LAUSR

BACKGROUND Tuberculosis (TB) is one of the leading causes of death in the post-Covid-19 era. It has been observed that there is a devastating condition with a 25-30% increase in TB patients. DNA gyrase B isoform has proved its high potential to be a therapeutically effective target for developing newer and safer anti-TB agents. OBJECTIVE This study aims to identify minimum structural requirements for the optimization of thiazolopyridine derivatives having DNA gyrase inhibitory activities. Moreover, developed QSAR models could be used to design new thiazolopyridine derivatives and predict their DNA gyrase B inhibitory activity before synthesis. METHODS 3D-QSAR and Group-based QSAR (G-QSAR) methodologies were adopted to develop accurate, reliable, and predictive QSAR models. Statistical methods such as kNN-MFA SW-FB and MLR SW-FB were used to correlate dependent parameters with descriptors. Both models were thoroughly validated for internal and external predictive abilities. RESULTS The 3D-QSAR model significantly correlated steric and electrostatic descriptors with q2 0.7491 and predicted r2 0.7792. The G-QSAR model showed that parameters such as SsOHE-index, slogP, ChiV5chain, and T_C_C_3 were crucial for optimizing thiazolopyridine derivatives as DNA gyrase inhibitors. The 3D-QSAR model was interpreted extensively with respect to 3D field points, and the pattern of fragmentation was studied in the G-QSAR model. CONCLUSION The 3D-QSAR and G-QSAR models were found to be highly predictive. These models could be useful for designing potent DNA gyrase B inhibitors before their synthesis.