Synthesis, characterization and antidiabetic evaluation of sulfonamide in corporated with 1,3,4-oxadiazole derivatives
- Vol.55(4), Oct-Dec
- Karnataka Association of Pharmaceutical Teachers of India (APTI) 2021
- 1145-1150p.
Aim/Background: There is an increasing prevalence of diabetes mellitus throughout the world, and new compounds are necessary to combat this. While the current available antidiabetic therapies are long-term complicated and side effects-prone, this has led to a demand for more affordable, more effective methods of tackling diabetes. Research is focused on finding alternative medicinal remedies with significant antidiabetic efficacy as well as low adverse effects. This study synthesized, characterized, and evaluated anti-diabetic properties of synthetic sulphonamide hybrid of 1,3,4-oxadiazole derivatives. Materials and Methods: An in vivo antihyperglycemic evaluation of the sulphonamide hybrid of 1,3,4-oxadiazole derivatives was conducted using wistar rat models of type II diabetes derived from a two-step synthesis. Our study examined the effects of synthesized compounds on a model induced by a high-fat diet combined with streptozotocin and nicotinamide injection. For assessment of diabetic effects, Vildagliptin (10 mg/kg/day) was used as the standard drug. On day 14th, 1,3,4-oxadiazole derivatives (50 mg/kg/day) significantly lowered the blood sugar of hyperglycemic rats. Results: Due HFD STZ with Nicotinamide blood glucose level of wistar rat was increased (295 ± 8.2). After 14th day administration of derivatives random blood glucose level under controlled. A-III (220± 7.5 B) and A-IV (222 ± 3.62 B) were lowered random blood glucose levels on wistar rat. As compared to diabetes control (295 ± 8.5), derivatives of 1,3,4-oxadiazole are considered promising lead compounds. Compounds A-III and A-IV were found to be the most effective in lowering blood glucose, indicating the potential of these compounds as antidiabetic agents. Conclusion: Hybrids developed in this study provide new classes of anti-diabetic agents, and further optimization can be performed using this information.