def PhyChem(smiles):
""" Calculating the 19D physicochemical descriptors for each molecules,
the value has been normalized with Gaussian distribution.
Arguments:
smiles (list): list of SMILES strings.
Returns:
props (ndarray): m X 19 matrix as normalized PhysChem descriptors.
m is the No. of samples
"""
props = []
for smile in smiles:
mol = Chem.MolFromSmiles(smile)
try:
MW = desc.MolWt(mol)
LOGP = Crippen.MolLogP(mol)
HBA = Lipinski.NumHAcceptors(mol)
HBD = Lipinski.NumHDonors(mol)
rotable = Lipinski.NumRotatableBonds(mol)
amide = AllChem.CalcNumAmideBonds(mol)
bridge = AllChem.CalcNumBridgeheadAtoms(mol)
heteroA = Lipinski.NumHeteroatoms(mol)
heavy = Lipinski.HeavyAtomCount(mol)
spiro = AllChem.CalcNumSpiroAtoms(mol)
FCSP3 = AllChem.CalcFractionCSP3(mol)
ring = Lipinski.RingCount(mol)
Aliphatic = AllChem.CalcNumAliphaticRings(mol)
aromatic = AllChem.CalcNumAromaticRings(mol)
saturated = AllChem.CalcNumSaturatedRings(mol)
heteroR = AllChem.CalcNumHeterocycles(mol)
TPSA = MolSurf.TPSA(mol)
valence = desc.NumValenceElectrons(mol)
mr = Crippen.MolMR(mol)
# charge = AllChem.ComputeGasteigerCharges(mol)
prop = [
MW, LOGP, HBA, HBD, rotable, amide, bridge, heteroA, heavy,
spiro, FCSP3, ring, Aliphatic, aromatic, saturated, heteroR,
TPSA, valence, mr
]
except Exception:
print(smile)
prop = [0] * 19
props.append(prop)
props = np.array(props)
props = Scaler().fit_transform(props)
return props
