BinAC/Software/Alphafold

The main documentation is available via module help bio/alphafold on the cluster. Most software modules for applications provide working example batch scripts.

Description	Content
module load	bio/alphafold
License	Apache License 2.0 - see [1]
Citing	See [2]
Links	DeepMind AlphaFold Website: [3]

Description

AlphaFold developed by DeepMind predicts protein structures from the amino acid sequence at or near experimental resolution.

Usage

The BinAC provides Alphafold via an Apptainer Container. Both, the container and the AlphaFold database is stored on the WORK filesystem. The module `bio/alphafold` provides a wrapper script called alphafold. Upon loading the module, the wrapper alphafold is in PATH and can be directly used. The wrapper behaves like the script used in DeepMind's AlphaFold GitHub repository. Thus, all options explained there are also applicable for our alphafold wrapper.

Parallel computing

The first steps of AlphaFold compute three multiple sequence alignments (MSA). These MSAs are computed on the CPU sequentially and the number of threads are hard-coded:

jackhmmer on UniRef90 using 8 threads jackhmmer on MGnify using 8 threads HHblits on BFD + Uniclust30 using 4 threads

Thus, it does not make sense to use more than 8 cores in your job! The additional cores will be idle.

The three MSAs are stored in the directory specified by --output_dir and can be reused with --use_precomputed_msas=true.

Only the model inference will run on the GPUs.