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Addressing sensitivity and non-uniqueness in the determination of enzyme kinetic parameters
ID Lakner, Mitja (Author), ID Plazl, Igor (Author)

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Abstract
Accurate determination of enzyme kinetic parameters is critical for model-based design and intensification of biocatalytic processes, particularly in microscale systems. While Michaelis-Menten kinetics provides a foundational framework, its extension to reversible, multi-substrate, and inhibited reactions introduces significant challenges in parameter estimation-most notably, parameter sensitivity and non-uniqueness. This study systematically investigates these challenges across three case studies of increasing complexity: (i) mono-substrate Michaelis-Menten kinetics, (ii) reversible enzymatic reactions with four parameters, and (iii) a six-parameter reversible mono-substrate kinetic model with substrate and product inhibition. In the first two cases, we show that vastly different parameter sets can yield nearly indistinguishable model fits to experimental data, exposing the limitations of classical graphical and nonlinear regression methods. In the mono-substrate case based on real experimental data, two parameter sets differing by nearly two orders of magnitude produce virtually identical model outputs, demonstrating practical non-uniqueness even for simple kinetic models. For the six-parameter inhibited system, a theoretical and numerical analysis reveals intrinsic non-uniqueness of the parameter estimation problem, characterized by an in finite family of parameter vectors yielding identical solutions. These results demonstrate that parameter non-uniqueness is not merely a consequence of experimental noise, but a structural property of complex kinetic models, emphasizing the need for more robust and structurally informed modeling approaches in biocatalysis.

Language:English
Keywords:enzyme kinetics, kinetic parameter estimation, parameter non-uniqueness
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FKKT - Faculty of Chemistry and Chemical Technology
Publication status:Published
Publication version:Version of Record
Year:2025
Number of pages:Str. 227-236
Numbering:Vol. 39, iss. 4
PID:20.500.12556/RUL-180086 This link opens in a new window
UDC:66.098:577.15
ISSN on article:1846-5153
DOI:10.15255/CABEQ.2025.2459 This link opens in a new window
COBISS.SI-ID:268739843 This link opens in a new window
Publication date in RUL:02.03.2026
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Downloads:20
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Record is a part of a journal

Title:Chemical & biochemical engineering quarterly
Shortened title:Chem. biochem. eng. q.
Publisher:Croatian Association of Chemical Engineers
ISSN:1846-5153
COBISS.SI-ID:524828441 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:encimska kinetika, določitev kinetičnih parametrov, parametrična neenoličnost

Projects

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0191-2020
Name:Kemijsko inženirstvo

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J7-50041-2023
Name:Razvoj imobiliziranih katalizatorjev za pripravo devteriranih organskih spojin

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J4-4562-2022
Name:Intenzifikacija biokatalitskih procesov z uporabo evtektičnih topil v mikropretočnih sistemih za trajnostno valorizacijo odpadkov - BioInDES

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J2-60044-2025
Name:Računalniško podprto okolje za sistematično sintezo, načrtovanje in vključevanje pretočne kemije in mikroprocesov v trajnostne proizvodne sisteme, ciljano na Moč-do-X

Funder:EC - European Commission
Project number:101160108
Name:Twinning for Building Excellence and Innovative Solutions in Flow Catalysis
Acronym:FLOWCAT

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