Quantitative comparison of adaptive sampling methods for protein dynamics

dc.citation.articleNumber244119en_US
dc.citation.issueNumber24en_US
dc.citation.journalTitleThe Journal of Chemical Physicsen_US
dc.citation.volumeNumber149en_US
dc.contributor.authorHruska, Eugenen_US
dc.contributor.authorAbella, Jayvee R.en_US
dc.contributor.authorNüske, Feliksen_US
dc.contributor.authorKavraki, Lydia E.en_US
dc.contributor.authorClementi, Ceciliaen_US
dc.contributor.orgCenter for Theoretical Biological Physicsen_US
dc.date.accessioned2019-01-18T17:51:31Zen_US
dc.date.available2019-01-18T17:51:31Zen_US
dc.date.issued2018en_US
dc.description.abstractAdaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. In this work, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a prioriknowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.en_US
dc.identifier.citationHruska, Eugen, Abella, Jayvee R., Nüske, Feliks, et al.. "Quantitative comparison of adaptive sampling methods for protein dynamics." <i>The Journal of Chemical Physics,</i> 149, no. 24 (2018) AIP Publishing LLC: https://doi.org/10.1063/1.5053582.en_US
dc.identifier.doihttps://doi.org/10.1063/1.5053582en_US
dc.identifier.urihttps://hdl.handle.net/1911/105113en_US
dc.language.isoengen_US
dc.publisherAIP Publishing LLCen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.titleQuantitative comparison of adaptive sampling methods for protein dynamicsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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