On the estimation errors of KMand V from time-course experiments using the Michaelis-Menten equation.
The conditions under which the Michaelis-Menten equation accurately captures the steady-state kinetics of a simple enzyme-catalyzed reaction is contrasted with the conditions under which the same equation can be used to estimate parameters, KMand V, from progress curve data. Validity of the underlying assumptions leading to the Michaelis-Menten equation are shown to be necessary, but not sufficient to guarantee accurate estimation of KMand V. Detailed error analysis and numerical "experiments" show the required experimental conditions for the independent estimation of both KMand V from progress curves. A timescale, tQ, measuring the portion of the time course over which the progress curve exhibits substantial curvature provides a novel criterion for accurate estimation of KMand V from a progress curve experiment. It is found that, if the initial substrate concentration is of the same order of magnitude as KM, the estimated values of the KMand V will correspond to their true values calculated from the microscopic rate constants of the corresponding mass-action system, only so long as the initial enzyme concentration is less than KM.
Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address: stroberg@umich.edu.
Wylie
W
Stroberg
Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Brehm Center for Diabetes Research, University of Michigan Medical School, Ann Arbor, MI 48105, USA. Electronic address: schnells@umich.edu.
Santiago
S
Schnell
D000465:Algorithms; D055162:Biocatalysis; D004798:Enzymes / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological; D008956:Models, Chemical
D004798:Enzymes
Experimental design; Inverse problem; Parameter estimation; Reproducibility