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

The automated optimisation of a coarse-grained force field using free energy data
The automated optimisation of a coarse-grained force field using free energy data
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 rejproduced hydration free energies of atomistic models and gave improved agreement with experiment
1463-9076
24842-24851
Caceres Delpiano, Javier
67ee9f15-f508-4a8d-b45d-37a31189f630
Wang, Lee-Ping
363d82f6-cffb-4a5b-868a-de5f8ac56d60
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Caceres Delpiano, Javier
67ee9f15-f508-4a8d-b45d-37a31189f630
Wang, Lee-Ping
363d82f6-cffb-4a5b-868a-de5f8ac56d60
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5

Caceres Delpiano, Javier, Wang, Lee-Ping and Essex, Jonathan W. (2021) The automated optimisation of a coarse-grained force field using free energy data. Physical Chemistry Chemical Physics, 23 (43), 24842-24851. (doi:10.1039/D0CP05041E).

Record type: Article

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 rejproduced hydration free energies of atomistic models and gave improved agreement with experiment

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Accepted/In Press date: 18 October 2021
e-pub ahead of print date: 19 October 2021
Published date: 21 November 2021
Additional Information: Funding Information: Calculations in this work made use of the Iridis4 supercomputers at the University of Southampton. LPW acknowledges funding support from NIH R01 AI130684-01A1. JCD gratefully acknowledges funding support from CONICYT-BECAS CHILE. Publisher Copyright: © the Owner Societies 2021.

Identifiers

Local EPrints ID: 452038
URI: http://eprints.soton.ac.uk/id/eprint/452038
ISSN: 1463-9076
PURE UUID: cd090e51-6cbb-4f22-b0d3-a5b2bd8f633e
ORCID for Jonathan W. Essex: ORCID iD orcid.org/0000-0003-2639-2746

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Date deposited: 09 Nov 2021 17:32
Last modified: 17 Mar 2024 02:40

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Contributors

Author: Javier Caceres Delpiano
Author: Lee-Ping Wang

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