molecular-descriptors-calculation

Molecular Descriptors Calculation

Usage

1. MCP Server Definition

Use the same ChemicalToolsClient class as defined in the molecular-properties-calculation skill.

2. Molecular Descriptors Calculation Workflow

This workflow calculates advanced molecular descriptors used in QSAR modeling, drug discovery, and computational chemistry.

Workflow Steps:

1. Calculate Kappa Shape Indices - Molecular shape descriptors
2. Calculate Connectivity Indices - Topological descriptors
3. Calculate Structural Features - Rings, bonds, and functional groups

Implementation:

## Initialize client
HEADERS = {"SCP-HUB-API-KEY": "<your-api-key>"}

client = ChemicalToolsClient(
    "https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem",
    HEADERS
)

if not await client.connect():
    print("connection failed")
    exit()

## Input: SMILES string to analyze
smiles = "CCO"  # Ethanol
print(f"=== Molecular Descriptors for {smiles} ===\n")

## Step 1: Calculate Kappa shape indices
print("Step 1: Kappa Shape Indices")
for tool in ["GetKappa1", "GetKappa2", "GetKappa3"]:
    result = await client.client.call_tool(
        tool,
        arguments={"smiles": smiles}
    )
    result_data = client.parse_result(result)
    print(f"{tool}: {result_data}")
print()

## Step 2: Calculate Chi connectivity indices
print("Step 2: Chi Connectivity Indices")
for tool in ["GetChi0n", "GetChi0v", "GetChi1n", "GetChi1v"]:
    result = await client.client.call_tool(
        tool,
        arguments={"smiles": smiles}
    )
    result_data = client.parse_result(result)
    print(f"{tool}: {result_data}")
print()

## Step 3: Calculate structural features
print("Step 3: Structural Features")

# Rotatable bonds
result = await client.client.call_tool(
    "GetRotatableBondsNum",
    arguments={"smiles": smiles}
)
print(f"Rotatable bonds: {client.parse_result(result)}")

# Hydrogen bond donors and acceptors
result = await client.client.call_tool(
    "GetHBDNum",
    arguments={"smiles": smiles}
)
print(f"H-bond donors: {client.parse_result(result)}")

result = await client.client.call_tool(
    "GetHBANum",
    arguments={"smiles": smiles}
)
print(f"H-bond acceptors: {client.parse_result(result)}")

# Ring counts
result = await client.client.call_tool(
    "GetRingsNum",
    arguments={"smiles": smiles}
)
print(f"Number of rings: {client.parse_result(result)}")

result = await client.client.call_tool(
    "GetAromaticRingsNum",
    arguments={"smiles": smiles}
)
print(f"Aromatic rings: {client.parse_result(result)}")
print()

## Step 4: Calculate physicochemical descriptors
print("Step 4: Physicochemical Descriptors")

# LogP and molar refractivity (Crippen descriptors)
result = await client.client.call_tool(
    "GetCrippenDescriptors",
    arguments={"smiles": smiles}
)
print(f"Crippen descriptors (LogP, MR): {client.parse_result(result)}")

# Topological polar surface area
result = await client.client.call_tool(
    "CalculateTPSA",
    arguments={"smiles": smiles}
)
print(f"TPSA: {client.parse_result(result)}")

# Fraction of sp3 carbons
result = await client.client.call_tool(
    "GetFractionCSP3",
    arguments={"smiles": smiles}
)
print(f"Fraction sp3 carbons: {client.parse_result(result)}")
print()

await client.disconnect()

Tool Descriptions

SciToolAgent-Chem Server:

Shape Descriptors:

• GetKappa1, GetKappa2, GetKappa3: Kappa shape indices (molecular shape)

Connectivity Indices:

• GetChi0n, GetChi0v: Zero-order chi indices
• GetChi1n, GetChi1v: First-order chi indices
• GetChi2n, GetChi2v: Second-order chi indices
• GetChi3n, GetChi3v, GetChi4n, GetChi4v: Higher-order chi indices

Structural Features:

• GetRotatableBondsNum: Count rotatable bonds (flexibility)
• GetHBDNum/GetHBANum: Hydrogen bond donors/acceptors
• GetRingsNum: Total ring count
• GetAromaticRingsNum: Aromatic ring count
• GetAliphaticRingsNum: Aliphatic ring count

Physicochemical Descriptors:

• GetCrippenDescriptors: LogP (lipophilicity) and molar refractivity
• CalculateTPSA: Topological polar surface area
• GetFractionCSP3: Fraction of sp³ hybridized carbons
• GetLabuteASA: Labute accessible surface area

Input/Output

Input:

• smiles: Molecule in SMILES format

Output:

• Kappa Indices: Molecular shape descriptors (1, 2, 3)
• Chi Indices: Topological connectivity indices
• Structural Counts: Rings, bonds, functional groups
• LogP: Lipophilicity (partition coefficient)
• TPSA: Topological polar surface area (Ų)
• Fraction sp³: Proportion of sp³ carbons (0-1)

Descriptor Applications

Kappa Shape Indices

• κ₁, κ₂, κ₃: Describe molecular shape from linear to spherical
• Used in: QSAR models, molecular shape comparison

Chi Connectivity Indices

• Encode information about branching and cyclicity
• Used in: Property prediction, similarity searching

Structural Features

• Rotatable bonds: Molecular flexibility, bioavailability
• H-bond donors/acceptors: Solubility, permeability
• Rings: Rigidity, drug-likeness

Physicochemical Descriptors

• LogP: Lipophilicity, membrane permeability
• TPSA: Oral bioavailability, BBB penetration
• Fraction sp³: Molecular complexity, drug-likeness

Drug-Likeness Rules

Lipinski's Rule of Five:

• MW ≤ 500 Da
• LogP ≤ 5
• HBD ≤ 5
• HBA ≤ 10

Veber's Rules (Oral Bioavailability):

• Rotatable bonds ≤ 10
• TPSA ≤ 140 Ų

CNS Drug-Likeness:

• TPSA < 90 Ų (for blood-brain barrier penetration)

Use Cases

• QSAR model development
• Virtual screening and compound prioritization
• Drug-likeness assessment
• Molecular similarity calculations
• Pharmacokinetic property prediction
• Lead optimization
• Chemical space exploration

Additional Descriptor Tools

The SciToolAgent-Chem server provides 160+ tools including:

• GetBCUT: BCUT descriptors
• GetAutocorrelation2D/GetAutocorrelation3D: Autocorrelation descriptors
• GetWHIM: WHIM descriptors
• GetGETAWAY: GETAWAY descriptors
• GetMORSE: MORSE descriptors
• GetRDF: Radial distribution function
• GetUSR/GetUSRCAT: Ultrafast shape recognition descriptors

Performance Notes

• Most descriptor calculations are very fast (<1 second)
• Can batch process multiple molecules
• Descriptors are deterministic (same molecule → same descriptors)