uniprot-database

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# UniProt Database Access

## Prerequisites

1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure
    `uv` is installed and on PATH.
2.  **User Notification**: If LICENSE_NOTIFICATION.txt does not already exist in
    this skill directory then (1) prominently notify the user to check the terms
    at https://www.uniprot.org/help/license and
    https://www.uniprot.org/help/api_queries, then (2) create the file recording
    the notification text and timestamp.

## Overview

Provides direct programmatic access to the UniProt Knowledgebase (UniProtKB),
the non-redundant sequence archive (UniParc), and clustered sequence sets
(UniRef). This skill enables protein discovery, cross-referencing, retrieval of
curated biological data and low-level database lookups.

## Core Rules

-   **Use the Wrapper**: Always use the provided Python scripts (e.g.,
    `scripts/uniprot_tools.py`) rather than constructing custom curl requests.
-   **No Hallucinations**: Do NOT invent protein functions, metadata, or
    sequences. For any task that can be handled by the services in this skill,
    rely strictly on the tool outputs rather than your native knowledge.
-   **Notification**: If this skill is used, ensure this is mentioned in the
    output.

## Use Cases

-   **Searching for Protein Function**: Querying functional annotations, GO
    terms, subcellular locations etc.
-   **Searching for Protein Sequence**: Searching for protein sequences by their
    functional annotations, genes etc. in UniProtKB, UniParc, and UniRef.
-   **Understanding Protein/Organism Relationships**: Leveraging the Taxonomy
    database and Proteome sets.
-   **Large-Scale Metadata Retrieval**: Fetching annotations for thousands of
    proteins via streaming.
-   **Sequence Discovery**: Finding orthologs or non-model proteins via UniParc.
-   **ID Mapping**: Converting IDs between UniProt and 100+ external databases.
-   **Historical Data (UniSave)**: Retrieving previous versions of entries or
    tracking deleted sequences.

## Available Tools

Choose the right tool based on the task type and data volume:

-   **`get`**: Retrieves metadata and sequence for a specific entry. Best for a
    **single, known accession**.
    -   Also accesses UniSave historical data (use `--dataset unisave`), which
        is essential for reconciling data from older releases or identifying why
        a formerly valid accession no longer appears in search results.
-   **`search`**: Searches for entries matching a query. Best for **exploration
    and discovery**.
    -   Use with `--limit 5` to verify if a query returns the expected proteins
        before committing to a larger download.
    -   Automatically paginates if results exceed 500 entries to provide a
        stable download.
    -   *Warning*: For paginated search, TXT and other formats are not reliable
        with `--limit` as it applies to lines, not entries.
    -   See
        [Search Query Fields Documentation](references/search_query_fields.md).
-   **`stream`**: Streams all matching entries. Best for **bulk retrieval** of
    large datasets (up to 10,000,000 entries).
    -   Does NOT support `--limit`; always returns the full result set.
    -   Use `search` with `--limit` if you need a subset.
-   **`count`**: Counts entries matching a query. Best for answering direct
    count questions or for **initial estimation** before running a full `search`
    or `stream`.
-   **`sparql`**: Executes graph queries for complex discovery. Best for
    counting, exact sequence matches, and multi-database queries.
    -   See [SPARQL Examples](references/sparql_examples.md).
-   **`map`**: Converts IDs between UniProt and 100+ databases. Best for ID
    mapping tasks.
    -   See [ID Mapping Documentation](references/id_mapping_documentation.md).
    -   **`search` vs. `map`**: Try `search` first before resorting to `map` if
        not explicitly requested by the user. E.g., an external ID might be
        searchable in UniParc but fail to map to UniProtKB.

## Workflows

### Typical Protein Research Workflow

Copy this checklist and track progress:

-   [ ] Step 1: Identify target protein(s) and organism(s).
-   [ ] Step 2: Search UniProtKB for reviewed entries (`reviewed:true`).
-   [ ] Step 3: If no reviewed entries, search unreviewed or use UniParc for
    sequence discovery.
-   [ ] Step 4: Map external IDs (e.g., Ensembl, PDB) to UniProt Accessions if
    necessary.
-   [ ] Step 5: Retrieve functional metadata or sequence in desired format
    (JSON, FASTA).

### Handling Search Misses (e.g. Gene Search in Non-Model Organisms)

If a direct query (e.g., `gene:SYMBOL`) fails:

1.  **Pivot to Protein Name**: Search for the common protein name (e.g.,
    `protein_name:Alpha-crystallin A`).
2.  **Use UniParc**: Search the UniParc dataset, which integrates sequences from
    across all of life, even if they aren't fully annotated in UniProtKB.
3.  **Check Orthologs/Canonical**: Resolve the Human/Mouse ortholog first to
    find the correct naming/mnemonic.

### Bulk Retrieval Priorities

> [!IMPORTANT] Always prefer **`stream`** or **`sparql`** for bulk data.
> `search` is suitable for exploration; if results exceed 500 entries, it
> automatically paginates to provide a stable download.

-   **Priority 0: `count`**: ALWAYS check the result count before running a
    `search` or `stream`.
-   **Priority 1: `stream`**: The primary method for bulk data retrieval (up to
    10M entries). Does NOT support `--limit`; always returns all results.
-   **Priority 2: `sparql`**: Best for complex filtering and exact matching
    during retrieval.

From MarceloClaro/OpenCode_Ecosystem, MIT.

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