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AttentionSiteDTI

This is The repository for supporting matterial of "AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification" https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbac272/6640006

Requirements

A suitable conda environment can be created:

conda env create -f noveldti.yml
conda activate noveldti

Data

All data used in this paper are publicly available and can be accessed here: DUD-E, BindingDB-IBM dataset, Human dataset and human sequence to pdb

Demo Instructions

After downloading the human dataset you and place it in the project root folder you can generate the preprocessed data by running

python human_data.py

After generating the human_part_train.pkl, human_part_val.pkl and human_part_test.pkl you can start training the model by running

python main2.py

Cite

If you find this repo to be useful, please cite our papers. Thank you.

@article{yazdani2022attentionsitedti,
  title={AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification},
  author={Yazdani-Jahromi, Mehdi and Yousefi, Niloofar and Tayebi, Aida and Kolanthai, Elayaraja and Neal, Craig J and Seal, Sudipta and Garibay, Ozlem Ozmen},
  journal={Briefings in Bioinformatics}
}
@article{10.1093/bib/bbad136,
    author = {Yousefi, Niloofar and Yazdani-Jahromi, Mehdi and Tayebi, Aida and Kolanthai, Elayaraja and Neal, Craig J and Banerjee, Tanumoy and Gosai, Agnivo and Balasubramanian, Ganesh and Seal, Sudipta and Ozmen Garibay, Ozlem},
    title = "{BindingSite-AugmentedDTA: enabling a next-generation pipeline for interpretable prediction models in drug repurposing}",
    journal = {Briefings in Bioinformatics},
    volume = {24},
    number = {3},
    pages = {bbad136},
    year = {2023},
    month = {04},
    issn = {1477-4054},
    doi = {10.1093/bib/bbad136},
    url = {https://doi.org/10.1093/bib/bbad136},
    eprint = {https://academic.oup.com/bib/article-pdf/24/3/bbad136/50410278/bbad136.pdf},
}