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  4. Parameter distribution analysis for enzyme kinetic models with inhibition
 
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Parameter distribution analysis for enzyme kinetic models with inhibition

Publikationstyp
Journal Article
Date Issued
2025-06-10
Sprache
English
Author(s)
Waluga, Thomas  
Systemverfahrenstechnik V-4  
Rosenthal, Katrin  
TORE-URI
https://hdl.handle.net/11420/55930
Journal
Industrial & engineering chemistry research  
Volume
64
Issue
25
Start Page
12536
End Page
12544
Citation
Industrial and Engineering Chemistry Research 64 (25): 12536-12544 (2025)
Publisher DOI
10.1021/acs.iecr.5c00435
Scopus ID
2-s2.0-105007808631
Publisher
ACS
The correct characterization of enzyme kinetics is an important issue for the successful implementation of an enzymatic process on an industrial scale. In this study, the calculation of parameter distribution (PD) based on the known approach of adsorption energy distribution is used to estimate the parameters of different enzyme kinetics with inhibition. For comparison, the parameters are also estimated by nonlinear regression. The results demonstrate that the PD is, in principle, capable of estimating the kinetic parameters of an enzymatic reaction with inhibition. Additionally, the application of this AED-based approach to in silico data demonstrates that the estimated parameters are in better agreement with the set parameters compared to the results obtained through nonlinear regression with a local solver. Furthermore, the efficacy of this approach in estimating kinetic parameters is also evident when it is applied to real experimental data. The successful application of the PD for the estimation of kinetic parameters opens up a further alternative to the multitude of different tools for the characterization of enzyme kinetic parameters. It should be noted that the computational effort is comparatively high. However, this must be considered in the overall context, as this approach requires very few data points and therefore not only can determine kinetic parameters very well but also has the potential to reduce experimental effort in the laboratory.
DDC Class
600: Technology
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