Novel Detection Methodology of Milk-Oligopeptides fingerprints using Ion-Sensitive BioFET [* Cross-Reference *]

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Naveen Kumar; Rakshita Dhar; César Pascual García; Vihar Georgiev, 2022, "Novel Detection Methodology of Milk-Oligopeptides fingerprints using Ion-Sensitive BioFET [* Cross-Reference *]", https://lore.list.lu/citation?persistentId=perma:LIST.KI83GG, LIST Open Repository, V1
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Description
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. (2022-10-27)
***This entry has been automatically imported via OpenAlex by LIST harvest scripts. Please refer to https://doi.org/10.26434/chemrxiv-2022-vxtgl for the original and latest version of the publication*** (2026-07-01)
Subject Chemistry; Engineering; Medicine, Health and Life Sciences; Physics
Keyword Tripeptide, Oligopeptide, Biological system, Noise (video), Chemistry, Peptide, Chromatography, Algorithm, Materials science, Computer science, Artificial intelligence, Biology, Biochemistry
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