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Automated fitting of transition state force fields for biomolecular simulations

The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we...

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Detalles Bibliográficos
Autores principales: Quinn, Taylor R., Patel, Himani N., Koh, Kevin H., Haines, Brandon E., Norrby, Per-Ola, Helquist, Paul, Wiest, Olaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912266/
https://www.ncbi.nlm.nih.gov/pubmed/35271647
http://dx.doi.org/10.1371/journal.pone.0264960
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author Quinn, Taylor R.
Patel, Himani N.
Koh, Kevin H.
Haines, Brandon E.
Norrby, Per-Ola
Helquist, Paul
Wiest, Olaf
author_facet Quinn, Taylor R.
Patel, Himani N.
Koh, Kevin H.
Haines, Brandon E.
Norrby, Per-Ola
Helquist, Paul
Wiest, Olaf
author_sort Quinn, Taylor R.
collection PubMed
description The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we have shown that transition state force fields (TSFFs), fitted to the functional form of MM3* force fields using the quantum guided molecular mechanics (Q2MM) method, provide an accurate description of transition states that can be used for stereoselectivity predictions of small molecule reactions. Here, we demonstrate the applicability of the method for fit TSFFs to the well-established Amber force field, which could be used for molecular dynamics studies of enzyme reaction. As a case study, the fitting of a TSFF to the second hydride transfer in Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed.
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spelling pubmed-89122662022-03-11 Automated fitting of transition state force fields for biomolecular simulations Quinn, Taylor R. Patel, Himani N. Koh, Kevin H. Haines, Brandon E. Norrby, Per-Ola Helquist, Paul Wiest, Olaf PLoS One Research Article The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we have shown that transition state force fields (TSFFs), fitted to the functional form of MM3* force fields using the quantum guided molecular mechanics (Q2MM) method, provide an accurate description of transition states that can be used for stereoselectivity predictions of small molecule reactions. Here, we demonstrate the applicability of the method for fit TSFFs to the well-established Amber force field, which could be used for molecular dynamics studies of enzyme reaction. As a case study, the fitting of a TSFF to the second hydride transfer in Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed. Public Library of Science 2022-03-10 /pmc/articles/PMC8912266/ /pubmed/35271647 http://dx.doi.org/10.1371/journal.pone.0264960 Text en © 2022 Quinn et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Quinn, Taylor R.
Patel, Himani N.
Koh, Kevin H.
Haines, Brandon E.
Norrby, Per-Ola
Helquist, Paul
Wiest, Olaf
Automated fitting of transition state force fields for biomolecular simulations
title Automated fitting of transition state force fields for biomolecular simulations
title_full Automated fitting of transition state force fields for biomolecular simulations
title_fullStr Automated fitting of transition state force fields for biomolecular simulations
title_full_unstemmed Automated fitting of transition state force fields for biomolecular simulations
title_short Automated fitting of transition state force fields for biomolecular simulations
title_sort automated fitting of transition state force fields for biomolecular simulations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8912266/
https://www.ncbi.nlm.nih.gov/pubmed/35271647
http://dx.doi.org/10.1371/journal.pone.0264960
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