Ultra-high sensitivity of the non-immunological affinity of graphene oxide-peptide-based surface plasmon resonance biosensors to detect human chorionic gonadotropin.

Specific peptide aptamers can be used in place of expensive antibody proteins, and they are gaining increasing importance as sensing probes due to their potential in the development of non-immunological assays with high sensitivity, affinity and specificity for human chorionic gonadotropin (hCG) protein. We combined graphene oxide (GO) sheets with a specific peptide aptamer to create a novel, simple and label-free tool to detect abnormalities at an early stage of pregnancy, a GO-peptide-based surface plasmon resonance (SPR) biosensor. This is the first binding interface experiment to successfully demonstrate binding specificity in kinetic analysis biomechanics in peptide aptamers and GO sheets. In addition to the improved affinity offered by the high compatibility with the target hCG protein, the major advantage of GO-peptide-based SPR sensors was their reduced nonspecific adsorption and enhanced sensitivity. The calculation of total electric field intensity (ΔE) in the GO-based sensing interfaces was significantly enhanced by up to 1.2 times that of a conventional SPR chip. The GO-peptide-based chip (1mM) had a high affinity (K _A ) of 6.37×10 ¹² M ^-1 , limit of detection of 0.065nM and ultra-high sensitivity of 16 times that of a conventional SPR chip. The sensitivity of the slope ratio of the low concentration hCG protein assay in linear regression analysis was GO-peptide (1mM): GO-peptide (0.1mM): conventional chip (8-mercaptooctanoic acid)-peptide (0.1mM)=8.6: 3.3: 1. In summary, the excellent binding affinity, low detection limit, high sensitivity, good stability and specificity suggest the potential of this GO-peptide-based SPR chip detection method in clinical application. The development of real-time whole blood analytic and diagnostic tools to detect abnormalities at an early stage of pregnancy is a promising technique for future clinical application.
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