Open AccessAutomated fitting of transition state force fields for biomolecular simulations
Author(s) -
Taylor R. Quinn,
Himani Patel,
Kevin H. Koh,
Brandon E. Haines,
PerOla Norrby,
Paul Helquist,
Olaf Wiest
Publication year - 2022
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0264960
Subject(s) - force field (fiction) , molecular dynamics , work (physics) , computational chemistry , molecule , transition state , chemistry , molecular mechanics , statistical physics , biological system , chemical physics , physics , thermodynamics , quantum mechanics , biology , biochemistry , catalysis
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 ( Pm HMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed.