AlphaFold Database

Overview

AlphaFold DB is a public repository of AI-predicted 3D protein structures maintained by Google DeepMind and EMBL-EBI. Release v6 (October 2025, synced to UniProt 2025_03) holds ~241 million predictions, including ~40k isoforms and the input MSAs; since March 2026 it also serves precomputed homodimer and heterodimer complex predictions. 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 (EMBL-EBI FTP or 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