Enzyme kinetic parameters estimation: A tricky task?
Juan Carlos Aledo
Abstract
Abstract We are living in the Big Data era, and yet we may have serious troubles when dealing with a handful of kinetic data if we are not properly instructed. The aim of this paper, related to enzyme kinetics, is to illustrate how to determine the K m and V max of a michaelian enzyme avoiding the pitfalls in which we often fall. To this end, we will resort to kinetic data obtained by second‐year Biochemistry students during a laboratory experiment using β ‐galactosidase as an enzyme model, assayed at different concentrations of its substrate. When these data were analyzed using conventional linear regression of double‐reciprocal plots, the range of K m and V max values obtained by different students varied widely. Even worse, some students obtained negative values for the kinetic parameters. Although such a scenario could make us think of a wide inter‐student variability regarding their skills to obtain reliable data, the reality was quite different: when properly analyzed (accounting for error propagation) the data obtained by all the students were good enough to allow a correct estimation of the K m (2.8 ± 0.3 mM) and V max (179 ± 27 mM/min) with a reduced intergroup standard deviation. A student‐accessible discussion of the importance of weighted linear regression in biochemical sciences is provided.