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Chemical Space Grid

Script adapted and developed to plot the molecular similarity in a chemical space grid.

This script has been adapted from iwatobipen, according to the papper written by Atsushi Yoshimori et.al.

I strongly advise to check iwatobipen github and blog if you are interested on chemical space, chemical similarity and other cheminformatics topics.

Libraries used

  • pandas - a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive.

  • NumPy - the fundamental package for array computing with Python

  • RDKit - Open source toolkit for cheminformatics

  • scikit-learn - Machine Learning in Python.

  • Matplotlib - a comprehensive library for creating static, animated, and interactive visualizations in Python.

  • seaborn - a Python data visualization library based on matplotlib.

  • SciPy.org - a Python-based ecosystem of open-source software for mathematics, science, and engineering.

  • pyLAPJV - Linear Assignment Problem solver using Jonker-Volgenant algorithm.

Libraries were used in a Miniconda3 environment using python 3.6.13, with exception of pyLAPJV.

Instalation

Miniconda3: Installation

pandas:

conda install -c anaconda pandas

numpy

conda install -c anaconda numpy

RDKit

conda install -c rdkit rdkit

scikit-learn

conda install -c anaconda scikit-learn

Matplotlib

conda install -c conda-forge matplotlib

seaborn

conda install -c anaconda seaborn

SciPy.org

conda install -c anaconda scipy

pyLAPJV (pip install)

pip3 install lapjv

How to use

  • Download the code and unzip it on the desirable directory

To run use the following command:

python chemical_space.py

Observations

This script has been elaborated using as references the following articles and codes:

The dataset used as example was made publically available by the Government of India as a part of their Drug Discovery Hackathon and is found at the following link:

Authorship

Social preview original photo by Brenda Ferrari (brendaferrari)