Molecularly Imprinted Viral Protein Integrated Zn–Cu–In–Se–P Quantum Dots Superlattice for Quantitative Ratiometric Electrochemical Detection of SARS-CoV-2 Spike Protein in Saliva

Solution-processable colloidal quantum dots (QDs) are promising materials for the development of rapid and low-cost, next-generation quantum-sensing diagnostic systems. In this study, we report on the synthesis of multinary Zn-Cu-In-Se-P (ZCISeP) QDs and the application of the QDs-modified electrode (QDs/SPCE) as a solid superlattice transducer interface for the ratiometric electrochemical detection of the SARS-CoV-2-S1 protein in saliva. The ZCISeP QDs were synthesized through the formation of In(Zn)PSe QDs from InP QDs, followed by the incorporation of Cu cations into the crystal lattice via cation exchange processes. A viral-protein-imprinted polymer film was deposited onto the QDs/SPCE for the specific binding of SARS-CoV-2. Molecular imprinting of the virus protein was achieved using a surface imprinting electropolymerization strategy to create the MIP@QDs/SPCE nanosensor. Characterization through spectroscopic, microscopic, and electrochemical techniques confirmed the structural properties and electronic-band state of the ZCISeP QDs. Cyclic voltammetry studies of the QDs/SPCE superlattice confirmed efficient electron transport properties and revealed an intraband gap energy state with redox peaks attributed to the Cu1+/2+ defects. Binding of SARS-CoV-2-S1 to the MIP@QDs/SPCE cavities induced a gating effect that modulated the Fe(CN)63-/4- and Cu1+/2+ redox processes at the nanosensor interface, producing dual off/on ratiometric electrical current signals. Under optimal assay conditions, the nanosensor exhibited a wide linear detection range (0.001-100 pg/mL) and a low detection limit (0.34 pg/mL, 4.6 fM) for quantitative detection of SARS-CoV-2-S1 in saliva. The MIP@QDs/SPCE nanosensor demonstrated excellent selectivity against nonspecific protein targets, and the integration with a smartphone-based potentiostat confirmed the potential for point-of-care applications.