Experimental and statistical analysis methods for peptide detection using surface‐enhanced Raman spectroscopy

Surface‐enhanced Raman spectroscopy (SERS) has the potential to make a significant impact in biology research due to its ability to provide information orthogonal to that obtained by traditional techniques such as mass spectrometry (MS). While SERS has been well studied for its use in chemical applications, detailed investigations with biological molecules are less common. In addition, a clear understanding of how methodology and molecular characteristics impact the intensity, the number of peaks, and the signal‐to‐noise of SERS spectra is largely missing. By varying the concentration and order of addition of the SERS‐enhancer salt (LiCl) with colloidal silver, we were able to evaluate the impact of these variables on peptide spectra using a quantitative measure of spectra quality based on the number of peaks and peak intensity. The LiCl concentration and order of addition that produced the best SERS spectra were applied to a panel of synthetic peptides with a range of charges and isoelectric points (pIs) where the pI was directly correlated with higher spectral quality. Those peptides with moderate to high pIs and spectra quality scores were differentiated from each other using the improved method and a hierarchical clustering algorithm. In addition, the same method and algorithm was applied to a set of highly similar phosphorylated peptides, and it was possible to successfully classify the majority of peptides on the basis of species‐specific peak differences.