Title:Assessment of Structural Basis for Thiazolopyridine Derivatives as DNA
Gyrase-B Inhibitors
Volume: 20
Issue: 4
Author(s): Vishal Prakash Zambre*, Nilesh Narayan Petkar, Vishal Pravin Dewoolkar, Swapnali Vilas Bhadke and Sanjay Dinkar Sawant
Affiliation:
- Pharmaceutical Chemistry Department, Sinhgad Technical Education Society’s Smt. Kashibai Navale College of
Pharmacy, Savitribai Phule Pune University, Kondhwa (Bk.) Pune, Pune, India
Keywords:
Thiazolopyridine derivatives, DNA gyrase B inhibitors, anti-tubercular agents, 3D-QSAR, G-QSAR, steric and electrostatic parameters.
Abstract:
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.
