AlphaFold & ColabFold

AlphaFold and ColabFold

(run on the HMS O2 cluster)

Alphafold (from DeepMind) & ColabFold are new tools for predicting protein structures. They are available as experimental modules on O2. This means that some features may not work as expected, as the code itself was not designed with standard HPC environments in mind. AlphaFold takes fewer parameters, and uses jackhmmer as an MSA generator instead of mmseqs2, which can make it slower than ColabFold for certain inputs. It may also require more resources to run so we recommend using ColabFold for protein structure prediction.

Townhall Resources

Thank you to those who attended our Townhall on June 8th! The following resources from that event are below:

Alphafold Townhall Recording

Townhall slides:

Dr. Sergey Ovchinnikov
• Introduction to AlphaFold & ColabFold and what they’re for, examples of input & output
Slides for Dr. Ovchinnikov’s presentation

Slides for CCB/RC
• Running AlphaFold/ColabFold on O2 – Alex Truong, Calvin Cox, Roger Vargas
Slides for CCB/RC Presentation

Dr. Mohammed AlQuraishi
• OpenFold: A trainable implementation of AlphaFold
Github page

Dr. Jason Key
• SBGrid & BioGrids: how to further evaluate predictions from AlphaFold/ColabFold
Slide for Dr. Key’s Presentation

Access AlphaFold & ColabFold

AlphaFold & ColabFold are up and running.

Documentation For Alphafold

Documentation For ColabFold


  • General questions about AlphaFold or ColabFold can be sent to Sunil Poudel
  • Technical questions about AlphaFold or ColabFold should be sent to Research Computing