Molecular Docking and Simulation Studies of Antidiabetic Agents Devised from Hypoglycemic Polypeptide-P of Momordica charantia

Abstract

Diabetes mellitus termed as metabolic disorder is a collection of interlinked diseases and mainly body’s inability to manage glucose level which leads to cardiovascular diseases, renal failure, neurological disorders, and many others. The drugs contemporarily used for diabetes have many inevitable side effects, and many of them have become less responsive to this multifactorial disorder. Momordica charantia commonly known as bitter gourd has many bioactive compounds with antidiabetic properties. The current study was designed to use computational methods to discover the best antidiabetic peptides devised from hypoglycemic polypeptide-P of M. charantia. The binding affinity and interaction patterns of peptides were evaluated against four receptor proteins (i.e., as agonists of insulin receptor and inhibitors of sodium-glucose cotransporter 1, dipeptidyl peptidase-IV, and glucose transporter 2) using molecular docking approach. A total of thirty-seven peptides were docked against these receptors. Out of which, top five peptides against each receptor were shortlisted based on their S-scores and binding affinities. Finally, the eight best ligands (i.e., LIVA, TSEP, EKAI, LKHA, EALF, VAEK, DFGAS, and EPGGGG) were selected as these ligands strictly followed Lipinski’s rule of five and exhibited good ADMET profiling. One peptide EPGGGG showed activity towards insulin and SGLT1 receptor proteins. The top complex for both these targets was subjected to 50 ns of molecular dynamics simulations and MM-GBSA binding energy test that concluded both complexes as highly stable, and the intermolecular interactions were dominated by van der Waals and electrostatic energies. Overall, the selected ligands strongly fulfilled the drug-like evaluation criterion and proved to have good antidiabetic properties.