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ligandmpnn

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Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.

resources/skills/ligandmpnn/SKILL.md

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# LigandMPNN

LigandMPNN extends the ProteinMPNN graph with non-protein atoms — small
molecules, nucleic acids, and metals are visible to the network — so it is the
right inverse-folding tool whenever the design surface includes a bound ligand
or cofactor that vanilla `proteinmpnn` would ignore. The same `run.py` is also
the most convenient runner for the other MPNN families because, unlike the
original ProteinMPNN script, it threads designs back onto the input structure
and writes PDBs alongside the FASTA. Code and weights are MIT
(github.com/dauparas/LigandMPNN). The model is small enough to run on CPU —
for a handful of designs on one structure that is seconds and usually faster
than dispatching, so the normal path is local with
`pip install torch numpy biopython ProDy ml_collections dm-tree`; a GPU helps
for batched campaigns.
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