Molecule Optimization by Explainable Evolution

@inproceedings{Chen2021MolEvol,
    title={Molecule Optimization by Explainable Evolution},
    author={Binghong Chen* and Tianzhe Wang* and Chengtao Li and Hanjun Dai and Le Song},
    booktitle={International Conference on Learning Representations},
    year={2021}
}

Overview

We release the PyTorch code for the MolEvol. [Paper]:

Details for Graph Explanation Process

Install Dependencies

You should install dependencies for chemprop and multiobj-rationale first.

Install chemprop

conda create -n chemprop python=3.8
conda activate chemprop
conda install pytorch==1.6.0 torchvision==0.7.0 -c pytorch
conda install -c conda-forge rdkit
pip install -r requirements.txt
pip install chemprop

Install multiobj-rationale

cd ..
git clone git@github.com:anonymous20201002/multiobj-rationale.git
cd multiobj-rationale
pip install -e .
cd ../mol_finder

How to Use

For instance, if you want to jointly optimize jnk3, gsk3, QED, SA for the molecules.

Run the following command:

export CUDA_VISIBLE_DEVICES=0
export TF_CPP_MIN_LOG_LEVEL=2
export PYTHONPATH=$PWD
python mol_finder/main.py --rounds=10 --epoch=1

You will get the molecule optimization model along with the optimized molecules in the experiment folder.