Pair-EGRET

This repository contains the implementation of our paper "Pair-EGRET: Enhancing the prediction of protein-protein interaction sites through graph attention networks and protein language models".

Datasets

Pair-EGRET was evaluated on three benchmark datasets: DBD5, Dockground, and MASIF. Training and test data used in this experiment can be found here. Save the train.pkl.gz and test.pkl.gz files of each dataset inside the corresponding inputs/{dataset_name} directory.

Alternatively, you can regenerate train and test features following these steps.

1. Download the pdb_files.zip file for a dataset and extract it at the correspoding inputs/{dataset_name} folder.
2. Set the dataset_name parameter in config.py
3. Run the following commands from the root directory of the repository. (The first step may take a while to complete).

    python generate_all_features.py
    python save_all_protein_data.py

4. train.pkl.gz and test.pkl.gz should be saved inside inputs/{dataset_name} now.

Run Experiments

Run the full pipeline on a dataset by setting the dataset_name parameter in config.py and running python run_egret.py from the root directory of the repository. You can run inference using existing models by setting the total_epochs parameter to 0.