Skills

Ligandmpnn

Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN...

Install

npx skills add aipoch/open-science --skill ligandmpnn -g -a claude-code -y
Repository
aipoch/open-science5.4k
Category
Design
Updated
3d ago
License
Apache-2.0
Context cost
Mediumabout 1,502 tokens
Runs scripts
No, instructions only

What it does

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.

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.

Running it

pip install torch numpy biopython ProDy ml_collections dm-tree
git clone --depth 1 https://github.com/dauparas/LigandMPNN.git ligandmpnn
cd ligandmpnn
sed -i 's/np\.int\b/np.int64/g' openfold/np/residue_constants.py   # repo pins numpy 1.23; alias removed in >=1.24
bash get_model_params.sh ./model_params
python run.py \
  --model_type ligand_mpnn \
  --checkpoint_ligand_mpnn ./model_params/ligandmpnn_v_32_010_25.pt \
  --pdb_path complex.pdb \
  --out_folder out \
  --batch_size 8 --number_of_batches 4 \
  --temperature 0.1 \
  --fixed_residues "A45 A46 A47 A48"

Residue selections are space-separated {chain}{resnum} tokens inside one quoted string ("A45 A46 B10"; insertion codes append directly, "B82A"). That is the format for --fixed_residues and --redesigned_residues; --bias_AA_per_residue and --omit_AA_per_residue instead take a path to a JSON file whose keys use the same {chain}{resnum} form, and --chains_to_design is comma-separated ("A,B"). If you want to redesign only the pocket, naming the pocket residues in --redesigned_residues is usually shorter than fixing everything else.

Read the whole SKILL.md on GitHub

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