ColabFold

Making Protein folding accessible to all via Google Colab!

• AlphaFold2_mmseqs2 - monomers=Yes, homoligomers=Yes, mmseqs2=Yes, jackhmmer=No, templates=Yes
• AlphaFold2_advanced - monomers=Yes, complexes=Yes, homoligomers=Yes, mmseqs2=Yes, jackhmmer=Yes, templates=No
• RoseTTAFold - monomers=Yes, homoligomers=No, mmseqs2=Yes, jackhmmer=No, templates=No

Official Notebook from Deepmind:

• AlphaFold2 - monomers=Yes, homoligomers=No, mmseqs2=No, jackhmmer=Yes, templates=No

OLD Experimental notebooks:

• AlphaFold2_complexes - monomers=No, complexes=Yes, mmseqs2=Yes, jackhmmer=No, templates=No
• AlphaFold2_jackhmmer - monomers=Yes, homoligomers=Yes, mmseqs2=Yes, jackhmmer=Yes, templates=No
• AlphaFold2_noTemplates_noMD
• AlphaFold2_noTemplates_yesMD

FAQ

• Can I use the models for Molecular Replacement?
  • Yes, but be CAREFUL, the bfactor column is populated with pLDDT confidence values (higher = better). Phenix.phaser expects a "real" bfactor, where (lower = better). See post from Claudia Millán.
• What is the maximum length?
  • Limits depends on free GPU provided by Google-Colab fingers-crossed
  • For GPU: Tesla T4 or Tesla P100 with ~16G the max length is ~1400
  • For GPU: Tesla K80 with ~12G the max length is ~1000
  • To check what GPU you got, open a new code cell and type !nvidia-smi

Tutorials & Presentations

• ColabFold Tutorial presented at the Boston Protein Design and Modeling Club. [video] [slides].

Acknowledgments

• We would like to thank the RoseTTAFold and AlphaFold team for doing an excellent job open sourcing the software.
• Also credit to David Koes for his awesome py3Dmol plugin, without whom these notebooks would be quite boring!
• A colab by Sergey Ovchinnikov (@sokrypton), Milot Mirdita (@milot_mirdita) and Martin Steinegger (@thesteinegger).

How do I reference this work?