In silico study of the anti-amylase activity of certain metabolites derived from marine organisms

Abstract

Diabetes mellitus is a prevalent chronic metabolic disorder characterized by persistent hyperglycemia resulting from impaired insulin secretion or reduced insulin activity in target tissues, which prevents the efficient utilization and storage of glucose. Although several antidiabetic medications are currently available, their adverse effects continue to limit therapeutic effectiveness. In this context, inhibition of human pancreatic α-amylase (HPA), a key enzyme involved in carbohydrate digestion, represents an important therapeutic strategy for the management of Type 2 Diabetes Mellitus (T2DM). The present study adopted a stepwise in silico strategy aimed at identifying safe and potent HPA inhibitors from marine-derived secondary metabolites. Initially, an extensive literature survey was conducted to collect compounds previously extracted, purified, and chemically characterized from marine organisms. The selected molecules were then subjected to safety filtering based on cardiotoxicity and carcinogenicity predictions in order to retain only safe compounds. Subsequently, the remaining safe candidates were evaluated through molecular docking against HPA using AutoDock Vina, while interaction analysis and visualization were performed with Discovery Studio Visualizer. The results revealed that several marine metabolites display strong binding affinity toward the catalytic site of HPA and exhibit favorable pharmacokinetic and safety profiles. Among them, Mol7, Mol22, and Mol23, derived from Aspergillus and Streptomyces species, demonstrated the highest inhibitory potential with binding energies of - 10.0 kcal/mol and -9.5 kcal/mol, respectively. Importantly, all selected compounds showed stronger binding affinities than the reference inhibitor acarbose (-7.9 kcal/mol). These findings highlight the potential of marine-derived secondary metabolites as promising candidates for the development of novel HPA inhibitors for the treatment of T2DM. Nevertheless, further in vitro and in vivo studies are required to validate these computational predictions.