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ColabFold: making protein folding accessible to all

📅 Published: May 30, 2022 👤 Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki et al. 📖 Nature Methods 📊 9,615 citations
AI-Generated Summary

ColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 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.
  • 2 Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding.
  • 3 ColabFold is open-source software available at https://github.com/sokrypton/ColabFold and its novel environmental databases are available at https://colabfold.mmseqs.com .
Why It Matters

These innovations can translate to real-world improvements in technology, infrastructure, and everyday tools.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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