Quantitative comparison of adaptive sampling methods for protein dynamics

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dc.citation.articleNumber244119
dc.citation.issueNumber24
dc.citation.journalTitleThe Journal of Chemical Physics
dc.citation.volumeNumber149
dc.contributor.authorHruska, Eugen
dc.contributor.authorAbella, Jayvee R.
dc.contributor.authorNüske, Feliks
dc.contributor.authorKavraki, Lydia E.
dc.contributor.authorClementi, Cecilia
dc.contributor.orgCenter for Theoretical Biological Physics
dc.date.accessioned2019-01-18T17:51:31Z
dc.date.available2019-01-18T17:51:31Z
dc.date.issued2018
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.
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.
dc.identifier.doihttps://doi.org/10.1063/1.5053582
dc.identifier.urihttps://hdl.handle.net/1911/105113
dc.language.isoeng
dc.publisherAIP Publishing LLC
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.
dc.titleQuantitative comparison of adaptive sampling methods for protein dynamics
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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