Novel Detection Methodology of Milk-Oligopeptides fingerprints using Ion-Sensitive BioFET

Protein sequencing is an important key to personalized medicines, but the process is complex enough to halt the ongoing progress in proteomics. In this paper, we have proposed a novel simulation methodology for the detection of oligopeptide fingerprints using a Field-Effect-Transistor. In our approach, the Gouy-Chapman-Stern and Site-Binding models are solved self-consistently to capture the response of immobilized peptides in the presence of an electrolyte. Our results show the unique signatures of two anti-hypertensive tripeptides in terms of variation in surface potential, inflection points and point-of-zero-charge in 2nd order differentiation of surface potential and total surface capacitance. We have shown that the presence of silanol sites, in presence of single or multiple oligopeptides, is responsible for reduced sensor’s sensitivity. We have proposed a novel noise-reduction technique to eliminate the noise present in the experimental data.