protein_complex_analysis
community[skill]
Protein Complex Visualization & Analysis - Analyze protein complex: download structure, visualize complex, extract chains, and calculate quality metrics. Use this skill for structural biology tasks involving retrieve protein data by pdbcode visualize complex extract pdb chains calculate pdb basic info. Combines 4 tools from 1 SCP server(s).
$
/plugin install InnoClawdetails
Protein Complex Visualization & Analysis
Discipline: Structural Biology | Tools Used: 4 | Servers: 1
Description
Analyze protein complex: download structure, visualize complex, extract chains, and calculate quality metrics.
Tools Used
retrieve_protein_data_by_pdbcodefromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolvisualize_complexfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolextract_pdb_chainsfromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Toolcalculate_pdb_basic_infofromserver-2(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
Workflow
- Download complex structure
- Visualize protein-ligand complex
- Extract individual chains
- Calculate structural statistics
Test Case
Input
{
"pdb_code": "6LU7"
}
Expected Steps
- Download complex structure
- Visualize protein-ligand complex
- Extract individual chains
- Calculate structural statistics
Usage Example
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
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-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-2"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool", stack)
# Execute workflow steps
# Step 1: Download complex structure
result_1 = await sessions["server-2"].call_tool("retrieve_protein_data_by_pdbcode", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Visualize protein-ligand complex
result_2 = await sessions["server-2"].call_tool("visualize_complex", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Extract individual chains
result_3 = await sessions["server-2"].call_tool("extract_pdb_chains", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Calculate structural statistics
result_4 = await sessions["server-2"].call_tool("calculate_pdb_basic_info", 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())
technical
- github
- SpectrAI-Initiative/InnoClaw
- stars
- 374
- license
- Apache-2.0
- contributors
- 16
- last commit
- 2026-04-20T01:27:21Z
- file
- .claude/skills/protein_complex_analysis/SKILL.md