl-sn-phosphatidylcholine (DLPC), 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine (POPC), 1,2-dioleoyl-sn-phosphatidylcholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine (POPE); simulations of a low hydration DOPC bilayer were also performed. Agreement with exptl. surface area is on av. within 2%, and the d. profiles agree well with neutron and x-ray diffraction expts. NMR deuterium order parameters (SCD) are well predicted with the new FF, including proper splitting of the SCD for the aliph. carbon adjacent to the carbonyl for DPPC, POPE, and POPC bilayers. The area compressibility modulus and frequency dependence of 13C NMR relaxation rates of DPPC and the water distribution of low hydration DOPC bilayers also agree well with expt. Accordingly, the presented lipid FF, referred to as C36, allows for mol. dynamics simulations to be run in the tensionless ensemble (NPT), and is anticipated to be of utility for simulations of pure lipid systems as well as heterogeneous systems including membrane proteins.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXmsVGjtrk%253D&md5=04c4d3aa1a59740190994d7df80cbb71
    59. 59
      Vanommeslaeghe, K.; MacKerell, A. D., Jr. Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 2012, 52, 3144– 3154,  DOI: 10.1021/ci300363c
      59
      Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing
      Vanommeslaeghe, K.; MacKerell, A. D.
      Journal of Chemical Information and Modeling (2012), 52 (12), 3144-3154CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug-like mols. alone or interacting with biol. systems. In simulations involving biol. macromols., the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and charges is required. In the present article, which is part I of a series of two, we present the algorithms for bond perception and atom typing for the CHARMM General Force Field (CGenFF). The CGenFF atom typer first assocs. attributes to the atoms and bonds in a mol., such as valence, bond order, and ring membership among others. Of note are a no. of features that are specifically required for CGenFF. This information is then used by the atom typing routine to assign CGenFF atom types based on a programmable decision tree. This allows for straight-forward implementation of CGenFF's complicated atom typing rules and for equally straight-forward updating of the atom typing scheme as the force field grows. The presented atom typer was validated by assigning correct atom types on 477 model compds. including in the training set as well as 126 test-set mols. that were constructed to specifically verify its different components. The program may be utilized via an online implementation at https://www.paramchem.org/.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhs1Gns7fL&md5=c6679293f4a2501f2bcadf2020ca1473
    60. 60
      Best, R. B.; Zhu, X.; Shim, J.; Lopes, P. E. M.; Mittal, J.; Feig, M.; Mackerell, A. D., Jr. Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone φ, ψ and Side-Chain χ(1) and χ(2) Dihedral Angles. J. Chem. Theory Comput. 2012, 8, 3257– 3273,  DOI: 10.1021/ct300400x
      60
      Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone .vphi., ψ and Side-Chain χ1 and χ2 Dihedral Angles
      Best, Robert B.; Zhu, Xiao; Shim, Jihyun; Lopes, Pedro E. M.; Mittal, Jeetain; Feig, Michael; MacKerell, Alexander D.
      Journal of Chemical Theory and Computation (2012), 8 (9), 3257-3273CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large no. of applications, limitations in the model with respect to the equil. between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non-Gly, -Pro) backbone CMAP potential has been refined against exptl. soln. NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mech. energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mech. energy surfaces, followed by addnl. empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against a collection of exptl. data: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equil. folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for modeling and simulation studies of proteins, including studies of protein folding, assembly, and functionally relevant conformational changes.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhtVKqurfP&md5=9a48a0c5770fb1e887c3bb34d45b1354
    61. 61
      Lane, J. R.; Abramyan, A. M.; Adhikari, P.; Keen, A. C.; Lee, K.-H.; Sanchez, J.; Verma, R. K.; Lim, H. D.; Yano, H.; Javitch, J. A.; Shi, L. Distinct Inactive Conformations of the Dopamine D2 and D3 Receptors Correspond to Different Extents of Inverse Agonism. eLife 2020, 9, e52189  DOI: 10.7554/eLife.52189
      61
      Distinct inactive conformations of the dopamine D2 and D3 receptors correspond to different extents of inverse agonism
      Lane, J. Robert; Abramyan, Ara M.; Adhikari, Pramisha; Keen, Alastair C.; Lee, Kuo-Hao; Sanchez, Julie; Verma, Ravi Kumar; Lim, Herman D.; Yano, Hideaki; Javitch, Jonathan A.; Shi, Lei
      eLife (2020), 9 (), e52189CODEN: ELIFA8; ISSN:2050-084X. (eLife Sciences Publications Ltd.)
      By analyzing and simulating inactive conformations of the highly homologous dopamine D2 and D3 receptors (D2R and D3R), we find that eticlopride binds D2R in a pose very similar to that in the D3R/eticlopride structure but incompatible with the D2R/risperidone structure. In addn., risperidone occupies a sub-pocket near the Na+ binding site, whereas eticlopride does not. Based on these findings and our exptl. results, we propose that the divergent receptor conformations stabilized by Na+ -sensitive eticlopride and Na+ -insensitive risperidone correspond to different degrees of inverse agonism. Moreover, our simulations reveal that the extracellular loops are highly dynamic, with spontaneous transitions of extracellular loop 2 from the helical conformation in the D2R/risperidone structure to an extended conformation similar to that in the D3R/eticlopride structure. Our results reveal previously unappreciated diversity and dynamics in the inactive conformations of D2R. These findings are crit. for rational drug discovery, as limiting a virtual screen to a single conformation will miss relevant ligands.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtlarsb7O&md5=e282f1721292b10c6a1ac5cfc44a98c4
    62. 62
      MacKerell, A. D., Jr.; Feig, M.; Brooks, C. L. Improved Treatment of the Protein Backbone in Empirical Force Fields. J. Am. Chem. Soc. 2004, 126, 698– 699,  DOI: 10.1021/ja036959e
      62
      Improved treatment of the protein backbone in empirical force fields
      MacKerell, Alexander D., Jr.; Feig, Michael; Brooks, Charles L., III
      Journal of the American Chemical Society (2004), 126 (3), 698-699CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
      Empirical force field-based calcns. of proteins, including protein-folding studies, have improved our understanding of the relationship of their structure to their biol. function. However, limitations in the accuracy of empirical force fields in the treatment of the peptide backbone exist. Presented is a grid correction approach to improve the treatment of the peptide backbone φ/ψ conformational energies. Inclusion of this correction with the CHARMM22 all-atom protein force field is shown to lead to significant improvement in the treatment of the conformational energies of both the peptide model compd., the alanine dipeptide, and of proteins in their crystal environment. The developed approach is suggested to lead to significant improvements in the accuracy of empirical force fields to treat peptides and proteins.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXhtVWisb7F&md5=a1426b50784d4eca888dc270643ef947
    63. 63
      Jo, J. C.; Kim, B. C. Determination of Proper Time Step for Molecular Dynamics Simulation. Bull. Korean Chem. Soc. 2000, 21, 419
      There is no corresponding record for this reference.
    64. 64
      Hollingsworth, S. A.; Dror, R. O. Molecular Dynamics Simulation for All. Neuron 2018, 99, 1129– 1143,  DOI: 10.1016/j.neuron.2018.08.011
      64
      Molecular Dynamics Simulation for All
      Hollingsworth, Scott A.; Dror, Ron O.
      Neuron (2018), 99 (6), 1129-1143CODEN: NERNET; ISSN:0896-6273. (Cell Press)
      A review. The impact of mol. dynamics (MD) simulations in mol. biol. and drug discovery has expanded dramatically in recent years. These simulations capture the behavior of proteins and other biomols. in full at. detail and at very fine temporal resoln. Major improvements in simulation speed, accuracy, and accessibility, together with the proliferation of exptl. structural data, have increased the appeal of biomol. simulation to experimentalists-a trend particularly noticeable in, although certainly not limited to, neuroscience. Simulations have proven valuable in deciphering functional mechanisms of proteins and other biomols., in uncovering the structural basis for disease, and in the design and optimization of small mols., peptides, and proteins. Here we describe, in practical terms, the types of information MD simulations can provide and the ways in which they typically motivate further exptl. work.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1cXhslGltLzL&md5=35e14022763288ed45c2a605cc900f61
    65. 65
      Lobanov, M. Y.; Bogatyreva, N. S.; Galzitskaya, O. V. Radius of Gyration as an Indicator of Protein Structure Compactness. Mol. Biol. 2008, 42, 623– 628,  DOI: 10.1134/S0026893308040195
      65
      Radius of gyration as an indicator of protein structure compactness
      Lobanov, M. Yu.; Bogatyreva, N. S.; Galzitskaya, O. V.
      Molecular Biology (Moscow, Russian Federation, English Edition) (2008), 42 (4), 623-628CODEN: MOLBBJ; ISSN:0026-8933. (Pleiades Publishing, Ltd.)
      Identification and study of the main principles underlying the kinetics and thermodn. of protein folding generate new insights into the factors that control this process. Statistical anal. of the radius of gyration for 3769 protein domains of four major classes (α, β, α/β, and α + β) showed that each class has a characteristic radius of gyration that dets. the protein's structural compactness. For instance, α proteins have the highest radius of gyration throughout the protein size range considered, suggesting a less tight packing as compared with β- and (α + β)-proteins. The lowest radius of gyration and, accordingly, the tightest packing are characteristic of α/β-proteins. The protein radius of gyration normalized by the radius of gyration of a ball with the same vol. is independent of the protein size, in contrast to compactness and the no. of contacts per residue.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXps1ahtrc%253D&md5=2eca54d4bb83f4cc3843bc2506fdd1a1
