MHC Binding Prediction (bioSkills)

A Claude Code skill that scores peptides for binding and natural presentation by MHC class I molecules to nominate candidate CD8 T-cell epitopes and neoantigens.


Type	Claude Skill
Supplier	GPTomics bioSkills (community OSS, MIT)
Availability	GA — part of the bioSkills collection
Pricing	Free / OSS (MIT)
Capabilities	Read/Write — Claude runs the skill’s workflow locally (Bash/Python), not as an MCP tool
Verified	works · 2026-07-20
Security	cleared · 2026-07-20 — provenance matches GPTomics, MIT repo maintained, no OSV advisories

How to install

bioSkills is not an npm package — clone the repo, then either run the installer for the whole category or copy the single skill directory.

Claude Code — clone and install via the bundled script:
```
git clone https://github.com/GPTomics/bioSkills
cd bioSkills
./install-claude.sh --categories "immunoinformatics"
```
The installer copies matching skills into ~/.claude/skills/ (default target). Use --list to preview and --dry-run to see what would be copied.
Claude Code / other agents — copy just this one skill:
```
cp -r bioSkills/immunoinformatics/mhc-binding-prediction ~/.claude/skills/
```
(run from inside your clone; otherwise replace bioSkills/ with the absolute path of your clone). Install MHCflurry (pip install mhcflurry && mhcflurry-downloads fetch) when prompted; NetMHCpan-4.1 and MixMHCpred are separate academic downloads.

What it does

Ranks peptides for MHC class I binding and presentation using three complementary predictors:

MHCflurry — pip-installable Python presentation predictor with flexible allele parsing.
NetMHCpan-4.1 — the field-standard predictor with the broadest allele coverage.
MixMHCpred — mass-spec–grounded presentation scoring.

The skill teaches the practical distinctions that matter (binding-affinity vs. eluted-ligand scoring, %Rank vs. raw nM for cross-allele comparisons) and the common failure modes (eluted-ligand abundance bias under-ranking low-expression neoantigens; pan-model extrapolation error on rare alleles). It stresses that predicted binding is necessary but not sufficient for immunogenicity.

Primary use cases: scanning proteins for class I epitopes, scoring tumor neoantigen candidates, choosing the right predictor for a given allele/question.

Notes

Distributed as a SKILL.md in the bioSkills collection — Claude executes the workflow locally via Bash/Python rather than as an MCP server. Upstream front-matter name: bio-immunoinformatics-mhc-binding-prediction. Complementary to the broader Epitope Prediction bioSkills skill (which also covers B-cell and class II). NetMHCpan/MixMHCpred require separate academic-use downloads from their vendors. Upstream directory: immunoinformatics/mhc-binding-prediction.

Sources

Installed this tool?

Share feedback — install path, OS, errors, workarounds. The form opens with this tool pre-selected and a link back to this page.