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ScaffoldGVAE

ScaffoldGVAE: A Variational Autoencoder Based on Multi-View Graph Neural Networks for Scaffold Generation and Scaffold Hopping of Drug Molecules

Installation

You can use the environment.yml file to create a new conda environment with all the necessary dependencies for ScaffoldGVAE.

git clone git@github.com:ecust-hc/ScaffoldGVAE.git
cd ScaffoldGVAE
conda env create -f environment.yml
conda activate ScaffoldGVAE

Usage

ScaffoldGVAE includes three sub-modules:

1. Sca_extraction.py: The molecular scaffolds was extracted and the data set was constructed.

2. Train.py: Used for pre-training on big dataset.

3. fine_tuning.py: Used for fine-tuning the pre-trained neural network on the known bioactive compounds against specific protein targets.

4. sample.py: Given a reference molecule and its corresponding scaffold ,sampling new scaffolds and adding side-chain for scaffold hopping.

Example of running the command:

python Sca_extraction.py

python pre_train.py

python fine_tuning.py

python sample.py