google-deepmind/alphafold v2.2.0

AlphaFold v2.2.0

on GitHub

Version v2.2.0 updates the AlphaFold-Multimer model parameters. These new models have greatly reduced numbers of clashes on average and are slightly more accurate. Read the updated AlphaFold-Multimer paper for more details.

A number of other bug fixes and small improvements have been made.

Change log

• Added new AlphaFold-Multimer models with greatly reduced numbers of clashes on average and slightly increased accuracy.
• Use DeviceRequest rather than runtime=nvidia to expose GPUs to the container (thanks @aburger).
• Simplified mounting of files in Docker.
• Removed unused bias argument in GlobalAttention (thanks @breadbread1984).
• Removed prokaryotic MSA pairing algorithm as it didn’t improve accuracy on average.
• Added the ability to run with multiple seeds per model to match the AlphaFold-Multimer paper.
• Fixed degraded performance when using num_recycle=0 with models trained with recycling due to incorrect skipping of layers (thanks @sokrypton).
• Added split_rng=False (current default) to sharded_map to support new Haiku release.
• Removed unused code in amber_minimize.py.