AGENT SKILL

interproscan-domain-analysis

Analyze protein sequences using InterProScan to identify functional domains, protein families, and Gene Ontology (GO) annotations.

License 许可
MIT
最近更新
2026-03-20
Stars
★ 172
Forks
10

01 前言 Front Matter

i18n
{ "zh": { "description": "用InterProScan分析。" } }
name
interproscan-domain-analysis
license
MIT license
metadata
{ "skill-author": "PJLab" }
description
Analyze protein sequences using InterProScan to identify functional domains, protein families, and Gene Ontology (GO) annotations.

03 SKILL.md 正文

InterProScan Protein Domain Analysis

Usage

1. MCP Server Definition

Use the same BioInfoToolsClient class as defined in the protein-blast-search skill.

2. InterProScan Domain Analysis Workflow

This workflow analyzes protein sequences using InterProScan to identify functional domains, protein families, binding sites, and associated Gene Ontology annotations.

Workflow Steps:

  1. Validate Sequence - Check protein sequence format and length
  2. Run InterProScan - Identify domains using multiple signature databases
  3. Extract Annotations - Parse domain locations, families, and GO terms

Implementation:

from datetime import timedelta

## Initialize client
client = BioInfoToolsClient(
    "https://scp.intern-ai.org.cn/api/v1/mcp/17/BioInfo-Tools",
    "<your-api-key>"
)

if not await client.connect():
    print("connection failed")
    exit()

## Input: Protein sequence to analyze
protein_sequence = """
MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVANALAHKYH
"""

## Step 1 & 2: Run InterProScan analysis
result = await client.session.call_tool(
    "interproscan_analyze",
    arguments={
        "sequence": protein_sequence.strip(),
        "sequence_id": "HBB_HUMAN",        # Optional identifier
        "databases": ["Pfam"],              # Signature databases to use
        "goterms": True                     # Include GO term annotations
    },
    read_timeout_seconds=timedelta(seconds=900)  # Allow up to 15 minutes
)

## Step 3: Parse and display results
result_data = client.parse_result(result)

if result_data.get("success"):
    results = result_data.get("results", {})
    domains = results.get("domains", [])
    go_terms = results.get("go_terms", [])

    print(f"✅ InterProScan analysis completed successfully")
    print(f"Execution time: {result_data.get('time_seconds', '?')} seconds")
    print(f"Domains found: {len(domains)}")
    print(f"GO annotations: {len(go_terms)}\n")

    # Display domain information
    if domains:
        print("=== Functional Domains ===\n")
        for i, domain in enumerate(domains, 1):
            print(f"{i}. {domain.get('name', 'N/A')}")
            print(f"   Accession: {domain.get('accession', 'N/A')}")
            print(f"   Database: {domain.get('database', 'N/A')}")
            if domain.get('description'):
                print(f"   Description: {domain.get('description')}")

            # Display domain locations
            locations = domain.get('locations', [])
            if locations:
                print(f"   Locations:")
                for loc in locations:
                    print(f"     - Position {loc.get('start')}-{loc.get('end')} aa")
                    if loc.get('score'):
                        print(f"       Score: {loc.get('score')}")
            print()

    # Display GO annotations
    if go_terms:
        print("=== Gene Ontology Annotations ===\n")

        # Group by category
        by_category = {}
        for go in go_terms:
            category = go.get('category', 'UNKNOWN')
            if category not in by_category:
                by_category[category] = []
            by_category[category].append(go)

        for category, terms in by_category.items():
            print(f"{category}:")
            for go in terms:
                print(f"  - {go.get('id', 'N/A')}: {go.get('name', 'N/A')}")
            print()
else:
    print(f"❌ InterProScan analysis failed: {result_data.get('error', 'Unknown error')}")

await client.disconnect()

Tool Descriptions

BioInfo-Tools Server:

  • interproscan_analyze: Analyze protein sequence using InterProScan
    • Args:
      • sequence (str): Protein sequence in amino acid single-letter code
      • sequence_id (str, optional): Identifier for the query sequence
      • databases (list, optional): Signature databases to query (default: ["Pfam"])
      • goterms (bool, optional): Include GO term annotations (default: True)
    • Returns:
      • success (bool): Whether analysis completed successfully
      • results (dict): Analysis results containing domains and GO terms
      • time_seconds (float): Execution time

Input/Output

Input:

  • sequence: Protein sequence (amino acid single-letter code)
  • sequence_id: Optional identifier for the query
  • databases: List of signature databases (e.g., ["Pfam", "SMART", "PRINTS"])
  • goterms: Whether to include Gene Ontology annotations

Output:

  • domains: List of identified protein domains, each containing:
    • name: Domain or family name
    • accession: Database accession number
    • database: Source database (e.g., "PFAM", "SMART")
    • description: Functional description
    • locations: List of domain positions in the sequence
      • start: Start position (amino acid number)
      • end: End position (amino acid number)
      • score: Match score (if available)
  • go_terms: List of GO annotations, each containing:
    • id: GO identifier (e.g., "GO:0020037")
    • name: GO term name
    • category: GO category (MOLECULAR_FUNCTION, BIOLOGICAL_PROCESS, or CELLULAR_COMPONENT)

Available Signature Databases

InterProScan integrates multiple signature databases:

  • Pfam: Protein families based on HMMs
  • SMART: Simple Modular Architecture Research Tool
  • PRINTS: Protein fingerprints
  • ProSite: Protein domains, families, and functional sites
  • SUPERFAMILY: Structural and functional annotation
  • And more...

Default: ["Pfam"] for fastest results

Performance Notes

  • Typical execution time:
    • Short sequences (~150 aa): 30-60 seconds
    • Medium sequences (~400 aa): 2-4 minutes
    • Long sequences (~800+ aa): 5-15 minutes
  • Timeout recommendation: Set to at least 900 seconds (15 minutes)
  • Multiple databases: Using more databases increases execution time but provides comprehensive annotation

Use Cases

  • Identify functional domains in novel protein sequences
  • Predict protein function from domain composition
  • Locate active sites and binding regions
  • Annotate protein families and superfamilies
  • Obtain GO term annotations for functional analysis
  • Compare domain architecture across homologous proteins

GO Term Categories

  • MOLECULAR_FUNCTION: Molecular-level activities (e.g., "heme binding", "catalytic activity")
  • BIOLOGICAL_PROCESS: Biological pathways and processes (e.g., "oxygen transport", "signal transduction")
  • CELLULAR_COMPONENT: Cellular locations (e.g., "cytoplasm", "membrane")

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