    66. 66
      Falsafi-Zadeh, S.; Karimi, Z.; Galehdari, H. VMD DisRg: New User-Friendly Implement for Calculation Distance and Radius of Gyration in VMD Program. Bioinformation 2012, 8, 341– 343,  DOI: 10.6026/97320630008341
      66
      VMD DisRg: New User-Friendly Implement for calculation distance and radius of gyration in VMD program
      Falsafi-Zadeh Sajad; Karimi Zahra; Galehdari Hamid
      Bioinformation (2012), 8 (7), 341-3 ISSN:.
      UNLABELLED: Molecular dynamic simulation is a practical and powerful technique for analysis of protein structure. Several programs have been developed to facilitate the mentioned investigation, under them the visual molecular dynamic or VMD is the most frequently used programs. One of the beneficial properties of the VMD is its ability to be extendable by designing new plug-in. We introduce here a new facility of the VMD for distance analysis and radius of gyration of biopolymers such as protein and DNA. AVAILABILITY: The database is available for free at http://trc.ajums.ac.ir/HomePage.aspx/?TabID/=12618/&Site/=trc.ajums.ac/&Lang/=fa-IR.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC38rpvFOhsg%253D%253D&md5=f235c8036e531f2540a1e08ed92e7dc5
    67. 67
      Shao, J.; Tanner, S. W.; Thompson, N.; Cheatham, T. E. Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms. J. Chem. Theory Comput. 2007, 3, 2312– 2334,  DOI: 10.1021/ct700119m
      67
      Clustering Molecular Dynamics Trajectories: 1. Characterizing the Performance of Different Clustering Algorithms
      Shao, Jianyin; Tanner, Stephen W.; Thompson, Nephi; Cheatham, Thomas E., III
      Journal of Chemical Theory and Computation (2007), 3 (6), 2312-2334CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      Mol. dynamics simulation methods produce trajectories of at. positions (and optionally velocities and energies) as a function of time and provide a representation of the sampling of a given mol.'s energetically accessible conformational ensemble. As simulations on the 10-100 ns time scale become routine, with sampled configurations stored on the picosecond time scale, such trajectories contain large amts. of data. Data-mining techniques, like clustering, provide one means to group and make sense of the information in the trajectory. In this work, several clustering algorithms were implemented, compared, and utilized to understand MD trajectory data. The development of the algorithms into a freely available C code library, and their application to a simple test example of random (or systematically placed) points in a 2D plane (where the pairwise metric is the distance between points) provide a means to understand the relative performance. Eleven different clustering algorithms were developed, ranging from top-down splitting (hierarchical) and bottom-up aggregating (including single-linkage edge joining, centroid-linkage, av.-linkage, complete-linkage, centripetal, and centripetal-complete) to various refinement (means, Bayesian, and self-organizing maps) and tree (COBWEB) algorithms. Systematic testing in the context of MD simulation of various DNA systems (including DNA single strands and the interaction of a minor groove binding drug DB226 with a DNA hairpin) allows a more direct assessment of the relative merits of the distinct clustering algorithms. Addnl., means to assess the relative performance and differences between the algorithms, to dynamically select the initial cluster count, and to achieve faster data mining by "sieved clustering" were evaluated. Overall, it was found that there is no one perfect "one size fits all" algorithm for clustering MD trajectories and that the results strongly depend on the choice of atoms for the pairwise comparison. Some algorithms tend to produce homogeneously sized clusters, whereas others have a tendency to produce singleton clusters. Issues related to the choice of a pairwise metric, clustering metrics, which atom selection is used for the comparison, and about the relative performance are discussed. Overall, the best performance was obsd. with the av.-linkage, means, and SOM algorithms. If the cluster count is not known in advance, the hierarchical or av.-linkage clustering algorithms are recommended. Although these algorithms perform well, it is important to be aware of the limitations or weaknesses of each algorithm, specifically the high sensitivity to outliers with hierarchical, the tendency to generate homogenously sized clusters with means, and the tendency to produce small or singleton clusters with av.-linkage.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXhtFaqsLzE&md5=668cff11c29736325a4788379cc43def
    68. 68
      Wu, X.; Wang, S. Self-Guided Molecular Dynamics Simulation for Efficient Conformational Search. J. Phys. Chem. B 1998, 102, 7238– 7250,  DOI: 10.1021/jp9817372
      68
      Self-Guided Molecular Dynamics Simulation for Efficient Conformational Search
      Wu, Xiongwu; Wang, Shaomeng
      Journal of Physical Chemistry B (1998), 102 (37), 7238-7250CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)
      Conformational searching is a basic approach in theor. and computational chem., and mol. dynamics [MD] simulation is a powerful computational tool to study structural, thermodn., and kinetic properties of mol. systems. In this paper, we report a new MD simulation method with the primary goal of improving dramatically the conformational searching efficiency in an MD simulation in order to study slow events in physics, chem., and biol. This new MD simulation method was based upon a new equation of motion in which a guiding force was introduced, in addn. to the instantaneous force, to accelerate the systematic motion. This guiding force may be calcd. as a time av. of the instantaneous force from the trajectory obtained from the very same MD simulation. Bonded substructures were defined for mol. systems in order to enhance effectively both the inter- and intramol. systematic motions. The improvement of the overall conformational searching efficiency and the possible alterations of ensemble properties and the conformational distribution of the system were investigated through comparative simulations of two peptide systems, an alanine dipeptide and a 16-residue synthetic peptide, both in vacuum and in explicit water. We demonstrated that the self-guided MD simulation method improved conformational searching efficiency but did not significantly alter the ensemble av. properties and the conformational distributions of the systems. The successful helix-folding simulations of the 16-residue synthetic peptide both in vacuum and in explicit water clearly showed that the self-guided MD simulations achieved a dramatic enhancement in the conformational searching efficiency and showed an extraordinary ability to overcome energy barriers, as compared to the conventional MD simulations. Our results suggest that this new MD simulation method may be used as a powerful tool to study many important yet slow events or processes in physics, chem., and biol.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXltlyhsLk%253D&md5=1365a5c8317e7418764214230507ffbc
    69. 69
      Wu, X.; Brooks, B. R. Beta-Hairpin Folding Mechanism of a Nine-Residue Peptide Revealed from Molecular Dynamics Simulations in Explicit Water. Biophys. J. 2004, 86, 1946– 1958,  DOI: 10.1016/S0006-3495(04)74258-7
      69
      β-hairpin folding mechanism of a nine-residue peptide revealed from molecular dynamics simulations in explicit water
      Wu, Xiongwu; Brooks, Bernard R.
      Biophysical Journal (2004), 86 (4), 1946-1958CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)
      The β-hairpin fold mechanism of a nine-residue peptide, which is modified from the β-hairpin of α-amylase inhibitor tendamistat (residues 15-23), is studied through direct folding simulations in explicit water at native folding conditions. Three 300-ns self-guided mol. dynamics (SGMD) simulations have revealed a series of β-hairpin folding events. During these simulations, the peptide folds repeatedly into a major cluster of β-hairpin structures, which agree well with NMR exptl. observations. This major cluster is found to have the min. conformational free energy among all sampled conformations. This peptide also folds into many other β-hairpin structures, which represent some local free energy min. states. In the unfolded state, the N-terminal residues of the peptide, Tyr-1, Gln-2, and Asn-3, have a confined conformational distribution. This confinement makes β-hairpin the only energetically favored structure to fold. The unfolded state of this peptide is populated with conformations with non-native intrapeptide interactions. This peptide goes through fully hydrated conformations to eliminate non-native interactions before folding into a β-hairpin. The folding of a β-hairpin starts with side-chain interactions, which bring two strands together to form interstrand hydrogen bonds. The unfolding of the β-hairpin is not simply the reverse of the folding process. Comparing unfolding simulations using MD and SGMD methods demonstrate that SGMD simulations can qual. reproduce the kinetics of the peptide system.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXivF2ns74%253D&md5=791be954834d05a48fcbf12fee8c11de
    70. 70
      Wu, X.; Wang, S. Helix Folding of an Alanine-Based Peptide in Explicit Water. J. Phys. Chem. B 2001, 105, 2227– 2235,  DOI: 10.1021/jp004048a
      70
      Helix folding of an alanine-based peptide in explicit water
      Wu, Xiongwu; Wang, Shaomeng
      Journal of Physical Chemistry B (2001), 105 (11), 2227-2235CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)
