To address these limitations, we introduce a novel framework: the Molecular Merged Hypergraph Neural Network (MMHNN). MMHNN innovatively incorporates a predefined set of molecular subgraphs, replacing each with a supernode to construct a compact hypergraph. This architectural change substantially reduces computational overhead while preserving essential molecular interactions.