Hao Han

This paper introduces ProAffinity-GNN, a deep learning framework for predicting protein-protein binding affinities using graph neural networks and a curated dataset of protein complexes with experimentally determined affinities.

The paper introduces a generalist model for drug design that predicts multiple properties simultaneously, achieving faster virtual screening and drug development with explainability.