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alphafold-database

Retrieve AlphaFold protein structures and confidence metrics by UniProt ID.

Updated Jan 10, 2026
Search Tags:#bioinformatics#protein structure#drug discovery#alphafold#uniprot#structural biology
One-click install
npx skills add https://github.com/robinbarvaag/poynt --skill alphafold-database-robinbarvaag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/alphafold-database
Command: npx skills add https://github.com/robinbarvaag/poynt --skill alphafold-database-robinbarvaag

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides programmatic access to AlphaFold's vast repository of AI-predicted protein structures, enabling researchers to retrieve, analyze, and utilize these crucial biological models.

Core Features & Use Cases

  • Structure Retrieval: Fetch protein structures by UniProt ID.
  • Confidence Analysis: Evaluate prediction reliability using pLDDT and PAE scores.
  • Bulk Data Access: Download entire proteomes or specific datasets via Google Cloud.
  • Use Case: A structural biologist needs to investigate the potential binding site of a newly identified protein. They use this Skill to download the predicted structure, analyze its confidence metrics, and visualize the 3D model for further study.

Quick Start

Use the alphafold-database skill to download the structure for UniProt ID P00520.

Frequently Asked Questions about alphafold-database

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

FAQPage Schema
How do I download AlphaFold predicted protein structures using a UniProt ID?▼

You can retrieve AlphaFold protein structures by providing a UniProt ID to fetch the corresponding PDB or mmCIF files. This enables direct access to AI-predicted 3D models for structural biology analysis.

How do I analyze AlphaFold pLDDT and PAE confidence scores programmatically?▼

AlphaFold pLDDT and PAE confidence scores can be analyzed by extracting them from retrieved prediction data to evaluate model reliability. This helps assess the structural confidence of specific protein regions.

Can I download entire AlphaFold proteomes in bulk via Google Cloud?▼

Yes, bulk downloading of entire AlphaFold proteomes is supported via Google Cloud. The Skill integrates Google Cloud BigQuery and gsutil to retrieve large-scale protein structure datasets programmatically.

What file formats are available when retrieving AlphaFold protein structures?▼

AlphaFold protein structures are available in PDB and mmCIF file formats. These standard structural biology formats enable you to load and analyze AI-predicted 3D models in compatible visualization software.

Does this AlphaFold database access tool require Biopython for structure analysis?▼

Yes, Biopython is required for parsing and analyzing retrieved AlphaFold protein structures. Additional dependencies like numpy, scipy, and pandas support the evaluation of confidence metrics and structural data processing.

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