The Transformer-based model , specifically designed for processing graph data that represent entities and their interactions, has demonstrated remarkable efficacy in studies such as GenScore 23 , RTMScore , and Karmadock 44 , particularly in analyzing protein-ligand interaction graphs. These investigations highlight the exceptional performance of Graph Transformer. By integrating a selfattention mechanism, the model establishes dynamic correlations between nodes, allowing for flexible adjustment of weights based on their relationships. In the input molecular graph