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WIREs Comput Mol Sci
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Predicting enzymatic reactivity: from theory to design

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Theoretical and computational tools can provide a detailed knowledge of the mode of action of enzymes. This knowledge can be systematized to be used as a guide for the design of new biocatalysts for industrial purposes. In this article, we illustrate the current view about the origin of enzymatic catalysis based on molecular simulations and its use in the design of new enzymes. Transition‐state stabilization in a preorganized active site seems to be the major source of catalysis, although some degree of protein flexibility is needed to reach the maximum catalytic efficiency. Development of a new enzyme must then consider the inclusion of TS stabilizing interactions either in a preexisting enzymatic structure (enzymatic redesign) or in a completely new designed enzyme (de novo design). However, the lack of a detailed understanding of the link between sequence, structure, flexibility, and function still prevents the complete success of these strategies. WIREs Comput Mol Sci 2014, 4:407–421.

This article is categorized under:

  • Structure and Mechanism > Computational Biochemistry and Biophysics
  • Electronic Structure Theory > Combined QM/MM Methods
  • Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
Free energy scheme for a simple enzyme‐catalyzed reaction (in red line) and the counterpart process in solution (blue line). (Reproduced from Ref . Reproduced by permission of The Royal Society of Chemistry.)
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Graphical representation of the computational methods applied to the design of new enzymes.
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The nucleophilic attack of a carboxylate group to 1,2‐dichloroethane is the first step of the reaction catalyzed by DhlA, a haloalkane dehalogenase. The reaction involves substantial rearrangement of hydrogen bond interactions (highlighted arrows) either with water molecules (for the reaction in solution) of with active‐site residue (in DhlA active site). The global process can be seen as three steps: desolvation of the nucleophile, bond breaking and forming, and solvation of the leaving group. The free energy surface for the reaction in aqueous solution (B) or in DhlA (C) can be obtained using a chemical coordinate (the antisymmetric combination of the CO and CCl distances) and an environmental or solvent coordinate (the antisymmetric combination of the electrostatic potential created on the nucleophilic O atom and the leaving Cl atom). The minimum free energy paths (traced as dotted lines) show that the environment rearranges before and after the change along the chemical coordinate in both cases, but the variation along the solvent coordinate is substantially larger in solution than in the enzyme.
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(A) Evolution of the enzyme along the catalytic cycle may involve not only a chemical transformation but also conformational changes. (B) Each of the states appearing along the cycle can be populated by myriads of different conformations separated by local conformation al changes (as side‐chain rotations) happening in shorter timescales than the changes between different states.
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(A) Methylation reaction of catecholate catalyzed by catechol O‐methyl transferase (COMT) that uses S‐adenosyl methionine as cofactor. The reaction proceeds from charged reactants to neutral products. (B) Projection of the electric field created by the environment on the methyl group along the donor–acceptor axis versus the reaction time (t = 0 corresponds to the passage of the system over the barrier top, negative times to the evolution to the reactants valley and positive times to the evolution toward products valley) in the active site of the enzyme (red line) and in aqueous solution (blue dots). The electrostatic force (represented as a black arrow) opposes to methyl transfer in aqueous solution while it stabilized the positioning of the methyl group at the TS configuration. (Reproduced with permission from Ref . Copyright 2005, American Chemical Society.)
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Electronic Structure Theory > Combined QM/MM Methods
Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
Structure and Mechanism > Computational Biochemistry and Biophysics

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