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The automated optimisation of a coarse-grained force field using free energy data.

ABSTRACT: Atomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number of degrees of freedom, at the cost of reduced accuracy. New optimisation processes to parameterise these models could improve their quality and range of applicability. We present an automated approach for the optimisation of coarse-grained force fields, by reproducing free energy data derived from atomistic molecular simulations. To illustrate the approach, we implemented hydration free energy gradients as a new target for force field optimisation in ForceBalance and applied it successfully to optimise the un-charged side-chains and the protein backbone in the SIRAH protein coarse-grain force field. The optimised parameters closely reproduced hydration free energies of atomistic models and gave improved agreement with experiment.

SUBMITTER: Caceres-Delpiano J

PROVIDER: S-EPMC8579472 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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The automated optimisation of a coarse-grained force field using free energy data.

Caceres-Delpiano Javier J Wang Lee-Ping LP Essex Jonathan W JW

Physical chemistry chemical physics : PCCP 20211110 43

Atomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number of degrees of freedom, at the cost of reduced accuracy. New optimisation processes to parameterise these models could improve their quality and range of applicability. We present an automated approach for the optimisation of coarse-grained force fields, by reproducin ...[more]

PMID: 34723311

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