proteinmpnn
ProteinMPNN
ProteinMPNN is the default inverse-folding step in the binder pipeline: a
message-passing network that sees backbone geometry only, so it is the right
choice when the design surface is protein–protein and the wrong one as soon as
a ligand, nucleic acid, or metal is part of the interface — ligandmpnn adds
those atoms to the graph with a near-identical CLI, and solublempnn swaps in
weights trained on soluble structures for an expression-biased prior. Code and
weights are MIT (github.com/dauparas/ProteinMPNN). The model is small enough
to run on CPU — for a handful of sequences on one backbone that is seconds and
usually faster than dispatching a remote job; a GPU helps for batched
campaigns (hundreds of backbones or large --num_seq_per_target). Either way
the repo is cloned in-job — there is no PyPI dist and the checkpoints are
bundled in the repo.