ligandmpnn SKILL.md skillA

ligandmpnn from aipoch/open-science is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add aipoch/open-science/ligandmpnn@git:20260814.c9a70d8

Pins git:20260814.c9a70d8 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
aipoch/open-science
Path
resources/skills/ligandmpnn/SKILL.md
Versions recorded
2
Latest version
git:20260814.c9a70d8, committed Aug 14, 2026
First version recorded
Jul 14, 2026
Size
6,821 bytes
Repository stars
5,279
License
Apache-2.0

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.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 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

```bash
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 \
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add aipoch/open-science/ligandmpnn@sha256:57ec2d14fafdbb4b

The line at the top of this page pins the label git:20260814.c9a70d8, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_bemcr4g3or33bzl5.svg)](https://markdownregistry.com/a/art_bemcr4g3or33bzl5)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between Jul 14, 2026 and Aug 14, 2026, about one every 31 days.

versioncommittedcommitsizeaudit
git:20260814.c9a70d8 latest2026-08-14 c9a70d8 6,821 BA view · diff
git:20260714.a2a32822026-07-14 a2a3282 6,217 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (6821 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

aipoch/open-science · 5,279 stars · license Apache-2.0 · pushed 2026-10-19 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_bemcr4g3or33bzl5
GET https://markdownregistry.com/api/v1/resolve?ref=aipoch/open-science/ligandmpnn
GET https://markdownregistry.com/api/v1/blob/57ec2d14fafdbb4b58d85b8db43d229ab65c5ef1dea4a486579c7c00d7284382

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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Every file in aipoch/open-science

Other files named ligandmpnn

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ligandmpnn SKILL.md skill
yichen-zju/claude-for-research · claude/skills/ligandmpnn/SKILL.md · Design protein sequences around ligand or small-molecule contexts with LigandMPNN-style workflows. Use when a task asks…
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ligandmpnn SKILL.md skill
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