The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of Km: The Example of Paraoxonase 1

11Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

Several approaches for determining an enzyme’s kinetic parameter Km (Michaelis constant) from progress curves have been developed in recent decades. In the present article, we compare different approaches on a set of experimental measurements of lactonase activity of paraoxonase 1 (PON1): (1) a differential-equation-based Michaelis–Menten (MM) reaction model in the program Dynafit; (2) an integrated MM rate equation, based on an approximation of the Lambert W function, in the program GraphPad Prism; (3) various techniques based on initial rates; and (4) the novel program “iFIT”, based on a method that removes data points outside the area of maximum curvature from the progress curve, before analysis with the integrated MM rate equation. We concluded that the integrated MM rate equation alone does not determine kinetic parameters precisely enough; however, when coupled with a method that removes data points (e.g., iFIT), it is highly precise. The results of iFIT are comparable to the results of Dynafit and outperform those of the approach with initial rates or with fitting the entire progress curve in GraphPad Prism; however, iFIT is simpler to use and does not require inputting a reaction mechanism. Removing unnecessary points from progress curves and focusing on the area around the maximum curvature is highly advised for all researchers determining Km values from progress curves.

Cite

CITATION STYLE

APA

Petrič, B., Goličnik, M., & Bavec, A. (2022). The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of Km: The Example of Paraoxonase 1. Molecules, 27(4). https://doi.org/10.3390/molecules27041306

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free