Parameter Estimation in Kinetic Models for Large Scale Metabolic Networks with Advanced Mathematical Programming Techniques

DI MAGGIO, JIMENA; DÍAZ RICCI, JUAN C.; DÍAZ, SOLEDAD MA.

Nápoles. Italia

Simposio; 20-ESCAPE; 2010

20º European Symposium of Computer Aided Process Engineering

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 halfsaturation constants, have been estimated with good agreement with available experimental data