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Published on: October 10, 2018
Estimating kinetic constants in the Michaelis-Menten model from one enzymatic assay using Approximate Bayesian
Jakub M Tomczak1, Ewelina Węglarz-Tomczak2
1Institute of Informatics, Faculty of Science, University of Amsterdam, The Netherlands.
Abstract:
The Michaelis-Menten equation is one of the most extensively used models in biochemistry for studying enzyme kinetics. However, this model requires at least a couple (e.g., eight or more) of measurements at different substrate concentrations to determine kinetic parameters. Here, we report the discovery of a novel tool for calculating kinetic constants in the Michaelis-Menten equation from only a single enzymatic assay. As a consequence, our method leads to reduced costs and time, primarily by lowering the amount of enzymes, since their isolation, storage and usage can be challenging when conducting research.
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