engleski

Lin-log Model of E. coli Central Metabolism

Mathematical models of dynamics of metabolic pathways are used for analysis of complex regulations of biochemical reactions as an intrinsic property of a metabolism. The models are derived under assumptions of kinetic rate functions and usually result in simplification in view of their theoretical scope and practical application. The main obstacle in kinetic modeling is the dimensionality of the parametric space, nonlinearity and ill-conditioned relations for parameter estimation. In this work these problems is effectively solved by use of approximate linear-logarithmic (Lin-log) applied in analysis of regulation of Escherichia coli central metabolism. Complex multiplicative Michaelis-Menten kinetic rate expressions are transformed into simple in parameter Lin-log functions and non-linear logarithmic dependencies on concentrations of substrates, and cofactors. The Lin-log kinetic rates enable direct estimation of rate elasticities which are the key parameters in metabolic control analysis (MCA). Due to in parameter linearity, the estimation problem is solved in non-iterative least square algorithm. The results reveal the main control interactions between phosphoenolepyruvate (PEP) on phosphotransferase system (PTS), the key role of phosphofructokinase (PFK), and the role of oxalacetate (OAA). Comparison of the simulation results by Lin-log and Michaelis-Menten model reveals that errors are of the same order of magnitude.

Lin-log kinetics; E. coli central metabolism; metabolic control analysis; rate elasticities

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