Shipped model weights
proteinmpnn/ holds the ProteinMPNN checkpoints BC2 redesigns with, so an installation carries them
and no campaign names a path. Three variants of the same four models, each directory named for the one it holds: weights_neutral/
is the original release, weights_negative/ the soluble-protein retraining BC2 uses by default, weights_positive/
the HyperMPNN thermostability retraining, each named for the surface charge it favours.
mpnn_variant selects between them and mpnn_model between v_48_002, v_48_010, v_48_020 and
v_48_030, the backbone-noise levels the models were trained at. Each checkpoint is an .npz
holding one array per parameter, keyed <module>|<parameter> beside the num_edges and
noise_level it was trained with, so loading one reads no pickle. Neutral and negative weights are
from dauparas/ProteinMPNN (MIT), positive weights from meilerlab/HyperMPNN (MIT).
alphafold/ is empty in the repository and is where a container bakes its AlphaFold parameters. The
2022-12-06 release is 5.3 GB, so an ordinary installation downloads it once into
~/.cache/bindcraft/alphafold on its first campaign instead. bindcraft fetch-weights does the same
download on demand, which is what a compute node with no route to the internet needs run for it on a
login node first. The parameters are CC-BY-4.0, DeepMind, and their licence travels in the archive.