{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Parvatikar A"],"funding":["National Institutes of Health-National Institute of General Medical Sciences","NIGMS NIH HHS"],"pagination":["2040-2043"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5961460"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["114(9)"],"pubmed_abstract":["Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates."],"journal":["Biophysical journal"],"pubmed_title":["ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations."],"pmcid":["PMC5961460"],"funding_grant_id":["R01 GM105978","GM105978"],"pubmed_authors":["Ramanathan A","Parvatikar A","Vacaliuc GS","Chennubhotla SC"],"additional_accession":[]},"is_claimable":false,"name":"ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.","description":"Anharmonicity in time-dependent conformational fluctuations is noted to be a key feature of functional dynamics of biomolecules. Although anharmonic events are rare, long-timescale (μs-ms and beyond) simulations facilitate probing of such events. We have previously developed quasi-anharmonic analysis to resolve higher-order spatial correlations and characterize anharmonicity in biomolecular simulations. In this article, we have extended this toolbox to resolve higher-order temporal correlations and built a scalable Python package called anharmonic conformational analysis (ANCA). ANCA has modules to: 1) measure anharmonicity in the form of higher-order statistics and its variation as a function of time, 2) output a storyboard representation of the simulations to identify key anharmonic conformational events, and 3) identify putative anharmonic conformational substates and visualization of transitions between these substates.","dates":{"release":"2018-01-01T00:00:00Z","publication":"2018 May","modification":"2026-04-29T07:19:31.63Z","creation":"2019-06-06T23:03:45Z"},"accession":"S-EPMC5961460","cross_references":{"pubmed":["29742397"],"doi":["10.1016/j.bpj.2018.03.021"]}}