--- name: drugsda-rgroup-sampling description: Generate new molecules sampling from the input scaffold. license: MIT license metadata: skill-author: PJLab --- # Molecule Generation ## 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. R-Group Sampling The description of tool *libinvent_rgroup_sampling_by_scaffold*. ```tex Generate new molecules sampling from the input scaffold. Args: scaffold (str): Input scaffold SMILES string containing R-group position markers such as [*:1], [*:2], etc. e.g., 'c1ccc([*:1])cc1C(=O)N[*:2]' n (int): Number of molecules for sampling lipinski (bool): Whether to apply Lipinski's rule of five filtering, default is True filter_preset (str): Filter preset, options: ['none', 'minimal', 'default', 'strict'], default is 'default' Return: status (str): success/error msg (str): message save_smiles_file (str): Path to the saved SMILES file output_smiles_list (List[str]): List of generated SMILES strings ``` How to use tool *libinvent_rgroup_sampling_by_scaffold* : ```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( "libinvent_rgroup_sampling_by_scaffold", arguments={ "scaffold": scaffold, "n": n, "lipinski": True, "filter_preset": filter_type } ) result = client.parse_result(response) output_smiles_list = result["output_smiles_list"] await client.disconnect() ```