Title : In silico investigation of thiazolo[4,5-b]pyridine derivatives as potential anti-inflammatory and antioxidant agents
Abstract:
This presentation focuses on the design, evaluation, and computational analysis of thiazolo[4,5-b]pyridine-2-one derivatives, with particular emphasis on in silico approaches used to predict their biological activity. While synthetic and pharmacological studies were performed, the core of the work lies in computational modeling and virtual screening techniques.
The in silico investigation employed three main strategies: ligand-based (QSAR analysis), receptor-based (molecular docking), and protein–ligand complex-based (3D pharmacophore modeling). QSAR (Quantitative Structure–Activity Relationship) analysis was used to establish mathematical relationships between molecular descriptors and biological activity, including anti-inflammatory and antioxidant effects. Molecular structures were optimized using semi-empirical methods, and a large set of descriptors was generated and refined. Statistically significant QSAR models demonstrated high predictive power (R ≈ 0.9), indicating reliable correlations between chemical structure and activity. Key descriptors such as electronegativity-based autocorrelations, molecular mass distribution, and electronic parameters were identified as crucial contributors to activity.
Receptor-based studies involved flexible molecular docking using COX-1, COX-2, and mPGES-1 enzymes, which are key targets in inflammatory pathways. The docking simulations predicted ligand binding modes, orientations, and affinities. Several compounds exhibited strong binding scores comparable or superior to reference drugs, suggesting their potential as multi-target inhibitors. The docking analysis also revealed important interactions such as hydrogen bonding and hydrophobic contacts within enzyme active sites.
Additionally, 3D pharmacophore modeling was applied to identify essential structural features required for biological activity. Pharmacophore models highlighted key interaction points such as hydrogen bond acceptors and hydrophobic regions, which are critical for effective ligand–receptor binding. High hit rates in pharmacophore validation confirmed the consistency between docking results and pharmacophore hypotheses.
Overall, the in silico results demonstrate that thiazolo[4,5-b]pyridine derivatives possess promising anti-inflammatory and antioxidant potential. The integration of QSAR modeling, molecular docking, and pharmacophore analysis provides a comprehensive understanding of structure–activity relationships and supports the rational design of new bioactive compounds. These findings highlight the importance of computational methods in modern drug discovery and guide further experimental validation.
