Project ID: plumID:22.005
Name: Collective Variable for Metadynamics Derived from AlphaFold Output
Archive: https://github.com/spiwokv/af2cv/raw/main/afmtd.zip
Category: bio
Keywords: AlphaFold, protein folding, protein structure prediction, metadynamics, deep learning, free energy simulation, collective variable
PLUMED version: 2.8
Contributor: Vojtech Spiwok
Submitted on: 03 Feb 2022
Last revised: 17 Feb 2022
Publication: V. Spiwok, M. Kurečka, A. Křenek, Collective Variable for Metadynamics Derived From AlphaFold Output. Frontiers in Molecular Biosciences. 9 (2022)
PLUMED input files
Last tested: 22 Apr 2024, 20:50:18
Project description and instructions
AlphaFold is the state of the art method for prediction of 3D structures of proteins from the amino acid sequence by neural networks. One of the outputs of AlphaFold is a probability profile of inter-residue distances for all residue pairs. We used this profile to evaluate any conformation of the studied protein to express its compliance with the AlphaFold prediction. This value can be used as a collective variable in metadynamics or parallel tempering metadynamics to accelerate protein folding in a molecular simulation. We applied this approach on folding of mini-proteins Trp-cage and beta hairpin.
Submission history
[v1] 03 Feb 2022: original submission
[v2] 17 Feb 2022: added data to archive
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