Kinetic method having a linear range for substrate concentrations that exceed Michaelis-Menten constants.

Abstract

We describe a new data-processing method for the kinetic quantification of substrates of enzyme-catalyzed reactions. Nonlinear regression is used to fit data for absorbance (A) and rate (dA/dt) vs time to the rate form of the Michaelis-Menten equation. Fitting parameters are the maximum velocity (Vmax), the Michaelis constant (Km), and the total absorbance change (delta A infinity) that would be observed if the reaction were monitored to completion. The method is evaluated with use of the uricase-catalyzed oxidation of uric acid, monitored at 293 nm, as a model reaction. Results for aqueous solutions demonstrate linear calibration plots for concentrations from well below to 3.5-fold the Michaelis constant, a zero temperature coefficient (36-38 degrees C), and near zero dependence on inhibitor (xanthine) concentrations that reduce the initial rate of 28% of its uninhibited value. Relative standard deviations (RSDs) vary from about 2 to 15%, depending on the data range (95-65% completion) used to process the data. For an 80% reaction data range, the pooled RSD was 6%. The sensitivity for uric acid is 1.15 x 10(4) L mol-1 cm-1 and the detection limit (95% confidence level) is 1.2 x 10(-6) mol/L.