Smallbone, K. and Simeonidis, E. and Broomhead, D.S. and Kell, D.B. (2007) Something from nothing: bridging the gap between constraint-based and kinetic modelling. FEBS Journal, 274 (21). pp. 5576-5585. ISSN 0014-2956
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Abstract
Two divergent modelling methodologies have been adopted to increase our understanding of metabolism and its regulation. Constraint-based modelling highlights the optimal path through a stoichiometric network within certain physicochemical constraints. Such an approach requires minimal biological data to make quantitative inferences about network behaviour; however, constraint-based modelling is unable to give an insight into cellular substrate concentrations. In contrast, kinetic modelling aims to characterize fully the mechanics of each enzymatic reaction. This approach suffers because parameterizing mechanistic models is both costly and time-consuming. In this paper, we outline a method for developing a kinetic model for a metabolic network, based solely on the knowledge of reaction stoichiometries. Fluxes through the system, estimated by flux balance analysis, are allowed to vary dynamically according to linlog kinetics. Elasticities are estimated from stoichiometric considerations. When compared to a popular branched model of yeast glycolysis, we observe an excellent agreement between the real and approximate models, despite the absence of (and indeed the requirement for) experimental data for kinetic constants. Moreover, using this particular methodology affords us analytical forms for steady state determination, stability analyses and studies of dynamical behaviour.
Item Type: | Article |
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Uncontrolled Keywords: | flux balance analysis linlog kinetics Saccharomyces cerevisiae |
Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 34 Ordinary differential equations MSC 2010, the AMS's Mathematics Subject Classification > 92 Biology and other natural sciences |
Depositing User: | Dr Kieran Smallbone |
Date Deposited: | 08 Sep 2008 |
Last Modified: | 20 Oct 2017 14:12 |
URI: | https://eprints.maths.manchester.ac.uk/id/eprint/1141 |
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