Home

Awesome

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

This repository is the official Tensorflow implementation of "Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation".

Jiaxuan You*, Bowen Liu*, Rex Ying, Vijay Pande, Jure Leskovec, Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

Installation

conda create -c rdkit -n my-rdkit-env rdkit
conda install mpi4py
pip install networkx=1.11
cd rl-baselines
pip install -e .
cd gym-molecule
pip install -e.

Code description

There are 4 important files:

Run

python run_molecule.py
mpirun -np 8 python run_molecule.py 2>/dev/null

2>/dev/null will hide the warning info provided by rdkit package.

We highly recommend using tensorboard to monitor the training process. To do this, you may run

tensorboard --logdir runs

All the generated molecules along the training process are stored in the molecule_gen folder, each run configuration is stored in a different csv file. Molecules are stored using SMILES strings, along with the desired properties scores.