Alphafold Database

The alphafold-database skill provides AI agents with direct access to the AlphaFold protein structure database, enabling rapid retrieval of experimentally determined and predicted 3D protein structures. It allows agents to fetch structural data for specific proteins using UniProt IDs or search by sequence, facilitating immediate analysis without external API calls.

When to use it

• Quickly retrieve high-confidence 3D structures for known proteins identified by UniProt ID during bioinformatics workflows.
• Validate predicted protein folds against existing database entries before proceeding with simulation or drug design tasks.
• Gather structural metadata, including confidence scores and PDB IDs, to inform downstream modeling decisions.

Key capabilities

• Fetches 3D protein structures directly from the AlphaFold Database.
• Supports queries using UniProt accession numbers for precise identification.
• Returns structured data including predicted models and associated metadata.

Example prompts

• "Retrieve the top-ranked AlphaFold model for the protein with UniProt ID P04637."
• "Fetch structural predictions for a list of human kinases from the AlphaFold database."
• "Get the confidence score and PDB ID for the structure of the enzyme EC 1.1.1.1."

Tips & gotchas

Ensure you have valid UniProt IDs for accurate results, as searching by generic names may yield ambiguous matches. This skill relies on pre-computed predictions; it does not generate new structures or perform custom molecular dynamics simulations.