About Alphafold/Colabfold

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

Info Sessions / Town Halls

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
• Colab
• Github page

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

Point of Contact (questions, etc.)