CDK-pywrapper 0.1.0

Python wrapper for CDK molecular descriptors and fingerprints

CDK Python wrapper

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

Installation

From source:

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

with pip:

pip install CDK-pywrapper

Get started

from CDK_pywrapper import CDK
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",
  # cisplatin
  "N.N.Cl[Pt]Cl"
]
mols = [Chem.AddHs(Chem.MolFromSmiles(smiles)) for smiles in smiles_list]

cdk = CDK()
print(cdk.calculate(mols))

The above calculates 222 molecular descriptors (23 1D and 200 2D).

The additional 65 three-dimensional (3D) descriptors may be obtained with the following: :warning: Molecules are required to have conformers for 3D descriptors to be calculated.

from rdkit.Chem import AllChem

for mol in mols:
    _ = AllChem.EmbedMolecule(mol)

cdk = CDK(ignore_3D=False)
print(cdk.calculate(mols))

To obtain molecular fingerprint, one can used the following:

from CDK_pywrapper import CDK, FPType
cdk = CDK(fingerprint=.PubchemFP)
print(cdk.calculate(mols))

The following fingerprints can be calculated:

FPType	Fingerprint name
FP	CDK fingerprint
ExtFP	Extended CDK fingerprint (includes 25 bits for ring features and isotopic masses)
EStateFP	Electrotopological state fingerprint (79 bits)
GraphFP	CDK fingerprinter ignoring bond orders
MACCSFP	Public MACCS fingerprint
PubchemFP	PubChem substructure fingerprint
SubFP	Fingerprint describing 307 substructures
KRFP	Klekota-Roth fingerprint
AP2DFP	Atom pair 2D fingerprint as implemented in PaDEL
HybridFP	CDK fingerprint ignoring aromaticity
LingoFP	LINGO fingerprint
SPFP	Fingerprint based on the shortest paths between two atoms
SigFP	Signature fingerprint
CircFP	Circular fingerprint

Documentation

class CDK(ignore_3D=True, fingerprint=None, nbits=1024, depth=6):

Constructor of a CDK calculator for molecular descriptors or fingerprints

Parameters:

• ignore_3D : bool Should 3D molecular descriptors be calculated (default: False). Ignored if a fingerprint is set.
• fingerprint : FPType
  Type of fingerprint to calculate (default: None). If None, calculate descriptors.
• nbits : int
  Number of bits in the fingerprint.
• depth : int
  Depth of the fingerprint.

```python def calculate(mols, show_banner=True, njobs=1, chunksize=1000): ```

Default method to calculate CDK molecular descriptors and fingerprints.

Parameters:

• mols : Iterable[Chem.Mol]
  RDKit molecule objects for which to obtain CDK descriptors.
• show_banner : bool
  Displays default notice about CDK.
• njobs : int
  Maximum number of simultaneous processes.
• chunksize : int
  Maximum number of molecules each process is charged of.