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Title

An optimized algorithm for flux estimation from isotopomer distribution in glucose metabolites
Authors

Vitaly A. Selivanov
Organization: 1Departamento de Bioquimica i Biologia Molecular, Facultat de Quimica and CERQT at Parc Cientic de Barcelona
Joaquim Puigjaner
A. Sillero
Josep J. Centelles
Antonio Ramos-Montoya
Organization: School of Molecular and Microbial Biosciences, University of Sydney, NSW,
Paul W. N. Lee
Organization: 4Department of Pediatrics, Harbor-UCLA Medical Center, Research and Education Institute,
Marta Cascante
Organization: 1Departamento de Bioquimica i Biologia Molecular, Facultat de Quimica and CERQT at Parc Cientic de Barcelona
Journal / Anthology

Bioinformatics
Year: 2004
Volume: 20
Issue: 18
Page range: 3387-3397
Description

Motivation: Analysis of the conversion of 13C glucose within the metabolic network allows the evaluation of the biochemical fluxes in interconnecting metabolic pathways. Such analyses require solving hundreds of equations with respect to individual isotopomer concentrations, and this assumes applying special software even for constructing the equations. The algorithm, proposed by others could be improved.

Method: A C-code linked to the program written in Mathematica (Wolfram Research Inc.), constructs and solves differential equations for all isotopomer concentrations, using the general enzyme characteristics (Km, equilibrium constant, etc.). This code uses innovative algorithm of determination for the isotopomers–products, thus essentially decreasing the computation time. Feasible metabolic fluxes are provided by the parameters of enzyme kinetics found from the data fitting.

Results: The software effectively evaluates metabolic fluxes based on the measured isotopomer distribution, as was illustrated by the analysis of glycolysis and pentose phosphate cycle. The mechanism of transketolase and transaldolase catalysis was shown to induce a specific kind of isotopomer re-distribution, which, despite the significance of its effect, usually is not taken into account.
Subject

*Science > Bioinformatics
URL

http://bq.ub.es/bioqint/label_distribution/