Analysis of Enzyme Kinetic Data

Henderson PJR 1993. Statistical analysis of enzyme kinetic data. Enzyme assays. A practical approach. Eisenthal R, Danson MJ, editors. Oxford Oxford University Press pp. 277-316. 

Comish-Bowden, A. (2002) Statistical analysis of enzyme kinetic data, Oxford University Press, Oxford, p.249-268 ... 

Notes Reprinted from table 9.1 (p. 156) from Analysis of Enzyme Kinetic Data by Athel Cornish-Bowden (1995) by permission of Oxford University Press. 

Reversible inhibition can be competitive or non-competitive. Competitive inhibitors bind to the active site and compete with the substrate for binding to the enzyme. However this means that increasing the S concentration will progressively outcompete the inhibitor. Accordingly a Lineweaver—Burk analysis of enzyme kinetic data obtained in the presence or absence of a competitive inhibitor will yield the same Fmax (at infinite S concentration) but the Am in the presence of the inhibitor (A, ) will be higher (poorer binding) than the Am measured in the absence of competitive inhibitor. Knowing the inhibitor concentration [I] one can calculate the A) from the relation ... 

Cleland WW (1979) Statistical analysis of enzyme kinetic data. In Methods in Enzymol-ogy, Vol. 63A, DL Punch, Ed. Academic Press, Orlando, FL. 

CornisH Bowden, a, Analysis of Enzyme Kinetic Data, New York Oxford University Press, 1995. 

Cleland, W. W. (1967a). The statistical analysis of enzyme kinetic data. Advan. Enzymol. 29, 1-32. 

Henderson, P.J.F., Statistical analysis of enzyme kinetic data. Techniques in the Life Sciences, Biochemistry vol. Bl/11, Techniques in Pmtein and Enzyme Biochemistry— PartH, Elsevier/North-Holland Biomedical Press, Amsterdam, the Netherlands, 1978, pp. B113/1-41. 

Before the advent of computer technology and the computerized statistical methods for data analysis, a procedure that was employed extensively in the analysis of enzyme kinetic data was linear regression. It is important to point out that linear regression performed by the least squares method should not be used unless the values are weighted. If it is used without proper weighting one can get bad results. 

Carnahan, B., Luther, H.A., Wilkes, J.O. Applied numerical methods, WUey, New York. Cornish-Bowden, A. (1995) Analysis of enzyme kinetic data, Oxford Science Publications, Oxford. Daniel, W.W. (1995) Biostatistics, 6th ed., Wiley, New York. 

Kuzmic P. Program DYNAFIT for the analysis of enzyme kinetic data application to HTV proteinase. Anal Biochem 1996 237 260-73. 

The treatment of enzyme kinetics in this book is radically different from the traditional way in which this topic is usually covered. In this book, I have tried to stress the understanding of how models are arrived at, what their Umitations are, and how they can be used in a practical fashion to analyze enzyme kinetic data. With the advent of computers, linear transformations of models have become unnecessary—this book does away with Unear transformations of enzyme kinetic models, stressing the use of nonUnear regression techniques. Linear transformations are not required to carry out analysis of enzyme kinetic data. In this book, I develop new ways of analyzing kinetic data, particularly in the study of pH effects on catalytic activity and multisubstrate enzymes. Since a large proportion of traditional enzyme kinetics used to deal with linearization of data, removing these has both decreased the amount of information that must be acquired and allowed for the development of a deeper understanding of the models used. This, in turn, will increase the efficacy of their use. 

Cleland, W.W. (1979). Statistical analysis of Enzyme Kinetic Data. Methods in EnzymoL, Vol. 63, pp. 103-138... 

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