BAPULM: Binding Affinity Prediction Using Language Models

Welcome to the BAPULM repository! This repository corresponds to the prediction of protein-ligand complex binding affinity.

Getting Started

1. Clone the Repository:
   Run the following command in your terminal:

   git clone https://github.com/radh55sh/BAPULM.git
   cd BAPULM

2. Install the required packages:
   Using conda:

     conda create --name bapulm-env python=3.10
     conda activate bapulm-env
     pip install -r requirements.txt
   

3. Download the datset:
   Download the prottrans_molformer dataset from the Hugging Face Platform and place it in the data/ directory.

4. To train the model and inference:
   First, train the model, and furthermore, to do inference on the model, download the model parameters from the Hugging Face Platform and place it in the data/ directory.

   python main.py # To train the model
   python inference.py # To perform inference 
   

Citation

If you use BAPULM in your research or project, please cite:

@misc{meda2024bapulmbindingaffinityprediction,
      title={BAPULM: Binding Affinity Prediction using Language Models}, 
      author={Radheesh Sharma Meda and Amir Barati Farimani},
      year={2024},
      eprint={2411.04150},
      archivePrefix={arXiv},
      primaryClass={q-bio.QM},
      url={https://arxiv.org/abs/2411.04150},
}