      Computer simulations using full at. representations for both the peptide and water mols. were performed to study the folding of a 16-residue alanine-based helical peptide in aq. soln. Using a recently developed self-guided mol. dynamics (SGMD) method, which was shown to improve the conformational searching efficiency significantly as compared to conventional MD simulation method, reversible folding (folding, unfolding and refolding) of a 16-residue alanine-based synthetic peptide in explicit water at 274 K was successfully accomplished. Consistent with exptl. results, the helix was found to be the major secondary structural element in aq. soln., and among different helix forms, the α-helix is the dominant form. Conformational anal. of our simulation results showed that turns and 310-helixes play an essential role in the folding of α-helix. Interestingly, our results showed that the propagation of a helix segment is more frequent at the C-end than at the N-end. In most helix conformations, the backbone carbonyl groups of the peptide prefer to simultaneously form intramol. hydrogen bonds with the backbone amide groups of the peptide and intermol. hydrogen bonds with water mols., indicating water accessibility to the backbone carbonyl groups is crucial for helix formation in water. Therefore, the helical propensities of amino acids may be related to the water accessibility of their backbone groups in helical conformation. Water mols. also function as hydrogen bonding bridges linking helical residue pairs (i, i + n, with n = 3, 4, 5), suggesting a role of water bridges in helix folding.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXhtFynur4%253D&md5=b73d2957b2e487a5e39aa6a3d168c732
    71. 71
      Bisol, L. W.; Brunstein, M. G.; Ottoni, G. L.; Ramos, F. L. P.; Borba, D. L.; Daltio, C. S.; de Oliveira, R. V.; Paz, G. E. G.; de Souza, S. E.; Bressan, R. A.; Lara, D. R. Is Flunarizine a Long-Acting Oral Atypical Antipsychotic? A Randomized Clinical Trial versus Haloperidol for the Treatment of Schizophrenia. J. Clin. Psychiatry 2008, 69, 1572– 1579,  DOI: 10.4088/jcp.v69n1007
      71
      Is flunarizine a long-acting oral atypical antipsychotic? A randomized clinical trial versus haloperidol for the treatment of schizophrenia
      Bisol, Luisa W.; Brunstein, Miriam G.; Ottoni, Gustavo L.; Ramos, Fernanda L. P.; Borba, Daniela L.; Daltio, Claudiane S.; de Oliveira, Ricardo V.; Paz, Gisele E. G.; de Souza, Sayuri E.; Bressan, Rodrigo A.; Lara, Diogo R.
      Journal of Clinical Psychiatry (Memphis, TN, United States) (2008), 69 (10), 1572-1579CODEN: JCLPDE; ISSN:0160-6689. (Physicians Postgraduate Press, Inc.)
      Background: Flunarizine is known as a non-specific calcium channel blocker that has been used for decades for the treatment of migraine, vertigo, and cognitive deficits related to cerebro-vascular disorders. Flunarizine also has dopamine D2 receptor blocking properties and was effective in animal models of predictive validity for antipsychotics. However, its clin. antipsychotic efficacy has never been investigated. Objective: To evaluate the therapeutic efficacy and tolerability of flunarizine compared to haloperidol in outpatients with stable and chronic DSM-IV-defined schizophrenia and schizoaffective disorder. Method: Seventy patients from 2 centers were randomly assigned and participated in a double-blind, parallel-group, flexible-dose study comparing flunarizine (10-50 mg/day) and haloperidol (2.5-12.5 mg/day) for 12 wk. Patients were assessed with the Pos. and Neg. Syndrome Scale (PANSS), the Clin. Global Impressions-Improvement (CGI-I), scale, the Extrapyramidal Symptom Rating Scale (ESRS), a battery for cognitive performance, and lab. examns. The study was conducted from Sept. 2004 to May 2007. Results: Mean doses at endpoint were 29.7 mg/day for flunarizine and 6.4 mg/day for haloperidol. Both groups showed significant symptom improvement during the study, with a redn. of 21% in the flunarizine group and 19% in the haloperidol group in PANSS total scores (p < .05). There were no significant differences in PANSS overall score and all subscales, CGI-I score, or cognitive performance. Dropout rates, ESRS scores, and prolactin levels were not different between groups, but significantly more patients reported emergence of akathisia in the haloperidol group (p = .04), and wt. gain was significantly higher with flunarizine (1.2 kg) than with haloperidol (-0.8 kg) (p < .05). Conclusion: This is the first study evaluating the antipsychotic properties of flunarizine, which showed good efficacy and tolerability for the treatment of schizophrenia, with a possible atypical profile. Its unique pharmacokinetic profiles as an oral drug with long half-life (2-7 wk), low cost, and low induction of extrapyramidal symptoms warrants further investigation, particularly in psychiatric patients with low adherence to treatment.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtlClu7jI&md5=9df07aa8c8d61e93e0f173fda4071c33
    72. 72
      Ambrosio, C.; Stefanini, E. Interaction of Flunarizine with Dopamine D2 and D1 Receptors. Eur. J. Pharmacol. 1991, 197, 221– 223,  DOI: 10.1016/0014-2999(91)90526-v
      72
      Interaction of flunarizine with dopamine D2 and D1 receptors
      Ambrosio, Caterina; Stefanini, Ennio
      European Journal of Pharmacology (1991), 197 (2-3), 221-3CODEN: EJPHAZ; ISSN:0014-2999.
      Flunarizine dose dependently inhibits the binding of both [3H]spiperone and [3H]SCH 23390 with Ki values of 112 and 532 nM, resp. The inhibition of [3H]spiperone binding by flunarizine was competitive as revealed by the Schild plot. The results indicate that flunarizine is a fairly potent dopamine D2 receptor antagonist and offer a possible explanation for the extrapyramidal side-effects obsd. in patients treated with the drug.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK3MXks1ClsLk%253D&md5=c7f29f3592474b0d91738106a67c5470
    73. 73
      Wöber, C.; Brücke, T.; Wöber-Bingöl, C.; Asenbaum, S.; Wessely, P.; Podreka, I. Dopamine D2 Receptor Blockade and Antimigraine Action of Flunarizine. Cephalalgia 1994, 14, 235– 240,  DOI: 10.1046/j.1468-2982.1994.014003235.x
      73
      Dopamine D2 receptor blockade and antimigraine action of flunarizine
      Wober C; Brucke T; Wober-Bingol C; Asenbaum S; Wessely P; Podreka I
      Cephalalgia : an international journal of headache (1994), 14 (3), 235-40 ISSN:0333-1024.
      We studied in vivo the influence of flunarizine on dopamine D2 receptors and investigated whether dopamine D2 receptor blockade is involved in its antimigraine action. Eleven migraine patients, treated with flunarizine, 10 mg per day, underwent single photon emission computer tomography (SPECT) using [123I] labeled iodobenzamide, a ligand with high affinity and high specificity for D2 receptors. There was a reduction of the dopamine D2 receptor binding potential in all patients compared to age-matched controls. The efficacy of flunarizine in migraine prophylaxis failed to correlate with the degree of the dopamine D2 receptor blockade. The antimigraine action of flunarizine may not involve antidopaminergic mechanisms.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADyaK2M%252Fkt1KksA%253D%253D&md5=b47a181903189786358c99422fcd22aa
    74. 74
      Yan, Y.; Pan, J.; Chen, Y.; Xing, W.; Li, Q.; Wang, D.; Zhou, X.; Xie, J.; Miao, C.; Yuan, Y.; Zeng, W.; Chen, D. Increased Dopamine and Its Receptor Dopamine Receptor D1 Promote Tumor Growth in Human Hepatocellular Carcinoma. Cancer Commun. 2020, 694,  DOI: 10.1002/cac2.12103
      74
      Increased dopamine and its receptor dopamine receptor D1 promote tumor growth in human hepatocellular carcinoma
      Yan Yan; Pan Jiahao; Xing Wei; Li Qiang; Wang Dongyin; Zhou Xiaoshuang; Xie Jingdun; Zeng Weian; Chen Dongtai; Yan Yan; Chen Yonghua; Miao Changhong; Yuan Yunfei
      Cancer communications (London, England) (2020), 40 (12), 694-710 ISSN:.
      BACKGROUND: Dopamine and dopamine receptor D1 (DRD1), a member of the dopamine receptor family, have been indicated to play important roles in cancer progression, but dopamine secretion in hepatocellular carcinoma (HCC) and the effects of DRD1 on HCC remain unclear. This study was designed to explore the contribution of the dopaminergic system to HCC and determine the relationship between DRD1 and prognosis in HCC patients. METHODS: The dopamine metabolic system was monitored using enzyme-linked immunosorbent assays (ELISAs). The expression of DRD1 was detected by microarray analysis, immunohistochemistry (IHC), and quantitative real-time PCR (qRT-PCR). Stable DRD1 knockout and overexpression cell lines were established for investigation. Transwell, colony formation, and Cell Counting Kit 8 (CCK8) assays were performed to assess the malignant behaviors of cancer cells. The cAMP/PI3K/AKT/ cAMP response element-binding (CREB) signaling pathway was evaluated by Western blot. This pathway, which is agitated by DRD1 in striatal neurons, had been proven to participate in tumor progression. Xenograft HCC tumors were generated for in vivo experiments. RESULTS: Dopamine secretion increased locally in HCC due to an imbalance in dopamine metabolism, including the upregulation of dopa decarboxylase (DDC) and the downregulation of monoamine oxidase A (MAOA). Dopamine promoted the proliferation and metastasis of HCC. DRD1 was highly expressed in HCC tissues and positive DRD1 expression was related to a poor prognosis in HCC patients. The upregulation of DRD1 agitated malignant activities, including proliferation and metastasis in HCC by regulating the cAMP/PI3K/AKT/CREB pathway, and the downregulation of DRD1 had opposing effects. The effects of dopamine on HCC was reversed by depleting DRD1. SCH23390, a selective DRD1 antagonist, inhibited the proliferation and metastasis of HCC cells both in vitro and in vivo. CONCLUSION: Dopamine secretion was locally increased in HCC and promoted HCC cell proliferation and metastasis. DRD1 was found to exert positive effects on HCC progression and play a vital role in the dopamine system, and could be a potential therapeutic target and prognostic biomarker for HCC.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB3s%252FnsFyrtg%253D%253D&md5=ebb589ca4c6414c523621969d7c1b7c4
    75. 75
