Literature DB >> 23613486

A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions.

Ivan Chang1, Pierre Baldi.   

Abstract

MOTIVATION: Oxidoreductases are a fundamental class of enzymes responsible for the catalysis of oxidation-reduction reactions, crucial in most bioenergetic metabolic pathways. From their common root in the ancient prebiotic environment, oxidoreductases have evolved into diverse and elaborate protein structures with specific kinetic properties and mechanisms adapted to their individual functional roles and environmental conditions. While accurate kinetic modeling of oxidoreductases is thus important, current models suffer from limitations to the steady-state domain, lack empirical validation or are too specialized to a single system or set of conditions.
RESULTS: To address these limitations, we introduce a novel unifying modeling framework for kinetic descriptions of oxidoreductases. The framework is based on a set of seven elementary reactions that (i) form the basis for 69 pairs of enzyme state transitions for encoding various specific microscopic intra-enzyme reaction networks (micro-models), and (ii) lead to various specific macroscopic steady-state kinetic equations (macro-models) via thermodynamic assumptions. Thus, a synergistic bridge between the micro and macro kinetics can be achieved, enabling us to extract unitary rate constants, simulate reaction variance and validate the micro-models using steady-state empirical data. To help facilitate the application of this framework, we make available RedoxMech: a Mathematica™ software package that automates the generation and customization of micro-models. AVAILABILITY: The Mathematica™ source code for RedoxMech, the documentation and the experimental datasets are all available from: http://www.igb.uci.edu/tools/sb/metabolic-modeling. CONTACT: pfbaldi@ics.uci.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23613486      PMCID: PMC3732027          DOI: 10.1093/bioinformatics/btt140

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  17 in total

Review 1.  The chemical basis of membrane bioenergetics.

Authors:  Stephan Berry
Journal:  J Mol Evol       Date:  2002-05       Impact factor: 2.395

2.  The kinetics of enzyme-catalyzed reactions with two or more substrates or products. I. Nomenclature and rate equations.

Authors:  W W CLELAND
Journal:  Biochim Biophys Acta       Date:  1963-01-08

Review 3.  Energy converting NADH:quinone oxidoreductase (complex I).

Authors:  Ulrich Brandt
Journal:  Annu Rev Biochem       Date:  2006       Impact factor: 23.643

4.  An enzyme mechanism language for the mathematical modeling of metabolic pathways.

Authors:  Chin-Rang Yang; Bruce E Shapiro; Eric D Mjolsness; G Wesley Hatfield
Journal:  Bioinformatics       Date:  2004-10-27       Impact factor: 6.937

5.  Physiological diversity of mitochondrial oxidative phosphorylation.

Authors:  G Benard; B Faustin; E Passerieux; A Galinier; C Rocher; N Bellance; J-P Delage; L Casteilla; T Letellier; R Rossignol
Journal:  Am J Physiol Cell Physiol       Date:  2006-06-28       Impact factor: 4.249

Review 6.  Supramolecular structure of the mitochondrial oxidative phosphorylation system.

Authors:  Egbert J Boekema; Hans-Peter Braun
Journal:  J Biol Chem       Date:  2006-11-13       Impact factor: 5.157

7.  The loneliness of the electrons in the bc1 complex.

Authors:  Stéphane Ransac; Nicolas Parisey; Jean-Pierre Mazat
Journal:  Biochim Biophys Acta       Date:  2008-05-15

8.  An automatic method for deriving steady-state rate equations.

Authors:  A Cornish-Bowden
Journal:  Biochem J       Date:  1977-07-01       Impact factor: 3.857

Review 9.  NADH/NAD+ interaction with NADH: ubiquinone oxidoreductase (complex I).

Authors:  Andrei D Vinogradov
Journal:  Biochim Biophys Acta       Date:  2008-04-18

10.  Modeling of mitochondria bioenergetics using a composable chemiosmotic energy transduction rate law: theory and experimental validation.

Authors:  Ivan Chang; Margit Heiske; Thierry Letellier; Douglas Wallace; Pierre Baldi
Journal:  PLoS One       Date:  2011-09-08       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.