protein-structure-for-gene

Resolve gene symbols to UniProt accessions and render domain maps.

64|12|Updated Apr 7, 2026

Search Tags:#bioinformatics #structure #pdb #alphafold #protein #uniprot #domain-map

Ready to run

npx skills add https://github.com/MDhewei/bioinfor-claw --skill protein-structure-for-gene

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: protein-structure-for-gene
Source: https://github.com/MDhewei/bioinfor-claw/tree/main/protein-structure-analysis/protein-structure-for-gene
Command: npx skills add https://github.com/MDhewei/bioinfor-claw --skill protein-structure-for-gene

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, pandas, requests, and includes scripts (resource) components.

What problem does it solve?

Retrieve comprehensive protein structural information for a given gene symbol by resolving to a UniProt accession, gathering domain/feature annotations, listing experimental PDB structures from RCSB, fetching AlphaFold2 predictions from AlphaFold DB, and rendering a publication-quality linear domain map.

Core Features & Use Cases

UniProt metadata retrieval: canonical accession, gene name, organism, sequence length, and features.
Domain and feature annotation retrieval from UniProt.
PDB structure discovery from RCSB (experimental structures) with method, resolution, and PubMed references.
AlphaFold2 prediction entry lookup from AlphaFold DB.
Domain map rendering: publication-ready linear schematic of annotated features.
All data is live from public APIs and does not require local data files.

Quick Start

Provide a gene symbol and an output directory to run the full protein-structure-for-gene workflow.

Frequently Asked Questions about protein-structure-for-gene

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

FAQPage Schema

How do I fetch protein structure data and domain annotations for a gene symbol?▼

To fetch protein structure data, provide a gene symbol to resolve its UniProt canonical accession, retrieving domain annotations, experimental PDB structures, and AlphaFold2 predictions.

What is the best way to generate a publication-quality linear domain map for a protein?▼

Generating a publication-quality linear domain map requires parsing UniProt feature annotations and PDB structures, rendering a visual schematic of annotated domains for downstream analysis.

Can I retrieve experimental PDB structures and AlphaFold predictions simultaneously?▼

Yes, you can retrieve experimental PDB structures and AlphaFold predictions simultaneously by querying the RCSB and AlphaFold DB public APIs using a resolved UniProt accession.

Do I need local data files to map UniProt domains and features?▼

No, you do not need local data files to map UniProt domains and features, as all metadata, domain annotations, and structural predictions are gathered live from public APIs.

What outputs are produced when retrieving protein metadata and structural entries?▼

Outputs produced when retrieving protein metadata include summary TSVs, feature tables containing domain annotations, and a rendered visualization of the linear domain map.