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.
import json
from contextlib import AsyncExitStack
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._stack = AsyncExitStack()
await self._stack.__aenter__()
self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self._stack.enter_async_context(self.session_ctx)
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):
"""Disconnect from server"""
try:
if hasattr(self, '_stack'):
await self._stack.aclose()
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)}
Tool 1: calculate_mol_basic_info
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
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
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
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
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
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
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
How to use these tools:
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()