The ultimate challenge of modern electroanalytical chemistry is to reach a single-molecule level of detection. In this framework, nanoimpact electrochemistry (NIE) has been recently developed. It allows studying at high throughput the reactivity of small entities such as nanoparticles, cells, or proteins, that collide on a biased ultramicroelectrode (UME) inside a solution or suspension.1 The collisions cause disturbances in the recorded chronoamperogram such as current spikes or current steps.2 Single enzyme electrochemistry (SEE) can contribute to uncovering effects of dynamics and non-equilibrium behavior of individual enzyme molecules on catalysis, which are hidden in measurements on ensembles due to averaging of the measured parameters over the entire molecular population. However, NIE of smaller entities such as enzymes, is very challenging due to the low sensitivity of the state-of-the-art electrochemical equipment, and most single enzyme techniques are currently based on fluorescence.3 One strategy to overcome this issue is the amplification of the current produced by a single enzyme molecule by fast catalysis: the single enzyme converts several substrate molecules per second consuming several electrons leading measurable current. Some of us reported the implementation of this strategy for the first time, designing a single-entity electrochemical experiment that allowed the detection of catalytic currents from single laccase molecules.4 Soon after the initial SEE report in 2016, a similar approach was applied for investigations of catalase,5 an enzyme that breaks down H2O2 to O2 and H2O with diffusion limited kinetics. However, the unequivocal attribution of current disturbances to the reduction of O2 (produced locally by enzyme) on the electrode during enzyme-electrode collisions remains a challenge. We will address this challenge based on the analysis of SEE experimental data under various conditions, on protein film voltammetry (PFV) studies on rotating disk electrode (RDE), and on simulations. The collected data from the SEE, that is the current spike characteristics in each set of conditions, are statistically analyzed and discussed. PFV studies are used to evaluate basic thermodynamic and kinetic parameters of the system. Finally, we have built a model using Comsol Multiphysics. To the best of our knowledge, this is the first model reported so far that can satisfactorily reproduce the experimental SEE data, using experimentally evaluated parameters as input. The developed methodology is the succesfully implemented to the study of superoxide dismutase.6
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