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Collective Variable for Metadynamics Derived From AlphaFold Output

AlphaFold is a neural network–based tool for the prediction of 3D structures of proteins. In CASP14, a blind structure prediction challenge, it performed significantly better than other competitors, making it the best available structure prediction tool. One of the outputs of AlphaFold is the probab...

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Autores principales: Spiwok, Vojtěch, Kurečka, Martin, Křenek, Aleš
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234394/
https://www.ncbi.nlm.nih.gov/pubmed/35769910
http://dx.doi.org/10.3389/fmolb.2022.878133
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author Spiwok, Vojtěch
Kurečka, Martin
Křenek, Aleš
author_facet Spiwok, Vojtěch
Kurečka, Martin
Křenek, Aleš
author_sort Spiwok, Vojtěch
collection PubMed
description AlphaFold is a neural network–based tool for the prediction of 3D structures of proteins. In CASP14, a blind structure prediction challenge, it performed significantly better than other competitors, making it the best available structure prediction tool. One of the outputs of AlphaFold is the probability profile of residue–residue distances. This makes it possible to score any conformation of the studied protein to express its compliance with the AlphaFold model. Here, we show how this score can be used to drive protein folding simulation by metadynamics and parallel tempering metadynamics. Using parallel tempering metadynamics, we simulated the folding of a mini-protein Trp-cage and β hairpin and predicted their folding equilibria. We observe the potential of the AlphaFold-based collective variable in applications beyond structure prediction, such as in structure refinement or prediction of the outcome of a mutation.
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spelling pubmed-92343942022-06-28 Collective Variable for Metadynamics Derived From AlphaFold Output Spiwok, Vojtěch Kurečka, Martin Křenek, Aleš Front Mol Biosci Molecular Biosciences AlphaFold is a neural network–based tool for the prediction of 3D structures of proteins. In CASP14, a blind structure prediction challenge, it performed significantly better than other competitors, making it the best available structure prediction tool. One of the outputs of AlphaFold is the probability profile of residue–residue distances. This makes it possible to score any conformation of the studied protein to express its compliance with the AlphaFold model. Here, we show how this score can be used to drive protein folding simulation by metadynamics and parallel tempering metadynamics. Using parallel tempering metadynamics, we simulated the folding of a mini-protein Trp-cage and β hairpin and predicted their folding equilibria. We observe the potential of the AlphaFold-based collective variable in applications beyond structure prediction, such as in structure refinement or prediction of the outcome of a mutation. Frontiers Media S.A. 2022-06-13 /pmc/articles/PMC9234394/ /pubmed/35769910 http://dx.doi.org/10.3389/fmolb.2022.878133 Text en Copyright © 2022 Spiwok, Kurečka and Křenek. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Spiwok, Vojtěch
Kurečka, Martin
Křenek, Aleš
Collective Variable for Metadynamics Derived From AlphaFold Output
title Collective Variable for Metadynamics Derived From AlphaFold Output
title_full Collective Variable for Metadynamics Derived From AlphaFold Output
title_fullStr Collective Variable for Metadynamics Derived From AlphaFold Output
title_full_unstemmed Collective Variable for Metadynamics Derived From AlphaFold Output
title_short Collective Variable for Metadynamics Derived From AlphaFold Output
title_sort collective variable for metadynamics derived from alphafold output
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234394/
https://www.ncbi.nlm.nih.gov/pubmed/35769910
http://dx.doi.org/10.3389/fmolb.2022.878133
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