Molecule Classifier

Overview

This is a web application that uses a machine learning model (LGBM) to classify molecules as Activator, Inhibitor, or Inactive. Draw a molecule in the Ketcher app and click the SEND button to classify it. The model was trained on a dataset from the NCATS CYP3A4 assay, which contains 5,239 molecules.

The model was trained using the LightGBM library, which is a gradient boosting framework that uses tree-based learning algorithms.

This web application was developed using Flask, a micro web framework for Python. It uses the EPAM Ketcher app to draw molecules and the RDKit library to convert the molecule SMILES string to a descriptor vector.

Testing Environments

This application was tested in the following operating systems:

• Ubuntu 20.04
• Windows 11

The following web browsers were tested:

• Google Chrome
• Mozilla Firefox
• Microsoft Edge

Dependencies

Python

This project requires Python 3.8 or higher. You can download Python from the official website.

PIP

PIP is a package manager for Python. You can install it by running the following command:

python -m ensurepip --upgrade

Python Libraries

It is recommended to create a virtual environment to manage the dependencies for this project. You can create a virtual environment by running the following command:

python -m venv venv

Activate the virtual environment by running the following command:

source venv/bin/activate

Once the virtual environment is activated, you can install the required libraries by running the following command:

pip install -r requirements.txt

Running the Application

Make sure you have activated the virtual environment before running the application. You can run the application by executing the following command:

python run.py
# or for hot reloading (development)
flask --app run.py --debug run

The application will be running on http://localhost:5000/.

Open the URL in a web browser and you should see the home page of the application, just like the screenshot below:

Usage

1. Draw a molecule in the Ketcher app. You can use the tools on the left side to draw the molecule or you can paste a SMILES string in the input box. To paste a SMILES string press Ctrl + O on your keyboard or select the folder icon on the top left corner of the Ketcher app.

2. Click the SEND button to classify the molecule.

3. The classification result will be displayed on the screen.