      Kafka, S. H.; Corbett, R. Selective Adenosine A2A Receptor/Dopamine D2 Receptor Interactions in Animal Models of Schizophrenia. Eur. J. Pharmacol. 1996, 295, 147– 154,  DOI: 10.1016/0014-2999(95)00668-0
      75
      Selective adenosine A2A receptor/dopamine D2 receptor interactions in animal models of schizophrenia
      Kafka, Sharon H.; Corbett, Roy
      European Journal of Pharmacology (1996), 295 (2/3), 147-54CODEN: EJPHAZ; ISSN:0014-2999. (Elsevier)
      In the apomorphine-induced climbing mouse assay, the potencies of the selective adenosine A1 receptor agonist, N6-cyclohexyladenosine (CHA), and the selective A2A adenosine receptor agonist, 2-p-(2-carboxyethyl) phenethylamino 5'-N-ethylcarboxamidoadenosine (CGS 21680), and various dopamine receptor antagonists were as follows: SCH 23390 = haloperidol > raclopride > CHA = CGS 21680. While in catalepsy, their potencies were SCH 23390 > haloperidol > raclopride > CGS 21680. CHA failed to induce catalepsy due to significant sedation/ataxia. The combined administration of the ED15 dose of CHA failed to potentiate the ED50 value of SCH 23390, raclopride, or haloperidol in the apomorphine-induced climbing mouse assay. However, the combined administration of the ED15 dose of CGS 21680 significantly decreased the ED50 of raclopride by 8.0-fold and haloperidol by 35-fold. The adenosine A2A receptor antagonist, 1,3,7-trimethyl-8-(3-chlorostyryl)xanthine (CSC), significantly decreased catalepsy induced by raclopride and haloperidol, while the adenosine A1 receptor antagonist, 1,3-dimethyl-8-phenylxanthine (8-PT), was ineffective. The present results show that in behavioral assays predictive for antipsychotic activity, adenosine receptor agonists block behaviors in a similar manner to dopamine receptor antagonists.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XjtVaruw%253D%253D&md5=4a9693816110c9f5625661786e74fd27
    76. 76
      Belforte, J. E.; Magariños-Azcone, C.; Armando, I.; Buño, W.; Pazo, J. H. Pharmacological Involvement of the Calcium Channel Blocker Flunarizine in Dopamine Transmission at the Striatum. Parkinsonism Relat. Disord. 2001, 8, 33– 40,  DOI: 10.1016/s1353-8020(01)00006-2
      76
      Pharmacological involvement of the calcium channel blocker flunarizine in dopamine transmission at the striatum
      Belforte J E; Magarinos-Azcone C; Armando I; Buno W; Pazo J H
      Parkinsonism & related disorders (2001), 8 (1), 33-40 ISSN:1353-8020.
      Single intrastriatal microinjections of 25, 50 and 100nmol/microl of flunarizine in normal rats produced a dose-dependent turning behavior toward the injected side when they were challenged with apomorphine (1mg/kg, s.c). This effect was seen at 1, 3 and 7 days following administration of the high dose of flunarizine, but had subsided by 24h after administration of the intermediate dose; the low dose was ineffective. However, intrastriatal injection of the high dose of flunarizine resulted in a local lesion and thereafter this dose was not used. A similar dose-response relationship was determined for nifedipine, an L-type calcium channel antagonist. Injection of this antagonist did not result in apomorphine-elicited rotational behavior, reflecting its lack of antidopaminergic action. Intrastriatal injections of haloperidol (5microg/microl), an antagonist of dopamine D(2) receptors, or the sodium channel blocker lidocaine (40microg/microl), were given in order to compare their effects to those observed with flunarizine. Intracerebral injection of haloperidol produced ipsilateral turning in response to systemic administration of apomorphine given 60min after. The same response was obtained with the injection of apomorphine 10min after the injection of intracerebral lidocaine. This effect was no longer apparent 24h after the microinjection of haloperidol and 60min after the injection of lidocaine. In rats rendered hemiparkinsionian by lesioning the nigrostriatal pathway with 6OHDA, intrastriatal microinjection of flunarizine (50nmol/microl) significantly reduced apomorphine (0.2mg/kg, s.c.)-elicited turning behavior towards the non-lesioned side. These results suggest an antidopaminergic effect of flunarizine mediated by antagonistic action of post-synaptic striatal dopamine receptors. However, an action of the drug on sodium channels may not be ruled out. These studies offer additional supporting evidence for the induction or aggravation of extrapyramidal side-effects in patients receiving flunarizine.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD38zgt1Khtg%253D%253D&md5=a6280d94b5b4e6e313debfbe5abf26d4
    77. 77
      Karsan, N.; Palethorpe, D.; Rattanawong, W.; Marin, J. C.; Bhola, R.; Goadsby, P. J. Flunarizine in Migraine-Related Headache Prevention: Results from 200 Patients Treated in the UK. Eur. J. Neurol. 2018, 25, 811– 817,  DOI: 10.1111/ene.13621
      77
      Flunarizine in migraine-related headache prevention: results from 200 patients treated in the UK
      Karsan N; Palethorpe D; Rattanawong W; Marin J C; Bhola R; Goadsby P J; Karsan N; Palethorpe D; Rattanawong W; Marin J C; Bhola R; Goadsby P J
      European journal of neurology (2018), 25 (6), 811-817 ISSN:.
      BACKGROUND AND PURPOSE: For over 20 years, as a group we have been using flunarizine in primary headache disorders. Flunarizine is widely used in Europe, but not licensed in the UK. In September 2014, the National Institute for Clinical Excellence published supportive guidelines for flunarizine use in migraine, based on randomized controlled evidence that it is as effective as propranolol and topiramate in adults. METHODS: We reviewed a cohort of adult patients (n = 200) treated with flunarizine from our practice. The clinical information of these patients, i.e. diagnosis, dose, efficacy, side effects and duration of treatment, was collected. RESULTS: The most common indication for flunarizine use was chronic migraine, followed by migraine with aura, sporadic hemiplegic migraine, familial hemiplegic migraine and new daily persistent headache with migrainous features. Flunarizine was generally effective, with only 24% (n = 47) of patients reporting no clinical effect. The most common dose used was 10 mg per day. Duration of treatment information was available for 39% (n = 78) of patients. Of these patients, 64% (n = 50) continued treatment for more than 1 year. Doses up to 15 mg were generally well tolerated, with only 10.5% (n = 21) of patients stopping treatment due to adverse effects. The most common adverse events were tiredness, mood change and weight gain. CONCLUSION: The data provide supportive evidence from tertiary headache practice in the UK for the use of flunarizine in migraine. The data encourages development of future guidance regarding flunarizine use in headache centres in countries where its use is not routine.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC1MrosFSkug%253D%253D&md5=dbd9bce6300fd702d4689846c737ca12
    78. 78
      Amery, W. K.; Caers, L. I.; Aerts, T. J. L. Flunarizine, a Calcium Entry Blocker in Migraine Prophylaxis. J. Headache Pain 1985, 25, 249– 254,  DOI: 10.1111/j.1526-4610.1985.hed2505249.x
      There is no corresponding record for this reference.
    79. 79
      Piccini, P.; Nuti, A.; Paoletti, A. M.; Napolitano, A.; Melis, G. B.; Bonuccelli, U. Possible Involvement of Dopaminergic Mechanisms in the Antimigraine Action of Flunarizine. Cephalalgia 1990, 10, 3– 8,  DOI: 10.1046/j.1468-2982.1990.1001003.x
      79
      Possible involvement of dopaminergic mechanisms in the antimigraine action of flunarizine
      Piccini P; Nuti A; Paoletti A M; Napolitano A; Melis G B; Bonuccelli U
      Cephalalgia : an international journal of headache (1990), 10 (1), 3-8 ISSN:0333-1024.
      Flunarizine, a calcium antagonist widely used in the prophylactic treatment of migraine, may interfere with dopaminergic systems. Flunarizine therapy can in fact induce extrapyramidal side effects and can increase basal as well as stimulated prolactin levels. To better define the mechanism of flunarizine action in migraine, we studied prolactin and growth hormone responses to thyrotropin releasing hormone and sulpiride in 13 female migraineurs before and after 60 days of flunarizine therapy. The treatment did not modify basal prolactin and growth hormone levels, but prolactin response to thyrotropin releasing hormone was enhanced. A paradoxical increase of growth hormone to thyrotropin releasing hormone observed before therapy was blunted after flunarizine treatment. These data indicate a modulatory action of flunarizine on dopaminergic systems which might to some extent explain the antimigraine action of this drug.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADyaK3c7pvFyntg%253D%253D&md5=feb337ba996ec12e6fc463edbb5789a3
    80. 80
      Frisch, M. J. Gaussian 09, Revision B.01, Gaussian, Inc. 2009.
      There is no corresponding record for this reference.
    81. 81
      O’Boyle, N. M.; Banck, M.; James, C. A.; Morley, C.; Vandermeersch, T.; Hutchison, G. R. Open Babel: An Open Chemical Toolbox. J. Cheminf. 2011, 3, 33,  DOI: 10.1186/1758-2946-3-33
      81
      Open Babel: an open chemical toolbox
      O'Boyle, Noel M.; Banck, Michael; James, Craig A.; Morley, Chris; Vandermeersch, Tim; Hutchison, Geoffrey R.
      Journal of Cheminformatics (2011), 3 (), 33CODEN: JCOHB3; ISSN:1758-2946. (Chemistry Central Ltd.)
      Background: A frequent problem in computational modeling is the interconversion of chem. structures between different formats. While std. interchange formats exist (for example, Chem. Markup Language) and de facto stds. have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chem. data, differences in the data stored by different formats (0D vs. 3D, for example), and competition between software along with a lack of vendor-neutral formats. Results: We discuss, for the first time, Open Babel, an open-source chem. toolbox that speaks the many languages of chem. data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chem. and mol. data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Conclusions: Open Babel presents a soln. to the proliferation of multiple chem. file formats. In addn., it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chem. data in areas such as org. chem., drug design, materials science, and computational chem. It is freely available under an open-source license.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVWjurbF&md5=74e4f19b7f87417f916d57f7abcfb761
