Open AccessGeneralizing the Discrete Gibbs Sampler-Based λ-Dynamics Approach for Multisite Sampling of Many Ligands
Author(s) -
Jonah Z. Vilseck,
Xinqiang Ding,
Ryan L. Hayes,
Charles L. Brooks
Publication year - 2021
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.1c00176
Subject(s) - molecular dynamics , gibbs free energy , chemistry , gibbs sampling , ligand (biochemistry) , nat , binding affinities , variety (cybernetics) , energy (signal processing) , computational chemistry , physics , mathematics , thermodynamics , bayesian probability , statistics , biochemistry , receptor
In this work, the discrete λ variant of the Gibbs sampler-based λ-dynamics ( d -GSλD) method is developed to enable multiple functional group perturbations to be investigated at one or more sites of substitution off a common ligand core. The theoretical framework and special considerations for constructing discrete λ states for multisite d -GSλD are presented. The precision and accuracy of the d -GSλD method is evaluated with three test cases of increasing complexity. Specifically, methyl → methyl symmetric perturbations in water, 1,4-benzene hydration free energies and protein-ligand binding affinities for an example HIV-1 reverse transcriptase inhibitor series are computed with d -GSλD. Complementary MSλD calculations were also performed to compare with d -GSλD's performance. Excellent agreement between d -GSλD and MSλD is observed, with mean unsigned errors of 0.12 and 0.22 kcal/mol for computed hydration and binding free energy test cases, respectively. Good agreement with experiment is also observed, with errors of 0.5-0.7 kcal/mol. These findings support the applicability of the d -GSλD free energy method for a variety of molecular design problems, including structure-based drug design. Finally, a discussion of d -GSλD versus MSλD approaches is presented to compare and contrast features of both methods.