In-Silico scrutinization of (Al, Ga, B, Si, Ge, and P)-doped C60 in sensing EGCG: An application based DFT study

Abstract

Since the invention of the biological sensor, many proposals and techniques have been developed to improve biosensor functionality. Because of its unique physicochemical properties, the recently developed carbon material “fullerene” improves the possibilities for developing highly sensitive biosensors. This study aims to conduct a computational investigations on utilization of fullerene (C₆₀) and the addition of elements as impurities into the same (doped-C₆₀) as sensors for EGCG. The introduction of impurities into nanomaterial structures increases intermolecular interaction. The fullerene structure, doped with Al, Ga, B, Si, Ge, and P, has been studied as an adsorbent. Density Functional Theory (DFT) based methods are used to investigate the interaction between fullerene or doped fullerene and EGCG. The interaction between the optimized doped structures and the optimized EGCG structure was investigated using the hybrid functional B3LYP, and 6-31G(d) basis set. To the best of our knowledge, this is the first such observation related to the intermolecular interaction between EGCG and doped-C₆₀ and its sensitivity. The sensitivity of the doped-C₆₀ towards EGCG were evaluated by the HOMO–LUMO energy gap and Conceptual Density Functional Theory (CDFT). The results depict Al-doped fullerene shows higher interaction/adsorption potential and sensitivity towards EGCG, as compared to the other studied C₆₀ materials. To acquire knowledge about the nature of intermolecular interactions during the adsorption phenomena, we have computed the Quantum Descriptors, Density of States(DOS) plots, Quantum Theory of Atoms in Molecules (QTAIM), and Non-Covalent Interaction (NCI) analysis. By creating high-sensitivity sensors for bioactive molecules like polyphenolic compounds (EGCG) in exploration of variety of dopants can be used in drug delivery, public health, and environmental monitoring. So, this study aims to improve biosensor technology and lays the foundations for future modular and accurate molecular sensor designs.