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.
Original language | English |
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Pages (from-to) | 2742-2750 |
Number of pages | 9 |
Journal | FEBS Letters |
Volume | 593 |
Issue number | 19 |
DOIs | |
Publication status | Published - 1 Oct 2019 |
Externally published | Yes |
Funding
EW-T is financed by a grant within Mobilnosc Plus V from the Polish Ministry of Science and Higher Education (Grant No. 1639/MOB/V/2017/0).
Keywords
- Approximate Bayesian Computation
- Bayesian statistics
- enzymology
- likelihood-free
- Michaelis–Menten kinetics