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these constraints are no longer applicable.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.