The comparison of the estimation of enzyme kinetic parameters by fitting reaction curve to the integrated Michaelis–Menten rate equations of different predictor variables

Abstract

The estimation of enzyme kinetic parameters by nonlinear fitting reaction curve to the integrated Michaelis–Menten rate equation ln( S 0/ S)+( S 0− S)/ K m=( V m/ K m)× twas investigated and compared to that by fitting to ( S 0− S)/ t= V m− K m×[ln( S 0/ S)/ t] (Atkins GL, Nimmo IA. The reliability of Michaelis-Menten constants and maximum velocities estimated by using the integrated Michaelis-Menten equation. Biochem J 1973;135:779-84) with uricase as the model. Uricase reaction curve was simulated with random absorbance error of 0.001 at 0.075 mmol/l uric acid. Experimental reaction curve was monitored by absorbance at 293 nm. For both CV and deviation <20% by simulation, K m from 5 to 100 μmol/l was estimated with Eq. (1) while K m from 5 to 50 μmol/l was estimated with Eq. (2). The background absorbance and the error in the lag time of steady-state reaction resulted in negative K m with Eq. (2), but did not affect K m estimated with Eq. (1). Both equations gave better estimation of V m. The computation time and the goodness of fit with Eq. (1) were 40-fold greater than those with Eq. (2). By experimentation, Eq. (1) yielded K m consistent with the Lineweaver–Burk plot analysis, but Eq. (2) gave many negative parameters. Apparent K m by Eq. (1) linearly increased, while V m were constant, vs. xanthine concentrations, and the inhibition constant was consistent with the Lineweaver–Burk plot analysis. These results suggested that the integrated rate equation that uses the predictor variable of reaction time was reliable for the estimation of enzyme kinetic parameters and applicable for the characterization of enzyme inhibitors.