Predicting Protein-Protein Interaction with Graph Convolutional Network

In this study, we propose SGPPI, a structure-aware prediction model for protein-protein interactions using graph convolutional network. Our model is able to accurately predict interactions even under rigorous conditions, such as low similarity with known interactions. We demonstrate the effectiveness of our approach on benchmark datasets and compare it with state-of-the-art methods.