Label-Free SERS Discrimination of Purine Small-Molecule Biomarkers: DFT Insight into Interfacial Binding Mechanism

In this study, we employed density functional theory (DFT) to investigate the interactions of uric acid (UA) and xanthine (Xa), two structurally similar molecules, with Au-enhanced substrates in the surface-enhanced Raman scattering (SERS) effect. Theoretical calculations of the molecular electrostatic potential (ESP) revealed pronounced electronegativity at the carbonyl groups on the purine cores of both molecules, with the N7 nitrogen atom in the imidazole ring of Xa also exhibiting notable electronegativity. These regions are therefore identified as potential active sites for molecule-substrate interactions. To account for possible docking configurations, UA/Xa-Au₆ complex models were constructed and their binding energies were calculated. The binding energy results confirmed the formation of stable molecule-metal complexes across different docking scenarios. Analysis of the frontier molecular orbitals (FMOs) and charge density differences (CDDs) of both the isolated molecules and their complexes demonstrated charge-transfer excitations between UA/Xa and the Au₆ cluster at various active sites. Theoretical Raman/SERS spectral analyses of the complexes revealed pronounced selective enhancement, shifts, and broadening of characteristic frequencies depending on the docking configuration. Based on the characteristic frequency variations of the two molecules, we propose a label-free detection strategy that is theoretically reproducible, highly sensitive, and high-throughput for analyzing structurally similar small-molecule biomarkers (UA and Xa) in complex physiological matrices. This study not only deepens our understanding of the physical mechanisms underlying molecule-substrate interactions in the SERS effect, but also demonstrates the theoretical feasibility of label-free identification of UA and Xa in complex physiological samples using SERS. Furthermore, it provides a promising and efficient label-free sensing strategy for detecting structurally similar small-molecule biomarkers.