Discrimination between rival laccase inhibition models from data sets with one inhibitor concentration using a penalized likelihood analysis and Akaike weights

Abstract

Laccase from the white-rot fungus Fomes fomentarius was used for the biodegradation of ferulic acid (FA) in the presence of chloride anions. The initial reaction rates of substrate depletion were obtained by reverse-phase HPLC determination of remaining FA since substrate and reaction products have absorption peaks at similar wavelengths. Modelling of time-course data was accomplished by discrimination of the best enzyme inhibition equation from an initial set of seven different models based on Michaelis–Menten kinetics: competitive; uncompetitive; non-competitive; mixed; mixed hyperbolic; mixed parabolic; mixed hyperbolic and parabolic. Corrected Akaike information criterion was used to evaluate the relative merit of each kinetic model in order to rank them and find the more likely one. The discrimination results showed that the models with higher probabilities were the competitive and mixed inhibition types, but Akaike weights supported the selection of competitive inhibition (CI). After optimization by nonlinear regression, laccase kinetic parameters of FA biodegradation in the presence of chloride anions were: Vmax = 0.11 μmol min−1 mg−1, Km = 44 μmol L−1 and a CI constant Kic = 14 mmol L−1.