ChemSpacE: Interpretable and Interactive Chemical Space Exploration

Official implementation of ChemSpacE, an efficient and effective approach to explore chemical space via aligning the latent space of molecular generative models, by Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou.

TMLR paper link

Setup and Installation

Environment Setup

Anaconda is recommended for managing the enviroment for this project. Create an environment for this project with:

conda env create -f environment.yml

Note: Examples are provided for the ZINC dataset. Files and parameters can be substituted to work with the qm9 dataset.

Data Preprocessing

Generate molecular graphs from SMILES strings:

cd data
python data_preprocess.py --data_name zinc250k

Download Trained Models

https://bit.ly/chemspace-models

Trained MoFlow models were obtained from https://github.com/calvin-zcx/moflow.

ChemSpacE Method

Randomly Generate Molecules

python chemspace.py --data_name zinc250k --random

Train SVM to Find Directions

python train_boundary_zinc.py

Traverse Learned Directions (Molecule Manipulation)

Single Property

python chemspace.py --data_name zinc250k --traverse

Multi-Property

python chemspace.py --data_name zinc250k --multi_property --traverse

Calculate Success Rate of Molecule Manipulation

Single Property

python calculate_statistics_single_prop.py --mani_range 1

Multi-Property

python calculate_statistics_multi_prop.py --mani_range 1

Molecule Optimization

Single Property

python optimize_property_chemspace.py --data_name zinc250k --property_name gsk3b --save_path gsk3b_0.6_range30 --topscore

Multi-Property

python optimize_property_chemspace.py --data_name zinc250k --property_name qed_plogp --save_path qed_plogp_0.6_range30 --multi_property --topscore

Contrained Molecule Optimization (enforce similarity to reference molecule)

Single Property

python optimize_property_chemspace.py --data_name zinc250k --path_range 30 --sim_cutoff 0.6 --property_name gsk3b --save_path gsk3b_0.6_range30 --consopt

Multi-Property

python optimize_property_chemspace.py --data_name zinc250k --path_range 30 --sim_cutoff 0.6 --property_name qed_plogp --save_path qed_plogp_0.6_range30 --multi_property --consopt

Cite us

@article{
  du2023chemspace,
  title={ChemSpacE: Interpretable and Interactive Chemical Space Exploration},
  author={Yuanqi Du and Xian Liu and Nilay Mahesh Shah and Shengchao Liu and Jieyu Zhang and Bolei Zhou},
  journal={Transactions on Machine Learning Research},
  issn={2835-8856},
  year={2023},
  url={https://openreview.net/forum?id=C1Xl8dYCBn},
  note={}
}