Parameter estimation in kinetic models for large scale metabolic networks with advanced mathematical programming techniques

DI MAGGIO, JIMENA; DIAZ RICCI, JUAN C.; DIAZ, M. SOLEDAD

Computer Aided Chemical Engineering

Elsevier

Año: 2010 vol. 28 p. 355 - 360

1570-7946

In this work, we formulate a parameter estimation problem for a large-scale dynamic metabolic network. The DAE system represents the dynamic model for the Embden-Meyerhof-Parnas pathway, the phosphotransferase system and the pentose-phosphate pathway of Escherichia coli K-12 W3110 (Chassagnole et al., 2002), with modifications on several enzyme kinetics and the addition of fermentation reactions. Model parameters have been estimated based on recently published experimental data for this strain. Most sensitive parameters have been ranked by performing global sensitivity analysis on the dynamic metabolic network (Di Maggio et al., 2009a,b). Eleven kinetic parameters, including maximum reaction rates, inhibition and half-saturation constants, have been estimated with good agreement with available experimental data. © 2010 Elsevier B.V.