BACKGROUND: 6-hydroxybenzothiazole-2-carboxamide is a novel, potent and specific inhibitor of monoamine oxidase B (MAO-B), which can be used to study the molecular structure and develop new neuroprotective strategies. OBJECTIVE: The aim of this study was to create an effective predictive model from 6-hydroxybenzothiazole-2-carboxamide derivatives to provide a reliable predictive basis for the development of neuroprotective MAO-B inhibitors for the treatment of neurodegenerative diseases. METHODS: First, the compounds were constructed and optimized using ChemDraw and Sybyl-X software. Subsequently, QSAR modeling was performed using the COMSIA method in Sybyl-X to predict the IC50 values of a set of novel 6-hydroxybenzothiazole-2-carboxamide derivatives. The ten most promising compounds were screened based on the IC50 values and tested for molecular docking. Finally, the binding stability and dynamic behavior of these compounds with MAO-B receptors were analyzed by molecular dynamics simulation (MD). RESULTS: The 3D-QSAR model showed good predictive ability, with a q CONCLUSION: In this study, the potential of 6-hydroxybenzothiazole-2-carboxamide derivatives as MAO-B inhibitors was systematically investigated by 3D-QSAR, molecular docking and MD simulations. The successfully designed compound 31.j3 not only demonstrated efficient inhibitory activity, but also verified its stable binding to MAO-B receptor by MD simulation, which provides strong support for the development of novel therapeutic drugs for neurodegenerative diseases. These findings provide important theoretical basis and practical guidance for future drug design and experimental validation.