alanine_scanning_pipeline: Скилл для анализа мутаций

--- name: alanine_scanning_pipeline description: "Alanine Scanning Mutagenesis Pipeline - Alanine scanning: design scan, compute properties for each mutant, predict interactions, and compare. Use this skill for protein biochemistry tasks involving AlanineScanningDesigner ComputeProtPara PredictDrugTargetInteraction calculate protein sequence properties. Combines 4 tools from 3 SCP server(s)." --- # Alanine Scanning Mutagenesis Pipeline **Discipline**: Protein Biochemistry | **Tools Used**: 4 | **Servers**: 3 ## Description Alanine scanning: design scan, compute properties for each mutant, predict interactions, and compare. ## Tools Used - **`AlanineScanningDesigner`** from `server-28` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent` - **`ComputeProtPara`** from `server-29` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio` - **`PredictDrugTargetInteraction`** from `server-29` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio` - **`calculate_protein_sequence_properties`** from `server-2` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool` ## Workflow 1. Design alanine scan mutants 2. Compute parameters for mutants 3. Predict interactions for mutants 4. Compare protein properties ## Test Case ### Input ```json { "sequence": "MKTIIALSYIFCLVFA" } ``` ### Expected Steps 1. Design alanine scan mutants 2. Compute parameters for mutants 3. Predict interactions for mutants 4. Compare protein properties ## Usage Example > **Note:** Replace `sk-b04409a1-b32b-4511-9aeb-22980abdc05c` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn). ```python import asyncio import json from contextlib import AsyncExitStack from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client from mcp.client.sse import sse_client SERVERS = { "server-28": "https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", "server-29": "https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio", "server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool" } async def connect(url, stack): transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"}) read, write, _ = await stack.enter_async_context(transport) ctx = ClientSession(read, write) session = await stack.enter_async_context(ctx) await session.initialize() return session 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) async def main(): async with AsyncExitStack() as stack: # Connect to required servers sessions = {} sessions["server-28"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", stack) sessions["server-29"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/29/SciToolAgent-Bio", stack) sessions["server-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack) # Execute workflow steps # Step 1: Design alanine scan mutants result_1 = await sessions["server-28"].call_tool("AlanineScanningDesigner", arguments={}) data_1 = parse(result_1) print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}") # Step 2: Compute parameters for mutants result_2 = await sessions["server-29"].call_tool("ComputeProtPara", arguments={}) data_2 = parse(result_2) print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}") # Step 3: Predict interactions for mutants result_3 = await sessions["server-29"].call_tool("PredictDrugTargetInteraction", arguments={}) data_3 = parse(result_3) print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}") # Step 4: Compare protein properties result_4 = await sessions["server-2"].call_tool("calculate_protein_sequence_properties", arguments={}) data_4 = parse(result_4) print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}") # Cleanup print("Workflow complete!") if __name__ == "__main__": asyncio.run(main()) ```