📝 SummarXiv

Abstract

Multifarious assembly models consider multiple structures assembled from a shared set of components, reflecting the efficient usage of components in biological self-assembly. These models are subject to a high-dimensional parameter space, with only a finite region of parameter space giving reliable self-assembly. Here we use a continuous-time Gillespie simulation method to study multifarious self-assembly and find that the region of parameter space in which reliable self-assembly can be achieved is smaller than what was obtained previously using a discrete-time Monte Carlo simulation method. We explain this discrepancy through a detailed analysis of the stability of assembled structures against chimera formation. We find that our continuous-time simulations of multifarious self-assembly can expose this instability in large systems even at moderate simulation times. In contrast, discrete-time simulations are slow to show this instability, particularly for large system sizes. For the remaining state space we find good agreement between the predictions of continuous- and discrete-time simulations. We present physical arguments that can help us predict the state boundaries in the parameter space, and gain a deeper understanding of multifarious self-assembly.