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Literature DB >> 2920027

A single-parameter family of adjustments for fitting enzyme kinetic models to progress-curve data.

Abstract

Current methods for fitting integrated rate equations to enzyme progress curves treat each observation as if it were an independent measurement. When the data are obtained by taking several successive readings from each of a series of progress curves, the data will not be truly independent and will exhibit autocorrelation. Here we propose a simple pragmatic extension of integrated rate equations which takes account of first-order autocorrelations. The value of the method is assessed when applied to five sets of experimental data.

Mesh：

Substances：
Enzymes

Year: 1989 PMID： 2920027 PMCID： PMC1135537 DOI： 10.1042/bj2570057

Source DB: PubMed Journal: Biochem J ISSN： 0264-6021 Impact factor: 3.857

10 in total

5. The effect of systematic error on the accuracy of Michaelis constants and maximum velocities estimated by using the integrated Michaelis-Menten equation.

Authors: P F Newman; G L Atkins; I A Nimmo
Journal: Biochem J Date: 1974-12 Impact factor: 3.857

6. Statistical estimations in enzyme kinetics. The integrated Michaelis equation.

Authors: H N Fernley
Journal: Eur J Biochem Date: 1974-04-01

7. The reliability of Michaelis constants and maximum velocities estimated by using the integrated Michaelis-Menten equation.

Authors: G L Atkins; I A Nimmo
Journal: Biochem J Date: 1973-12 Impact factor: 3.857

8. Progress curve analysis in enzyme kinetics: model discrimination and parameter estimation.

Authors: R G Duggleby; J F Morrison
Journal: Biochim Biophys Acta Date: 1978-10-12

9. Analysis of progress curves for a highly concentrated Michaelian enzyme in the presence or absence of product inhibition.

Authors: N Kellershohn; M Laurent
Journal: Biochem J Date: 1985-10-01 Impact factor: 3.857

10. Analysis of progress curves in enzyme kinetics: bias and convergent set in the differential and in the integral method.

Authors: M Markus; T Plesser; M Kohlmeier
Journal: J Biochem Biophys Methods Date: 1981-02

10 in total

3 in total

A single-parameter family of adjustments for fitting enzyme kinetic models to progress-curve data.

1. Integrated steady state rate equations and the determination of individual rate constants.

2. The analysis of progress curves for enzyme-catalysed reactions by non-linear regression.

3. Progress-curve analysis in enzyme kinetics. Numerical solution of integrated rate equations.

4. Analytical methods for fitting integrated rate equations. A discontinuous assay.

5. The effect of systematic error on the accuracy of Michaelis constants and maximum velocities estimated by using the integrated Michaelis-Menten equation.

6. Statistical estimations in enzyme kinetics. The integrated Michaelis equation.

7. The reliability of Michaelis constants and maximum velocities estimated by using the integrated Michaelis-Menten equation.

8. Progress curve analysis in enzyme kinetics: model discrimination and parameter estimation.

9. Analysis of progress curves for a highly concentrated Michaelian enzyme in the presence or absence of product inhibition.

10. Analysis of progress curves in enzyme kinetics: bias and convergent set in the differential and in the integral method.

1. Fitting integrated enzyme rate equations to progress curves with the use of a weighting matrix.

2. Kinetic analysis of lactate dehydrogenase using integrated rate equations.

3. Site-directed mutagenesis of beta-lactamase I. Single and double mutants of Glu-166 and Lys-73.