Bioinformatics Programming
tanimoto_similarities.py: A Python script to calculate Tanimoto similarities of multiple compounds using RDKit.
RDKit [1] is a very nice cheminformatics software. It allows us to perform a wide range of operations on chemical compounds/ ligands. We have provided a Python script to perform fingerprinting using Tanimoto similarity on multiple compounds using RDKit.
Introduction
tanimoto_similarities.py script calculates Tanimoto similarities of given molecules in the form of smiles.
Let’s say we have a list of smiles of 15 molecules in a CSV file named ‘smiles.csv’. This file may also consist of other information such as ligand name, serial number, and so on. In that case, you can extract the smiles column from the CSV file. The smiles are available under the column named “SMILES” (or edit the column name in the script as per your file).
Availability
The script is available on GitHub under the package ‘tanimoto_similarities‘.
Requirements
This script requires Python3 and uses RDKit along with some additional packages. Install them using the following commands.
$ conda create -c conda-forge -n my-rdkit-env rdkit
$ conda activate my-rdkit-env
$ pip3 install seaborn
$ sudo apt-get install python3-matplotlib
$ conda install pandas
$ pip3 install numpy
Usage
$ python3 tanimoto_similarities.py
Note: If you still get an error stating “rdkit not found”, then perhaps you have not activated the rdkit environment. Run the conda activate my-rdkit-env command again and then run the script.
References
- Landrum, G. (2013). Rdkit documentation. Release, 1 (1-79), 4.
With the new year, we are going to start with a very simple yet complicated topic (for beginners) in bioinformatics. In this tutorial, we provide a simple code to plot swarm boxplot using matplotlib and seaborn. (more…)
Previously, we provided a similar script to download ligand SMILES from PDB ligand IDs. In this article, we are downloading PDB ligand structures from their corresponding IDs. (more…)
Fetching SMILE strings for a given number of SDF files of chemical compounds is not such a trivial task. We can quickly obtain them using RDKit or OpenBabel. But what if you don’t have SDF files of ligands in the first place? All you have is Ligand IDs from PDB. If they are a few then you can think of downloading SDF files manually but still, it seems time-consuming, especially when you have multiple compounds to work with. Therefore, we provide a Python script that will read all Ligand IDs and fetch their SDF files, and will finally convert them into SMILE strings. (more…)
You must be logged in to post a comment Login