article Open AccessTop 1% cited
ColabFold: making protein folding accessible to all
Nature Methods · 2022 · Vol. 19(6) · pp. 679–682
Milot Mirdita✉(Max Planck Institute for the Study of Religious and Ethnic Diversity)Konstantin Schütze(Seoul National University)Yoshitaka Moriwaki(The University of Tokyo)Lim Heo(Michigan State University)Sergey Ovchinnikov✉(Harvard University Press)Martin Steinegger✉(Seoul National University)
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 .
Genomics and Phylogenetic StudiesMachine Learning in BioinformaticsProtein Structure and DynamicsComputer scienceProtein foldingFolding (DSP implementation)SoftwareGraphics processing unitMolecular graphicsOpen source softwareGraphicsComputational biologyProtein structure
MeSH terms
ComputersProteinsSoftwareDatabases, FactualProtein Folding
Funding
- National Science Foundation
- Japan Agency for Medical Research and Development
- National Research Foundation
- Bundesministerium für Bildung und Forschung
- Seoul National University
- Georg-August-Universität Göttingen
- National Research Foundation of Korea
- Max-Planck-Gesellschaft
- National Institutes of Health
Citations
9,275
FWCI
772.39
field-weighted impact
References
35
Percentile
100%
vs. same field & year
Citations per year
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