UniProt Database Access

SkillAI & models

Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the UniProt Database Access skill

What this skill tells your AI

The instructions your AI receives, as published by biotender-max/awesome-bio-agent-skills in skills/adaptyv/uniprot/SKILL.md and read by ahel’s review.

Note: This skill uses the UniProt REST API directly. No Modal deployment needed - all operations run locally via HTTP requests.

Fetching Sequences

By Accession

# FASTA format
curl "https://rest.uniprot.org/uniprotkb/P00533.fasta"

# JSON format with annotations
curl "https://rest.uniprot.org/uniprotkb/P00533.json"

Using Python

import requests

def get_uniprot_sequence(accession):
    """Fetch sequence from UniProt."""
    url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta"
    response = requests.get(url)
    if response.ok:
        lines = response.text.strip().split('\n')
        header = lines[0]
        sequence = ''.join(lines[1:])
        return header, sequence
    return None, None

Getting Annotations

Full Entry

def get_uniprot_entry(accession):
    """Fetch full UniProt entry as JSON."""
    url = f"https://rest.uniprot.org/uniprotkb/{accession}.json"
    response = requests.get(url)
    return response.json() if response.ok else None

entry = get_uniprot_entry("P00533")
print(f"Protein: {entry['proteinDescription']['recommendedName']['fullName']['value']}")

Domain Boundaries

def get_domains(accession):
    """Extract domain annotations."""
    entry = get_uniprot_entry(accession)
    domains = []

    for feature in entry.get('features', []):
        if feature['type'] == 'Domain':
            domains.append({
                'name': feature.get('description', ''),
                'start': feature['location']['start']['value'],
                'end': feature['location']['end']['value']
            })

    return domains

# Example: EGFR domains
domains = get_domains("P00533")
# [{'name': 'Kinase', 'start': 712, 'end': 979}, ...]

Searching UniProt

By Gene Name

def search_uniprot(query, organism=None, limit=10):
    """Search UniProt by query."""
    url = "https://rest.uniprot.org/uniprotkb/search"
    params = {
        "query": query,
        "format": "json",
        "size": limit
    }
    if organism:
        params["query"] += f" AND organism_id:{organism}"

    response = requests.get(url, params=params)
    return response.json()['results']

# Search for human EGFR
results = search_uniprot("EGFR", organism=9606)

By Sequence Similarity (BLAST)

# Use UniProt BLAST
# https://www.uniprot.org/blast

Cross-References

Get PDB Structures

def get_pdb_references(accession):
    """Get PDB structures for UniProt entry."""
    entry = get_uniprot_entry(accession)
    pdbs = []

    for xref in entry.get('uniProtKBCrossReferences', []):
        if xref['database'] == 'PDB':
            pdbs.append({
                'pdb_id': xref['id'],
                'method': xref.get('properties', [{}])[0].get('value', ''),
                'chains': xref.get('properties', [{}])[1].get('value', '')
            })

    return pdbs

# Example: PDB structures for EGFR
pdbs = get_pdb_references("P00533")

Common Use Cases

Target Selection

# 1. Find protein by name
results = search_uniprot("insulin receptor", organism=9606)

# 2. Get accession
accession = results[0]['primaryAccession']  # e.g., P06213

# 3. Get domains
domains = get_domains(accession)

# 4. Find PDB structure
pdbs = get_pdb_references(accession)

# 5. Download best structure for design

Sequence Alignment Info

def get_sequence_variants(accession):
    """Get natural variants from UniProt."""
    entry = get_uniprot_entry(accession)
    variants = []

    for feature in entry.get('features', []):
        if feature['type'] == 'Natural variant':
            variants.append({
                'position': feature['location']['start']['value'],
                'original': feature.get('alternativeSequence', {}).get('originalSequence', ''),
                'variant': feature.get('alternativeSequence', {}).get('alternativeSequences', [''])[0],
                'description': feature.get('description', '')
            })

    return variants

API Reference

EndpointDescription
/uniprotkb/{id}.fastaFASTA sequence
/uniprotkb/{id}.jsonFull entry JSON
/uniprotkb/searchSearch entries
/uniprotkb/streamBatch download

Troubleshooting

Entry not found: Check accession format (e.g., P00533) Rate limits: Add delay between requests Large downloads: Use stream endpoint with pagination


Next: Use sequence with esm for embeddings or colabfold for structure.

Signals

GitHub stars
178
Forks
32
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
uniprot-biotender-max
Source
github.com/biotender-max/awesome-bio-agent-skills