# ColabFold: making protein folding accessible to all

> 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 o...

## Metadata
- Authors: Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, Lim Heo, Sergey Ovchinnikov, Martin Steinegger
- Journal: Nature Methods
- Published: 2022-05-30
- DOI: https://doi.org/10.1038/s41592-022-01488-1
- Citations: 9,813
- Source: OpenAlex
- Access: Open Access

## Technology Hub
- Hub: Protein Structure Prediction
- Discipline: Biochemistry / AI
- Hub URL: https://science-database.com/technology/protein-structure
- Hub llms.txt: https://science-database.com/technology/protein-structure/llms.txt

## 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 .

## Links
- DOI: https://doi.org/10.1038/s41592-022-01488-1
- OpenAlex: https://openalex.org/W4281790889
- PDF: https://www.nature.com/articles/s41592-022-01488-1.pdf
- JSON API: https://science-database.com/api/v1/technology/protein-structure

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Paper ID: oa-W4281790889 | Hub: protein-structure