Herbal informatics approach for the selection of natural compounds targeting diabetes mellitus

Abstract

Diabetes mellitus is a chronic metabolic disorder where the Beta-cells present on the islets of Langerhans of pancreas fail to produce enough insulin resulting in unstable blood glucose level that pave the way for insulin resistance by tissues. According to recent WHO (2016) report, 422 million populations were suffering from this metabolic disorder worldwide. Inflammatory mediators such as Alpha-glucosidase, Glucose Transporter Type-4, Sodium Glucose Transporter Type-2, Glucagon like peptide-1, 11 beta-Hydroxysteroid dehydrogenases, etc., are known to play an important role in pathogenesis of this disease and have been considered as potential therapeutic targets. However, despite the great progress achieved in synthesis of drugs designed to act on targeted molecules, treatment to diabetes is still a challenge because of the common side effects associate with these medicines. Medicinal plants and their biomolecules may be feasible alternative for treatment of diabetes. In the present study, we have utilized <em>in silico </em> herbal informatics model to develop a natural remedies with minimal or no side effects which can inhibit the mediators of disease. In this study bio-prospection model were used where random search is included, followed by the index and rationale based selection of plant products targeting the diabetic factors. These models provide <em>Nigella sativa </em> L.<em>, Momordica charantia </em>L. and <em> Camellia sinensis </em> (L.) Kuntze as identified plants that can be used to target the disease at both <em>in vitro</em> and <em> in vivo</em> level.