Progress curve analysis in enzyme kinetics: model discrimination and parameter estimation. 1978

R G Duggleby, and J F Morrison

The method of progress curve analysis for enzyme-catalyzed reactions (Duggleby, R.G. and Morrison, J.F. (1977) Biochim. Biophys. acta 481, 297--312) has been extended to a two substrate, reversible reaction through the use of enzyme-catalyzed recycling of one of the products. The reaction investigated was that catalyzed by aspartate aminotransferase (L-aspartate:2-oxoglutarate aminotransferase, EC 2.6.1.1) and the product, alpha-ketoglutarate was recycled to glutamate using NADH and NH4Cl in the presence of glutamate dehydrogenase. The values determined for the kinetic parameters of the aminotransferase were found to agree well with those obtained from steady-state velocity measurements. The standard errors of the parameters, as calculated by the procedure originally described, were found to underestimate the observed variation between different experiments. Therefore, a procedure of data compression was devised which leads to more realistic values for standard errors. The compressed data obtained with aspartate aminotransferase have been fitted to the integrated rate equations that describe a variety of kinetic mechanisms. The best fit was obtained with the Ping-Pong model which is applicable to the aspartate aminotransferase reaction. Thus, progress curve analysis may be used to determine the kinetic mechanism of, and values of the kinetic parameters associated with, an enyzme-catalyzed reaction.

UI MeSH Term Description Entries
D007700 Kinetics The rate dynamics in chemical or physical systems.
D008956 Models, Chemical Theoretical representations that simulate the behavior or activity of chemical processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment. Chemical Models,Chemical Model,Model, Chemical
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D004798 Enzymes Biological molecules that possess catalytic activity. They may occur naturally or be synthetically created. Enzymes are usually proteins, however CATALYTIC RNA and CATALYTIC DNA molecules have also been identified. Biocatalyst,Enzyme,Biocatalysts
D001219 Aspartate Aminotransferases Enzymes of the transferase class that catalyze the conversion of L-aspartate and 2-ketoglutarate to oxaloacetate and L-glutamate. EC 2.6.1.1. Aspartate Aminotransferase,Aspartate Transaminase,Glutamic-Oxaloacetic Transaminase,SGOT,Aspartate Apoaminotransferase,Glutamate-Aspartate Transaminase,L-Aspartate-2-Oxoglutarate Aminotransferase,Serum Glutamic-Oxaloacetic Transaminase,Aminotransferase, Aspartate,Aminotransferase, L-Aspartate-2-Oxoglutarate,Aminotransferases, Aspartate,Apoaminotransferase, Aspartate,Glutamate Aspartate Transaminase,Glutamic Oxaloacetic Transaminase,Glutamic-Oxaloacetic Transaminase, Serum,L Aspartate 2 Oxoglutarate Aminotransferase,Serum Glutamic Oxaloacetic Transaminase,Transaminase, Aspartate,Transaminase, Glutamate-Aspartate,Transaminase, Glutamic-Oxaloacetic,Transaminase, Serum Glutamic-Oxaloacetic

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