Install

The skill file stays in the publisher's repository.

Paste the copied command in a terminal. It installs this SKILL.md into that agent.

npx skills add aipoch/open-science --skill proteinmpnn -a cursor -y

Download skill

resources/skills/proteinmpnn/SKILL.md on GitHub

Questions

How do I install proteinmpnn?

Download resources/skills/proteinmpnn/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.

Where does proteinmpnn live?

The publisher keeps it at https://github.com/aipoch/open-science.

Which agents can use proteinmpnn?

Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.

name: proteinmpnn description: > Inverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding. license: Apache-2.0 category: biomodels metadata: display-name: ProteinMPNN

Dauparas). verified 2026-06-30

third_party: - kind: weights name: ProteinMPNN license: MIT terms_url: https://github.com/dauparas/ProteinMPNN/blob/main/LICENSE

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 — adds those atoms to the graph with a near-identical CLI, and 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 ). Either way the repo is cloned in-job — there is no PyPI dist and the checkpoints are bundled in the repo.

`--model_name`	training noise	use
`v_48_002`	0.02 Å	highest recovery; close-to-native redesigns
`v_48_020` (default)	0.20 Å	de novo backbones — tolerates RFdiffusion imperfection
`v_48_030`	0.30 Å	very rough backbones; lowest recovery
`--use_soluble_model`	—	swaps to the soluble-trained set; see `solublempnn`

You see	It means / do this
`KeyError: 'A'`	Chain letter not in the PDB — `grep '^ATOM' file.pdb \| cut -c22 \| sort -u` to see what is.
`JSONDecodeError` on a `*_jsonl` flag	The flag wants a file path, not inline JSON; write the file first.
All positions redesigned despite `--fixed_positions_jsonl`	Outer PDB-stem key missing — see the gotcha above.
`ModuleNotFoundError` for relative imports	Script run from the wrong cwd — `cd` into the cloned repo first; the imports are repo-relative.

proteinmpnn

Install

Related skills

Questions

github.com/dauparas/ProteinMPNN/blob/main/LICENSE: MIT (© 2022 Justas

Dauparas). verified 2026-06-30

third_party: - kind: weights name: ProteinMPNN license: MIT terms_url: https://github.com/dauparas/ProteinMPNN/blob/main/LICENSE

ProteinMPNN

Running it

A flat chain map in `--fixed_positions_jsonl` silently redesigns every residue

Checkpoints — which one to pick

Errors worth recognizing

Install

Related skills

Questions

github.com/dauparas/ProteinMPNN/blob/main/LICENSE: MIT (© 2022 Justas

Dauparas). verified 2026-06-30

third_party: - kind: weights name: ProteinMPNN license: MIT terms_url: https://github.com/dauparas/ProteinMPNN/blob/main/LICENSE

ProteinMPNN

Running it

A flat chain map in --fixed_positions_jsonl silently redesigns every residue

Checkpoints — which one to pick

Errors worth recognizing

A flat chain map in `--fixed_positions_jsonl` silently redesigns every residue