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The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1
Several approaches for determining an enzyme’s kinetic parameter K(m) (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 di...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874660/ https://www.ncbi.nlm.nih.gov/pubmed/35209091 http://dx.doi.org/10.3390/molecules27041306 |
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author | Petrič, Boštjan Goličnik, Marko Bavec, Aljoša |
author_facet | Petrič, Boštjan Goličnik, Marko Bavec, Aljoša |
author_sort | Petrič, Boštjan |
collection | PubMed |
description | Several approaches for determining an enzyme’s kinetic parameter K(m) (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 K(m) values from progress curves. |
format | Online Article Text |
id | pubmed-8874660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88746602022-02-26 The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 Petrič, Boštjan Goličnik, Marko Bavec, Aljoša Molecules Article Several approaches for determining an enzyme’s kinetic parameter K(m) (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 K(m) values from progress curves. MDPI 2022-02-15 /pmc/articles/PMC8874660/ /pubmed/35209091 http://dx.doi.org/10.3390/molecules27041306 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Petrič, Boštjan Goličnik, Marko Bavec, Aljoša The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title | The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title_full | The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title_fullStr | The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title_full_unstemmed | The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title_short | The Removal of Time–Concentration Data Points from Progress Curves Improves the Determination of K(m): The Example of Paraoxonase 1 |
title_sort | removal of time–concentration data points from progress curves improves the determination of k(m): the example of paraoxonase 1 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874660/ https://www.ncbi.nlm.nih.gov/pubmed/35209091 http://dx.doi.org/10.3390/molecules27041306 |
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