    82. 82
      Jaiteh, M.; Rodríguez-Espigares, I.; Selent, J.; Carlsson, J. Performance of Virtual Screening against GPCR Homology Models: Impact of Template Selection and Treatment of Binding Site Plasticity. PLoS Comput. Biol. 2020, 16, e1007680– e1007680,  DOI: 10.1371/journal.pcbi.1007680
      82
      Performance of virtual screening against GPCR homology models: impact of template selection and treatment of binding site plasticity
      Jaiteh, Mariama; Rodriguez-Espigares, Ismael; Selent, Jana; Carlsson, Jens
      PLoS Computational Biology (2020), 16 (3), e1007680/1-e1007680/25CODEN: PCBLBG; ISSN:1553-7358. (Public Library of Science)
      Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small no. of available at. resoln. structures. We assessed the use of homol. modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Comparison of the homol. models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. Mol. docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Mol. dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homol. models. These results provide guide-lines for successful application of structure-based ligand discovery using GPCR homol. models.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXps1Wrtrk%253D&md5=a39e9cd1e6a711f8f8765ce7fd347f36
    83. 83
      Morris, G. M.; Lim-Wilby, M. Molecular Docking. Methods Mol. Biol. 2008, 443, 365– 382,  DOI: 10.1007/978-1-59745-177-2_19
      83
      Molecular docking
      Morris, Garrett M.; Lim-Wilby, Marguerita
      Methods in Molecular Biology (Totowa, NJ, United States) (2008), 443 (Molecular Modeling of Proteins), 365-382CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)
      A review. Mol. docking is a key tool in structural mol. biol. and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compds., rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of mol. docking software, and covers the usage of some of the most-cited docking software.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXktFCis74%253D&md5=3125f282b5fc4d65f9828445a5eb46bb
    84. 84
      Pettersen, E. F.; Goddard, T. D.; Huang, C. C.; Couch, G. S.; Greenblatt, D. M.; Meng, E. C.; Ferrin, T. E. UCSF Chimera--a Visualization System for Exploratory Research and Analysis. J. Comput. Chem. 2004, 25, 1605– 1612,  DOI: 10.1002/jcc.20084
      84
      UCSF Chimera-A visualization system for exploratory research and analysis
      Pettersen, Eric F.; Goddard, Thomas D.; Huang, Conrad C.; Couch, Gregory S.; Greenblatt, Daniel M.; Meng, Elaine C.; Ferrin, Thomas E.
      Journal of Computational Chemistry (2004), 25 (13), 1605-1612CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale mol. assemblies such as viral coats, and Collab., which allows researchers to share a Chimera session interactively despite being at sep. locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and assocd. structures; ViewDock, for screening docked ligand orientations; Movie, for replaying mol. dynamics trajectories; and Vol. Viewer, for display and anal. of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2cXmvVOhsbs%253D&md5=944b175f440c1ff323705987cf937ee7
    85. 85
      Guner, O.; Clement, O.; Kurogi, Y. Pharmacophore Modeling and Three Dimensional Database Searching for Drug Design Using Catalyst: Recent Advances. Curr. Med. Chem. 2004, 11, 2991– 3005,  DOI: 10.2174/0929867043364036
      85
      Pharmacophore modeling and three dimensional database searching for drug design using catalyst: recent advances
      Guner Osman; Clement Omoshile; Kurogi Yasuhisa
      Current medicinal chemistry (2004), 11 (22), 2991-3005 ISSN:0929-8673.
      Perceiving a pharmacophore is the first essential step towards understanding the interaction between a receptor and a ligand. Once a pharmacophore is established, a beneficial use of it is 3D database searching to retrieve novel compounds that would match the pharmacophore. As the 3D searching technology has evolved over the years, it has been effectively used for lead optimization, combinatorial library focusing, as well as virtual high-throughput screening. This paper is an update to the original paper published in this journal earlier: Kurogi, Y, and Guner, O. F. "Pharmacophore Modeling and Three-Dimensional Database Searching for Drug Design Using Catalyst," in Current Medicinal Chemistry, 2001, 8(9), 1035-1055.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BD2crnt1eiuw%253D%253D&md5=2a9b7d5a86415bad0959dcd9e737f934
    86. 86
      Cheng, F.; Li, W.; Zhou, Y.; Shen, J.; Wu, Z.; Liu, G.; Lee, P. W.; Tang, Y. AdmetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties. J. Chem. Inf. Model. 2012, 52, 3099– 3105,  DOI: 10.1021/ci300367a
      86
      admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties
      Cheng, Feixiong; Li, Weihua; Zhou, Yadi; Shen, Jie; Wu, Zengrui; Liu, Guixia; Lee, Philip W.; Tang, Yun
      Journal of Chemical Information and Modeling (2012), 52 (11), 3099-3105CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      A review. Absorption, distribution, metab., excretion, and toxicity (ADMET) properties play key roles in the discovery/development of drugs, pesticides, food additives, consumer products, and industrial chems. This information is esp. useful when to conduct environmental and human hazard assessment. The most crit. rate limiting step in the chem. safety assessment workflow is the availability of high quality data. This paper describes an ADMET structure-activity relationship database, abbreviated as admetSAR. It is an open source, text and structure searchable, and continually updated database that collects, curates, and manages available ADMET-assocd. properties data from the published literature. In admetSAR, over 210 000 ADMET annotated data points for more than 96,000 unique compds. with 45 kinds of ADMET-assocd. properties, proteins, species, or organisms have been carefully curated from a large no. of diverse literatures. The database provides a user-friendly interface to query a specific chem. profile, using either CAS registry no., common name, or structure similarity. In addn., the database includes 22 qual. classification and 5 quant. regression models with highly predictive accuracy, allowing to est. ecol./mammalian ADMET properties for novel chems. AdmetSAR is accessible free of charge at http://www.admetexp.org.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFGmtbnJ&md5=93b02a243f5b50a8d457880ef867007b
    87. 87
      Anbu, V.; Karthick, T.; Vijayalakshmi, K. A. Combined Experimental and Computational Approach for the Vibrational Characteristics and Theoretical Evaluation of Binding Activities and ADME Descriptors of 2,6-Di-Tert-Butyl-p-Cresol. Polycyclic Aromat. Compd. 2020, 1– 17,  DOI: 10.1080/10406638.2020.1768567
      There is no corresponding record for this reference.
    88. 88
      Newby, D.; Freitas, A. A.; Ghafourian, T. Decision Trees to Characterise the Roles of Permeability and Solubility on the Prediction of Oral Absorption. Eur. J. Med. Chem. 2015, 90, 751– 765,  DOI: 10.1016/j.ejmech.2014.12.006
      88
      Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption
      Newby, Danielle; Freitas, Alex A.; Ghafourian, Taravat
      European Journal of Medicinal Chemistry (2015), 90 (), 751-765CODEN: EJMCA5; ISSN:0223-5234. (Elsevier Masson SAS)
      Oral absorption of compds. depends on many physiol., physiochem. and formulation factors. Two important properties that govern oral absorption are in vitro permeability and soly., which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aq. soly., m.p., and max. dose for the same compds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a soly.-related parameter such as exptl. or predicted soly., or the m.p. based absorption potential (MPbAP), along with structural mol. descriptors were developed and validated to predict oral absorption class. The decision trees were able to det. the individual roles of permeability and soly. in oral absorption process. Poorly permeable compds. with high soly. show low intestinal absorption, whereas poorly water sol. compds. with high or low permeability may have high intestinal absorption provided that they have certain mol. characteristics such as a small polar surface or specific topol.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVyksrvM&md5=b7904ecbe359d31b61e298b23afb4cf9
    89. 89
      Ursu, O.; Rayan, A.; Goldblum, A.; Oprea, T. I. Understanding Drug-Likeness. WIREs Comput. Mol. Sci. 2011, 1, 760– 781,  DOI: 10.1002/wcms.52
      89
      Understanding drug-likeness
      Ursu, Oleg; Rayan, Anwar; Goldblum, Amiram; Oprea, Tudor I.
      Wiley Interdisciplinary Reviews: Computational Molecular Science (2011), 1 (5), 760-781CODEN: WIRCAH; ISSN:1759-0884. (Wiley-Blackwell)
      A review. "Drug-likeness", a qual. property of chems. assigned by experts committee vote, is wedely integrated into the early stages of lead and drug discovery. Its conceptual evolution paralleled work related to Pfizer's "rule of five" and lead-likeness, and is placed within this framework. The discrimination between "drugs" (represented by a collection of pharmaceutically relevant small mols., some of which are marketed drugs) and "nondrugs" (typically, chem. reagents) is possible using a wide variety of statistical tools and chem. descriptor systems. Here we summarize 18 papers focused on drug-likeness, and provide a comprehensive overview of progress in the field. Tools that est. drug-likeness are valuable in the early stages of lead discovery, and can be used to filter out compds. with undersirable properties from screening libraries and to prioritize hits from primary screens. As the goal is, most often, to develop orally available drugs, it is also useful to optimize drug-like pharmacokinetic properties. We examine tools that evaluate drug-likeness and some of their shortcomings, challenges facing these tools, and address the following issues: What is the definition of drug-likeness and how can it be utilized to reduce attrition rate in drug discovery. How difficult is it to distinguish drugs from nondrugs. Are nondrug datasets reliable. Can we est. oral drug-likeness. We discuss a drug-like filter and recent advances in the prediction of oral drug-likeness. The heuristic aspect of drug-likeness is also addressed.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFWrtrbO&md5=3cd46a7a7a082d6d3730e6bbf16712d2
