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dc.contributor.authorVakser, Ilya A.
dc.contributor.authorGrudinin, Sergei
dc.contributor.authorJenkins, Nathan W.
dc.contributor.authorKundrotas, Petras J.
dc.contributor.authorDeeds, Eric J.
dc.date.accessioned2023-02-17T16:58:09Z
dc.date.available2023-02-17T16:58:09Z
dc.date.issued2022-10-03
dc.identifier.citationVakser, I. A., Grudinin, S., Jenkins, N. W., Kundrotas, P. J., & Deeds, E. J. (2022). Docking-based long timescale simulation of cell-size protein systems at atomic resolution. Proceedings of the National Academy of Sciences of the United States of America, 119(41), e2210249119. https://doi.org/10.1073/pnas.2210249119en_US
dc.identifier.urihttp://hdl.handle.net/1808/33826
dc.description.abstractComputational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, thus far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions but are relatively slow, if carried out at all-atom resolution, or are significantly coarse grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise fast Fourier transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.en_US
dc.publisherNational Academy of Sciencesen_US
dc.rightsCopyright © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectProtein recognitionen_US
dc.subjectProtein crowdingen_US
dc.subjectEnergy landscapeen_US
dc.subjectProtein interactionsen_US
dc.titleDocking-based long timescale simulation of cell-size protein systems at atomic resolutionen_US
dc.typeArticleen_US
kusw.kuauthorVakser, Ilya A.
kusw.kuauthorJenkins, Nathan W.
kusw.kuauthorKundrotas, Petras J.
kusw.kudepartmentComputational Biology Programen_US
kusw.kudepartmentMolecular Biosciencesen_US
dc.identifier.doi10.1073/pnas.2210249119en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-1903-7220en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-6817-1568en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC9565162en_US
dc.rights.accessrightsopenAccessen_US


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Copyright © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).
Except where otherwise noted, this item's license is described as: Copyright © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).