---
license: mit
tags:
- drug-discovery
- protein-ligand-binding
- binding-kinetics
- deep-learning
- computational-biology
- bioinformatics
library_name: pytorch
datasets:
- kineticX
---

# BiCoA-Net: Bidirectional Co-Attention Network

## Model Description

BiCoA-Net predicts protein-ligand dissociation rate constants (k_off) using bidirectional co-attention mechanisms between protein and ligand representations.

**Key Features:**
- Predicts binding kinetics (k_off) for drug-target interactions
- Uses ESM-2 protein embeddings + MolFormer ligand embeddings
- Bidirectional co-attention fusion mechanism
- Trained on curated KineticX datasets


## Training Details

- Optimizer: AdamW
- Learning Rate: 1e-4
- Batch Size: 32
- Epochs: 100
- Loss Function: MSE on log(k_off)



## License

MIT License - Free for academic and commercial use.

## Contact

For questions or issues, please open an issue on the GitHub repository or contact the authors.