--- name: drugsda-mol-properties description: Calculate different types of molecular properties based on SMILES strings, covering basic physicochemical properties, hydrophobicity, hydrogen bonding capability, molecular complexity, topological structures, charge distribution, and custom complexity metrics, respectively. license: MIT license metadata: skill-author: PJLab --- # Molecular Properties Calculation ## 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. Tool Description Tool 1: *calculate_mol_basic_info* ```tex Compute a set of basic molecular properties for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing feature keys. --smiles (str): A SMILES string of smiles_list --molecular_formula (str): Molecular formula, e.g. "C9H11NO3" --exact_molecular_weight (float): Exact molecular weight --molecular_weight (float): Average molecular weight --num_heavy_atoms (int): Number of heavy atoms --num_atoms (int): Number of total atoms --num_bonds (int): Number of bonds --num_valence_electrons (int): Number of valence electrons --formal_charge (int): Number of formal charge ``` Tool 2: calculate_mol_hydrophobicity ```tex Compute hydrophobicity-related molecular descriptors for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing feature keys. --smiles (str): A SMILES string of smiles_list --logp (float): The octanol-water partition coefficient (logP) --molar_refractivity (float): Molar refractivity ``` Tool 3: calculate_mol_hbond ```tex Compute hydrogen bonding-related properties for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing several feature keys. --smiles (str): A SMILES string of smiles_list --num_h_donors (int): Number of hydrogen bond donors --num_h_acceptors (int): Number of hydrogen bond acceptors ``` Tool 4: calculate_mol_structure_complexity ```tex Compute a set of molecular complexity descriptors for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing feature keys. --smiles (str): A SMILES string of smiles_list --num_rotatable_bonds (int): Number of rotatable bonds --num_rings (int): Number of total rings --num_aromatic_rings (int): Number of aromatic rings --num_aliphatic_rings (int): Number of aliphatic rings --num_saturated_rings (int): Number of saturated rings --num_heteroatoms (int): Number of heteroatoms --fraction_csp3 (float): The fraction of sp³-hybridized carbon atoms (Fsp³) --num_bridgehead_atoms (int): Number of bridgehead atoms ``` Tool 5: calculate_mol_topology ```tex Compute a set of topological descriptors for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing several feature keys. --smiles (str): A SMILES string of smiles_list --tpsa (float): Topological polar surface area --chi0v (float): Non-valence molecular connectivity index --chi1v (float): Non-valence molecular connectivity index --chi2v (float): Non-valence molecular connectivity index --chi3v (float): Non-valence molecular connectivity index --chi4v (float): Non-valence molecular connectivity index --chi0n (float): Non-valence molecular connectivity index --chi1n (float): Non-valence molecular connectivity index --chi2n (float): Non-valence molecular connectivity index --chi3n (float): Non-valence molecular connectivity index --chi4n (float): Non-valence molecular connectivity index --hall_kier_alpha (float): Hall–Kier alpha value --kappa1 (float): Kappa shape index --kappa2 (float): Kappa shape index --kappa3 (float): Kappa shape index ``` Tool 6: calculate_mol_charge ```tex Compute Gasteiger partial charges and formal charge for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing several feature keys. --smiles (str): A SMILES string of smiles_list --min_gasteiger_charge (float): Minimum of Gasteiger charges --max_gasteiger_charge (float): Maximum of Gasteiger charges --avg_gasteiger_charge (float): Average of Gasteiger charges --gasteiger_charge_range (float): Range of Gasteiger charges --formal_charge (int): Formal charge ``` Tool 7: calculate_mol_complexity ```tex Compute custom molecular complexity-related descriptors for each SMILES. Args: smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"]) Return: status (str): success/error msg (str): message metrics (List[dict]): List of dict, each containing feature keys. --smiles (str): A SMILES string of smiles_list --molecular_complexity (int): Molecular complexity --aromatic_proportion (float): Aromatic proportion --asphericity (float): Asphericity ``` ### 3. Example Code How to use these tools: ```python client = DrugSDAClient("https://scp.intern-ai.org.cn/api/v1/mcp/2/DrugSDA-Tool") if not await client.connect(): print("connection failed") return ## The tool can be replaced with another based on actual requirements. response = await client.session.call_tool( "calculate_mol_basic_info", arguments={ "smiles_list": smiles_list } ) result = client.parse_result(response) metrics = result["metrics"] await client.disconnect() ```