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Motor enzymes are remarkable molecular machines that use the energy derivedfrom the hydrolysis of a nucleoside triphosphate to generate mechanicalmovement, achieved through different steps that constitute their kinetic cycle.These macromolecules, nowadays investigated with advanced experimentaltechniques to unveil their molecular mechanisms and the properties of theirkinetic cycles, are implicated in many biological processes, ranging frombiopolymerisation (e.g. RNA polymerases and ribosomes) to intracellulartransport (motor proteins such as kinesins or dyneins). Although the kineticsof individual motors is well studied on both theoretical and experimentalgrounds, the repercussions of their stepping cycle on the collective dynamicsstill remains unclear. Advances in this direction will improve ourcomprehension of transport process in the natural intracellular medium, whereprocessive motor enzymes might operate in crowded conditions. In this work, wetherefore extend the current statistical kinetic analysis to study collectivetransport phenomena of motors in terms of lattice gas models belonging to theexclusion process class. Via numerical simulations, we show how to interpretand use the randomness calculated from single particle trajectories in crowdedconditions. Importantly, we also show that time fluctuations and non-Poissonianbehavior are intrinsically related to spatial correlations and the emergence oflarge, but finite, clusters of co-moving motors. The properties unveiled by ouranalysis have important biological implications on the collective transportcharacteristics of processive motor enzymes in crowded conditions.

Stepping and crowding of molecular motors: statistical kinetics from an exclusion process perspective