VIRTUAL SCREENING BY IN SILICO MOLECULAR DOCKING AND PHARMACOKINETIC OF CHALCONE HYBRID AS α-GLUCOSIDASE INHIBITOR

Abstract

Diabetes, particularly type 2, is increasing in prevalence every year and has emerged as the third-most significant global health issue. One of the critical approaches to targeting enzymes that regulate carbohydrate metabolism is the α-glucosidase enzyme. Inhibiting this enzyme can reduce glucose absorption in the blood by causing the carbohydrates to break down. Commercially available drugs usually have unwanted side effects; hence, the development of novel drugs is a must. This current study aims to develop anti-diabetic drugs using a computational approach to screen out the best compounds (1–9). We performed in silico molecular docking using Auto Dock 4.0 and visualized the results using PyMOL and Discovery Studio. The study found binding energies (BE) that were greater than or equal to acarbose (-8.08 kcal/mol) and between -6.65 and -8.70 kcal/mol. The drug-like properties, pharmacokinetics, toxicity profile, and drug score were performed using the SwissADME, AdmetSAR, and Molsoft programs. Compounds 1–9 obeyed the Lipinski Rule of Five, and most of the compounds had drug-like properties and were non-toxic. Besides, they have promising interactions with α-glucosidase enzyme. Hence, they have the potential to develop into potent anti-diabetic drugs with lesser toxicity.