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Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis
Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907816/ https://www.ncbi.nlm.nih.gov/pubmed/24384841 http://dx.doi.org/10.3390/ijms15010401 |
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author | Gherib, Rami Dokainish, Hisham M. Gauld, James W. |
author_facet | Gherib, Rami Dokainish, Hisham M. Gauld, James W. |
author_sort | Gherib, Rami |
collection | PubMed |
description | Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. |
format | Online Article Text |
id | pubmed-3907816 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-39078162014-01-31 Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis Gherib, Rami Dokainish, Hisham M. Gauld, James W. Int J Mol Sci Review Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. Molecular Diversity Preservation International (MDPI) 2013-12-31 /pmc/articles/PMC3907816/ /pubmed/24384841 http://dx.doi.org/10.3390/ijms15010401 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland http://creativecommons.org/licenses/by/3.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Gherib, Rami Dokainish, Hisham M. Gauld, James W. Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title | Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title_full | Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title_fullStr | Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title_full_unstemmed | Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title_short | Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis |
title_sort | multi-scale computational enzymology: enhancing our understanding of enzymatic catalysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907816/ https://www.ncbi.nlm.nih.gov/pubmed/24384841 http://dx.doi.org/10.3390/ijms15010401 |
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