DrugMetric: Quantitative Drug-likeness Scoring Based on Chemical Space Distance

Requirements

• RDKit (version >= 2019)
• Python (version >= 3.8)
• PyTorch (version >= 1.8)
• autogluon (version >= 0.6.2)
• streamlit (version >= 1.14.0)

To install RDKit, please follow the instructions here http://www.rdkit.org/docs/Install.html

We highly recommend you to use conda for package management.

Quick Start

vae training

This project comprises the following three directories:

python preprocess.py  --train_path data/train/train_data.txt \
                      --output_path data/train_data_processed 
                      

python vae_train.py  --train data/train_data_processed \
                      --vocab data/vocab/all_data_vocab.txt
                      

DrugMetric score

python DrugMetric_score.py --input molecules_files \
                           --vocab data/vocab/all_data_vocab.txt \
                           --model_path fast_molvae/vae_model/model.epoch-19 \
               

webserver

DrugMetric webserver can run locally using Streamlit. To deploy DrugMetric locally, you need to install Streamlit.

pip install streamlit
               

Once Streamlit is installed, you can start the application by navigating to the DrugMetric directory in your terminal and running the following command:

streamlit run web_server/dashboard.py