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Docking-based long timescale simulation of cell-size protein systems at atomic resolution

Computational 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...

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Autores principales: Vakser, Ilya A., Grudinin, Sergei, Jenkins, Nathan W., Kundrotas, Petras J., Deeds, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565162/
https://www.ncbi.nlm.nih.gov/pubmed/36191203
http://dx.doi.org/10.1073/pnas.2210249119
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author Vakser, Ilya A.
Grudinin, Sergei
Jenkins, Nathan W.
Kundrotas, Petras J.
Deeds, Eric J.
author_facet Vakser, Ilya A.
Grudinin, Sergei
Jenkins, Nathan W.
Kundrotas, Petras J.
Deeds, Eric J.
author_sort Vakser, Ilya A.
collection PubMed
description Computational 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.
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spelling pubmed-95651622022-10-15 Docking-based long timescale simulation of cell-size protein systems at atomic resolution Vakser, Ilya A. Grudinin, Sergei Jenkins, Nathan W. Kundrotas, Petras J. Deeds, Eric J. Proc Natl Acad Sci U S A Biological Sciences Computational 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. National Academy of Sciences 2022-10-03 2022-10-11 /pmc/articles/PMC9565162/ /pubmed/36191203 http://dx.doi.org/10.1073/pnas.2210249119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Vakser, Ilya A.
Grudinin, Sergei
Jenkins, Nathan W.
Kundrotas, Petras J.
Deeds, Eric J.
Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title_full Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title_fullStr Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title_full_unstemmed Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title_short Docking-based long timescale simulation of cell-size protein systems at atomic resolution
title_sort docking-based long timescale simulation of cell-size protein systems at atomic resolution
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9565162/
https://www.ncbi.nlm.nih.gov/pubmed/36191203
http://dx.doi.org/10.1073/pnas.2210249119
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