AlphaFold (https://github.com/deepmind/alphafold ) is a new tool for predicting protein structures from DeepMind. It is available as an experimental module 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.
Your output directory should contain several .pdb files, of which the “best” one should be called ranked_0.pdb. You should also find a .json file that contains the rankings, and .pkl files that contain metrics for each prediction. If one of these types of files is missing, it is possible that your run did not complete correctly.
Other Important Details
The number of threads/cores was hardcoded within the AlphaFold internal code, you should request ~8 CPU cores when submitting AlphaFold jobs. Requesting more cores will not improve performance, and it will make your job pend longer before it starts.
The required database was downloaded into a centralized location (i.e., /n/shared_db/alphafold/) for the benefit of all O2 users. Please don’t download the 2 terabytes yourself, as that would be a waste of space.
For version 2.2.0, submissions will assume you are running on a GPU by default. If for some reason you desire to run explicitly on CPU, please specify the --use_cpu flag.
As of version 2.2.0, the base implementation has changed how the amber relaxation step is requested by the user. If you would like to run your analysis WITHOUT the relaxed models with the 2.2.0 module, please include the --no_run_relax flag.