NANO - ENABLED COMPUTATIONAL INSIGHTS INTO FRUIT PHYTOCHEMICALS AS DUAL MODULATORS OF INSULIN RECEPTOR AND PPAR

Abstract

The rising global burden of type 2 diabetes mellitus underscores the need for therapeutic approaches capable of regulating multiple control points within insulin signalling networks. Although dietary phytochemicals have been widely associated with antidiabetic effects, their practical application is frequently limited by poor molecular stability and variable interaction with biological targets. In this study, a nano-enabled computational strategy was applied to investigate fruit-derived phytochemicals against two complementary antidiabetic targets: a computationally defined organic binding region within the insulin receptor ectodomain (PDB ID: 7BW8), which plays a key role in signal initiation, and peroxisome proliferator-activated receptor gamma (PPARγ; PDB ID: 7AWC), a major regulator of insulin sensitivity. A total of sixty-five phytochemicals identified from banana, mango, and jackfruit were screened using molecular docking and MM-GBSA binding free energy calculations, followed by adsorption and electronic interaction analyses on AgNO₃ surfaces to evaluate nano-interface stabilization. Selected high-affinity ligands were further examined through independent 100 ns molecular dynamics simulations using the Desmond engine. Among the screened compounds, 1,3,6-tri-O-galloyl-β-D-glucose displayed strong affinity toward PPARγ, achieving docking scores of approximately −10.4 kcal/mol and MM-GBSA binding energies below −65 kcal/mol, surpassing the reference drug acarbose. In the case of the insulin receptor target, 4-epicyclomusalenone showed stable binding characterized by persistent hydrogen bonds with Asn541 and Ser540, together with sustained hydrophobic interactions involving Trp493 and Tyr492, maintaining an average of three to four contacts throughout the simulation period. Collectively, these findings highlight nano-stabilized phytochemicals as promising dual modulators of insulin signalling pathways and provide a robust computational basis for future experimental validation.