Exact stochastic simulations of intra-cellular transport by mechanically coupled molecular motors

Numerous processes in live cells depend on active, motor-driven transport of cargo and organelles along the filaments of the cytoskeleton. Understanding the resulting dynamics and the underlying biophysical and biochemical processes critically depends on computational models of intra-cellular transport. A number of motor–cargo models have hence been developed to reproduce experimentally observed transport dynamics on various levels of detail. Computer simulations of these models have so far exclusively relied on approximate time-discretization methods. Using a consensus motor–cargo model that unites several existing models from the literature we demonstrate that this simulation approach is not correct. The numerical errors do not vanish even for arbitrarily small time steps, rendering the algorithm inconsistent. We propose a novel exact simulation algorithm for intra-cellular transport models that is also computationally more efficient than the approximate one. Furthermore, we introduce a robust way of analyzing the different time scales in the model dynamics using velocity autocorrelation functions.

► Objects in biological cells are often actively transported by motor proteins.
► Understanding this process relies on computational models and computer simulations.
► Currently used simulation algorithms are inconsistent and may fail to provide correct predictions.
► We demonstrate this on a consensus model of intracellular transport and provide a new, exact simulation algorithm.
► We show that the new algorithm produces correct results and is computationally more efficient than previous approaches.