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.
Highlights
Enzyme assays are an important tool for characterizing enzymes
We are interested in understanding how to characterize a primary enzyme in a non-standard coupled enzyme assay, where one of the products of the auxiliary enzyme is a substrate for the primary enzyme and where we explicitly account for the reversibility of the auxiliary enzyme reaction
Our analysis allows us to obtain estimates for when we expect to see a linear growth in NADH concentration, the typical regime measured in enzyme assays since it allows a quick sanity check of experimental results and is much easier to fit to data
Summary
Enzyme assays are an important tool for characterizing enzymes. In the classic assay, a single reaction converts a substrate into a product, using an enzyme as a catalyst, and the product is measured over time to estimate the initial reaction velocity (Bisswanger 2014). Experimental noise can increase the error when attempting to implement an accurate fit in nonlinear systems - restricting oneself to a linear growth regime significantly reduces this issue For these reasons, we use singular perturbation theory (Bender and Orszag 2013; Kevorkian and Cole 2013) to analyse the mathematical systems we derive, and to understand how to determine the kinetic parameter values of the primary enzyme in such a system. We use singular perturbation theory (Bender and Orszag 2013; Kevorkian and Cole 2013) to analyse the mathematical systems we derive, and to understand how to determine the kinetic parameter values of the primary enzyme in such a system This provides a significant reduction of the complexity of the system, and allows us to minimize issues associated with experimental noise, as we aim to determine functional forms for the measurable reaction velocities.
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