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Skill v1.0.1
currentAutomated scan100/100internscience/scp/drugsda-mol-properties
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version: "1.0.1" 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 jsonfrom mcp.client.streamable_http import streamablehttp_clientfrom mcp import ClientSessionclass DrugSDAClient:def __init__(self, server_url: str):self.server_url = server_urlself.session = Noneasync 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 Trueexcept Exception as e:print(f"✗ connect failure: {e}")import tracebacktraceback.print_exc()return Falseasync 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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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/errormsg (str): messagemetrics (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()