Journal
FEBS LETTERS
Volume 593, Issue 19, Pages 2742-2750Publisher
WILEY
DOI: 10.1002/1873-3468.13531
Keywords
Approximate Bayesian Computation; Bayesian statistics; enzymology; likelihood-free; Michaelis-Menten kinetics
Funding
- Mobilnosc Plus V from the Polish Ministry of Science and Higher Education [1639/MOB/V/2017/0]
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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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