Detection of type-Ⅱ diabetes using graphene-based biosensors

Abstract

Diabetes is a global pandemic that increases the risk of various health complications, including heart attacks, renal failure, blindness, stroke, and peripheral neuropathy. Type-2 diabetes (T2D) results from an imbalance in lipid and glucose metabolism due to hostility to insulin action and insufficient insulin production response. Valine amino acid has been identified as a potential biomarker for T2D, but there have been no rigorous studies on its interaction with branch chain amino acids. In this study, we investigated the potential of graphene/modified graphene as a valine biosensor using density functional theory to examine the electronic properties and adsorption behaviour of graphene, Si-doped graphene (SiG), and P-doped graphene (PG). The adsorption of valine over the substrates was physisorption in nature, and the adsorption energies were in the order of SiG > G > PG. Density of states (DOS) and partial DOS calculations confirmed the molecule’s adsorption over the monolayers and indicated variations in the electronic properties. We also performed recovery time calculations to examine the reusability of the nano-surfaces as potential biosensors. Ultrafast recovery times were predicted for all three systems, with SiG showing the best results. Our study suggests that SiG could be used as a biosensor for valine, providing a real-time and efficient diagnostic tool for T2D.