probability of transforming into an olive state and ∼1.8% probability of undergoing a transition to blue. It is worth noting that the transition probabilities between different states depend on the rate at which we sampled the trajectory. These transition probabilities can be easily converted into transition rates between the various states by dividing (normalizing) them by the interval ∆t between the frames (1 ns). However, here we are not much interested into quantitative numbers or rates (also considering that the CG dynamics is usually greatly accelerated), but rather in comparing between the pathways and the hierarchical steps underpinning the creation and resorption of defects in the various assemblies. In this sense, we find that in this specific case the data are more meaningfully discussed in terms of (sampling-dependent) normalized surviving and transition probabilities for the different states.