/bayesian_retro

A bayesian retrosynthesis algorithm

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Bayesian Retrosynthesis

This is the code for the "A Bayesian retrosynthesis algorithm"

Requirements

The forward prediction model (fine-tuned Molecular Transformer), ranking model (glmnet) and files storing nearest neighbors of each reactant candidate can be found here Download these files and put them to appropriate directories.

wget -O nearest_neighbor.zip https://ndownloader.figshare.com/articles/11954913/versions/1
unzip nearest_neighbor.zip -d data/
rm nearest_neighbor.zip
wget -O forward_models/fine_tuned_model_on_liu_dataset_0p02.pt https://ndownloader.figshare.com/files/21945630
wget -O utils/glmnet_grouped.RData https://ndownloader.figshare.com/files/21947469

A new conda environment can be created by BayesRetro_environment.sh

./BayesRetro_environment.sh

Sequential Monte Carlo algorithm for retrosynthesis

quick_start.sh is an example to try the SMC algorithm for retrosynthesis. Each step of SMC takes about 30 sec. Step number is set to 600. The total search will take 6 h .

./quick_start.sh

Ranking candidate synthetic routes

The ranking model is in single-step/ranking directory. Install R packages glmnet and reticulate from CRAN to use this model.

install.packages("glmnet")
install.packages("reticulate")

Rank the detected synthetic routes

./ranking.sh

t-SNE embedding