Cell-free bioelectrocatalysis has drawn significant research attention as the world transitions towards sustainable bioenergy sources. This technology utilizes electrodes to drive challenging enzymatic redox reactions, such as CO2 reduction and selective oxidation of lignin biomass. At these bioelectrochemical interfaces, enzymes are rarely capable of direct exchange of electrons with the electrode surface because many redox enzymes harbor cofactors that are buried within protein matrices that act as an electrical insulator. In such cases, electrochemically active small molecules, called redox mediators, have been proven effective in enabling efficient electron transfer by acting as electron shuttles between the electrode and enzyme cofactor. However, the task of selecting suitable redox mediators remains challenging due to lack of comprehensive design criteria. Presently, their design relies on a trial-and-error approach that emphasizes redox potential as the only parameter while overlooking the significance of other structural features. It is crucial to acknowledge that while the redox potential of the mediator serves as a thermodynamic descriptor, it falls short in fully describing the kinetic behavior of redox mediators. This thesis describes efforts in developing strategies for designing and understanding the behavior of redox species using quinone-mediated glucose oxidation by glucose oxidase as a model system.The work begins by showcasing the application of parameterized modeling – specifically, supervised machine learning – to identify which structural components of quinone redox mediators correlate to enhanced reactivity with a model enzyme, glucose oxidase (GOx). Through this analysis, redox potential and mediator area (or molecular size) were identified as crucial chemical parameters to optimize when designing mediators. The role of other steric parameters (i.e. redox mediator projected area) when accessing GOx via its active site tunnel was investigated further. Using two complementary computational techniques, steered molecular dynamics and umbrella sampling, a rate-limiting step was identified from a series of elementary steps. Specifically, it was determined that the transport of redox species in the protein tunnel constitutes the rate-limiting step in the overall process. Utilizing molecular docking and molecular dynamics simulations, a specific quinone-functionalized polymer was examined with the goal of determining why it exhibits activity with glucose dehydrogenase (FAD-GDH) but not with GOx, despite both structurally similar enzymes exhibiting activity to the corresponding freely diffusing mediator. Docking simulations coupled with MD refinement reveal that the active site of GOx is inaccessible to the polymer-bound redox mediator due to the added steric bulk; this contrasts with FAD-GDH which has a wider molecular tunnel to its active site. This work serves as an exemplary demonstration of employing parameterized modeling in the design and engineering of redox mediators. Although these strategies were developed using GOx as a model system, a similar approach holds promise for designing bioelectrocatalytic platforms involving redox mediators. Additionally, these computational simulations can effectively address fundamental questions where experimental continuum models are inadequate. This integrated effort brings us closer to design of next-generation effective bioelectrodes for mediated bioelectrocatalysis.
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