A method to detect enzymatic reactions with field effect transistor
Year: 2024
Type: article
Abstract: Study of enzyme-substrate interactions is a task of great practical and scientific importance. This paper describes the application of ion-sensitive field effect transistors in quasi-equilibrium state for examination of enzymatic reactions. A reaction occurring in the liquid gate affects the chemical potential of electrons in this gate, and this phenomenon may be used to explore biochemical interactions. This strategy can be applied to detect interactions of enzymes with substrates, inhibitors and activators regardless of their optical and electrochemical properties. Using the developed method, the reactions catalyzed by the enzymes belonging to six different EC classes were analyzed, and Michaelis constants for their substrates were determibed. K m values obtained using the proposed method were in good agreement with those obtained with standard colorimetric and fluorimentric assays. Practical potential of the described method was demonstrated by studying the interactions of a diagnostically significant enzyme α-D-galactosidase with its natural and artificial substrates and its inhibitor. K m values for α-D-galactosidase using melibiose and raffinose as substrates and IC50 value for the enzyme inhibitor 1-deoxygalactonojirimycin were determined. The described method allows rapid and label-free investigation of enzyme interactions with substrates, inhibitors and activators for a wide range of biocatalysts. • A new principle of chemical reaction detection by field effect transistor is described. • The proposed method allows detection of the enzyme-substrate interaction for the main 6 classes of enzymes. • The interaction of significant enzyme α-D-galactosidase with its natural and artificial substrates and inhibitor was studied.
Source: Sensors International
Language: English
Subfield: Bioengineering
Field: Chemical Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $840
Funder: Russian Science Foundation
Award: G2847633039
OpenAlex ID: W4402629654
