alphafold-database

Name: alphafold-database
Availability: InStock
Author: OwnLab

Retrieve AlphaFold protein structures and confidence data by UniProt ID.

21|1|Updated Mar 19, 2026

Search Tags:#pdb #pae #plddt #alphafold #protein-structure #uniprot

Ready to run

npx skills add https://github.com/OwnLabAI/ownlab --skill alphafold-database-ownlabai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/OwnLabAI/ownlab/tree/main/mart/skills/scientific-skills/alphafold-database
Command: npx skills add https://github.com/OwnLabAI/ownlab --skill alphafold-database-ownlabai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Retrieve and analyze AI-predicted protein structures from AlphaFold DB by UniProt ID, download coordinates and confidence metrics, and integrate these predictions into computational workflows for research and development.

Core Features & Use Cases

Retrieve AlphaFold predictions by UniProt accession and protein name for targeted analyses.
Download model coordinates (mmCIF/BCIF/PDB), confidence scores (pLDDT), and predicted aligned error (PAE) data for downstream processing.
Access bulk datasets and metadata via Google Cloud and BigQuery to compare across proteomes and enable large-scale analyses.
Compare predicted structures with experimental data and incorporate AlphaFold results into structure-based workflows.

Quick Start

Retrieve the AlphaFold prediction for a given UniProt ID and download the associated model file and confidence data for analysis.

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 protein structures and pLDDT confidence scores using a UniProt ID?▼

AlphaFold structures can be retrieved using a UniProt accession ID to download model files in mmCIF, BCIF, or PDB formats. This process also fetches associated confidence metrics like pLDDT and PAE data for downstream processing.

What is the best way to retrieve AlphaFold PAE data and model files for large-scale protein sets?▼

The best way to retrieve AlphaFold PAE data and model files for large-scale protein sets is by leveraging Google Cloud and BigQuery. This approach supports bulk dataset access and metadata querying to compare predictions across entire proteomes.

Can I use BigQuery to access bulk AlphaFold DB metadata for structural biology workflows?▼

Yes, you can use BigQuery to access bulk AlphaFold DB metadata for structural biology workflows. The implementation supports large-scale processing of versioned data, enabling proteome-wide comparisons and integration into computational research pipelines.

Does this tool provide direct API access to download AlphaFold predictions in CIF, JSON, and PNG formats?▼

Yes, it provides direct API access to AlphaFold resources for downloading predicted protein structures. You can retrieve model coordinates, confidence data, and images in CIF, JSON, and PNG formats for your engineering workflows.

What AlphaFold DB version is supported for retrieving predicted aligned error data?▼

AlphaFold DB version 4 is supported for retrieving predicted aligned error (PAE) data. The system implements robust error handling and direct API access to ensure accurate retrieval of versioned structural predictions and metrics.