protein-solubility-optimization

name	protein_solubility_optimization
description	Protein Solubility Optimization - Optimize protein solubility: calculate properties, predict solubility, predict hydrophilicity, and suggest mutations. Use this skill for protein engineering tasks involving calculate protein sequence properties predict protein function ComputeHydrophilicity zero shot sequence prediction. Combines 4 tools from 3 SCP server(s).
i18n	{"zh":{"description":"优化蛋白质溶解性：计算属性、预。"}}

Protein Solubility Optimization

Discipline: Protein Engineering | Tools Used: 4 | Servers: 3

Description

Optimize protein solubility: calculate properties, predict solubility, predict hydrophilicity, and suggest mutations.

Tools Used

• calculate_protein_sequence_properties from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
• predict_protein_function from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory
• ComputeHydrophilicity from server-29 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio
• zero_shot_sequence_prediction from server-1 (sse) - https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory

Workflow

1. Calculate physicochemical properties
2. Predict solubility
3. Compute hydrophilicity profile
4. Predict beneficial mutations for solubility

Test Case

Input

{
    "sequence": "MKTIIALSYIFCLVFAGKRDEFPSTWYV"
}

Expected Steps

1. Calculate physicochemical properties
2. Predict solubility
3. Compute hydrophilicity profile
4. Predict beneficial mutations for solubility

Usage Example

Note: Replace <YOUR_SCP_HUB_API_KEY> with your own SCP Hub API Key. You can obtain one from the SCP Platform.

import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool",
    "server-1": "https://scp.intern-ai.org.cn/api/v1/mcp/1/VenusFactory",
    "server-29": "https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
    read, write, _ = await transport.__aenter__()
    ctx = ClientSession(read, write)
    session = await ctx.__aenter__()
    await session.initialize()
    return session, ctx, transport

def parse(result):
    try:
        if hasattr(result, 'content') and result.content:
            c = result.content[0]
            if hasattr(c, 'text'):
                try: return json.loads(c.text)
                except: return c.text
        return str(result)
    except: return str(result)

  ():
    
    sessions = {}
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )
    sessions[], _, _ =  connect(, )

    
    
    result_1 =  sessions[].call_tool(, arguments={})
    data_1 = parse(result_1)
    ()

    
    result_2 =  sessions[].call_tool(, arguments={})
    data_2 = parse(result_2)
    ()

    
    result_3 =  sessions[].call_tool(, arguments={})
    data_3 = parse(result_3)
    ()

    
    result_4 =  sessions[].call_tool(, arguments={})
    data_4 = parse(result_4)
    ()

    
    ()

 __name__ == :
    asyncio.run(main())