In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates

Abstract

Background: One of the causes of death is diabetes. Anti-diabetic drugs currently available do not work optimally because some have been reported to have side effect and resistance. Objective: This study aimed to flavonoid compounds from Syzygium cumini var. album with the greatest anti-diabetic activity and lower toxicity than acarbose. Materials and Methods: This research is an in silico study of nine flavonoid compounds from Syzygium cumini var. album, starting with PASS online was used to predict the activity spectrum of substances, drug-likeness prediction using DruLiTo, ADMET prediction (absorption, distribution, metabolism, excretion, and toxicity) using pkCSM online. Molecular docking was carried out by the AutoDock 4.2.6 program on α-glucosidase targeting. Visualization is done with the Discovery Studio Visualizer software. Results: From the data obtained, D-(+)-Catechin has a high affinity for α-glucosidase with a free energy of binding (ΔG) -5.94 kcal/mol and an inhibition constant (Ki) of 44270 nm. Conclusion: Based on the results of the study, it can be concluded that the flavonoid compounds from Syzygium cumini var. album has the potential as a promising anti-diabetic drug candidate, where the best candidate is D- (+)-Catechin. However, further studies of flavonoid compounds from Syzygium cumini var. album are needed. Key words: α-glucosidase, Molecular docking, PASS, Pharmacokinetics, Flavonoid