    90. 90
      Rankovic, Z. CNS Drug Design: Balancing Physicochemical Properties for Optimal Brain Exposure. J. Med. Chem. 2015, 58, 2584– 2608,  DOI: 10.1021/jm501535r
      90
      CNS Drug Design: Balancing Physicochemical Properties for Optimal Brain Exposure
      Rankovic, Zoran
      Journal of Medicinal Chemistry (2015), 58 (6), 2584-2608CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      A review. The human brain is a uniquely complex organ, which has evolved a sophisticated protection system to prevent injury from external insults and toxins. Designing mols. that can overcome this protection system and achieve optimal concn. at the desired therapeutic target in the brain is a specific and major challenge for medicinal chemists working in CNS drug discovery. Analogous to the now widely accepted rule of 5 in the design of oral drugs, the physicochem. properties required for optimal brain exposure have been extensively studied in an attempt to similarly define the attributes of successful CNS drugs and drug candidates. This body of work is systematically reviewed here, with a particular emphasis on the interplay between the most crit. physicochem. and pharmacokinetic parameters of CNS drugs as well as their impact on medicinal chem. strategies toward mols. with optimal brain exposure. A summary of modern CNS pharmacokinetic concepts and methods is also provided.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXitVyhsrrP&md5=f01e3f2dc4e2eff7b0618124277a5cf8
    91. 91
      Ghose, A. K.; Herbertz, T.; Hudkins, R. L.; Dorsey, B. D.; Mallamo, J. P. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery. ACS Chem. Neurosci. 2012, 3, 50– 68,  DOI: 10.1021/cn200100h
      91
      Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery
      Ghose, Arup K.; Herbertz, Torsten; Hudkins, Robert L.; Dorsey, Bruce D.; Mallamo, John P.
      ACS Chemical Neuroscience (2012), 3 (1), 50-68CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
      The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochem. and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compds., we analyzed the physicochem. property and the chem. structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined anal. provided the following guidelines for designing high-quality CNS drugs: (i) topol. mol. polar surface area of <76 Å2 (25-60 Å2), (ii) at least one (one or two, including one aliph. amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) vol. of 740-970 Å3, (vi) solvent accessible surface area of 460-580 Å2, and (vii) pos. QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The chemoinformatics approaches for graphically analyzing multiple properties efficiently are presented.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhsVSit7rO&md5=4c20ba34c3d5397170b50242975ce25d
    92. 92
      Zafar, F.; Gupta, A.; Thangavel, K.; Khatana, K.; Sani, A. A.; Ghosal, A.; Tandon, P.; Nishat, N. Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives. ACS Omega 2020, 5, 6021– 6030,  DOI: 10.1021/acsomega.9b04398
      92
      Physicochemical and Pharmacokinetic Analysis of Anacardic Acid Derivatives
      Zafar, Fahmina; Gupta, Anjali; Thangavel, Karthick; Khatana, Kavita; Sani, Ali Alhaji; Ghosal, Anujit; Tandon, Poonam; Nishat, Nahid
      ACS Omega (2020), 5 (11), 6021-6030CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
      Anacardic acid (AA) and its derivs. are well-known for their therapeutic applications ranging from antitumor, antibacterial, antioxidant, anticancer, and so forth. However, their poor pharmacokinetic and safety properties create significant hurdles in the formulation of the final drug mol. As a part of our endeavor to enhance the potential and exploration of the anticancer activities, a detailed study on the properties of selected AA derivs. was performed in this work. A comprehensive anal. of the drug-like properties of 100 naturally occurring AA derivs. was performed, and the results were compared with certain marketed anticancer drugs. The work focused on the understanding of the interplay among eight physicochem. properties. The relationships between the physicochem. properties, absorption, distribution, metab., and excretion attributes, and the in silico toxicity profile for the set of AA derivs. were established. The ligand efficacy of the finally scrutinized 17 AA derivs. on the basis of pharmacokinetic properties and toxicity parameters was further subjected to dock against the potential anticancer target cyclin-dependent kinase 2 (PDB ID: 1W98). In the docked complex, the ligand mols. (AA derivs.) selectively bind with the target residues, and a high binding affinity of the ligand mols. was ensured by the full fitness score using the SwissDock Web server. The BOILED-Egg model shows that out of 17 scrutinized mols., 3 mols. exhibit gastrointestinal absorption capability and 14 mols. exhibit permeability through the blood-brain barrier penetration. The anal. can also provide some useful insights to chemists to modify the existing natural scaffolds in designing new anacardic anticancer drugs. The increased probability of success may lead to the identification of drug-like candidates with favorable safety profiles after further clin. evaluation.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXkslemsr0%253D&md5=9f1d51d83ba9c30498a508229afafaa4
    93. 93
      Singh, N.; Kumar, N.; Rathee, G.; Sood, D.; Singh, A.; Tomar, V.; Dass, S. K.; Chandra, R. Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches. ACS Omega 2020, 5, 2267– 2279,  DOI: 10.1021/acsomega.9b03479
      93
      Privileged Scaffold Chalcone: Synthesis, Characterization and Its Mechanistic Interaction Studies with BSA Employing Spectroscopic and Chemoinformatics Approaches
      Singh, Nidhi; Kumar, Neeraj; Rathee, Garima; Sood, Damini; Singh, Aarushi; Tomar, Vartika; Dass, Sujata K.; Chandra, Ramesh
      ACS Omega (2020), 5 (5), 2267-2279CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
      Chalcone, a privileged structure, is considered as an effective template in the field of medicinal chem. for potent drug discovery. In the present study, a privileged template chalcone was designed, synthesized, and characterized by various spectroscopic techniques (NMR, high-resoln. mass spectrometry, Fourier transform IR (FT-IR) spectroscopy, UV spectroscopy, and single-crystal X-ray diffraction). The mechanism of binding of chalcone with bovine serum albumin (BSA) was detd. by multispectroscopic techniques and computational methods. Steady-state fluorescence spectroscopy suggests that the intrinsic fluorescence of BSA was quenched upon the addn. of chalcone by the combined dynamic and static quenching mechanism. Time-resolved spectroscopy confirms complex formation. FT-IR and CD spectroscopy suggested the presence of chalcone in the BSA mol. microenvironment and also the possibility of rearrangement of the native structure of BSA. Moreover, mol. docking studies confirm the moderate binding of chalcone with BSA and the mol. dynamics simulation anal. shows the stability of the BSA-drug complex system with minimal deformability fluctuations and potential interaction by the covariance matrix. Moreover, pharmacodynamics and pharmacol. anal. show good results through Lipinski rules, with no toxicity profile and high gastrointestinal absorptions by boiled egg permeation assays. This study elucidates the mechanistic profile of the privileged chalcone scaffold to be used in therapeutic applications.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhs1Smtbs%253D&md5=7b683aaf8be2e0760e619929e1a2b845
    94. 94
      Al-Blewi, F.; Rezki, N.; Naqvi, A.; Qutb Uddin, H.; Al-Sodies, S.; Messali, M.; Aouad, M. R.; Bardaweel, S. A Profile of the In Vitro Anti-Tumor Activity and In Silico ADME Predictions of Novel Benzothiazole Amide-Functionalized Imidazolium Ionic Liquids. Int. J. Mol. Sci. 2019, 20, 2865,  DOI: 10.3390/ijms20122865
      94
      A profile of the in vitro anti-tumor activity and in silico ADME predictions of novel benzothiazole amide-functionalized imidazolium ionic liquids
      Al-Blewi, Fawzia; Rezki, Nadjet; Naqvi, Arshi; Uddin, Husna Qutb; Al-Sodies, Salsabeel; Messali, Mouslim; Aouad, Mohamed Reda; Bardaweel, Sanaa
      International Journal of Molecular Sciences (2019), 20 (12), 2865CODEN: IJMCFK; ISSN:1422-0067. (MDPI AG)
      A focused array of green imidazolium ionic liqs. (ILs) encompassing benzothiazole ring and amide linkage were designed and synthesized using quaternization and metathesis protocols. The synthesized ILs have been fully characterized by usual spectroscopic methods and screened for their anticancer activities against human cancer cell lines originating from breast and colon cancers. Collectively, our biol. data demonstrate that the newly synthesized series has variable anticancer activities in the examd. cancer types. The synthesized ILs 8, 10 and 21-29 comprising the Me and Me sulfonyl benzothiazole ring emerged as the most potent compds. with promising antiproliferative activities relative to their benzothiazole ring counterparts. Furthermore, the mechanism underlying the obsd. anticancer activity was investigated. The most active compd. 22 appears to exert its anticancer effect through apoptosis dependent pathway in breast cancer cells. Interestingly, compd. 22 has also shown good in silico absorption (81.75%) along with high gastro-intestinal absorption as per ADME predictions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFGrs7c%253D&md5=4ea3bb4d9142d32a6248248dd27dc96c
    95. 95
      Ahmad, S. S.; Sinha, M.; Ahmad, K.; Khalid, M.; Choi, I. Study of Caspase 8 Inhibition for the Management of Alzheimer’s Disease: A Molecular Docking and Dynamics Simulation. Molecules 2020, 25, 2071,  DOI: 10.3390/molecules25092071
      95
