This gives you programmatic access to AlphaFold's 200+ million AI-predicted protein structures through both Biopython and direct REST APIs. You can pull structures by UniProt ID, download PDB/mmCIF files, and analyze confidence metrics like pLDDT scores and PAE matrices to figure out which parts of a prediction are reliable. The skill covers bulk downloads via Google Cloud for whole proteomes and shows how to parse structures for computational work. Honestly most useful when you need a structural starting point for proteins without experimental data, or when you're doing structure-based drug discovery at scale. The confidence metrics are critical since not all predictions are equally trustworthy, and this walks through interpreting them properly.
npx -y skills add davila7/claude-code-templates --skill alphafold-database --agent claude-codeInstalls into .claude/skills of the current project.
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