Anti-inflammatory potential of thienopyridines as possible alternative to NSAIDs.

The present study was designed to evaluate the anti-inflammatory and antiarthritic activity of the new synthetic thienopyridine analogs. The anti-inflammatory activity of thienopyridines was assayed by using carrageenan; dextran and arachidonic acid induced paw edema models (acute), cotton pellet granuloma model (Sub acute) and Freund's complete adjuvant induced arthritis (chronic) in experimental rats. The compounds BN-4, BN-14 and BN-16 have shown significant inhibition of edema in carrageenan and arachidonic acid induced paw edema model at a dose of 100mg/kg compared to the dextran induced paw edema model and also showed significant inhibition in granuloma tissue formation and Freund's complete adjuvant induced arthritis in experimental rats. These thienopyridine analogs also inhibited the proinflammatory mediators such as Tumor necrosis factor (TNF)-α, Interleukin (IL)-1ß and Nitric Oxide (NO) in Lipopolysaccharide (LPS) challenged murine macrophages. Ulcerogenecity study results revealed less ulcerogenic potential of BN-4, BN-14 and BN-16 compared to nonsteroidal anti-inflammatory drug (NSAID) indomethacin in rats. In conclusion, the new thienopyridine analogs were promising for the potential use as anti-inflammatory agents for both acute and chronic inflammatory disorders with low toxic effects.

Molecular modeling evaluation of non-steroidal aromatase inhibitors.

A recent discovery of aromatase crystal structure triggered the efforts to design novel aromatase inhibitors for breast cancer therapy. While correlating docking scores with inhibitory potencies of known ligands, feeble robustness of scoring functions toward prediction was observed. This prompted us to develop new prediction models using stepwise regression analysis based on consensus of different docking and their scoring methods (GOLD, LIGANDFIT, and GLIDE). Quantitative structure-activity relationships were developed between the aromatase inhibitory activity (pIC(50) ) of flavonoid derivatives (n=39) and docking scores and docking descriptors. QSAR models have been validated internally [using leave-one-out cross-validated r(2)(cv) (LOO-Q2))] and externally to ensure the predictive capacity of the models. Model 2 [M2] developed using consensus of docking scores of scoring functions viz. ASP, potential of mean force and DOCK Score (r(2)(cv)=0.850, r(2) = 0.870, r(2)(pred) = 0.633, RMSE = 0.363 µm, r(2)(m(test)) =0.831, r(2)(m(overall)) =0.832) was found to be better in predicting aromatase inhibitory potency (pIC(50) ) compared to the Model 1 [M1] based on docking descriptors (r(2)(cv)= 0.848, r(2) = 0.825, r(2)(pred) =0.788, RMSE=0.421µm, r(2)(m(test)) =0.808, r(2)(m(overall)) =0.821). It has been observed that the natural flavonoids and their derivatives were less potent compared to these scaffolds with imidazolylmethyl substitution owing to the interaction of nitrogen atom of the imidazole ring toward the heme (Fe(3+) ) of the aromatase. Results confirm the potential of our methodology for the design of new potent non-steroidal aromatase inhibitors.