Novel Quantification of Cascade Kinetics of Electrostatic Channeling
Authors: Liu Yuanchao , Matanovic Ivana , Atanassov Plamen , Calabrese Barton Scott 
Published: February 2020

Taking advantage of sequential reactions, cascade catalysis is able to fully utilize the energy stored in each chemical bond, enabling biofuel cells with higher energy density and biosensors with greater sensitivity. A key factor limiting utilization of cascades is the mass transport of reaction intermediates, which in nature is found to be largely facilitated by substrate channeling, whereby intermediate molecules are transferred directly to the next active site instead of equilibrating into the bulk environment.1 Electrostatic bound diffusion represents a channeling mechanism wherein charged intermediate molecules actively interact with oppositely charged pathways. In past decades, significant work has been done on natural cascade, such as structural characterization2, coarse-grained molecular simulation3, continuum modeling4 and experiment kinetics5. However, the gap between molecular-level interaction and phenomenal kinetics hinders the application to artificial cascades. Our group and collaborators recently reported the first synthetic cascade, where poly-lysine peptide was found to be an effective bridge to facilitate the channeling of glucose 6-phosphate (G6P) through a surface hopping mechanism (Figure 1a).6 Here, explore the kinetics of this system using Molecular Dynamics (MD) and Kinetic Monte Carlo (KMC). Using MD simulation, the energy barriers for surface hopping and desorption were quantified based on transition state theory (TST) and Umbrella Sampling, as shown Figure 1 b and c. Specifically, surface hopping takes place in a Stern layer created by strong hydrogen bond interaction. With low ion screening, additionally, the hops can be protected from desorption by a diffuse layer created by long-range electrostatic interaction.

Parameters of the system that are energy-related (e.g., k
hop, k
des) and experimentally determined (e.g., k
cat) are integrated by a KMC model (Figure 1d), in order to calculated the overall kinetics. Consequently, a direct comparison is made with experiment results, as shown in Figure 1e. By tuning the channeling leakage through ionic strength and bridge length (Table 1), it is found that a balance between average hopping times and leaking probability can be made to design an optimal cascade. In summary, this work provides a novel and detailed quantification approach to cascade kinetics, which can be applied to either natural or artificial cascades. More importantly, it expands structure-function understanding to include quantitative kinetics.

Acknowledgement

We gratefully acknowledge support from Army Research Office MURI (#W911NF1410263) via The University of Utah

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Figure 1