gu-yaowen / Anti-TB

Code and datasets for "Machine learning-led virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations"

Anti-TB

Codes and datasets for "Machine learning-led virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations"

Reference

If you make advantage of the MilGNet model or its modules proposed in our paper, please cite the following in your manuscript:

TBD

Workflow Overview

Datasets

ChEMBL_dataset.csv
Our collected Anti-Mycobacterium tuberculosis bioactivity dataset from ChEMBL database.

DrugBank_predicted.csv
The estimated Anti-TB bioactivities of molecules in DrugBank database predcited by our ML and GNN models.

DrPurHub_predicted.xlsx
The estimated Anti-TB bioactivities of molecules in Drug Repurposing Hub database predcited by our ML and GNN models.

Codes

processing.ipynb
To collect, clean, and preprocess our Anti-TB bioactivity dataset from source.

inference.ipynb
To train the ML models. Also conduct testing and inference results from trained ML and GNN models. To train the GNN models, please refer our previous work CurrMG.