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

Naveen Kumar*, Cesar Pascual Garcia, Ankit Dixit, Ali Rezaei, Vihar Georgiev

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 the 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.

Original languageEnglish
Title of host publication2023 IEEE BioSensors Conference, BioSensors 2023 - Proceedings
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Electronic)9798350346046
DOIs
Publication statusPublished - 17 Oct 2023
Event1st Annual IEEE BioSensors Conference, BioSensors 2023 - London, United Kingdom
Duration: 30 Jul 20231 Aug 2023

Publication series

Name2023 IEEE BioSensors Conference, BioSensors 2023 - Proceedings

Conference

Conference1st Annual IEEE BioSensors Conference, BioSensors 2023
Country/TerritoryUnited Kingdom
CityLondon
Period30/07/231/08/23

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