## 3 Results and Discussion
### Detection of S, RBD, and BSA Proteins in Saliva: Specificity, Sensitivity, and Selectivity Studies  
In all of the measurements presented in this section, we used S, RBD, and BSA proteins with a concentration of \(10^{-9}\) M. The saliva (SL) has not been treated by any means to remove debris. Each SERS spectrum was recorded during an acquisition time of 3 s. Each spectrum is the result of an average of three spectra taken from three positions. We dropped a 1.5 uL of the saliva sample with S protein (SLS) and another control without the S protein (SL). After 20 min of drying, we measured the SERS spectra in different positions. Figure 6 shows the different spectra on five positions for the SL and SLS. A good signal-to-noise ratio (SNR) is observed in the spectra. We collected Raman spectra from the SL and SLS for a short integration time of 3 s and with very low power. In order to verify the reproducibility of the measurement, we carried out a multivariate analysis on the SERS spectra by using principal component analysis (PCA) (Figure 7). We used principal component analysis for spectroscopy applications' apps of Origin pro to perform the analysis. We started by smoothing our spectra, then we subtracted the background by using a baseline correction, and finally, we normalized all the spectra before executing the PCA analysis. If we take the middle of each set of proteins in Figure 7, the distance is around 5, however, the distance between two points is around 0.25, that's mean the two proteins are separated  
Figure 5: (**a**) Concentration-dependent SERS study of S protein by varying the concentration from \(10^{-6}\) M to \(10^{-10}\) M (**b**) A semi-log plot of the intensity as a function of the concentration of S protein. (**c**) A semi-log plot of the intensity as a function of the concentration of RBD protein. Acquisition time 3 s, Laser wavelength 632.8 nm. SERS spectra are recorded on the same substrate; each spectrum is the result of an average of three spectra taken from three different positions. enough. No one point of the S protein is inside the saliva (SL) circle, the latter confirms a 0% uncertainty. We observed clearly, from the PCA analysis, how the S protein is identified from the control (SL). The most important conclusion from this statistical study is that the samples containing the S protein are very close, while those containing just SL are scattered (Figure 7). The latter confirms the sensitivity and specificity of SERS to detect a very small quantity of the S proteins in a complex medium such as saliva. In order to check the specificity of our method, we replaced the S protein with the RBD. We dropped 1.5 \(\mu\)L of the RBD protein immersed in saliva (SLR) and one control SL without the RBD protein (SL). After 20 min of drying, we measured the SERS spectra in different positions. Figure 8 shows different spectra on five positions for the SL and SLR. We can observe the presence signal in the spectra. We collected Raman spectra from the SL and SLR for a short integration time of 3 s and very low power. In order to verify the reproducibility of the SERS method, we carried out a multivariate analysis on the SERS spectra by using principal component analysis (PCA) (Figure 9). Pretreatment processing such as smoothing, background subtraction, and normalization have been performed before statistical studies. If we take the middle of each set of the proteins in Figure 9, the distance between the two circles is around 3, however, the distance between the two points is 1. All the points are inside, except one point of SL that exists outside the two areas. We conclude that the uncertainty here is around 10% and it is lower than the case of the S protein. We can observe clearly from the PCA analysis how the RBD protein is identified from the control (SL). We conclude with the present analysis that the identification of the S protein is more accurate than the RBD. The latter could be attributed to the size of the S protein (1273 residues) compared to the RBD protein (197 residues).