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 Km and Vmax 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 Km and Vmax 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 Km (2.8 ± 0.3 mM) and Vmax (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.

Full Text

Published Version

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.