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 |
|---|---|
| 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 |
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Keywords
- Approximate Bayesian Computation
- Bayesian statistics
- enzymology
- likelihood-free
- Michaelis–Menten kinetics
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Estimating kinetic constants in the Michaelis–Menten model from one enzymatic assay using Approximate Bayesian Computation. / Tomczak, Jakub M.; Węglarz-Tomczak, Ewelina.
In: FEBS Letters, Vol. 593, No. 19, 01.10.2019, p. 2742-2750.Research output: Contribution to Journal › Article › Academic › peer-review
TY - JOUR
T1 - Estimating kinetic constants in the Michaelis–Menten model from one enzymatic assay using Approximate Bayesian Computation
AU - Tomczak, Jakub M.
AU - Węglarz-Tomczak, Ewelina
PY - 2019/10/1
Y1 - 2019/10/1
N2 - 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.
AB - 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.
KW - Approximate Bayesian Computation
KW - Bayesian statistics
KW - enzymology
KW - likelihood-free
KW - Michaelis–Menten kinetics
UR - http://www.scopus.com/inward/record.url?scp=85069862689&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069862689&partnerID=8YFLogxK
U2 - 10.1002/1873-3468.13531
DO - 10.1002/1873-3468.13531
M3 - Article
VL - 593
SP - 2742
EP - 2750
JO - FEBS Letters
JF - FEBS Letters
SN - 0014-5793
IS - 19
ER -