byalterlab-ieu· 90 skills
Design protein sequences for a fixed backbone with ProteinMPNN (Dauparas 2022) — message-passing inverse folding that outputs sequences predicted to fold to a given structure, with fixed positions, tied/symmetric chains, amino-acid bias, and a soluble-model variant. Use when inverse-folding a backbone PDB into sequences, redesigning selected positions, imposing symmetry across chains, or generating the sequence step of a design→fold→score loop. For pocket/interface design WITH a bound ligand, metal, or nucleic acid prefer alterlab-ligandmpnn; to GENERATE a new backbone prefer alterlab-rfdiffusion; to refold and validate a design prefer alterlab-alphafold; for generative multimodal design prefer alterlab-esm. Part of the AlterLab Academic Skills suite.
$npx -y skills add alterlab-ieu/alterlab-academic-skills --skill alterlab-proteinmpnnInstalls into the current project.
Run `npx skills use "https://github.com/alterlab-ieu/alterlab-academic-skills" --skill "alterlab-ieu/alterlab-academic-skills/alterlab-proteinmpnn"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/alterlab-ieu/alterlab-academic-skills" that are relevant to the current task. Run `npx skills add "https://github.com/alterlab-ieu/alterlab-academic-skills"` and select the relevant skills, then follow their instructions.