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Scanned 9/11/2026
Install to Claude Code
npx -y skills add InternScience/DrClaw --skill drugsda-p2rank --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: drugsda-p2rank
description: null
license: MIT license
metadata:
skill-author: PJLab
i18n:
zh:
description: 使用P2Rank预测蛋白口袋。
---
# P2Rank Pocket Location
## Usage
### 1. MCP Server Definition
```python
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class DrugSDAClient:
def __init__(self, server_url: str):
self.server_url = server_url
self.session = None
async def connect(self):
print(f"server url: {self.server_url}")
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": "sk-a0033dde-b3cd-413b-adbe-980bc78d6126"}
)
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()
session_id = self.get_session_id()
print(f"✓ connect success")
return True
except Exception as e:
print(f"✗ connect failure: {e}")
import traceback
traceback.print_exc()
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("✓ already disconnect")
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)}
```
### 2. Locate Protein Pocket
The description of tool *pred_pocket_prank*.
```tex
Use P2Rank to predict ligand binding pockets in the input protein.
Args:
pdb_file_path (str): Path to the protein structure file (PDB format)
Return:
status (str): success/error
msg (str): message
pred_pockets (List[dict]): List of dict, each containing pocket confidence and center position information. The first pocket (pred_pockets[0]) has the highest score and is usually used for molecular docking.
--site_id (str): Pocket id
--probability (float): Predicted confidence score (0~1) of the pocket
--center_x (float): Center X of the pocket
--center_y (float): Center Y of the pocket
--center_z (float): Center Z of the pocket
```
How to use tool *pred_pocket_prank* :
```python
client = DrugSDAClient("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool")
if not await client.connect():
print("connection failed")
return
response = await client.session.call_tool(
"pred_pocket_prank",
arguments={
"pdb_file_path": pdb_file_path
}
)
result = client.parse_result(response)
pred_pockets = result["pred_pockets"]
await client.disconnect()
```
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