R-Enzymology
Kinetic Mechanisms and Parameters for Bi-Bi Reactions
Non-linear Least-squares Fitting of the MM equation
Eisenthal & Cornish-Bowden
Eadie-Hofstee Transformation
Fitted Progress Curve for Enzyme-Catalyzed Reaction
Hanes-Woolf Transformation
Linearization of The Integrated Michaelis-Menten Equation
Lineweaver-Burk Transformation
Progress Curve for Enzyme-Catalyzed Reaction
Contains utilities for the analysis of Michaelian kinetic data. Beside the classical linearization methods (Lineweaver-Burk, Eadie-Hofstee, Hanes-Woolf and Eisenthal-Cornish-Bowden), features include the ability to carry out weighted regression analysis that, in most cases, substantially improves the estimation of kinetic parameters (Aledo (2021) <doi:10.1002/bmb.21522>). To avoid data transformation and the potential biases introduced by them, the package also offers functions to directly fitting data to the Michaelis-Menten equation, either using ([S], v) or (time, [S]) data. Utilities to simulate substrate progress-curves (making use of the Lambert W function) are also provided. The package is accompanied of vignettes that aim to orientate the user in the choice of the most suitable method to estimate the kinetic parameter of an Michaelian enzyme.