Insights into Enzymatic Bioelectrocatalysis
Authors: Babanova Sofia , Matanovic Ivana , Atanassov Plamen 
Published: February 2020

Enzymatic bioelectrocatalysis is a phenomenon widely explored by the humanity in various directions: biochemical assays, food and pharmaceutical industry, cosmetics, production of detergents, etc. All these application rely on the advantages of the enzymatic catalysis: specificity, selectivity, fast reaction rate and regulation capacity. The same advantages have been explored in the design of bioelectrochemical systems for energy conversion and biosensing.

The enzymes capable of bioelectrocatalysis were referred as redox proteins. The unique feature of these proteins is their ability to catalyze electrochemical transformation of different substrates and participate in biological electron transport. Electron transfer reactions play a central role in all biological systems and are essential to the processes by which living cells capture and explore energy. Therefore a detailed study of the electron transfer within a simple enzymatic reaction is of a great importance for further understanding of the complicated electron passage within electron transport chains.

A new method specifically designed for the current study was developed. This method implies naturally occurring recognition mechanisms, specific for enzymes i.e. “lock-and-key theory”, the properties of carbon nanomaterials and electrochemical techniques to study in situthe enzymatically catalyzed electron transfer from and to various substrates. The term substrate in this study is used to describe the enzymes` electron donors and acceptors at the same time, where the enzyme donor is referred as S1 and the acceptor as S2.

Two types of enzymes belonging to the family of MCOs and PQQ-dependent enzymes were explored. These enzymes were selected based on their ability for direct electron transfer (DET) and their utilization as oxidizing (PQQ-glucose dehydrogenase) and reducing (laccase and bilirubin oxidase) bioelectrocatalysts [1, 2]. Taking into account the specific features of these enzymes, carbon nanomaterials were modified with the enzyme`s natural substrate and the corresponding enzyme (Fig. 1), providing: i) specific recognition of the substrate modified nanomaterial surface; ii) proper enzyme orientation and iii) decreased distance between the enzymes` active center and the electrode surface. Different enzyme substrates (S1 or S2) were explored and parameters such as electron transfer rate, potential difference, adsorption energies, orientation efficiency, electrostatic potential of the substrates mapped onto the electron density surface, etc. were evaluated electrochemically and by the utilization of computational chemistry approaches. It was established that among these factors the different activity of redox enzymes toward various substrates could be attributed mainly to differences in substrates redox potentials and the feasibility of the electrochemical transformation of the substrates themselves. An optimal ΔE between the redox potential of the enzyme active center and the redox potential of the substrate was observed (0.2-0.3V for MCOs and 0.25-0.35V for PQQ-GDH) (Fig. 2). Lower ΔE with high activation energy of substrate electrochemical transformation is not sufficient enough to drive the reaction with a high rate and at the same time higher ΔE than the optimal leads to potential losses and decrease of the reaction effectiveness.

The proposed electrochemical approach along with quantum mechanical calculations provides the opportunity to monitor enzymatic reactions in situand down select the parameters driving the electron transfer in a higher rate.

1. Strack, G., Babanova, S., Farrington, K., Luckarift, H., Atanassov, P., Johnson, G., Enzyme-Modified Buckypaper for Bioelectrocatalysis. Journal of the Electrochemical Society, 2013. 160(7): p. 10.1149/2.028307jes.

2. Lopez, R.J., et al., Improved Interfacial Electron Transfer in Modified Bilirubin Oxidase Bio-cathodes. Chem. Electro. Chem., 2014. 1(1): p. 241-248.