tailieunhanh - Báo cáo khóa học: A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics

The control properties of biochemical pathways can be described by control coefficients and elasticities, as defined in the framework of metabolic control analysis. The determination of these parameters using the traditional metabolic control analysis relationships is, however, lim-ited by experimental difficulties (. realizing and meas-uring small changes in biological systems) and lack of appropriate mathematical procedures (. when the more practical large changes are made). | Eur. J. Biochem. 271 3348-3359 2004 FEBS 2004 doi A new framework for the estimation of control parameters in metabolic pathways using lin-log kinetics Liang Wu Weiming Wang Wouter A. van Winden Walter M. van Gulik and Joseph J. Heijnen Department of Biotechnology Delft University of Technology the Netherlands The control properties of biochemical pathways can be described by control coefficients and elasticities as defined in the framework of metabolic control analysis. The determination of these parameters using the traditional metabolic control analysis relationships is however limited by experimental difficulties . realizing and measuring small changes in biological systems and lack of appropriate mathematical procedures . when the more practical large changes are made . In this paper the recently developed lin-log approach is proposed to avoid the above-mentioned problems and is applied to estimate control parameters from measurements obtained in steady state experiments. The lin-log approach employs approximative linear-logarithmic kinetics parameterized by elasticities and provides analytical solutions for fluxes and metabolite concentrations when large changes are made. Published flux and metabolite concentration data are used obtained from a reconstructed section of glycolysis converting 3-phospho-glycerate to pyruvate Giersch C. 1995 Eur. J. Biochem. 227 194-201 . With the lin-log approach all data from different experiments can be combined to give realistic elasticity and flux control coefficient estimates by linear regression. Despite the large changes a good agreement of fluxes and metabolite concentrations is obtained between the measured and calculated values according to the lin-log model. Furthermore it is shown that the lin-log approach allows a rigorous statistical evaluation to identify the optimal reference state and the optimal model structure assumption. In conclusion the lin-log approach addresses .