A Monte Carlo study of the particle mobility in crowded nearly one-dimensional systems.

Abstract: The study of crowding effects on particle diffusion is a large subject with implications in many scientific areas. The studies span from pure theoretical calculations to experiments actually measuring the movement of proteins diffusing in a cell. Even though the subject is important and has been studied heavily there are still aspects not fully understood.   This report describes a Monte Carlo simulation approach (Gillespie algorithm) to study the effects of crowding on particle diffusion in a quasi one-dimensional system. With quasi meaning that the particles diffuses on a one-dimensional lattice but has the possibility to disassociate from the lattice and then rebind at a latter stage. Different binding strategies are considered: rebinding to the same location and randomly choosing the binding location. The focus of the study is how these strategies affects the mobility (diffusion coefficient) of a tracer particle. The main result of this thesis is a graph showing the diffusion coefficient as a function of the binding rate for different binding strategies and particle densities. We provide analytical estimates for the diffusion coefficient in the unbinding rate limits which show good agreement with the simulations.