Collective Variable for Metadynamics Derived From AlphaFold Output

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22330%2F22%3A43924443" target="_blank" >RIV/60461373:22330/22:43924443 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216224:14610/22:00129134

Výsledek na webu

<a href="https://www.frontiersin.org/articles/10.3389/fmolb.2022.878133/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fmolb.2022.878133/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fmolb.2022.878133" target="_blank" >10.3389/fmolb.2022.878133</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Collective Variable for Metadynamics Derived From AlphaFold Output

Popis výsledku v původním jazyce

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. Copyright © 2022 Spiwok, Kurečka and Křenek.

Název v anglickém jazyce

Collective Variable for Metadynamics Derived From AlphaFold Output

Popis výsledku anglicky

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. Copyright © 2022 Spiwok, Kurečka and Křenek.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Frontiers in Molecular Biosciences

ISSN

2296-889X

e-ISSN

2296-889X

Svazek periodika

9

Číslo periodika v rámci svazku

Neuveden

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

10

Strana od-do

"878133_1"-"878133_10"

Kód UT WoS článku

000816408600001

EID výsledku v databázi Scopus

2-s2.0-85133463409