Skip to main content

Research Repository

Advanced Search

Using singular perturbation theory to determine kinetic parameters in a non-standard coupled enzyme assay

Dalwadi, Mohit P.; Orol, Diego; Walter, Frederik; Minton, Nigel P.; King, John R.; Kovács, Katalin

Using singular perturbation theory to determine kinetic parameters in a non-standard coupled enzyme assay Thumbnail


Authors

Mohit P. Dalwadi

Diego Orol

Frederik Walter

JOHN KING JOHN.KING@NOTTINGHAM.AC.UK
Professor of Theoretical Mechanics



Abstract

We investigate how to characterize the kinetic parameters of an aminotransaminase using a non-standard coupled (or auxiliary) enzyme assay, where the peculiarity arises for two reasons. First, one of the products of the auxiliary enzyme is a substrate for the primary enzyme and, second, we explicitly account for the reversibility of the auxiliary enzyme reaction. Using singular perturbation theory, we characterize the two distinguished asymptotic limits in terms of the strength of the reverse reaction, which allows us to determine how to deduce the kinetic parameters of the primary enzyme for a characterized auxiliary enzyme. This establishes a parameter-estimation algorithm that is applicable more generally to similar reaction networks. We demonstrate the applicability of our theory by performing enzyme assays to characterize a novel putative aminotransaminase enzyme, CnAptA (UniProtKB Q0KEZ8) from Cupriavidus necator H16, for two different omega-amino acid substrates.

Citation

Dalwadi, M. P., Orol, D., Walter, F., Minton, N. P., King, J. R., & Kovács, K. (2020). Using singular perturbation theory to determine kinetic parameters in a non-standard coupled enzyme assay. Journal of Mathematical Biology, 81(2), 649-690. https://doi.org/10.1007/s00285-020-01524-8

Journal Article Type Article
Acceptance Date Jul 14, 2020
Online Publication Date Aug 6, 2020
Publication Date Aug 6, 2020
Deposit Date Aug 10, 2020
Publicly Available Date Mar 28, 2024
Journal Journal of Mathematical Biology
Print ISSN 0303-6812
Electronic ISSN 1432-1416
Peer Reviewed Peer Reviewed
Volume 81
Issue 2
Pages 649-690
DOI https://doi.org/10.1007/s00285-020-01524-8
Keywords Agricultural and Biological Sciences (miscellaneous); Modelling and Simulation; Applied Mathematics
Public URL https://nottingham-repository.worktribe.com/output/4816350
Publisher URL https://link.springer.com/article/10.1007%2Fs00285-020-01524-8
Additional Information Received: 7 August 2019; Revised: 29 June 2020; First Online: 6 August 2020

Files




You might also like



Downloadable Citations