Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.