SynTwins

Implementation of synthetic accessible analog design with SynTwins developed by MICC group at SNU (contact: yousung@gmail.com).

Contents

• Developer
• OS Requirements
• Python Dependencies
• Installation Guide
• Reproduce the results
• Citation

Developer

Shuan Chen (shuan75@snu.ac.kr)

OS Requirements

This repository has been tested on both Linux and Windows operating systems.

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 SynTwins.
This process usually takes few munites to complete.

git clone https://github.com/snu-micc/SynTwins.git
cd SynTwins
conda create -c conda-forge -n rdenv python=3.6 -y
conda activate rdenv

Reproduce the results

Data preperation

The necessary files-including reaction templates, retro-reaction templates, and builing blocks- are provided in the data directory. You can replace the building blocks and reaction templates following the same format.
No futher preprocessing or training is needed to implement SynTwins.

Synthetically accessible analog design

Try to make synthetically accessible analog with SynTwins following the examples in Demo.ipynb!
Test files used in this paper are all available at the data/test directory.

Molecule Optimization

Run run_optimization.py to reproduce the molecule optimization results.
This experiment was largely reproduced using the script from the mol-opt repsitory.
Note that the python package tdc needed to be installed to run this experiment. You can install it by

pip install PyTDC

Citation

under review