Evidence map›Paper›PMID 34723311›Full record

ArticlePhysical chemistry chemical physics : PCCP2021

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

Javier Caceres-Delpiano, Lee-Ping Wang, Jonathan W Essex

Abstract read
In one paragraph

Article in Physical chemistry chemical physics : PCCP, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Javier Caceres-DelpianoSchool of Chemistry, University of Southampton, Southapton, S017 1BJ, UK. j.w.essex@soton.ac.uk.ORCID http://orcid.org/0000-0002-8758-1244
Lee-Ping WangDepartment of Chemistry, University of California, Davis, California 95616, USA. leeping@ucdavis.edu.ORCID http://orcid.org/0000-0003-3072-9946
Jonathan W EssexSchool of Chemistry, University of Southampton, Southapton, S017 1BJ, UK. j.w.essex@soton.ac.uk.ORCID http://orcid.org/0000-0003-2639-2746

Funding

Supplement: Exploring the biology of O-acetyl sialic acids using stable synthetic mimicsR01AI130684 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CHEN, XI, VARKI, AJIT P · 2017 to 2020
$2.3M
NIAID NIH HHS R01 AI130684
6 · The paper itself

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.

Indexed as

AutomationMolecular Dynamics SimulationThermodynamicsProteinsProteins

Identifiers

PMID34723311
PMCPMC8579472

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.