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 value of 0.569, r value of 0.915, SEE of 0.109 and F value of 52.714 for the COMSIA model. Based on the model, we designed a series of novel 6-HBC derivatives and predicted their IC50 values by the QSAR model. Among them, compound 31.j3 exhibited the highest predicted IC50 value and obtained the highest score in the molecular docking test. MD simulation results showed that compound 31.j3 was stable in binding to the MAO-B receptor, and the RMSD values fluctuated between 1.0 and 2.0 Å, indicating its conformational stability. In addition, energy decomposition analysis revealed the contribution of key amino acid residues to the binding energy, especially Van der Waals interactions and electrostatic interactions play an important role in stabilizing the complex.

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.