ABSTRACT: Protein sequencing is key to many biological fields to advance science and prospect medical applications based on proteomics. However, even with advanced techniques such as mass spectrometry it is hard to detect the fluctuations in AA sequences and optical/geometrical isomers, and cannot provide wide access to ex-novo sequencing of low quantities of proteins. We are presenting a new and disruptive method based on FET sensors for AA/polypeptide detection. We show unique signals (fingerprints) of every single AA and polypeptide mutations by solving the site-binding model self-consistently with the Gouy-Chapman-Stern model. The surface potential (Ψo), 2 nd gradient of the surface potential (δΨo 2 /δpH 2 ) and total surface capacitance (CT) are used as fingerprint signals to differentiate between the amino acids including the drain current variation as the signal transduction. These fingerprints are based on orthogonal properties of the AAs, which are the different proton affinities of each of the radicals, their dielectric constant and effective length, which is sensitive to the relative positions of the radicals to distinguish between isomers.