venv/Lib/site-packages/CDK_pywrapper-0.1.0.dist-info/METADATA

Metadata-Version: 2.1
Name: CDK_pywrapper
Version: 0.1.0
Summary: Python wrapper for CDK molecular descriptors and fingerprints
Home-page: https://github.com/OlivierBeq/CDK_pywrapper
Author: Olivier J. M. Béquignon
Author-email: "olivier.bequignon.maintainer@gmail.com"
Maintainer: Olivier J. M. Béquignon
Maintainer-email: "olivier.bequignon.maintainer@gmail.com"
Keywords: Chemistry Development Kit,molecular descriptors,molecular fingerprints,cheminformatics,QSAR
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: more-itertools
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: rdkit
Requires-Dist: install-jdk ==0.3.0
Requires-Dist: bounded-pool-executor ==0.0.3
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Requires-Dist: sphinx-autodoc-typehints ; extra == 'docs'
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

# CDK Python wrapper

Python wrapper to ease the calculation of [CDK](https://cdk.github.io/) molecular descriptors and fingerprints.

## Installation

From source:

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

with pip:

```bash
pip install CDK-pywrapper
```

### Get started

```python
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).<br/>

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.<br/>

```python
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:

```python
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

```python
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.
<br/>
<br/>
```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.