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PyCGTOOL v2.0.0: Generate coarse-grained molecular dynamics models from atomistic trajectories.

PyCGTOOL v2.0.0: Generate coarse-grained molecular dynamics models from atomistic trajectories.
PyCGTOOL v2.0.0: Generate coarse-grained molecular dynamics models from atomistic trajectories.
PyCGTOOL is a tool to aid in parametrising coarse-grained (CG) molecular mechanics models of small molecules, for example for simulations using the popular MARTINI model. It generates coarse-grained model parameters from atomistic simulation trajectories using a user-provided mapping. Equilibrium values and force constants of bonded terms are calculated by Boltzmann Inversion of bond distributions collected from the input trajectory.
Zenodo
Graham, James
ba426094-6e0d-4ecf-a1e5-4a4e0a4f62fd
Shearer, Jonathan
44810f0c-f875-465e-be3b-810155814bc5
Wright, David W.
79cde6eb-ae74-41dc-9877-86d3144f56c7

(2022) PyCGTOOL v2.0.0: Generate coarse-grained molecular dynamics models from atomistic trajectories. Zenodo doi:10.5281/zenodo.6363673 [Software]

Record type: Software

Abstract

PyCGTOOL is a tool to aid in parametrising coarse-grained (CG) molecular mechanics models of small molecules, for example for simulations using the popular MARTINI model. It generates coarse-grained model parameters from atomistic simulation trajectories using a user-provided mapping. Equilibrium values and force constants of bonded terms are calculated by Boltzmann Inversion of bond distributions collected from the input trajectory.

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More information

Published date: 16 March 2022

Identifiers

Local EPrints ID: 457549
URI: http://eprints.soton.ac.uk/id/eprint/457549
PURE UUID: d8b689ec-5110-46f5-8a1f-44c065f60869
ORCID for James Graham: ORCID iD orcid.org/0000-0001-5217-3104

Catalogue record

Date deposited: 13 Jun 2022 16:33
Last modified: 30 Jan 2023 20:29

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Contributors

Programmer: James Graham ORCID iD
Programmer: Jonathan Shearer
Other: David W. Wright

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