Stochastic nanoswimmer: a multistate model for enzyme self-propulsion and enhanced diffusion

TL;DR

This paper presents a multistate model of enzyme self-propulsion as nanoswimmers, demonstrating conditions where enzymes exhibit high speeds and enhanced diffusion consistent with experimental data.

Contribution

It introduces a three-state enzymatic cycle model that accounts for high self-propulsion speeds and increased diffusion, addressing limitations of previous nanoswimmer models.

Findings

Enzymes can exhibit run-and-tumble motion with fluctuating mobility.

A three-state model explains high self-propulsion speeds observed experimentally.

Conditions for enhanced diffusion are identified within the enzymatic cycle.

Abstract

Several enzymes exhibit enhanced diffusion in the presence of a substrate. One explanation of this enhancement arises from fluctuating dimer models, which suggest that enzymes have a higher diffusion constant when interacting with substrates compared to when they are free. Another possible mechanism, suggested in both experimental and theoretical studies, is that enzymes act as nanoswimmers. However, existing nanoswimmer models have struggled to account for the exceptionally high self-propulsion speeds observed in experiments, with estimated increases in diffusion due to self-propulsion found to be minimal. In this study, we model enzymes as dimers with fluctuating mobility. We show that even dimers can exhibit run-and-tumble motion when transitioning between states of varying mobility within the enzymatic cycle. By exploring a three-state enzymatic cycle, we identify the conditions under which self-propulsion speeds and increases in diffusion rate consistent with experimental observations can be achieved.