Literature DB >> 23380188

Optimization of reorganization energy drives evolution of the designed Kemp eliminase KE07.

A Labas1, E Szabo, L Mones, M Fuxreiter.   

Abstract

Understanding enzymatic evolution is essential to engineer enzymes with improved activities or to generate enzymes with tailor-made activities. The computationally designed Kemp eliminase KE07 carries out an unnatural reaction by converting of 5-nitrobenzisoxazole to cyanophenol, but its catalytic efficiency is significantly lower than those of natural enzymes. Three series of designed Kemp eliminases (KE07, KE70, KE59) were shown to be evolvable with considerable improvement in catalytic efficiency. Here we use the KE07 enzyme as a model system to reveal those forces, which govern enzymatic evolution and elucidate the key factors for improving activity. We applied the Empirical Valence Bond (EVB) method to construct the free energy pathway of the reaction in the original KE07 design and the evolved R7 1/3H variant. We analyzed catalytic effect of residues and demonstrated that not all mutations in evolution are favorable for activity. In contrast to the small decrease in the activation barrier, in vitro evolution significantly reduced the reorganization energy. We developed an algorithm to evaluate group contributions to the reorganization energy and used this approach to screen for KE07 variants with potential for improvement. We aimed to identify those mutations that facilitate enzymatic evolution, but might not directly increase catalytic efficiency. Computational results in accord with experimental data show that all mutations, which appear during in vitro evolution were either neutral or favorable for the reorganization energy. These results underscore that distant mutations can also play role in optimizing efficiency via their contribution to the reorganization energy. Exploiting this principle could be a promising strategy for computer-aided enzyme design. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.
Copyright © 2013 Elsevier B.V. All rights reserved.

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Year:  2013        PMID: 23380188     DOI: 10.1016/j.bbapap.2013.01.005

Source DB:  PubMed          Journal:  Biochim Biophys Acta        ISSN: 0006-3002


  6 in total

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Authors:  K Świderek; I Tuñón; V Moliner; J Bertran
Journal:  Arch Biochem Biophys       Date:  2015-03-19       Impact factor: 4.013

2.  CADEE: Computer-Aided Directed Evolution of Enzymes.

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Journal:  IUCrJ       Date:  2017-01-01       Impact factor: 4.769

Review 3.  Harnessing Conformational Plasticity to Generate Designer Enzymes.

Authors:  Rory M Crean; Jasmine M Gardner; Shina C L Kamerlin
Journal:  J Am Chem Soc       Date:  2020-06-17       Impact factor: 15.419

Review 4.  Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently.

Authors:  Andrew Currin; Neil Swainston; Philip J Day; Douglas B Kell
Journal:  Chem Soc Rev       Date:  2015-03-07       Impact factor: 54.564

5.  The evolution of multiple active site configurations in a designed enzyme.

Authors:  Nan-Sook Hong; Dušan Petrović; Richmond Lee; Ganna Gryn'ova; Miha Purg; Jake Saunders; Paul Bauer; Paul D Carr; Ching-Yeh Lin; Peter D Mabbitt; William Zhang; Timothy Altamore; Chris Easton; Michelle L Coote; Shina C L Kamerlin; Colin J Jackson
Journal:  Nat Commun       Date:  2018-09-25       Impact factor: 14.919

6.  Bottom-Up Nonempirical Approach To Reducing Search Space in Enzyme Design Guided by Catalytic Fields.

Authors:  Wiktor Beker; W Andrzej Sokalski
Journal:  J Chem Theory Comput       Date:  2020-04-23       Impact factor: 6.006

  6 in total

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