{
  "schemaVersion": 1,
  "slug": "thermompnn",
  "name": "thermompnn",
  "description": "Predict ddG of folding for point mutants with ThermoMPNN — site-saturation scans on CPU from a PDB. Covers the sign convention, how output positions map back to residue numbers, and why scoring against the repo's own test files anticorrelates.",
  "category": "models",
  "version": "1.0.0",
  "author": "Heureka Labs",
  "license": "CC-BY-4.0",
  "tags": [
    "protein-stability",
    "ddg",
    "protein-design",
    "thermompnn"
  ],
  "covers": [
    "protein stability",
    "thermostability",
    "ddG",
    "folding free energy",
    "point mutant",
    "missense",
    "site-saturation mutagenesis",
    "stabilizing mutation",
    "destabilizing mutation",
    "protein engineering",
    "mutation effect prediction",
    "megascale",
    "barnase",
    "inverse folding features"
  ],
  "updatedAt": "2026-10-14T08:21:46-04:00",
  "source": {
    "repo": "heurekalabsco/heurekaskills",
    "commit": "87bef344c860de2523de46617b1f9e4d0a34c5ac",
    "path": "skills/thermompnn"
  },
  "checksum": "sha256:a5de31b12f021781ccee7f9e8a1c0f198a19eeab6933d64f7c806eff2b41429a",
  "signals": null,
  "files": [
    {
      "path": "SKILL.md",
      "url": "https://heurekaskills.com/thermompnn/files/SKILL.md",
      "size": 23283,
      "sha256": "a9c26c48ed57e448da8e147907cca3d45bbafe827b562d481dbd24c4d8c248a1"
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}