Queue-based method for efficient simulation of biological self-assembly systems

Self-assembly systems are central to a broad range of critical biological processes. Developing methods for quantitative simulation of self-assembly dynamics on cellular scales is therefore an essential sub-step in the broader goal of building predictive models of cellular function. Yet several aspects of self-assembly systems challenge key assumptions of conventional methods for biochemical simulation. Innovations are thus required in the rapid, quantitative simulation of self-assembly on cellular scales. In this paper, we describe a novel discrete-event queuing strategy for time- and memory-efficient quantitative simulation of self-assembly systems in continuous time. The method will typically allow simulation of interactions of even large, complex assembly structures in space and amortized run time per time step linear in system size. It can therefore be expected to extend the applicability of quantitative discrete-event methods to biologically important systems and scales inaccessible to prior techniques. In addition to presenting the method, we provide empirical evidence for its efficiency on two model systems.