Molecular Dynamics of Rare-Event Electrostatic Channeling
Authors: Xie Yan , Calabrese Barton Scott 
Published: July 2021

Cascade reactions are potential green reactions since all the reaction transformations take place in a single pot without purification steps, but their reaction efficiency is limited by the transport efficiency of intermediates between adjacent steps [1]. Understanding the mechanism of multi-enzyme metabolic pathways is of great importance for the design of practical cascades for chemical conversion. Molecular dynamics simulations of cascades can elucidate and quantify physicochemical effects on intermediate transport, but is challenged by processes whose time scales exceed the typical picosecond to nanosecond range. Here, we show how infrequent metadynamics (InMetaD) [2], umbrella sampling (US) and kinetic Monte Carlo (KMC) can be combined to elucidate rare-event transport processes. We build on a previously studied glucose-6-phosphate (G6P) intermediate within a bridged supramolecular structure comprising the enzymes hexokinase (HK) and glucose-6-dehydrogenase (G6PDH) [3].

When the previous polylysine bridge is replaced by polyarginine, electrostatic interactions between negatively-charged G6P and the positively charged bridge are enhanced, but diffusive transport of G6P on the bridge surface, via a hopping mechanism, is slowed to time scales exceeding 10 ns. InMetaD is an advanced sampling technique that boosts a system out of energy minima by biasing the predefined collective variables and estimates unbiased kinetics by reweighting the biased time. We investigated the hopping mechanism of G6P on arginine peptides as a rare event using InMetaD, and computed the hopping time to be 125.5 ± 2.7 ns at 310 K and hopping activation energy to be 25.1 ± 3.7 kJ/mol at the ionic strength of 0 mM.

We conducted US simulations to capture the configurational change in the desorption process and calculate the desorption energy. By considering the energy barriers calculated above, the KMC simulations were performed to study the transfer efficiency of G6P. The results show that even at a high ionic strength of 120 mM, arginine peptides are still able to transfer G6P with the lag time 5 seconds, much smaller than lysine peptides with the lag time of 59 seconds reported before [4]. Our work indicates that arginine peptides are a better bridge candidate for electrostatic channeling in terms of decreased lag time compared with lysine peptides. This can help in the future design of efficient artificial cascade reactions by using electrostatic channeling.

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Figure 1