A New Approach For Modelling And Optimizing Batch Enzymatic Proteolysis

In this manuscript, an original approach is described for modelling and optimizing batch enzymatic proteolysis. It was the first time that a multicriteria optimization methodology of the enzymatic proteolysis that integrates enzymatic cost and reaction duration was proposed. First, a simulation procedure was developed to predict the kinetics of the protein conversion rate and the degree of hydrolysis at any set of pH, temperature, and Enzyme/ Substrate ratio conditions. This was achieved by a hybrid approach based on second order kinetic models and design of experiments methodology. The applicability of the methodology was positively validated with the hydrolysis of rapeseed albumins by Alcalase 2.4L. The ANOVA analysis showed that both models were reliable (R-2 for k(Xp) = 0.95; for kDH = 0.85) and no significant lack of fit was observed (p-value < 0.05). The approach was also validated with good and significant (p-value < 0.05) correlations between experimental and predicted values for the rapeseed albumins hydrolysis with two other proteases in both existing proteolysis mechanisms. A generic multicriteria optimization tool was then applied to search for the best reaction duration/ enzymatic cost trade-offs. The kinetic equations were implemented in a genetic-evolutionary algorithm to generate the Pareto's front (duration/ enzymatic cost trade-offs) and domain (corresponding sets of operating conditions). The approach offers an attractive tool for industrial to reduce important reaction costs to produce hydrolysate of interest. This easy-to-use methodology would present important advances in proteolysis process implementation.