I will discuss an approach to use Markov state models (MSMs) to enhance sampling in simulations of virus assembly and other self-assembly problems. In the MSM approach, the time evolution of system properties on long timescales is determined from many short trajectories run in parallel. We recently adapted the MSM framework that was developed for protein simulations to enable its application to a wide variety of self-assembly problems. I will now discuss an extension that allows efficiently sampling self-assembly reactions at arbitrarily low subunit concentrations, allowing simulations of experimentally realistic parameter values.

Markov state model approach to simulating self-assembly at low concentrations

2019 Spring National Meeting

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