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In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function

Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of...

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Autores principales: Verma, Rajni, Mitchell-Koch, Katie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241538/
https://www.ncbi.nlm.nih.gov/pubmed/30464857
http://dx.doi.org/10.3390/catal7070212
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author Verma, Rajni
Mitchell-Koch, Katie
author_facet Verma, Rajni
Mitchell-Koch, Katie
author_sort Verma, Rajni
collection PubMed
description Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme–substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly.
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spelling pubmed-62415382018-11-19 In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function Verma, Rajni Mitchell-Koch, Katie Catalysts Article Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme–substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly. 2017-07-14 2017 /pmc/articles/PMC6241538/ /pubmed/30464857 http://dx.doi.org/10.3390/catal7070212 Text en Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Verma, Rajni
Mitchell-Koch, Katie
In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title_full In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title_fullStr In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title_full_unstemmed In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title_short In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function
title_sort in silico studies of small molecule interactions with enzymes reveal aspects of catalytic function
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241538/
https://www.ncbi.nlm.nih.gov/pubmed/30464857
http://dx.doi.org/10.3390/catal7070212
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