Structural kinetic modeling of metabolic networks

  • To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: theTo develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.show moreshow less

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Metadaten
Author:Ralf SteuerORCiD, Thilo GrossORCiDGND, Joachim SelbigGND, Bernd BlasiusORCiD
DOI:https://doi.org/10.1073/pnas.0600013103
ISSN:0027-8424
ISSN:1091-6490
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=16880395
Parent Title (English):Proceedings of the National Academy of Sciences of the United States of America
Publisher:National Academy of Sciences
Place of publication:Washington
Document Type:Article
Language:English
Date of first Publication:2006/08/08
Year of Completion:2006
Release Date:2020/06/24
Tag:biological robustness; computational biochemistry; metabolic regulation; metabolomics; systems biology
Volume:103
Issue:32
Pagenumber:6
First Page:11868
Last Page:11873
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Peer Review:Referiert
Publication Way:Open Access
Open Access / Bronze Open-Access
Institution name at the time of publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik