alphafold-database

Name: alphafold-database
Availability: InStock
Author: Org-GAgent

Retrieve AlphaFold protein structures and confidence metrics via REST API.

Updated Aug 23, 2026

Search Tags:#drug-discovery #pae #plddt #alphafold #protein-structure #uniprot

Ready to run

npx skills add https://github.com/Org-GAgent/result-interpreter --skill alphafold-database-org-gagent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/Org-GAgent/result-interpreter/tree/main/.skills/scientific-skills/alphafold-database
Command: npx skills add https://github.com/Org-GAgent/result-interpreter --skill alphafold-database-org-gagent

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AlphaFold DB provides researchers with access to AI-predicted protein structures and their confidence metrics, enabling rapid exploration and integration into computational workflows.

Core Features & Use Cases

Retrieve predictions by UniProt accession, organism, or query; download structure files in mmCIF, bcif, or PDB formats.
Analyze per-residue confidence (pLDDT) and the Predicted Aligned Error (PAE) to assess reliability and domain arrangement.
Use Case: Bulk proteome analyses and structure-based drug discovery by comparing high-confidence regions across proteins.

Quick Start

Use the AlphaFold REST API to fetch a prediction by UniProt accession and download its structure file along with confidence metrics for immediate analysis.

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 structure predictions using a UniProt accession?▼

Per-residue confidence is measured using pLDDT, while the Predicted Aligned Error (PAE) evaluates domain arrangement reliability. Analyzing pLDDT and PAE helps assess the structural confidence of AlphaFold predictions.

Can I perform bulk proteome-scale analyses with AlphaFold structure data?▼

AlphaFold predictions are AI-generated models, meaning confidence varies across regions. Low pLDDT scores or high PAE values indicate unreliable areas, so researchers should validate critical structural features experimentally.

Why should I check pLDDT and PAE metrics when analyzing AlphaFold structures?▼

Checking pLDDT and PAE metrics is essential because pLDDT measures per-residue confidence and PAE assesses domain arrangement reliability. Together they determine which regions of AlphaFold protein structures are trustworthy.

What is the best way to download AlphaFold structure files for computational workflows?▼

The best way to download AlphaFold structure files is via the REST API, which provides access to mmCIF, bcif, and PDB formats. This allows seamless integration into computational workflows for structural biology.