Diagnosis of Enzyme Inhibition Using Excel Solver: A Combined Dry and Wet Laboratory Exercise

Abstract

In enzyme kinetic studies, linear transformations of the Michaelis–Menten equation, such as the Lineweaver–Burk double-reciprocal transformation, present some constraints. The linear transformation distorts the experimental error and the relationship between x and y axes; consequently, linear regression of transformed data is less accurate when compared with methodologies that use nonlinear regression. However, linear transformations are widely used. Explanations for this are the facility to determine model parameters by hand calculations, and until recently, the use of nonlinear regression was difficult as specialized software was not readily available to most scientists and students. Because utilization of personal computers is widespread, these constraints are no longer applicable. This work describes how to perform nonlinear regression with the Solver supplement of Microsoft Office Excel. It is easy to use and to view the results graphically. The F-test was applied to discriminate between models. These methodologies are important in any biochemistry syllabus and can be used to create an active-learning environment where students discriminate between different kinetic models and explore their own experimental results based on several hypotheses.