PaDEL-pywrapper 1.0.0.post2

Python wrapper for the PaDEL descriptors

PaDEL Python wrapper

Python wrapper to ease the calculation of PaDEL molecular descriptors and fingerprints.

Copyright notice

Olivier J. M. Béquignon is neither the copyright holder of PaDEL nor responsible for it.

The work carried out here concerns

• the Python wrapper,
• the ePaDEL executable,
• the extendedlibpadeldescriptor library.

Installation

From source:

git clone https://github.com/OlivierBeq/PaDEL_pywrapper.git
pip install ./PaDEL_pywrapper

with pip:

pip install padel-pywrapper

Get started

1D and 2D descriptors

Descriptors of the module PaDEL_pywrapper.descriptors can be computed as follows:

from PaDEL_pywrapper import PaDEL
from PaDEL_pywrapper.descriptor import ALOGP, Crippen, FMF
from rdkit import Chem

smiles_list = [
    # erlotinib
    "n1cnc(c2cc(c(cc12)OCCOC)OCCOC)Nc1cc(ccc1)C#C",
    # midecamycin
    "CCC(=O)O[C@@H]1CC(=O)O[C@@H](C/C=C/C=C/[C@@H]([C@@H](C[C@@H]([C@@H]([C@H]1OC)O[C@H]2[C@@H]([C@H]([C@@H]([C@H](O2)C)O[C@H]3C[C@@]([C@H]([C@@H](O3)C)OC(=O)CC)(C)O)N(C)C)O)CC=O)C)O)C",
    # selenofolate
    "C1=CC(=CC=C1C(=O)NC(CCC(=O)OCC[Se]C#N)C(=O)O)NCC2=CN=C3C(=N2)C(=O)NC(=N3)N",
]
mols = [Chem.MolFromSmiles(smiles) for smiles in smiles_list]

descriptors = [ALOGP, Crippen, FMF]

padel = PaDEL(descriptors)
print(padel.calculate(mols))

Instances of descriptors can be supplied as well.

descriptors = [ALOGP(), Crippen(), FMF()]

padel = PaDEL(descriptors)
print(padel.calculate(mols))

To calculate all possible descriptors, import the descriptors list from the module PaDEL_pywrapper directly:

from PaDEL_pywrapper import descriptors

padel = PaDEL(descriptors)
print(padel.calculate(mols))

3D descriptors

By default, the ignore_3D parameter is set to True, preventing any provided 3D descriptor to be calculated.

Should molecules with 3D coordinates be provided, one can turn on 3D descriptor calculation.

from rdkit.Chem import AllChem

mols = [Chem.AddHs(mol) for mol in mols]
_ = [AllChem.EmbedMolecule(mol) for mol in mols]

padel = PaDEL(descriptors, ignore_3D=False)
print(padel.calculate(mols))

:warning: A warning is raised if molecules lack hydrogens.
:warning: An exception is raised if molecules do not have 3D coordinates.

mol = Chem.MolFromSmiles('CCC')

padel = PaDEL(descriptors, ignore_3D=False)
print(padel.calculate([mol]))
# ValueError: Cannot calculate descriptors for a conformer-less molecule

Fingerprints

Fingerprints of the module `PaDEL_pywrapper.descriptors can be computed as follows:

from PaDEL_pywrapper.descriptor import GraphOnlyFP

fp = GraphOnlyFP

padel = PaDEL([fp], ignore_3D=False)
print(padel.calculate(mols))

Custom parameter sets can be provided for some fingerprints:

fp = GraphOnlyFP(size=2048, searchDepth=8)

padel = PaDEL([fp], ignore_3D=False)
print(padel.calculate(mols))

Other parameters

class PaDEL:
    ...
    def calculate(self, mols: Iterable[Chem.Mol], show_banner: bool = True, njobs: int = 1, chunksize: int = 100):

Parameters

• mols : Iterable[Chem.Mol]
  RDKit molecule objects for which to obtain PaDEL descriptors.
• show_banner : bool
  Displays default notice about PaDEL descriptors.
• njobs : int
  Maximum number of simultaneous processes. Ignored if self.descriptors are instances and not class names.
• chunksize : int
  Maximum number of molecules each process is charged of. Ignored if self.descriptors are instances and not class names.

Details about descriptors

Details about each descriptor and fingerprint can be obtained as follows:

print(ALOGP.description)

print(GraphOnlyFP.description)

For full details about all descriptors, one can obtain the path to the original Excel file of the PaDEL descriptors with:

print(padel.details)