chemopy2 1.1.0

A Python library calculating molecular descriptors.

ChemoPy2

A Python library calculating molecular descriptors.

💪 Getting Started

from chemopy import ChemoPy
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",
]
# Ensure hydrogens are explicit
mols = [Chem.AddHs(Chem.MolFromSmiles(smiles)) for smiles in smiles_list]

cmp = ChemoPy()
print(cmp.calculate(mols))

The above calculates 632 two-dimensional (2D) molecular descriptors.

The additional 552 three-dimensional (3D) molecular descriptors can be computed as follows:
:warning: Molecules are required to have conformers for descriptors to be calculated.

from rdkit.Chem import AllChem

# Ensure molecules have 3D conformations
for mol in mols:
    _ = AllChem.EmbedMolecule(mol)

cmp = ChemoPy(ignore_3D=False)
print(cmp.calculate(mols))

To obtain 11 2D molecular fingerprints with default folding size, one can use the following:

from chemopy import Fingerprint

for mol in mols:
    print(Fingerprint.get_all_fps(mol))

Other methods of the Fingerprint submodule allow to change folding size and depth of the compatible fingerprints.

Currently, only one 3D fingerprint may be obtained with the following:

from chemopy import Fingerprint3D

for mol in mols:
    print(Fingerprint3D.get_all_fps(mol))

Conveniently, the calculation of molecular descriptors and fingerprints can be coupled:

# 2D molecular descriptors and fingerprints
cmp =  ChemoPy(include_fps=True)
print(cmp.calculate(mols))

# 2D and 3D molecular descriptors and fingerprints
cmp =  ChemoPy(ignore_3D=False, include_fps=True)
print(cmp.calculate(mols))

Finally, details on either one or all molecular descriptors can be obtained like so:

# Obtain details about Thara
print(cmp.get_details('Thara'))

# Obtain details for all descriptors and fingerprints
print(cmp.get_details())

🚀 Installation

ChemoPy requires OpenMOPAC and OpenBabel to be installed.

conda install openbabel mopac -c conda-forge

The most recent release can be installed from PyPI with:

$ pip install chemopy2

The most recent code and data can be installed directly from GitHub with:

$ pip install git+https://github.com/OlivierBeq/chemopy.git

👐 Contributing

Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.md for more information on getting involved.

👋 Attribution

📖 Citation

1. Cao et al., ChemoPy: freely available python package for computational biology and chemoinformatics. Bioinformatics 2013; 29(8), 1092–1094. doi:10.1093/bioinformatics/btt105

🍪 Cookiecutter

This package was created with @audreyfeldroy's cookiecutter package using @cthoyt's cookiecutter-snekpack template.