alphafold-database

Name: alphafold-database
Availability: InStock
Author: HolobiomicsLab

Retrieve AlphaFold protein structures and confidence metrics by UniProt ID.

4|1|Updated Jun 18, 2025

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

Ready to run

npx skills add https://github.com/HolobiomicsLab/Toolomics --skill alphafold-database-holobiomicslab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/HolobiomicsLab/Toolomics/tree/main/mcp_host/skills/scientific-skills/scientific-skills/alphafold-database
Command: npx skills add https://github.com/HolobiomicsLab/Toolomics --skill alphafold-database-holobiomicslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

AlphaFold DB provides ready-to-use protein structure predictions and confidence data, enabling researchers to access structural models without building predictions from scratch.

Core Features & Use Cases

Retrieve predictions by UniProt ID or gene name
Downloading model coordinates (mmCIF/bcif/pdb) and confidence metrics (pLDDT, PAE)
Analyze confidence metrics to prioritize high-confidence regions for modeling or docking
Leverage Google Cloud or BigQuery for bulk access and analytics

Quick Start

Query a UniProt accession like P00520 to fetch the AlphaFold prediction and download the model_v4.cif for local 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 predicted protein structures using a UniProt ID?▼

To download AlphaFold predicted protein structures, query the database by UniProt accession like P00520 to retrieve model coordinates and download them in mmCIF, bcif, or PDB format for local structural biology analysis.

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

pLDDT and PAE confidence metrics in AlphaFold predictions indicate per-residue positional confidence and predicted aligned error, helping researchers prioritize high-confidence regions for downstream modeling or docking workflows.

Can I retrieve AlphaFold model coordinates in PDB format instead of mmCIF?▼

Yes, you can retrieve AlphaFold model coordinates in PDB format. The database supports downloading predictions in multiple coordinate formats including mmCIF, bcif, and PDB to accommodate various structural biology workflows.

What is the best way to access bulk AlphaFold structures and confidence metrics for large-scale analysis?▼

The best way to access bulk AlphaFold structures and confidence metrics is by leveraging Google Cloud or BigQuery, which supports bulk access and analytics for large-scale downstream processing without querying individual predictions individually.

Does the AlphaFold database provide model predictions compatible with the v4 data version?▼

Yes, the AlphaFold database provides model predictions compatible with the v4 data version. You can download the model_v4.cif file directly using a valid UniProt ID to ensure you are using the latest prediction data.

What are the limitations of using AlphaFold DB confidence metrics for docking workflows?▼

AlphaFold DB confidence metrics like pLDDT and PAE should be used to identify reliable domains, but high confidence does not guarantee accurate docking interfaces, meaning you must independently validate interaction surfaces for downstream docking workflows.