Literature DB >> 15135031

Thermodynamic constraints for biochemical networks.

Daniel A Beard1, Eric Babson, Edward Curtis, Hong Qian.   

Abstract

The constraint-based approach to analysis of biochemical systems has emerged as a useful tool for rational metabolic engineering. Flux balance analysis (FBA) is based on the constraint of mass conservation; energy balance analysis (EBA) is based on non-equilibrium thermodynamics. The power of these approaches lies in the fact that the constraints are based on physical laws, and do not make use of unknown parameters. Here, we show that the network structure (i.e. the stoichiometric matrix) alone provides a system of constraints on the fluxes in a biochemical network which are feasible according to both mass balance and the laws of thermodynamics. A realistic example shows that these constraints can be sufficient for deriving unambiguous, biologically meaningful results. The thermodynamic constraints are obtained by comparing of the sign pattern of the flux vector to the sign patterns of the cycles of the internal cycle space via connection between stoichiometric network theory (SNT) and the mathematical theory of oriented matroids.

Mesh:

Year:  2004        PMID: 15135031     DOI: 10.1016/j.jtbi.2004.01.008

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  58 in total

Review 1.  Systematizing the generation of missing metabolic knowledge.

Authors:  Jeffrey D Orth; Bernhard Ø Palsson
Journal:  Biotechnol Bioeng       Date:  2010-10-15       Impact factor: 4.530

2.  Thermodynamic calculations for biochemical transport and reaction processes in metabolic networks.

Authors:  Stefan J Jol; Anne Kümmel; Vassily Hatzimanikatis; Daniel A Beard; Matthias Heinemann
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

3.  Kinetic constraints for formation of steady states in biochemical networks.

Authors:  Junli Liu
Journal:  Biophys J       Date:  2005-02-24       Impact factor: 4.033

4.  The geometry of the flux cone of a metabolic network.

Authors:  Clemens Wagner; Robert Urbanczik
Journal:  Biophys J       Date:  2005-09-23       Impact factor: 4.033

5.  Dynamics of muscle glycogenolysis modeled with pH time course computation and pH-dependent reaction equilibria and enzyme kinetics.

Authors:  Kalyan Vinnakota; Melissa L Kemp; Martin J Kushmerick
Journal:  Biophys J       Date:  2006-04-14       Impact factor: 4.033

6.  Thermodynamically feasible kinetic models of reaction networks.

Authors:  Michael Ederer; Ernst Dieter Gilles
Journal:  Biophys J       Date:  2007-01-05       Impact factor: 4.033

7.  The thermodynamic meaning of metabolic exchange fluxes.

Authors:  Wolfgang Wiechert
Journal:  Biophys J       Date:  2007-05-25       Impact factor: 4.033

8.  Candidate states of Helicobacter pylori's genome-scale metabolic network upon application of "loop law" thermodynamic constraints.

Authors:  Nathan D Price; Ines Thiele; Bernhard Ø Palsson
Journal:  Biophys J       Date:  2006-03-13       Impact factor: 4.033

9.  Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

Authors:  Joshua J Hamilton; Vivek Dwivedi; Jennifer L Reed
Journal:  Biophys J       Date:  2013-07-16       Impact factor: 4.033

10.  Flux modules in metabolic networks.

Authors:  Arne C Müller; Alexander Bockmayr
Journal:  J Math Biol       Date:  2013-10-19       Impact factor: 2.259

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.