biostudies-literatureParvatikar ANational Institutes of Health-National Institute of General Medical SciencesNIGMS NIH HHS2040-2043https://www.ebi.ac.uk/biostudies/studies/S-EPMC5961460biostudies-literatureUnknown114(9)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.Biophysical journalANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.PMC5961460R01 GM105978GM105978Ramanathan AParvatikar AVacaliuc GSChennubhotla SCfalseANCA: Anharmonic Conformational Analysis of Biomolecular Simulations.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.2018-01-01T00:00:00Z2018 May2026-04-29T07:19:31.63Z2019-06-06T23:03:45ZS-EPMC59614602974239710.1016/j.bpj.2018.03.021