ProAffinity-GNN: A Novel Approach to Structure-based Protein-Protein Binding Affinity Prediction via a Curated Dataset and Graph Neural Networks
Zhiyuan Zhou, Yueming Yin, Hao Han, Yiping Jia, Jun Hong Koh, Adams Wai‐Kin Kong, Yuguang Mu
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.
Journal of Chemical Information and Modeling · Nov 19, 2024Peer-reviewedBioinformatics