internscience Molecular Properties Calculation
Usage
1. MCP Server Definition
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
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
3. Example Code
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()