uniprot-database — скилл для Claude Code: что делает и как установить

---
name: uniprot-database
description: >-
  Access protein metadata, function, taxonomy, and sequences across UniProtKB,
  UniParc, and UniRef. Use when searching for proteins, mapping identifiers, or
  retrieving functional annotations and publications. Don't use for sequence
  alignment, protein folding, or sequence similarity search (use specialized
  skills for those tasks).
---

# 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 .licenses/uniprot_database_LICENSE.txt does not
    already exist in the workspace root 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.

### Sequence-Based Search (Exact Match)

> [!IMPORTANT] Use **SPARQL** when searching for a protein by its full amino
> acid sequence. The REST API `/search` endpoint does not support direct
> sequence-string lookups. For any non-exact match use specialized sequence
> similarity search skills. Use UniParc if you cannot find query in UniProt.

**SPARQL Query Pattern (UniProt):**

```text
PREFIX up: <http://purl.uniprot.org/core/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?protein ?name WHERE {
  ?protein a up:Protein ;
           up:sequence/rdf:value "SEQUENCE_HERE" .
  OPTIONAL {
    ?protein up:recommendedName/up:fullName ?name .
  }
}
```

**SPARQL Query Pattern (UniParc):**

```text
PREFIX up: <http://purl.uniprot.org/core/>
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>

SELECT ?uniparc ?val WHERE {
  GRAPH <http://sparql.uniprot.org/uniparc> {
    ?uniparc a up:Sequence ;
             rdf:value ?val .
    FILTER (?val = "SEQUENCE_HERE")
  }
}
```

### Counting Entries Efficiently

> [!IMPORTANT] Use **`count`** or **`SPARQL`** for counting entries (e.g., "How
> many proteins in Human?").

**Counting Pattern (Proteins per Organism):**

```text
PREFIX up: <http://purl.uniprot.org/core/>
PREFIX taxon: <http://purl.uniprot.org/taxonomy/>
SELECT (COUNT(?protein) AS ?count) WHERE {
  ?protein a up:Protein ;
           up:reviewed true ;
           up:organism taxon:9606 .
}
```

### REST Search Syntax

-   **No Commas in Lists**: Commas are treated as literals. Use capitalized `OR`
    to separate items.
    *   Grouped: `accession:(P12345 OR P67890)`
    *   Repeated: `accession:P12345 OR accession:P67890`
-   **Space = AND**: E.g., `gene:p53 human` searches for both.

## Example Commands

Below are example commands for each mode of `uniprot_tools.py`.

Count total number of entries for a given query.

```bash
uv run scripts/uniprot_tools.py count "taxonomy_id:9606"
```

Search for entries.

```bash
uv run scripts/uniprot_tools.py search "gene:p53 AND reviewed:true" --limit 5
```

Retrieve a single entry by accession.

```bash
uv run scripts/uniprot_tools.py get P04637
```

Retrieve Historical/Deleted Entry (UniSave).

```bash
uv run scripts/uniprot_tools.py get P04637 --dataset unisave
```

Stream large result sets for bulk retrieval (returns ALL matched entries, no
`--limit` support).

```bash
uv run scripts/uniprot_tools.py stream "taxonomy_id:9606 AND reviewed:true" --format tsv --fields accession,gene_names > human_reviewed.tsv
```

Map IDs from one database to another.

```bash
uv run scripts/uniprot_tools.py map "P04637" --from_db UniProtKB_AC-ID --to_db Gene_Name
```

Execute graph queries with SPARQL.

```bash
uv run scripts/uniprot_tools.py sparql 'PREFIX up: <http://purl.uniprot.org/core/> SELECT ?protein WHERE { ?protein a up:Protein ; up:reviewed true . } LIMIT 5'
```

## Common Mistakes

-   **Using `name:` instead of `protein_name:`**: `name:` is not a supported
    query term, use `protein_name:` instead.
-   **Ignoring UniParc**: Non-model organisms might only exist in UniParc.
-   **Confusing Accession with UPI**: UniProtKB Accessions (e.g., `P04637`) are
    linked to functional metadata; UniParc IDs (`UPI...`) are for sequences
    only. You can find cross-references from UniParc IDs to UniProtKB Accessions
    using the ID Mapping tool.
-   **Using UniProtKB-AC as Target in ID Mapping**: Use `UniProtKB` instead.
-   **Giving up on Complex Queries**: If a complex search query fails, try to
    use SPARQL instead of giving up.
-   **Using IDs Without Verifying Meaning**: NEVER assume you know the meaning
    of an ID (e.g. keyword, GO term, Pfam ID etc.). ALWAYS look up the natural
    language description/meaning of an ID in UniProt before using it for search
    to ensure it matches your intended search term.
-   **Ignoring Citation Noise in Broad Searches**: Broad text searches (`search
    "term"`) frequently return false positives (e.g., common maintenance
    proteins) because UniProt searches full metadata, including publication
    titles. ALWAYS prefer field-specific filters like `cc_function:` or
    `protein_name:` for functional discovery.
-   **Forgetting to Quote Short Search Terms**: Short, unquoted terms (e.g.,
    `lanM`) can match substrings in organism names (e.g., *Lan*cefieldella) or
    other fields. Use quotes and field prefixes (e.g., `gene:lanM`) to isolate
    true hits.
-   **Manipulating Protein Sequences Directly**: Always use code and tools for
    sequence-based operations. Do not attempt to edit, truncate, or modify
    protein sequences manually.
-   **Over-using Search for Bulk Data**: DO NOT use `search` for retrieving
    millions of entries if `stream` or `sparql` can do the job. Streaming is
    more efficient for very large datasets. Note that `stream` has a hard limit
    of 10,000,000 outputs and does NOT support `--limit`.
-   **Forgetting to Check Data Volume**: ALWAYS perform a `count` before running
    a `search` without `--limit` or before using `stream`. Unlimited queries can
    take a long time and consume significant resources if millions of entries
    are returned.
-   **Using `--limit` with `stream`**: The `stream` command does NOT support
    `--limit`. If you need a limited number of results, use `search` with
    `--limit` instead.
-   **Forgetting the License Notice**: Do not neglect to state that the UniProt
    Database was used and to advise the user to review the licensing terms when
    presenting results for the **first time**. Even if the task is concise, this
    attribution is required in the first response containing UniProt data.

## Reference Materials

-   [SPARQL Examples](references/sparql_examples.md)
-   [Search Query Fields Documentation](references/search_query_fields.md)
-   [ID Mapping Documentation](references/id_mapping_documentation.md)
-   [UniProt Evidence Docs](https://www.uniprot.org/help/evidences)
-   **Underlying API Endpoints** (Used by `scripts/uniprot_tools.py`):
    -   `get`, `search`, `stream`, `count` -> `rest.uniprot.org/{dataset}/`
    -   `map` -> `rest.uniprot.org/idmapping/`
    -   `sparql` -> `sparql.uniprot.org/sparql`
    -   `get --dataset unisave` -> `rest.uniprot.org/unisave/`