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Computational tools for the evaluation of laboratory-engineered biocatalysts

Biocatalysis is based on the application of natural catalysts for new purposes, for which the enzymes were not designed. Although the first examples of biocatalysis were reported more than a century ago, biocatalysis was revolutionized after the discovery of an in vitro version of Darwinian evolution called Directed Evolution (DE). Despite the recent advances in the field, major challenges remain to be addressed. Up to date, the best experimental approach consists of creating multiple mutations simultaneously but limit the choices using statistical methods. Still, tens of thousands of variants need to be tested experimentally, and little information is available as to how these mutations lead to enhanced enzyme proficiency. This review aims to provide a brief description of available computational techniques to unveil the molecular basis of improved catalysis achieved by DE. An overview of the strengths and weaknesses of current computational strategies are explored, together with some recent representative examples. The understanding of how this powerful technique is able to obtain highly active variants is of importance for the future development of more robust computational methods to predict amino-acid changes needed for activity

A.R.R. thanks the Generalitat de Catalunya for PhD fellowship (2015-FI-B-00165), M.G.B is grateful to the European Community for CIG project (PCIG14-GA-2013-630978), and Spanish MINECO for project CTQ2014-52525-P. S.O. thanks the Spanish MINECO CTQ2014-59212-P, Ramón y Cajal contract (RYC-2014-16846), the European Community for CIG project (PCIG14-GA-2013-630978), and the funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC-2015-StG 679001)

© Chemical Communications, 2016, vol. 53, núm. 2, p. 284-297

Royal Society of Chemistry (RSC)

Autor: Romero Rivera, Adrián
Garcia Borràs, Marc
Osuna Oliveras, Sílvia
Data: 6 setembre 2016
Resum: Biocatalysis is based on the application of natural catalysts for new purposes, for which the enzymes were not designed. Although the first examples of biocatalysis were reported more than a century ago, biocatalysis was revolutionized after the discovery of an in vitro version of Darwinian evolution called Directed Evolution (DE). Despite the recent advances in the field, major challenges remain to be addressed. Up to date, the best experimental approach consists of creating multiple mutations simultaneously but limit the choices using statistical methods. Still, tens of thousands of variants need to be tested experimentally, and little information is available as to how these mutations lead to enhanced enzyme proficiency. This review aims to provide a brief description of available computational techniques to unveil the molecular basis of improved catalysis achieved by DE. An overview of the strengths and weaknesses of current computational strategies are explored, together with some recent representative examples. The understanding of how this powerful technique is able to obtain highly active variants is of importance for the future development of more robust computational methods to predict amino-acid changes needed for activity
A.R.R. thanks the Generalitat de Catalunya for PhD fellowship (2015-FI-B-00165), M.G.B is grateful to the European Community for CIG project (PCIG14-GA-2013-630978), and Spanish MINECO for project CTQ2014-52525-P. S.O. thanks the Spanish MINECO CTQ2014-59212-P, Ramón y Cajal contract (RYC-2014-16846), the European Community for CIG project (PCIG14-GA-2013-630978), and the funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC-2015-StG 679001)
Format: application/pdf
ISSN: 1359-7345 (versió paper)
1364-548X (versió electrònica)
Accés al document: http://hdl.handle.net/10256/12724
Llenguatge: eng
Editor: Royal Society of Chemistry (RSC)
Col·lecció: MINECO/PN 2011-2015/CTQ2014-52525-P
MINECO/PE 2015-2017/CTQ2014-59212-P
Reproducció digital del document publicat a: http://dx.doi.org/10.1039/C6CC06055B
Articles publicats (D-Q)
info:eu-repo/grantAgreement/EC/FP7/630978
info:eu-repo/grantAgreement/EC/H2020/679001
És part de: © Chemical Communications, 2016, vol. 53, núm. 2, p. 284-297
Drets: Attribution-NonCommercial 3.0 Spain
URI Drets: http://creativecommons.org/licenses/by-nc/3.0/es/
Matèria: Enzims
Enzymes
Catalitzadors
Catalysts
Títol: Computational tools for the evaluation of laboratory-engineered biocatalysts
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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