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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.
Afiliação
  • Vakser IA; Computational Biology Program, The University of Kansas, Lawrence, KS.
  • Grudinin S; Department of Molecular Biosciences, The University of Kansas, Lawrence, KS.
  • Jenkins NW; University of Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France.
  • Kundrotas PJ; Computational Biology Program, The University of Kansas, Lawrence, KS.
  • Deeds EJ; Computational Biology Program, The University of Kansas, Lawrence, KS.
Proc Natl Acad Sci U S A ; 119(41): e2210249119, 2022 10 11.
Article em En | MEDLINE | ID: mdl-36191203
ABSTRACT
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Simulação de Dinâmica Molecular Tipo de estudo: Health_economic_evaluation Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Simulação de Dinâmica Molecular Tipo de estudo: Health_economic_evaluation Idioma: En Ano de publicação: 2022 Tipo de documento: Article