uniprot-protein-retrieval

name	uniprot-protein-retrieval
description	Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.
license	MIT license
metadata	{"skill-author":"PJLab"}

UniProt Protein Sequence Retrieval

Usage

1. MCP Server Definition

Use the standard MCP client pattern for Origene-UniProt server.

2. Protein Sequence Retrieval Workflow

This workflow retrieves protein sequences and associated information from the UniProt database using protein names or identifiers.

Workflow Steps:

1. Query by Protein Name - Search UniProt using common protein names
2. Retrieve Sequence Data - Get amino acid sequence and metadata

Implementation:

from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
import json

class OrigeneClient:
    def __init__(self, server_url: str):
        self.server_url = server_url
        self.session = None

    async def connect(self):
        try:
            self.transport = streamablehttp_client(
                url=self.server_url,
                headers={"SCP-HUB-API-KEY": "<your-api-key>"}
            )
            self.read, self.write, self.get_session_id = await self.transport.__aenter__()
            self.session_ctx = ClientSession(self.read, self.write)
            self.session = await self.session_ctx.__aenter__()
            await self.session.initialize()
            print("✓ Connected to Origene-UniProt")
            return True
        except Exception as e:
            print(f"✗ Connection failed: {e}")
            return False

    async def disconnect(self):
        try:
            if self.session:
                await self.session_ctx.__aexit__(None, None, None)
            if hasattr(self, 'transport'):
                await self.transport.__aexit__(None, None, None)
            print("✓ Disconnected")
        except Exception as e:
            print(f"✗ Disconnect error: {e}")

    def parse_result(self, result):
        try:
            if hasattr(result, 'content') and result.content:
                content = result.content[0]
                if hasattr(content, 'text'):
                    return json.loads(content.text)
            return str(result)
        except Exception as e:
            return {"error": f"Parse error: {e}", "raw": str(result)}

## Initialize client
client = OrigeneClient("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt")
if not await client.connect():
    print("Connection failed")
    return

## Step 1: Retrieve protein sequence by name
protein_name = "insulin"  # Can be common name, gene symbol, or UniProt ID

result = await client.session.call_tool(
    "get_protein_sequence_by_name",
    arguments={
        "protein_name": protein_name
    }
)

result_data = client.parse_result(result)

## Display results
print(f"\nProtein: {protein_name}")
print("=" * 80)

if "sequence" in result_data:
    sequence = result_data["sequence"]
    print(f"Amino Acid Sequence ({len(sequence)} residues):")
    print(sequence)

    # Format sequence in blocks of 60
    print("\nFormatted Sequence:")
    for i in range(0, len(sequence), 60):
        position = i + 1
        block = sequence[i:i+60]
        print(f"{position:6d} {block}")

if "uniprot_id" in result_data:
    print(f"\nUniProt ID: {result_data['uniprot_id']}")

if "protein_names" in result_data:
    print(f"Protein Names: {result_data['protein_names']}")

if "organism" in result_data:
    print(f"Organism: {result_data['organism']}")

if "function" in result_data:
    print(f"Function: {result_data['function'][:200]}...")

await client.disconnect()

Extended Example: Multiple Protein Retrieval

## Retrieve multiple proteins
protein_list = ["p53", "BRCA1", "insulin", "hemoglobin"]

sequences = {}
for protein in protein_list:
    result = await client.session.call_tool(
        "get_protein_sequence_by_name",
        arguments={"protein_name": protein}
    )
    data = client.parse_result(result)

    if "sequence" in data:
        sequences[protein] = {
            "sequence": data["sequence"],
            "length": len(data["sequence"]),
            "uniprot_id": data.get("uniprot_id", "N/A")
        }

## Display summary
print("\nProtein Sequence Summary:")
print(f"{'Protein':<15} {'UniProt ID':<12} {'Length':<10}")
print("-" * 40)
for name, info in sequences.items():
    print(f"{name:<15} {info['uniprot_id']:<12} {info['length']:<10}")

Tool Description

Origene-UniProt Server:

• get_protein_sequence_by_name: Retrieve protein sequence from UniProt database
  • Args:
    • protein_name (str): Protein common name, gene symbol, or UniProt ID
  • Returns:
    • sequence (str): Amino acid sequence (one-letter code)
    • uniprot_id (str): UniProt accession number
    • protein_names (str): Official and alternative protein names
    • organism (str): Source organism
    • function (str): Protein function description
    • length (int): Sequence length in residues
    • mass (float): Molecular mass (Da)

Input/Output

Input:

• protein_name: Protein identifier (flexible format)
  • Examples: "insulin", "P53", "BRCA1", "P01308"
  • Supports: common names, gene symbols, UniProt IDs

Output:

• Protein sequence and comprehensive metadata
• Ready for downstream analysis (alignment, structure prediction, etc.)

Supported Query Types

1. Common Names: "insulin", "hemoglobin", "actin"
2. Gene Symbols: "TP53", "BRCA1", "EGFR"
3. UniProt IDs: "P01308", "P04637"
4. Protein Families: "kinase", "protease" (returns multiple entries)

Applications

Use retrieved sequences for:

• Protein alignment and homology analysis
• Structure prediction (AlphaFold, ESM Fold)
• Primer design for cloning
• Antibody epitope mapping
• Conservation analysis
• Mutation impact assessment
• Phylogenetic studies

Integration with Other Workflows

Combine with:

1. Protein BLAST → Find homologs
2. InterProScan → Identify domains
3. AlphaFold → Predict 3D structure
4. STRING → Find protein interactions
5. OpenTargets → Link to diseases

Example: Complete Protein Analysis Pipeline

## 1. Retrieve sequence
result = await uniprot_client.session.call_tool(
    "get_protein_sequence_by_name",
    arguments={"protein_name": "BRCA1"}
)
sequence = uniprot_client.parse_result(result)["sequence"]

## 2. Find similar proteins (BLAST)
result = await biotools_client.session.call_tool(
    "blast_search",
    arguments={
        "sequence": sequence,
        "evalue": 1e-10,
        "max_hits": 20
    }
)
homologs = biotools_client.parse_result(result)

## 3. Identify domains (InterProScan)
result = await biotools_client.session.call_tool(
    "interproscan_analyze",
    arguments={
        "sequence": sequence,
        "databases": ["Pfam", "SMART"]
    }
)
domains = biotools_client.parse_result(result)

## 4. Get disease associations (OpenTargets)
result = await opentargets_client.session.call_tool(
    "get_target_associated_diseases",
    arguments={"gene_symbol": "BRCA1"}
)
diseases = opentargets_client.parse_result(result)

print(f"Complete analysis for BRCA1:")
print(f"- Sequence length: {len(sequence)} amino acids")
print(f"- Homologs found: {len(homologs)}")
print(f"- Functional domains: {len(domains)}")
print(f"- Associated diseases: ")

Error Handling

Common issues:

• Protein not found: Check spelling, try alternative names or UniProt ID
• Multiple matches: Use more specific identifier (UniProt ID preferred)
• No sequence available: Some entries may lack sequence data
• Network timeout: Retry with exponential backoff

Data Quality Notes

• UniProt is manually curated (Swiss-Prot) and computationally annotated (TrEMBL)
• Sequence quality: Swiss-Prot entries are highly reliable
• Updates: UniProt is updated regularly; sequences may change
• Isoforms: Multiple isoforms may exist; canonical sequence is returned by default