Modelling cytoskeletal transport by clusters of non-processive molecular motors with limited binding sites

Abstract

Molecular motors are responsible for intracellular transport of a variety of biological cargo. We consider the collective behaviour of a finite number of motors attached on a cargo. We extend previous analytical work on processive motors to the case of non-processive motors, which stochastically bind on and off cytoskeletal filaments with a limited number of binding sites available. Physically, motors attached to a cargo cannot bind anywhere along the filaments, so the number of accessible binding sites on the filament should be limited. Thus, we analytically study the distribution and the velocity of a cluster of non-processive motors with limited number of binding sites. To validate our analytical results and to go beyond the level of detail possible analytically, we perform Monte Carlo latticed based stochastic simulations. In particular, in our simulations, we include sequence preservation of motors performing stepping and binding obeying a simple exclusion process. We find that limiting the number of binding sites reduces the probability of non-processive motors binding but has a relatively small effect on force–velocity relations. Our analytical and stochastic simulation results compare well to published data from in vitro and in vivo experiments.

Moving in the mesoscale: Understanding the mechanics of cytoskeletal molecular motors by combining mesoscale simulations with imaging

“…Two distinct computational approaches have been used to model cytoskeletal molecular motors; spatially resolved models, where proteins are represented explicitly as physical objects, and kinetic or reaction-diffusion based models, where differential equations that describe chemical rates are used to evolve the system as a function of time. While here we concentrate specifically on spatially resolved simulations, much insight has also been obtained from simulations that represent processes (rather than objects) using sets of kinetic equations 57,58 and in some cases, these have been coupled to spatially resolved models (e.g., MEDYAN model of the cytoskeleton, Figure 2g, described below).…”