NAG2G: Node-Aligned Graph-to-Graph Model

Welcome to the NAG2G (Node-Aligned Graph-to-Graph) repository! NAG2G is a state-of-the-art neural network model for retrosynthesis prediction.

Research Paper

For detailed information about the method and experimental results, please refer to our research paper.

Platform

Uni-Retro platform: A multi-step retrosynthesis platform that integrates the NAG2G algorithm.

Environment Setup

To begin working with NAG2G, you'll need to set up your environment. Below is a step-by-step guide to get you started:

# Install Uni-Core
git clone https://github.com/dptech-corp/Uni-Core
cd Uni-Core
pip install .
cd -

# Install Unimol plus
cd unimol_plus
pip install .
cd -

# Install additional dependencies
pip install rdchiral transformers tokenizers omegaconf rdkit

Datasets and Pretrained Weights

You can obtain the dataset USPTO-50k and pretrained model weights for USPTO-50k from the Google Drive:

Model Validation

To validate the NAG2G model with the provided weights, follow the instructions below:

# Execute the validation script with the specified checkpoint file
sh valid.sh path2weight/NAG2G_unimolplus_uspto_50k_20230513-222355/checkpoint_last.pt

For any questions or issues, please open an issue on our GitHub repository.

Thank you for your interest in NAG2G!

dptech-corp / NAG2G