alphafold-database

Retrieve, analyze, and bulk download AlphaFold protein structures and confidence metrics.

Updated May 10, 2026

Search Tags:#bioinformatics #alphafold #protein modeling #structure prediction #cloud data #protein structures #confidence metrics

Ready to run

npx skills add https://github.com/Imad-Oute/ResearchForge --skill alphafold-database-imad-oute

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/Imad-Oute/ResearchForge/tree/main/OpenSource-Projects/claude-scientific-skills/scientific-skills/alphafold-database
Command: npx skills add https://github.com/Imad-Oute/ResearchForge --skill alphafold-database-imad-oute

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires biopython, requests, google-cloud-bigquery, gsutil, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides seamless access to AlphaFold's extensive database of AI-predicted protein structures, enabling researchers to retrieve detailed structural information efficiently.

Core Features & Use Cases

Structure Retrieval: Fetch predicted 3D structures by UniProt ID or protein name for drug discovery and structural biology research.
Confidence Analysis: Analyze confidence metrics like pLDDT and PAE to assess prediction reliability for individual residues and domain arrangements.
Bulk Data Access: Download entire proteome datasets via Google Cloud Platform for large-scale proteomics studies. Example: obtain all human proteome models for comparative analysis.

Quick Start

Query a protein accession to download its predicted structure files or analyze confidence scores for structural assessment.

Frequently Asked Questions about alphafold-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I retrieve AlphaFold protein structures using a UniProt ID?▼

AlphaFold protein structures can be retrieved by querying a protein accession or UniProt ID to download predicted 3D structure files and associated metadata in mmCIF, PDB, and JSON formats.

What do pLDDT and PAE confidence metrics indicate in AlphaFold predictions?▼

pLDDT and PAE confidence metrics assess the reliability of AlphaFold structure predictions for individual residues and domain arrangements, enabling researchers to validate structural models for proteomics studies.

Can I download entire proteome datasets from AlphaFold for large-scale analysis?▼

You can download entire AlphaFold proteome datasets via Google Cloud Platform using BigQuery and gsutil, enabling large-scale comparative proteomics studies such as obtaining all human proteome models.

Does this AlphaFold database retrieval method require Google Cloud credentials?▼

Bulk downloading AlphaFold proteome datasets via Google Cloud Platform requires appropriate cloud credentials to utilize BigQuery and gsutil for large-scale structure prediction retrieval.

What is the best way to analyze AlphaFold confidence scores for specific protein domains?▼

Analyzing AlphaFold confidence scores involves retrieving JSON metadata files to evaluate pLDDT and PAE metrics, enabling detailed assessment of prediction reliability for specific domain arrangements.