alphafold-database

# AlphaFold Database ## Overview AlphaFold DB is a public repository of AI-predicted 3D protein structures for over 200 million proteins, maintained by DeepMind and EMBL-EBI. Access structure predictions with confidence metrics, download coordinate files, retrieve bulk datasets, and integrate predictions into computational workflows. ## When to Use This Skill This skill should be used when working with AI-predicted protein structures in scenarios such as: - Retrieving protein structure predictions by UniProt ID or protein name - Downloading PDB/mmCIF coordinate files for structural analysis - Analyzing prediction confidence metrics (pLDDT, PAE) to assess reliability - Accessing bulk proteome datasets via Google Cloud Platform - Comparing predicted structures with experimental data - Performing structure-based drug discovery or protein engineering - Building structural models for proteins lacking experimental structures - Integrating AlphaFold predictions into computational pipelines ## Core Capabilities ### 1. Searching and Retrieving Predictions **Using Biopython (Recommended):** The Biopython library provides the simplest interface for retrieving AlphaFold structures: ```python from Bio.PDB import alphafold_db # Get all predictions for a UniProt accession predictions = list(alphafold_db.get_predictions("P00520")) # Download structure file (mmCIF format) for prediction in predictions: cif_file = alphafold_db.download_cif_for(prediction, directory="./structure...