Claas Michalik

Mechanistic kinetic model for symmetric carboligations using benzaldehyde lyase

For reactions using thiamine diphosphate (ThDP)‐dependent enzymes many empirically‐derived kinetic models exist. However, there is a lack of mechanistic kinetic models. This is especially true for the synthesis of symmetric 2‐hydroxy ketones from two identical aldehydes, with one substrate acting as the donor and the other as the acceptor. In this contribution, a systematic approach for deriving such a kinetic model for thiamine diphosphate (ThDP)‐dependent enzymes is presented. The derived mechanistic kinetic model takes this donor–acceptor principle into account by containing two Km‐values even for identical substrate molecules. As example the stereoselective carbon–carbon coupling of two 3,5‐dimethoxy‐benzaldehyde molecules to (R)‐3,3′,5,5′‐tetramethoxy‐benzoin using benzaldehyde lyase (EC 4.1.2.38) from Pseudomonas fluorescens is studied. The model is derived using a model‐based experimental analysis method which includes parameter estimation, model analysis, optimal experimental design, in silico experiments, sensitivity analysis and model revision. It is shown that this approach leads to a robust kinetic model with accurate parameter estimates and an excellent prediction capability. Biotechnol. Biotechnol. Bioeng. 2008;101: 27–38.

Mechanistic model for prediction of formate dehydrogenase kinetics under industrially relevant conditions

Formate dehydrogenase (FDH) from Candida boidinii is an important biocatalyst for the regeneration of the cofactor NADH in industrial enzyme‐catalyzed reductions. The mathematical model that is currently applied to predict progress curves during (semi‐)batch reactions has been derived from initial rate studies. Here, it is demonstrated that such extrapolation from initial reaction rates to performance during a complete batch leads to considerable prediction errors. This observation can be attributed to an invalid simplification during the development of the literature model. A novel mechanistic model that describes the course and performance of FDH‐catalyzed NADH regeneration under industrially relevant process conditions is introduced and evaluated. Based on progress curve instead of initial reaction rate measurements, it was discriminated from a comprehensive set of mechanistic model candidates. For the prediction of reaction courses on long time horizons (>1 h), decomposition of NADH has to be considered. The model accurately describes the regeneration reaction under all conditions, even at high concentrations of the substrate formate and thus is clearly superior to the existing model. As a result, for the first time, course and performance of NADH regeneration in industrial enzyme‐catalyzed reductions can be accurately predicted and used to optimize the cost efficiency of the respective processes.

Determination of Temporal and Spatial Concentration Gradients in Hydrogel Beads Using Multiphoton Microscopy Techniques

Multiphoton microscopy is a promising technique to detect spatially and temporally resolved concentration gradients of chemical compounds, e.g., reactants in hydrogel-encapsulated biocatalysts. In contrast to current techniques, the improved spatial and temporal resolution of this method in data acquisition and its ability to measure hydrogel beads facilitates the identification of various kinetic phenomena. To our knowledge, multiphoton microscopy is used here for the first time to examine diffusion, mass transfer, and reaction in immobilized hydrogel systems. In a first step, the phenomena of diffusion and diffusion-coupled mass transfer through the phase interface are investigated in the bead center. Finally, the complete system—consisting of diffusion, mass transfer, and enzymatic reaction—is observed by measuring concentration gradients along the bead radius with temporal and spatial resolution. This metrology enables a subsequent mechanistic model identification, which in turn leads to an enhanced knowledge of reaction kinetics and supports the design of biotechnological processes. This task was only possible due to excellent spatial (25 μm) and temporal (5 s) resolution and the accuracy (±1%) achieved by using a multiphoton microscopy setup.

Incremental Identification of Hybrid Models of Dynamic Process Systems

This contribution presents the so called incremental approach to the general modeling task and shows various fields of application as well as conceptual extensions of the method. The incremental model identification procedure has been developed within a collaborative interdisciplinary research center (CRC) at RWTH Aachen. First, the so called MEXA process, which is at the core of the research at the CRC is presented. Next, the incrementalmodel identification approach (which is one crucial step within the MEXA process) is contrasted with the classical simultaneous approach. The application of the incremental approach is then shown for the special case of hybrid reaction kinetic models. In a next step, the basic idea of the incremental approach - the decomposition of the problem into simpler subproblems - is generalized to also account for (mechanistic and hybrid) algebraic and dynamic models (from arbitrary fields, e.g., not necessarily reaction kinetics). Finally, open questions within the incremental framework are discussed and the future research focus is given.