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Published in

American Chemical Society, Journal of Chemical Theory and Computation, 11(9), p. 4874-4889, 2013

DOI: 10.1021/ct4005036

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Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field

This paper is available in a repository.
This paper is available in a repository.

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Abstract

Simulations using residue-scale coarse-grained models of biomolecules are less computationally demanding than simulations employing full-atomistic force fields. However, the coarse-grained models are often difficult and tedious to parametrize for certain applications. Therefore, a systematic and objective method to help develop or adapt the coarse-grained models is needed. We present an automatic method that implements an evolutionary algorithm to find a set of optimal force field parameters for a one-bead coarse-grained model. In addition to an optimized force field, parameter correlations and significance of the potential energy terms can be determined. The method is applied to two classes of problems: the dynamics of an RNA helix and the RNA structure prediction.