Abstract

Abstract ColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold’s 40−60-fold faster search and optimized model utilization enables prediction of close to 1,000 structures per day on a server with one graphics processing unit. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at https://github.com/sokrypton/ColabFold and its novel environmental databases are available at https://colabfold.mmseqs.com .

Keywords

Computer scienceProtein foldingFolding (DSP implementation)SoftwareGraphics processing unitMolecular graphicsOpen source softwareGraphicsComputational biologyProtein structureComputational scienceComputer graphicsComputer graphics (images)BioinformaticsChemistryProgramming languageOperating systemBiologyBiochemistryEngineering

MeSH Terms

ComputersDatabasesFactualProtein FoldingProteinsSoftware

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Publication Info

Year
2022
Type
article
Volume
19
Issue
6
Pages
679-682
Citations
8663
Access
Closed

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Cite This

Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki et al. (2022). ColabFold: making protein folding accessible to all. Nature Methods , 19 (6) , 679-682. https://doi.org/10.1038/s41592-022-01488-1

Identifiers

DOI
10.1038/s41592-022-01488-1
PMID
35637307
PMCID
PMC9184281

Data Quality

Data completeness: 86%