Rigorous Model-Based Design and Experimental Verification of Enzyme-Catalyzed Carboligation under Enzyme Inactivation

Abstract

Enzyme catalyzed reactions are complex reactions due to the interplay of the enzyme, the reactants, and the operating conditions. To handle this complexity systematically and make use of a design space without technical restrictions, we apply the model based approach of elementary process functions (EPF) for selecting the best process design for enzyme catalysis problems. As a representative case study, we consider the carboligation of propanal and benzaldehyde catalyzed by benzaldehyde lyase from Pseudomonas fluorescens (PfBAL) to produce (R)-2-hydroxy-1-phenylbutan-1-one, because of the substrate dependent reaction rates and the challenging substrate dependent PfBAL inactivation. The apparatus independent EPF concept optimizes the material fluxes influencing the enzyme catalyzed reaction for the given process intensification scenarios. The final product concentration is improved by 13% with the optimized feeding rates, and the optimization results are verified experimentally. In general, the rigorous model driven approach could lead to selecting the best existing reactor, designing novel reactors for enzyme catalysis, and combining protein engineering and process systems engineering concepts.

Modeling and simulation‐based design of electroenzymatic batch processes catalyzed by unspecific peroxygenase from A. aegerita

“…The deviation between simulated and experimental data in Figure 6b can be explained by an unsteady H 2 O 2 production in the GDE during this experiment, for example, caused by the bubble formation, changes in the ambient temperature or aging of the electrode. The high agreement between experimental and predicted data shows that the established model can not only be used descriptively but also predictively and thus lays the groundwork for further potential investigations such as model‐based design of optimal production processes (Hertweck, Emenike, Spiess, & Schenkendorf, 2020).…”