tessl/pypi-rdkit

Platform wheels for RDKit - a comprehensive cheminformatics and machine-learning library with Python bindings

1.01x

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Molecular Descriptors

Name: tessl/pypi-rdkit
Author: tessl

Calculation of 2D molecular descriptors for characterizing chemical properties. RDKit provides 217+ molecular descriptors covering molecular weight, lipophilicity, topological indices, structural features, and pharmacophore properties for quantitative structure-activity relationship (QSAR) analysis and chemical space exploration.

Capabilities

Basic Descriptors

Fundamental molecular properties including molecular weight, heavy atom count, and basic structural metrics.

def MolWt(mol: Mol) -> float:
    """
    Calculate molecular weight.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Molecular weight in Daltons
    """

def ExactMolWt(mol: Mol) -> float:
    """
    Calculate exact molecular weight using isotopic masses.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Exact molecular weight in Daltons
    """

def HeavyAtomCount(mol: Mol) -> int:
    """
    Count heavy (non-hydrogen) atoms.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of heavy atoms
    """

def NumHeteroatoms(mol: Mol) -> int:
    """
    Count heteroatoms (non-carbon heavy atoms).
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of heteroatoms
    """

Lipophilicity Descriptors

Descriptors related to molecular lipophilicity and solubility properties.

def MolLogP(mol: Mol) -> float:
    """
    Calculate Wildman-Crippen LogP.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Calculated LogP value
    """

def MolMR(mol: Mol) -> float:
    """
    Calculate Wildman-Crippen molar refractivity.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Molar refractivity value
    """

def TPSA(mol: Mol) -> float:
    """
    Calculate topological polar surface area.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    TPSA value in Ų
    """

Hydrogen Bonding Descriptors

Descriptors for hydrogen bond donors and acceptors, critical for drug-like property assessment.

def NumHDonors(mol: Mol) -> int:
    """
    Count hydrogen bond donors.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of hydrogen bond donors
    """

def NumHAcceptors(mol: Mol) -> int:
    """
    Count hydrogen bond acceptors.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of hydrogen bond acceptors
    """

Ring Descriptors

Descriptors characterizing ring systems and cyclic structures.

def RingCount(mol: Mol) -> int:
    """
    Count number of rings.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Total number of rings
    """

def NumAromaticRings(mol: Mol) -> int:
    """
    Count aromatic rings.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of aromatic rings
    """

def NumAliphaticRings(mol: Mol) -> int:
    """
    Count aliphatic rings.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of aliphatic rings
    """

def NumSaturatedRings(mol: Mol) -> int:
    """
    Count saturated rings.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of saturated rings
    """

Topological Descriptors

Graph-based descriptors characterizing molecular topology and connectivity.

def BertzCT(mol: Mol) -> float:
    """
    Calculate Bertz topological complexity.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Bertz complexity index
    """

def Kappa1(mol: Mol) -> float:
    """
    Calculate first kappa shape index.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Kappa1 shape index
    """

def Kappa2(mol: Mol) -> float:
    """
    Calculate second kappa shape index.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Kappa2 shape index
    """

def Kappa3(mol: Mol) -> float:
    """
    Calculate third kappa shape index.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Kappa3 shape index
    """

Comprehensive Descriptor Calculation

Functions for calculating multiple descriptors simultaneously.

def CalcMolDescriptors(mol: Mol) -> dict:
    """
    Calculate all available molecular descriptors.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Dictionary mapping descriptor names to values
    """

_descList: list
"""
List of all available descriptor names and functions.
Contains 217 descriptor definitions in version 2024.9.6.
Each entry is a tuple of (name, function).
"""

Fragment Descriptors

Descriptors based on molecular fragments and substructures.

def fr_Al_COO(mol: Mol) -> int:
    """
    Count aliphatic carboxylic acid fragments.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of aliphatic carboxylic acid groups
    """

def fr_ArN(mol: Mol) -> int:
    """
    Count aromatic nitrogen fragments.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of aromatic nitrogens
    """

def fr_benzene(mol: Mol) -> int:
    """
    Count benzene rings.
    
    Parameters:
    - mol: Input molecule
    
    Returns:
    Number of benzene rings
    """

Usage Examples

Basic Descriptor Calculations

from rdkit import Chem
from rdkit.Chem import Descriptors

# Calculate basic descriptors
mol = Chem.MolFromSmiles('CCO')  # Ethanol
mw = Descriptors.MolWt(mol)
logp = Descriptors.MolLogP(mol)
tpsa = Descriptors.TPSA(mol)
hbd = Descriptors.NumHDonors(mol)
hba = Descriptors.NumHAcceptors(mol)

print(f"Molecular Weight: {mw:.2f}")
print(f"LogP: {logp:.2f}")
print(f"TPSA: {tpsa:.2f}")
print(f"H-bond Donors: {hbd}")
print(f"H-bond Acceptors: {hba}")

Calculate All Descriptors

from rdkit import Chem
from rdkit.Chem import Descriptors

# Calculate all available descriptors
mol = Chem.MolFromSmiles('CCO')
all_descriptors = Descriptors.CalcMolDescriptors(mol)

print(f"Total descriptors calculated: {len(all_descriptors)}")
for name, value in list(all_descriptors.items())[:10]:  # Show first 10
    print(f"{name}: {value}")

Drug-like Property Assessment

from rdkit import Chem
from rdkit.Chem import Descriptors

def assess_drug_likeness(smiles):
    """Assess Lipinski's Rule of Five compliance."""
    mol = Chem.MolFromSmiles(smiles)
    if mol is None:
        return None
    
    mw = Descriptors.MolWt(mol)
    logp = Descriptors.MolLogP(mol)
    hbd = Descriptors.NumHDonors(mol)
    hba = Descriptors.NumHAcceptors(mol)
    
    violations = 0
    if mw > 500: violations += 1
    if logp > 5: violations += 1
    if hbd > 5: violations += 1
    if hba > 10: violations += 1
    
    return {
        'MW': mw,
        'LogP': logp,
        'HBD': hbd,
        'HBA': hba,
        'Violations': violations,
        'Drug-like': violations <= 1
    }

# Test with aspirin
result = assess_drug_likeness('CC(=O)OC1=CC=CC=C1C(=O)O')
print(result)

Descriptor List Access

from rdkit.Chem import Descriptors

# Access all available descriptors
print(f"Total descriptors available: {len(Descriptors._descList)}")

# Show first 10 descriptor names
for i, (name, func) in enumerate(Descriptors._descList[:10]):
    print(f"{i+1}: {name}")

Install with Tessl CLI

npx tessl i tessl/pypi-rdkit