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Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics

Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with th...

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Detalles Bibliográficos
Autores principales: Blue, Tamra C., Davis, Katherine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124187/
https://www.ncbi.nlm.nih.gov/pubmed/33946806
http://dx.doi.org/10.3390/molecules26092590
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author Blue, Tamra C.
Davis, Katherine M.
author_facet Blue, Tamra C.
Davis, Katherine M.
author_sort Blue, Tamra C.
collection PubMed
description Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical S-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover.
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spelling pubmed-81241872021-05-17 Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics Blue, Tamra C. Davis, Katherine M. Molecules Review Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical S-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover. MDPI 2021-04-29 /pmc/articles/PMC8124187/ /pubmed/33946806 http://dx.doi.org/10.3390/molecules26092590 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Blue, Tamra C.
Davis, Katherine M.
Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title_full Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title_fullStr Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title_full_unstemmed Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title_short Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
title_sort computational approaches: an underutilized tool in the quest to elucidate radical sam dynamics
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124187/
https://www.ncbi.nlm.nih.gov/pubmed/33946806
http://dx.doi.org/10.3390/molecules26092590
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