MOLECULAR DOCKING ANALYSIS OF QUERCETIN, BERBERINE, AND EPIGALLOCATECHIN-3-GALLATE AGAINST KEY ANTIDIABETIC, ANTIOXIDANT, AND ANTI-INFLAMMATORY TARGETS IN DIABETES MELLITUS

Abstract

Diabetes mellitus is characterized by deregulated glucose homeostasis accompanied by chronic inflammation and oxidative stress that contribute to progression of micro- and macrovascular complications. Nutraceutical polyphenols such as quercetin, berberine, and epigallocatechin-3-gallate (EGCG) have pleiotropic effects relevant to glycemic control, antioxidant defense, and inflammatory modulation, but systematic comparative in silico assessment against multiple diabetes-relevant protein targets remains limited. To evaluate and compare the binding potential of quercetin, berberine, and EGCG against a panel of antidiabetic, antioxidant, and anti-inflammatory protein targets using molecular docking, and to rank compounds by multitarget binding profile and drug-like/ADMET predictions. Three ligands (quercetin, berberine, EGCG) were retrieved from PubChem and energy minimized (Open Babel/Chem3D). Eleven protein targets were selected from the RCSB PDB covering antidiabetic (DPP-4, α-glucosidase, PPARγ, AMPK), antioxidant (Nrf2–Keap1 complex interface, SOD, catalase), and anti-inflammatory (TNF-α, COX-2, NF-κB) pathways. Proteins were prepared by removal of crystallographic ligands/waters, addition of hydrogens, and Kollman charge assignment. Docking was performed with AutoDock Vina using target-specific grid boxes and exhaustiveness 8–20. Binding poses were analyzed with PyMOL and Discovery Studio for hydrogen bonds, hydrophobic and π interactions. Drug-likeness (Lipinski, SwissADME) and ADMET properties were predicted in silico. Docking produced target-dependent binding affinities ranging approximately from −4.6 to −10.8 kcal·mol−1. Quercetin showed high affinity for DPP-4 (−9.0 kcal·mol−1) and COX-2 (−9.4 kcal·mol−1) with multiple hydrogen bonds to Glu205/Glu206 and Tyr355 (DPP-4) and Ser530/Arg120 (COX-2). Berberine favored PPARγ (−9.6 kcal·mol−1) and AMPK (−9.0 kcal·mol−1), primarily via hydrophobic π–π stacking with Phe and Tyr residues and a salt-bridge-like interaction near His323. EGCG displayed strong binding to α-glucosidase (−10.2 kcal·mol−1) and Keap1 (−10.8 kcal·mol−1) forming 4–6 hydrogen bonds to key polar residues (e.g., Asp69, Arg415 in α-glucosidase; Ser363, Arg483 in Keap1). SwissADME indicated quercetin and berberine satisfy Lipinski space while EGCG shows borderline violations due to polar surface area; ADMET predicted moderate GI absorption for quercetin and berberine and low BBB penetration for all three, with low predicted hepatotoxicity and mixed CYP inhibition profiles. In silico findings suggest complementary multitarget potential: EGCG shows the strongest predicted interaction with antioxidant Keap1 and carbohydrate digestive enzymes, berberine preferentially engages nuclear metabolic regulators (PPARγ, AMPK), and quercetin provides balanced anti-inflammatory and antidiabetic engagement. These results support prioritization of EGCG for antioxidant pathway modulation, berberine for metabolic receptor modulation, and quercetin as a broad-spectrum lead. Experimental validation (enzyme assays, cellular models, and pharmacokinetic studies) is required to confirm these computational predictions.