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ColabFold: making protein folding accessible to all

Cited 0 time in Web of Science Cited 2267 time in Scopus
Authors

Mirdita, Milot; Schutze, Konstantin; Moriwaki, Yoshitaka; Heo, Lim; Ovchinnikov, Sergey; Steinegger, Martin

Issue Date
2022-06
Publisher
Nature Publishing Group
Citation
Nature Methods, Vol.19 No.6, pp.679-+
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.cpm/sokrypton/colabfold and its novel environmental databases are available at https://colab-fold.mmseqs.com.
ISSN
1548-7091
URI
https://hdl.handle.net/10371/185150
DOI
https://doi.org/10.1038/s41592-022-01488-1
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