KINETIC QUANTITATION OF ENZYME SUBSTRATES USING NONLINEAR REGRESSION METHODS
Abstract
A new data-processing method for the kinetic quantitation of substrates of enzyme-catalyzed reactions has been developed and evaluated using the enzymatic oxidation of uric acid in aqueous solutions as a model reaction, and the enzymatic oxidation of lactic acid in plasma as a practical example. Nonlinear regression is used to fit data for absorbance (A) and rate (dA/dt) vs time collected during a substantial fraction of the reaction to the rate form of the Michaelis-Menten equation. Fitting parameters are the maximum velocity (V(,MAX)), the Michaelis constant (K(,m)), and the total absorbance change ((DELTA)A(,(INFIN))) that would be observed if the reaction were monitored to equilibrium. Results show that this method resolved two problems traditionally associated with kinetic methods; the linear range is extended to substrate concentrations exceeding the Michaelis constant, and the method is insensitive to experimental variables such as temperature and enzyme activity. Uric acid data, obtained using a data range corresponding to 80% reaction, exhibit linearity 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 to 28% of its uninhibited value. The pooled relative standard deviation was 6%, the sensitivity was 1.15 x 10('4) Lmol('-1) cm('-1) and the detection limit was 1.2 x 10('-6) mol/L. For lactic acid the computed absorbance change, using a fixed data range of 200 s, was linear for concentrations in plasma of 2 to 26 mmol/L. Variations in enzyme activity causing a 20% reduction in initial rate had little or no effect on results from the proposed method. Comparison with a commercial equilibrium method for 25 canine plasma samples gave a least-squares equation of y = 1.01-0.01, indicating good agreement between the methods. The pooled relative standard deviation was 2.1%, the sensitivity was 5.36 x 10('3) L mol('-1) cm('-1) and the detection limit was 4.1 x 10('-6) mol/L.
Degree
Ph.D.
Subject Area
Analytical chemistry
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