MechFinder

Implementation of MechFinder developed by Prof. Yousung Jung group at Seoul National University (contact: yousung.jung@snu.ac.kr)

Open-Source Release Notice

This is the open-source release of MechFinder. Some core functions are not available in this version and will raise NotImplementedError when called. For access to the full implementation, please contact the developers for commercial licensing.

Contents

• Open-Source Release Notice
• Developer
• Python Dependencies
• Installation Guide
• Mechanism labeling
• Publication
• License

Developer

Shuan Chen (shuan75@snu.ac.kr), Ramil Babazade (ramil_babazade@kaist.ac.kr)

Python Dependencies

• Python (version >= 3.6)
• Numpy (version >= 1.16.4)
• RDKit (version >= 2019)

Installation Guide

Create a virtual environment to run the code of MechFinder.

git clone https://github.com/kaist-amsg/MechFinder.git
cd MechFinder
conda create -c conda-forge -n rdenv python -y
conda activate rdenv

Mechanism labeling

See Demo.ipynb for running instructions and expected output for single and multiple reaction mechanism labeling with MechFinder.

Note: The following expected results require the full implementation. The open-source release will raise NotImplementedError for core functions.

Single reaction labeling

from MechFinder import MechFinder
finder = MechFinder(collection_dir='collections')

updated_reaction, LRT, MT_class, electron_path = finder.get_electron_path(sampled_rxn)

Expected output:

Identified mechanistic class: nucleophilic_attack_to_(thio)carbonyl_or_sulfonyl
Generated mechanism: [(26, 1), ([1, 9], 9), (9, [9, 1]), ([1, 101], 101)]

Dataset labeling

for rxn in tqdm(dataset_rxns['reaction'], total=len(dataset_rxns)):
    updated_rxn, LRT, MT_class, electron_path = finder.get_electron_path(rxn)

Expected output:

100%|█████████████████████████████████████████| 33099/33099 [04:46<00:00, 115.42it/s]
Labeled 31364 reactions.

Publication

@article{chen2024large,
  title={A large-scale reaction dataset of mechanistic pathways of organic reactions},
  author={Chen, Shuan and Babazade, Ramil and Kim, Taewan and Han, Sunkyu and Jung, Yousung},
  journal={Scientific Data},
  volume={11},
  number={1},
  pages={863},
  year={2024},
  publisher={Nature Publishing Group UK London}
}

License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

For commercial licensing inquiries, please contact Prof. Yousung Jung (yousung.jung@snu.ac.kr).