Optimization of Productivity and Thermodynamic Performance of Metabolic Pathways
In this contribution, a novel optimization strategy has been presented that combines the metabolic flux analysis and pathway identification with the thermodynamic analysis of cellular metabolic systems. First, an optimal metabolic flux distribution among elementary pathways is identified by LP optim...
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Published in | Industrial & engineering chemistry research Vol. 47; no. 15; pp. 5669 - 5679 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Washington, DC
American Chemical Society
06.08.2008
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Subjects | |
Online Access | Get full text |
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Summary: | In this contribution, a novel optimization strategy has been presented that combines the metabolic flux analysis and pathway identification with the thermodynamic analysis of cellular metabolic systems. First, an optimal metabolic flux distribution among elementary pathways is identified by LP optimization subject to constraints on flux balance analysis, pathway analysis, and negative Gibbs free energy change for pathways, for achieving the maximum yield of products. The Gibbs free energy change for pathways is calculated from the new transformed Gibbs free energy of formation of external metabolites and cofactors that are in stoichiometric balance in metabolic pathways. The consideration of thermodynamic constraints on pathways ensures the selection of feasible pathways. Thereafter, the Gibbs free energy change of pathways is minimized to predict the optimal reaction conditions that facilitate such pathways. Thus, the optimization approach derives the optimal pathway distribution and conditions for the best performance of cellular systems. The effectiveness of the methodology is demonstrated by a case study on the optimization of pentose phosphate pathway (PPP) and the glycolysis cycle of the insilico Escherichia coli. |
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Bibliography: | ark:/67375/TPS-MRQ2D1P2-H istex:1FF4E978F006E78BA747E2B17902354A8C8C34BA ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/ie070352f |