Network-based cheminformatics models represent molecular structures, interactions, and biological data as networks or graphs by using network science ideas ( ). Networkbased cheminformatics models offer a methodical technique to investigate and grasp complex interactions within biological and chemical systems. Network-based models provide essential insights into network pharmacology, interactions between medications and their targets, and the operation of molecules. Network-based models are significant in fitting several data kinds-including chemical structures, biological pathways, and protein-protein interactions-into a coherent framework ( ). This integration helps to investigate network properties, identify critical molecular players, and project new therapeutic targets or cooperative drug combinations. Using linked data benefits finding emergent properties, improving knowledge of pharmacological activities at a systems level, and creating logical drug design methods emphasising network-level interactions ( ). Improving our understanding of complex biological systems and accelerating drug discovery depends critically on network-based models.