      Study of caspase 8 inhibition for the management of Alzheimer's disease: A Molecular Docking and Dynamics Simulation
      Ahmad, Syed Sayeed; Sinha, Meetali; Ahmad, Khurshid; Khalid, Mohammad; Choi, Inho
      Molecules (2020), 25 (9), 2071CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
      Alzheimer's disease (AD) is the most common type of dementia and usually manifests as diminished episodic memory and cognitive functions. Caspases are crucial mediators of neuronal death in a no. of neurodegenerative diseases, and caspase 8 is considered a major therapeutic target in the context of AD. In the present study, we performed a virtual screening of 200 natural compds. by mol. docking with respect to their abilities to bind with caspase 8. Among them, rutaecarpine was found to have the highest (neg.) binding energy (-6.5 kcal/mol) and was further subjected to mol. dynamics (MD) simulation anal. Caspase 8 was detd. to interact with rutaecarpine through five amino acid residues, specifically Thr337, Lys353, Val354, Phe355, and Phe356, and two hydrogen bonds (ligand: H35-A: LYS353:O and A:PHE355: N-ligand: N5). Furthermore, a 50 ns MD simulation was conducted to optimize the interaction, to predict complex flexibility, and to investigate the stability of the caspase 8-rutaecarpine complex, which appeared to be quite stable. The obtained results propose that rutaecarpine could be a lead compd. that bears remarkable anti-Alzheimer's potential against caspase 8.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhtFWgurfN&md5=42c8668c9347e7077ec9ac18edb4b0b8
    96. 96
      Loureiro, D. R. P.; Soares, J. X.; Costa, J. C.; Magalhães, Á. F.; Azevedo, C. M. G.; Pinto, M. M. M.; Afonso, C. M. M. Structures, Activities and Drug-Likeness of Anti-Infective Xanthone Derivatives Isolated from the Marine Environment: A Review. Molecules 2019, 24, 243,  DOI: 10.3390/molecules24020243
      96
      Structures, activities and drug-likeness of anti-infective xanthone derivatives isolated from the marine environment: a review
      Loureiro, Daniela R. P.; Soares, Jose X.; Costa, Joana C.; Magalhaes, Alvaro F.; Azevedo, Carlos M. G.; Pinto, Madalena M. M.; Afonso, Carlos M. M.
      Molecules (2019), 24 (2), 243/1-243/23CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)
      Marine organisms represent almost half of total biodiversity and are a very important source of new bioactive substances. Within the varied biol. activities found in marine products, their antimicrobial activity is one of the most relevant. Infectious diseases are responsible for high levels of morbidity and mortality and many antimicrobials lose their effectiveness with time due to the development of resistance. These facts justify the high importance of finding new, effective and safe anti-infective agents. Among the variety of biol. activities of marine xanthone derivs., one that must be highlighted is their anti-infective properties. In this work, a literature review of marine xanthones with anti-infective activity, namely antibacterial, antifungal, antiparasitic and antiviral, is presented. Their structures, biol. activity, sources and the methods used for bioactivity evaluation are described. The xanthone derivs. are grouped in three sets: xanthones, hydroxanthones and glycosylated derivs. Moreover, mol. descriptors, biophysico-chem. properties, and pharmacokinetic parameters were calcd., and the chem. space occupied by marine xanthone derivs. is recognized. The chem. space was compared with marketed drugs and framed accordingly to the drug-likeness concept in order to profile the pharmacokinetic of anti-infective marine xanthone derivs.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXnvVWksro%253D&md5=5af03f519089965e4f182ae4656dda3b
    97. 97
      Kehinde, I.; Ramharack, P.; Nlooto, M.; Gordon, M. The Pharmacokinetic Properties of HIV-1 Protease Inhibitors: A Computational Perspective on Herbal Phytochemicals. Heliyon 2019, 5, e02565– e02565,  DOI: 10.1016/j.heliyon.2019.e02565
      There is no corresponding record for this reference.
    98. 98
      Garg, P.; Verma, J.; Roy, N. In Silico Modeling for Blood—Brain Barrier Permeability Predictions. Drug Absorpt. Stud. 2008, 510– 556,  DOI: 10.1007/978-0-387-74901-3_22
      There is no corresponding record for this reference.
    99. 99
      Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R. GROMACS: A Message-Passing Parallel Molecular Dynamics Implementation. Comput. Phys. Commun. 1995, 91, 43– 56,  DOI: 10.1016/0010-4655(95)00042-E
      99
      GROMACS: A message-passing parallel molecular dynamics implementation
      Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R.
      Computer Physics Communications (1995), 91 (1-3), 43-56CODEN: CPHCBZ; ISSN:0010-4655. (Elsevier)
      A parallel message-passing implementation of a mol. dynamics (MD) program that is useful for bio(macro)mols. in aq. environment is described. The software has been developed for a custom-designed 32-processor ring GROMACS (Groningen MAchine for Chem. Simulation) with communication to and from left and right neighbors, but can run on any parallel system onto which a a ring of processors can be mapped and which supports PVM-like block send and receive calls. The GROMACS software consists of a preprocessor, a parallel MD and energy minimization program that can use an arbitrary no. of processors (including one), an optional monitor, and several anal. tools. The programs are written in ANSI C and available by ftp (information: [email protected]). The functionality is based on the GROMOS (Groningen Mol. Simulation) package (van Gunsteren and Berendsen, 1987; BIOMOS B.V., Nijenborgh 4, 9747 AG Groningen). Conversion programs between GROMOS and GROMACS formats are included.The MD program can handle rectangular periodic boundary conditions with temp. and pressure scaling. The interactions that can be handled without modification are variable non-bonded pair interactions with Coulomb and Lennard-Jones or Buckingham potentials, using a twin-range cut-off based on charge groups, and fixed bonded interactions of either harmonic or constraint type for bonds and bond angles and either periodic or cosine power series interactions for dihedral angles. Special forces can be added to groups of particles (for non-equil. dynamics or for position restraining) or between particles (for distance restraints). The parallelism is based on particle decompn. Interprocessor communication is largely limited to position and force distribution over the ring once per time step.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXps1Wrtr0%253D&md5=04d823aeab28ca374efb86839c705179
    100. 100
      Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E. GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 435– 447,  DOI: 10.1021/ct700301q
      100
      GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
      Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik
      Journal of Chemical Theory and Computation (2008), 4 (3), 435-447CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      Mol. simulation is an extremely useful, but computationally very expensive tool for studies of chem. and biomol. systems. Here, we present a new implementation of our mol. simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decompn. algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addn. used a Multiple-Program, Multiple-Data approach, with sep. node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest nos. of std. cluster nodes.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhsVSqurc%253D&md5=d53c94901386260221792ea30f151c5f
    101. 101
      van der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. GROMACS: Fast, Flexible, and Free. J. Comput. Chem. 2005, 26, 1701– 1718,  DOI: 10.1002/jcc.20291
      101
      GROMACS: Fast, flexible, and free
      Van 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.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1SlsbbO&md5=4aa71b1dc0b5b4978a88b0568245a265
    102. 102
      Michino, M.; Boateng, C. A.; Donthamsetti, P.; Yano, H.; Bakare, O. M.; Bonifazi, A.; Ellenberger, M. P.; Keck, T. M.; Kumar, V.; Zhu, C.; Verma, R.; Deschamps, J. R.; Javitch, J. A.; Newman, A. H.; Shi, L. Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor. J. Med. Chem. 2017, 60, 580– 593,  DOI: 10.1021/acs.jmedchem.6b01148
      102
      Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor
      Michino, Mayako; Boateng, Comfort A.; Donthamsetti, Prashant; Yano, Hideaki; Bakare, Oluyomi M.; Bonifazi, Alessandro; Ellenberger, Michael P.; Keck, Thomas M.; Kumar, Vivek; Zhu, Clare; Verma, Ravi; Deschamps, Jeffrey R.; Javitch, Jonathan A.; Newman, Amy Hauck; Shi, Lei
      Journal of Medicinal Chemistry (2017), 60 (2), 580-593CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
      Both dopamine D3 receptor (D3R) partial agonists and antagonists have been implicated as potential medications for substance use disorders. In contrast to antagonists, partial agonists may cause fewer side effects since they maintain some dopaminergic tone and may be less disruptive to normal neuronal functions. Here, the authors report three sets of 4-phenylpiperazine stereoisomers that differ considerably in efficacy: the (R)-enantiomers are antagonists/weak partial agonists, whereas the (S)-enantiomers are much more efficacious. To investigate the structural basis of partial agonism, the authors performed comparative microsecond-scale mol. dynamics simulations starting from the inactive state of D3R in complex with these enantiomers. Anal. of the simulation results reveals common structural rearrangements near the ligand binding site induced by the bound (S)-enantiomers, but not by the (R)-enantiomers, that are features of partially activated receptor conformations. These receptor models bound with partial agonists may be useful for structure-based design of compds. with tailored efficacy profiles.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XitFSgu7nK&md5=91e378048c5dfd4c44fb54746a2e1df2
    103. 103
      Wassenaar, T. A.; Mark, A. E. The Effect of Box Shape on the Dynamic Properties of Proteins Simulated under Periodic Boundary Conditions. J. Comput. Chem. 2006, 27, 316– 325,  DOI: 10.1002/jcc.20341
