Computational screening of phytochemicals for anti-diabetic drug discovery

Diabetes is one of the most common chronic and progressive diseases around the world and the number of people with diabetes is projected to rise in the next few years. Although many synthetic drugs are effective in controlling diabetes, their long-term usage has undesirable side effects. Hence, there is a growing scientific interest to replace synthetic drugs with natural drugs from medicinal plants. However, understanding the role of molecules and their interaction are necessary for the effective anti-diabetic drug discovery. Over the years, computational biology methods, such as molecular docking, simulations of biomolecules, computer-aided drug design (CADD), and multi-scale biological modeling have been developed in the drug discovery process. Therefore, the present chapter aimed to understand the characteristics of diabetes, the role of phytochemicals from natural sources in controlling diabetes, and the anti-diabetic mechanism of phytochemicals. The chapter also covers the computational screening techniques using phytochemicals in anti-diabetic drug discovery. Many phytochemicals from natural sources showed potential anti-diabetic properties. The use of CADD will speed up the drug discovery process, mitigate risk, and help to identify well-established targets with more innovative drugs in the future.