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Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-bonded Interactions
Published
Author(s)
Richard A. Messerly, S. M. Razavi, Michael R. Shirts
Abstract
In this study, we develop an approach for rapid force field parameterization and uncertainty quantification of the non-bonded interaction parameters for classical force fields. The accuracy of most thermophysical properties, and especially vapor-liquid equilibria (VLE), obtained from molecular simulation depends strongly on the non-bonded interactions. Traditionally, non-bonded interactions are parameterized to agree with macroscopic properties by performing large amounts of direct molecular simulation. Due to the computational cost of molecular simulation, surrogate models are an essential tool for high-dimensional parameterization and uncertainty quantification of non-bonded interactions. The present study compares two different configuration-sampling-based surrogate models, namely, Multistate Bennett Acceptance Ratio (MBAR) and Pair Correlation Function Rescaling (PCFR). MBAR and PCFR are coupled with the Isothermal Isochoric (ITIC) thermodynamic integration method for estimating vapor-liquid saturation properties. The conclusion is that MBAR and PCFR are complementary in their roles. Specifically, PCFR is preferred when exploring distant regions of the parameter space while MBAR is better in the local domain.
Messerly, R.
, Razavi, S.
and Shirts, M.
(2018),
Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-bonded Interactions, Journal of Chemical Theory and Computation, [online], https://doi.org/10.1021/acs.jctc.8b00223
(Accessed October 16, 2025)