| name | drug_target_structure |
| description | Drug-Target Structural Biology - Integrate drug and target structure: get drug from ChEMBL, target structure from PDB, dock them, and predict ADMET. Use this skill for structural pharmacology tasks involving get drug by name retrieve protein data by pdbcode quick molecule docking pred molecule admet. Combines 4 tools from 3 SCP server(s). |
Drug-Target Structural Biology
Discipline: Structural Pharmacology | Tools Used: 4 | Servers: 3
Description
Integrate drug and target structure: get drug from ChEMBL, target structure from PDB, dock them, and predict ADMET.
Tools Used
get_drug_by_name from chembl-server (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL
retrieve_protein_data_by_pdbcode from server-2 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool
quick_molecule_docking from server-3 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model
pred_molecule_admet from server-3 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model
Workflow
- Get drug data from ChEMBL
- Download target structure
- Perform molecular docking
- Predict ADMET for drug
Test Case
Input
{
"drug": "imatinib",
"pdb_code": "1IEP"
}
Expected Steps
- Get drug data from ChEMBL
- Download target structure
- Perform molecular docking
- Predict ADMET for drug
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.
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 = {
"chembl-server": "https://scp.intern-ai.org.cn/api/v1/mcp/4/Origene-ChEMBL",
"server-2": "https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool",
"server-3": "https://scp.intern-ai.org.cn/api/v1/mcp/3/DrugSDA-Model"
}
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)
: (result)
():
AsyncExitStack() stack:
sessions = {}
sessions[] = connect(, stack)
sessions[] = connect(, stack)
sessions[] = connect(, stack)
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())