      103
      The effect of box shape on the dynamic properties of proteins simulated under periodic boundary conditions
      Wassenaar, Tsjerk A.; Mark, Alan E.
      Journal of Computational Chemistry (2006), 27 (3), 316-325CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      The effect of the box shape on the dynamic behavior of proteins simulated under periodic boundary conditions is evaluated. In particular, the influence of simulation boxes defined by the near-densest lattice packing (NDLP) in conjunction with rotational constraints is compared to that of std. box types without these constraints. Three different proteins of varying size, shape, and secondary structure content were examd. in the study. The statistical significance of differences in RMSD, radius of gyration, solvent-accessible surface, no. of hydrogen bonds, and secondary structure content between proteins, box types, and the application or not of rotational constraints has been assessed. Furthermore, the differences in the collective modes for each protein between different boxes and the application or not of rotational constraints have been examd. In total 105 simulations were performed, and the results compared using a three-way multivariate anal. of variance (MANOVA) for properties derived from the trajectories and a three-way univariate anal. of variance (ANOVA) for collective modes. It is shown that application of roto-translational constraints does not have a statistically significant effect on the results obtained from the different simulations. However, the choice of simulation box was found to have a small (5-10%), but statistically significant effect on the behavior of two of the three proteins included in the study.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xht12qtL8%253D&md5=88830b82651ff8ea52559687a503a00c
    104. 104
      Ali, J.; Camilleri, P.; Brown, M. B.; Hutt, A. J.; Kirton, S. B. In Silico Prediction of Aqueous Solubility Using Simple QSPR Models: The Importance of Phenol and Phenol-like Moieties. J. Chem. Inf. Model. 2012, 52, 2950– 2957,  DOI: 10.1021/ci300447c
      104
      In Silico Prediction of Aqueous Solubility Using Simple QSPR Models: The Importance of Phenol and Phenol-like Moieties
      Ali, Jogoth; Camilleri, Patrick; Brown, Marc B.; Hutt, Andrew J.; Kirton, Stewart B.
      Journal of Chemical Information and Modeling (2012), 52 (11), 2950-2957CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Recently the authors published a robust QSPR model of aq. soly. which exploited the computationally derived mol. descriptor topog. polar surface area (TPSA) alongside exptl. detd. m.p. and logP. This model (the "TPSA model") is able to accurately predict to within ± one log unit the aq. soly. of 87% of the compds. in a chem. diverse data set of 1265 mols. This is comparable to results achieved for established models of aq. soly. e.g. ESOL (79%) and the General Soly. Equation (81%). Hierarchical clustering of this data set according to chem. similarity shows that a significant no. of mols. with phenolic and/or phenol-like moieties are poorly predicted by these equations. Modification of the TPSA model to addnl. incorporate a descriptor pertaining to a simple count of phenol and phenol-like moieties improves the predictive ability within ± one log unit to 89% for the full data set (1265 compds. -8.48 < logS < 1.58) and 82% for a reduced data set (1160 compds. 6.00 < logS < 0.00) which excludes compds. at the sparsely populated extremities of the data range. This improvement can be rationalized as the addnl. descriptor in the model acting as a correction factor which acknowledges the effect of phenolic substituents on the electronic characteristics of arom. mols. i.e. the generally pos. contribution to aq. soly. made by phenolic moieties.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38XhsFOlsbjE&md5=b16631526dbac405a0840b6e57667cc8
    105. 105
      Okuda, S.; Yamada, T.; Hamajima, M.; Itoh, M.; Katayama, T.; Bork, P.; Goto, S.; Kanehisa, M. KEGG Atlas Mapping for Global Analysis of Metabolic Pathways. Nucleic Acids Res. 2008, 36, W423– W426,  DOI: 10.1093/nar/gkn282
      105
      KEGG Atlas mapping for global analysis of metabolic pathways
      Okuda, Shujiro; Yamada, Takuji; Hamajima, Masami; Itoh, Masumi; Katayama, Toshiaki; Bork, Peer; Goto, Susumu; Kanehisa, Minoru
      Nucleic Acids Research (2008), 36 (Web Server), W423-W426CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      KEGG Atlas is a new graphical interface to the KEGG suite of databases, esp. to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an assocd. viewer for metab., covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technol. The mapping of high-throughput exptl. data onto the global map is the main use of KEGG Atlas. In the global metab. map, the node (circle) is a chem. compd. and the edge (line) is a set of reactions linked to a set of KEGG Orthol. (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K no. identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chem. compds. are converted to the C no. identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXptlKku7Y%253D&md5=4f2397c5ebc8c0cddb5a922e339bfea4
    106. 106
      Kanehisa, M.; Goto, S.; Sato, Y.; Furumichi, M.; Tanabe, M. KEGG for Integration and Interpretation of Large-Scale Molecular Data Sets. Nucleic Acids Res. 2012, 40, D109– D114,  DOI: 10.1093/nar/gkr988
      106
      KEGG for integration and interpretation of large-scale molecular data sets
      Kanehisa, Minoru; Goto, Susumu; Sato, Yoko; Furumichi, Miho; Tanabe, Mao
      Nucleic Acids Research (2012), 40 (D1), D109-D114CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/ or http://www.kegg.jp/) is a database resource that integrates genomic, chem. and systemic functional information. In particular, gene catalogs from completely sequenced genomes are linked to higher-level systemic functions of the cell, the organism and the ecosystem. Major efforts have been undertaken to manually create a knowledge base for such systemic functions by capturing and organizing exptl. knowledge in computable forms; namely, in the forms of KEGG pathway maps, BRITE functional hierarchies and KEGG modules. Continuous efforts have also been made to develop and improve the cross-species annotation procedure for linking genomes to the mol. networks through the KEGG Orthol. system. Here we report KEGG Mapper, a collection of tools for KEGG PATHWAY, BRITE and MODULE mapping, enabling integration and interpretation of large-scale data sets. We also report a variant of the KEGG mapping procedure to extend the knowledge base, where different types of data and knowledge, such as disease genes and drug targets, are integrated as part of the KEGG mol. networks. Finally, we describe recent enhancements to the KEGG content, esp. the incorporation of disease and drug information used in practice and in society, to support translational bioinformatics.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhs12htbrO&md5=d234c2f8945fbec1d3767e11fa96710b
    107. 107
      Kanehisa, M.; Goto, S.; Furumichi, M.; Tanabe, M.; Hirakawa, M. KEGG for Representation and Analysis of Molecular Networks Involving Diseases and Drugs. Nucleic Acids Res. 2010, 38, D355– D360,  DOI: 10.1093/nar/gkp896
      107
      KEGG for representation and analysis of molecular networks involving diseases and drugs
      Kanehisa, Minoru; Goto, Susumu; Furumichi, Miho; Tanabe, Mao; Hirakawa, Mika
      Nucleic Acids Research (2010), 38 (Database Iss), D355-D360CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
      Most human diseases are complex multi-factorial diseases resulting from the combination of various genetic and environmental factors. In the KEGG database resource (http://www.genome.jp/kegg/), diseases are viewed as perturbed states of the mol. system, and drugs as perturbants to the mol. system. Disease information is computerized in two forms: pathway maps and gene/mol. lists. The KEGG PATHWAY database contains pathway maps for the mol. systems in both normal and perturbed states. In the KEGG DISEASE database, each disease is represented by a list of known disease genes, any known environmental factors at the mol. level, diagnostic markers and therapeutic drugs, which may reflect the underlying mol. system. The KEGG DRUG database contains chem. structures and/or chem. components of all drugs in Japan, including crude drugs and TCM (Traditional Chinese Medicine) formulas, and drugs in the USA and Europe. This database also captures knowledge about two types of mol. networks: the interaction network with target mols., metabolizing enzymes, other drugs, etc. and the chem. structure transformation network in the history of drug development. The new disease/drug information resource named KEGG MEDICUS can be used as a ref. knowledge base for computational anal. of mol. networks, esp., by integrating large-scale exptl. datasets.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3cXktlygtg%253D%253D&md5=925b12b2f02668850a855f4606cce2a0

  • Supporting Information

    Supporting Information

    ARTICLE SECTIONS
    Jump To

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.0c05984.

    • (Table S1) Molecular docking calculations of 70 promising drug repositioning candidates for schizophrenia with D2-like receptors and prediction of GI absorption - BBB permeation; (Table S2) physicochemical properties, lipophilicity, and drug likeness parameters of the drugs considered in this study; and (Figures S1–S3) representative snapshot from molecular dynamics trajectory of flunarizine with DRs (PDF)


    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

PDF [ 8MB]

Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

Pair your accounts.

Export articles to Mendeley

Get article recommendations from ACS based on references in your Mendeley library.

You’ve supercharged your research process with ACS and Mendeley!

STEP 1:
Click to create an ACS ID

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

Please note: If you switch to a different device, you may be asked to login again with only your ACS ID.

MENDELEY PAIRING EXPIRED
Your Mendeley pairing has expired. Please reconnect