alphafold-database

Topics in the source

• AlphaFold Database
• Overview
• When to Use This Skill
• Core Capabilities
• 1. Searching and Retrieving Predictions
• 2. Downloading Structure Files
• 3. Working with Confidence Metrics
• 4. Bulk Data Access via Google Cloud

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. 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 Using Biopython (Recommended): The Biopython library provides the simplest interface for retrieving AlphaFold structures: Direct API Access: Query predictions using REST endpoints: Using UniProt to Find Accessions: Search UniProt to find protein accessions first: AlphaFold pro

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