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Non-Markovian modeling of protein folding
We extract the folding free energy landscape and the time-dependent friction function, the two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular dynamics (MD) simulations of the [Formula: see text]-helix forming polypeptide [Formula: see text] for a one-dimensiona...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346879/ https://www.ncbi.nlm.nih.gov/pubmed/34326249 http://dx.doi.org/10.1073/pnas.2023856118 |
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author | Ayaz, Cihan Tepper, Lucas Brünig, Florian N. Kappler, Julian Daldrop, Jan O. Netz, Roland R. |
author_facet | Ayaz, Cihan Tepper, Lucas Brünig, Florian N. Kappler, Julian Daldrop, Jan O. Netz, Roland R. |
author_sort | Ayaz, Cihan |
collection | PubMed |
description | We extract the folding free energy landscape and the time-dependent friction function, the two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular dynamics (MD) simulations of the [Formula: see text]-helix forming polypeptide [Formula: see text] for a one-dimensional reaction coordinate based on the sum of the native H-bond distances. Folding and unfolding times from numerical integration of the GLE agree accurately with MD results, which demonstrate the robustness of our GLE-based non-Markovian model. In contrast, Markovian models do not accurately describe the peptide kinetics and in particular, cannot reproduce the folding and unfolding kinetics simultaneously, even if a spatially dependent friction profile is used. Analysis of the GLE demonstrates that memory effects in the friction significantly speed up peptide folding and unfolding kinetics, as predicted by the Grote–Hynes theory, and are the cause of anomalous diffusion in configuration space. Our methods are applicable to any reaction coordinate and in principle, also to experimental trajectories from single-molecule experiments. Our results demonstrate that a consistent description of protein-folding dynamics must account for memory friction effects. |
format | Online Article Text |
id | pubmed-8346879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-83468792021-08-23 Non-Markovian modeling of protein folding Ayaz, Cihan Tepper, Lucas Brünig, Florian N. Kappler, Julian Daldrop, Jan O. Netz, Roland R. Proc Natl Acad Sci U S A Physical Sciences We extract the folding free energy landscape and the time-dependent friction function, the two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular dynamics (MD) simulations of the [Formula: see text]-helix forming polypeptide [Formula: see text] for a one-dimensional reaction coordinate based on the sum of the native H-bond distances. Folding and unfolding times from numerical integration of the GLE agree accurately with MD results, which demonstrate the robustness of our GLE-based non-Markovian model. In contrast, Markovian models do not accurately describe the peptide kinetics and in particular, cannot reproduce the folding and unfolding kinetics simultaneously, even if a spatially dependent friction profile is used. Analysis of the GLE demonstrates that memory effects in the friction significantly speed up peptide folding and unfolding kinetics, as predicted by the Grote–Hynes theory, and are the cause of anomalous diffusion in configuration space. Our methods are applicable to any reaction coordinate and in principle, also to experimental trajectories from single-molecule experiments. Our results demonstrate that a consistent description of protein-folding dynamics must account for memory friction effects. National Academy of Sciences 2021-08-03 2021-07-29 /pmc/articles/PMC8346879/ /pubmed/34326249 http://dx.doi.org/10.1073/pnas.2023856118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Ayaz, Cihan Tepper, Lucas Brünig, Florian N. Kappler, Julian Daldrop, Jan O. Netz, Roland R. Non-Markovian modeling of protein folding |
title | Non-Markovian modeling of protein folding |
title_full | Non-Markovian modeling of protein folding |
title_fullStr | Non-Markovian modeling of protein folding |
title_full_unstemmed | Non-Markovian modeling of protein folding |
title_short | Non-Markovian modeling of protein folding |
title_sort | non-markovian modeling of protein folding |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346879/ https://www.ncbi.nlm.nih.gov/pubmed/34326249 http://dx.doi.org/10.1073/pnas.2023856118 |
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