alterlab-uniprot

name	alterlab-uniprot
description	Provide direct REST API access to UniProt (Swiss-Prot/TrEMBL) for protein sequence searches, FASTA retrieval, functional annotations (GO terms, domains), and cross-database ID mapping. Use when looking up a protein entry, fetching a protein FASTA sequence, or mapping accessions between databases over raw HTTP/REST; for EXPERIMENTAL 3D structures prefer alterlab-pdb, for AI-PREDICTED 3D structures prefer alterlab-alphafold-db, for protein-protein interaction networks prefer alterlab-string-db, and for Python workflows spanning many databases prefer bioservices instead. Part of the AlterLab Academic Skills suite.
license	MIT
allowed-tools	Read WebFetch Bash(curl:*) Bash(python:*)
compatibility	Keyless UniProt REST API (no authentication required)
metadata	{"skill-author":"AlterLab","version":"1.0.0"}

UniProt Database

Overview

UniProt is the world's leading comprehensive protein sequence and functional information resource. Search proteins by name, gene, or accession, retrieve sequences in FASTA format, perform ID mapping across databases, access Swiss-Prot/TrEMBL annotations via REST API for protein analysis.

When to Use This Skill

This skill should be used when:

• Searching for protein entries by name, gene symbol, accession, or organism
• Retrieving protein sequences in FASTA or other formats
• Mapping identifiers between UniProt and external databases (Ensembl, RefSeq, PDB, etc.)
• Accessing protein annotations including GO terms, domains, and functional descriptions
• Batch retrieving multiple protein entries efficiently
• Querying reviewed (Swiss-Prot) vs. unreviewed (TrEMBL) protein data
• Streaming large protein datasets
• Building custom queries with field-specific search syntax

Core Capabilities

1. Searching for Proteins

Search UniProt using natural language queries or structured search syntax.

Common search patterns:

# Search by protein name
query = "insulin AND organism_name:\"Homo sapiens\""

# Search by gene name
query = "gene:BRCA1 AND reviewed:true"

# Search by accession
query = "accession:P12345"

# Search by sequence length
query = "length:[100 TO 500]"

# Search by taxonomy
query = "taxonomy_id:9606"  # Human proteins

# Search by GO term
query = "go:0005515"  # Protein binding

Use the API search endpoint: https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}

Supported formats: JSON, TSV, Excel, XML, FASTA, RDF, TXT

2. Retrieving Individual Protein Entries

Retrieve specific protein entries by accession number.

Accession number formats:

• Classic: P12345, Q1AAA9, O15530 (6 characters: letter + 5 alphanumeric)
• Extended: A0A022YWF9 (10 characters for newer entries)

Retrieve endpoint: https://rest.uniprot.org/uniprotkb/{accession}.{format}

Example: https://rest.uniprot.org/uniprotkb/P12345.fasta

3. Batch Retrieval and ID Mapping

Map protein identifiers between different database systems and retrieve multiple entries efficiently.

ID Mapping workflow:

1. Submit mapping job (POST): https://rest.uniprot.org/idmapping/run with from, to, ids
2. Poll job status: https://rest.uniprot.org/idmapping/status/{jobId}
3. Retrieve results: https://rest.uniprot.org/idmapping/results/{jobId}

Two non-obvious gotchas (both handled in scripts/uniprot_client.py):

• The status endpoint returns {"jobStatus":"RUNNING"} then {"jobStatus":"FINISHED"} (a finished job also 303-redirects to the results URL). It does NOT return a results/failedIds key, so poll on jobStatus == "FINISHED", not on the presence of results.
• Results are paginated (default size=25, max 500). The first page is only part of a large mapping; follow the next Link response header (response.links["next"] in requests) until it is gone. The same next-Link pagination applies to the /uniprotkb/search endpoint — the JSON body carries only results, never a next key.

Supported databases for mapping:

• UniProtKB AC/ID
• Gene names
• Ensembl, RefSeq, EMBL
• PDB, AlphaFoldDB
• KEGG, GO terms
• And many more (see /references/id_mapping_databases.md)

Limitations:

• Maximum 100,000 IDs per job
• Results stored for 7 days

4. Streaming Large Result Sets

For large queries that exceed pagination limits, use the stream endpoint:

https://rest.uniprot.org/uniprotkb/stream?query={query}&format={format}

The stream endpoint returns all results without pagination, suitable for downloading complete datasets.

5. Customizing Retrieved Fields

Specify exactly which fields to retrieve for efficient data transfer.

Common fields:

• accession - UniProt accession number
• id - Entry name
• gene_names - Gene name(s)
• organism_name - Organism
• protein_name - Protein names
• sequence - Amino acid sequence
• length - Sequence length
• go_* - Gene Ontology annotations
• cc_* - Comment fields (function, interaction, etc.)
• ft_* - Feature annotations (domains, sites, etc.)

Example: https://rest.uniprot.org/uniprotkb/search?query=insulin&fields=accession,gene_names,organism_name,length,sequence&format=tsv

See /references/api_fields.md for complete field list.

Python Implementation

For programmatic access, use the provided helper script scripts/uniprot_client.py which implements:

• search_proteins(query, format) - Search UniProt with any query
• get_protein(accession, format) - Retrieve single protein entry
• map_ids(ids, from_db, to_db) - Map between identifier types
• batch_retrieve(accessions, format) - Retrieve multiple entries
• stream_results(query, format) - Stream large result sets

Alternative Python packages:

• Unipressed: Modern, typed Python client for UniProt REST API
• bioservices: Comprehensive bioinformatics web services client

Query Syntax Examples

Boolean operators:

kinase AND organism_name:human
(diabetes OR insulin) AND reviewed:true
cancer NOT lung

Field-specific searches:

gene:BRCA1
accession:P12345
organism_id:9606
taxonomy_name:"Homo sapiens"
annotation:(type:signal)

Range queries:

length:[100 TO 500]
mass:[50000 TO 100000]

Wildcards:

gene:BRCA*
protein_name:kinase*

See /references/query_syntax.md for comprehensive syntax documentation.

Best Practices

1. Use reviewed entries when possible: Filter with reviewed:true for Swiss-Prot (manually curated) entries
2. Specify format explicitly: Choose the most appropriate format (FASTA for sequences, TSV for tabular data, JSON for programmatic parsing)
3. Use field selection: Only request fields you need to reduce bandwidth and processing time
4. Handle pagination: For large result sets, implement proper pagination or use the stream endpoint
5. Cache results: Store frequently accessed data locally to minimize API calls
6. Rate limiting: Be respectful of API resources; implement delays for large batch operations
7. Check data quality: TrEMBL entries are computational predictions; Swiss-Prot entries are manually reviewed

Resources

scripts/

uniprot_client.py - Python client with helper functions for common UniProt operations including search, retrieval, ID mapping, and streaming.

references/

• api_fields.md - Complete list of available fields for customizing queries
• id_mapping_databases.md - Supported databases for ID mapping operations
• query_syntax.md - Comprehensive query syntax with advanced examples
• api_examples.md - Code examples in multiple languages (Python, curl, R)

Additional Resources

• API Documentation: https://www.uniprot.org/help/api
• Interactive API Explorer: https://www.uniprot.org/api-documentation
• REST Tutorial: https://www.uniprot.org/help/uniprot_rest_tutorial
• Query Syntax Help: https://www.uniprot.org/help/query-fields
• SPARQL Endpoint: https://sparql.uniprot.org/ (for advanced graph queries)