Modeling and engineering of oxidoreductase proteins for miniaturized energy applications

Metabolic Control Analysis was for the first time applied to artificial networks in the context of bioenzymatic electrodes. Using an indirect approach based on accurate estimates of the kinetic mechanism and parameters, elasticity coefficients were calculated. The connectivity and summation principles allowed for the flux control coefficients to be estimated. A commonly researched osmium-mediated Glucose oxidase/Laccase enzymatic biofuel cell generates electrical current from a glucose source. The flux of electrons through the system is the only link between the two enzymatic reactions. The result of this analysis show that the control of electron flux strongly depends on the total mediator concentrations and the extent of polarization of the individual electrodes. A dominant flux control coefficient at the anode results under normal operating conditions where the electrodes are highly polarized and will contain high mediator concentrations. The results for a balanced system with equal flux control coefficients at various oxygen and mediator concentrations are also presented. The application of MCA was extended to a multienzymatic electrode, specifically to a quadruple dehydrogenase anode. In this case, three of the enzymes are linked by a linear carbon pathway while all four share a common coenzyme for the transport of electrons. The results suggest that at intermediate metabolite pool concentrations, lower than their respective KM S, the first enzyme of the pathway controls the carbon flux. At a particular intermediate pool and cofactor concentrations, a balance system with respect to the carbon flux is obtained. Those findings were utilized for the application of MCA to the branched electron flux pathway to obtain a new overall balance after a few iterations. A balanced system, where all flux control coefficients are equal, is able to better sustain perturbations. The distribution of enzyme control over a flux is correlated to enzyme loading and indirectly to enzyme activity and specificity. One of the major hurdles in the application of bioenzymatic fuel cells is their low current density. Therefore we started the process of engineering a laccase with high redox potential which could indirectly alleviate this issue. Computational protein design was used to create an enzyme suitable for prokaryotic expression based on the structure of a fungal laccase with a high redox potential. The gene was heterologously expressed in E. coli and the majority of the protein was found in inclusion bodies. Both soluble and refolded insoluble protein were purified in a monomeric form and characterized via spectroscopic methods. Both proteins did not contain bound copper atoms and therefore they were enzymatically inactive. Circular dichroism spectroscopy studies suggest that the native and refolded protein adopt a structure similar to the in vitro denatured and refolded native fungal protein, which is significantly different to the functionally natively secreted fungal protein