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The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters

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Department of Plant Sciences, Department of Physics of Complex Systems, and §Department of Biological Chemistry, The Weizmann Institute of Science, Rehovot 76100, Israel
*E-mail: [email protected]. Phone: +972505714697. Fax: +97289344540.
Cite this: Biochemistry 2011, 50, 21, 4402–4410
Publication Date (Web):April 20, 2011
https://doi.org/10.1021/bi2002289
Copyright © 2011 American Chemical Society

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    Abstract

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    The kinetic parameters of enzymes are key to understanding the rate and specificity of most biological processes. Although specific trends are frequently studied for individual enzymes, global trends are rarely addressed. We performed an analysis of kcat and KM values of several thousand enzymes collected from the literature. We found that the “average enzyme” exhibits a kcat of ∼10 s–1 and a kcat/KM of ∼105 s–1 M–1, much below the diffusion limit and the characteristic textbook portrayal of kinetically superior enzymes. Why do most enzymes exhibit moderate catalytic efficiencies? Maximal rates may not evolve in cases where weaker selection pressures are expected. We find, for example, that enzymes operating in secondary metabolism are, on average, ∼30-fold slower than those of central metabolism. We also find indications that the physicochemical properties of substrates affect the kinetic parameters. Specifically, low molecular mass and hydrophobicity appear to limit KM optimization. In accordance, substitution with phosphate, CoA, or other large modifiers considerably lowers the KM values of enzymes utilizing the substituted substrates. It therefore appears that both evolutionary selection pressures and physicochemical constraints shape the kinetic parameters of enzymes. It also seems likely that the catalytic efficiency of some enzymes toward their natural substrates could be increased in many cases by natural or laboratory evolution.

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    The entire data set of kinetic parameters, a detailed description of the data sets used in our analysis and a discussion of the dependencies between the kinetic parameters and of the reasons for the noise in the data sets, the affiliation of metabolic modules to one of the four primary metabolic groups, an analysis of the effect of host organisms on the kinetics of enzymes, the effect of the physicochemical properties on KM, the energetic contribution of each non-hydrogen atom to binding, and the decrease in KM upon substitution with large modifiers, the statistical tools used in the analysis, and a mathematical model for the evolution of suboptimal catalytic constants. This material is available free of charge via the Internet at http://pubs.acs.org.

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