Automated fitting of transition state force fields for biomolecular simulations

Taylor R Quinn, Himani N Patel, Kevin H Koh, Brandon E Haines, Per-Ola Norrby, Paul Helquist and Olaf Wiest

PLOS ONE, 2022, vol. 17, issue 3, 1-13

Abstract: 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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0264960

DOI: 10.1371/journal.pone.0264960

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