Repurposing FDA-Approved Drugs and Exploring Nutraceuticals for Diabetes Management via Molecular Docking and ADMET Analysis

Abstract

Diabetes mellitus is a chronic metabolic disorder characterised by persistent hyperglycaemia and complications that may affect multiple organ systems. This study used a computational approach to compare selected nutraceutical compounds with FDA-approved antidiabetic drugs for their potential interactions with diabetes-related protein targets. Twenty compounds, comprising ten nutraceutical molecules and ten approved antidiabetic drugs, were evaluated by molecular docking against two target proteins, 3A4A and 2PRG. Docking simulations were conducted using AutoDock 4.2, and the resulting binding affinities and amino acid interactions were assessed. The predicted pharmacokinetic and toxicity characteristics were further examined through in silico ADMET analysis, including drug-likeness, gastrointestinal absorption, blood-brain barrier permeability, P-glycoprotein substrate prediction, and toxicity parameters. Among the nutraceutical compounds, glycyrrhetinic acid showed the strongest interaction with 3A4A, with a docking score of −7.12 kcal/mol, while berberine demonstrated a docking score of −6.34 kcal/mol. For 2PRG, glycyrrhetinic acid and berberine also showed favourable interactions, with docking scores of −7.55 kcal/mol and −7.20 kcal/mol, respectively. The approved drugs metformin and linagliptin also exhibited strong binding profiles, supporting the comparative docking approach used in this study. The ADMET results indicated that several nutraceutical compounds had acceptable predicted pharmacokinetic features and toxicity profiles comparable to those of selected conventional drugs. Overall, the findings suggest that glycyrrhetinic acid, berberine, metformin, and linagliptin may warrant further experimental evaluation as candidates or reference compounds in diabetes-related drug discovery. These computational results should be interpreted as preliminary and require biological validation before therapeutic relevance can be confirmed in future diabetes research and practice.