Applying Cellular Crowding Models to Simulations of Virus Capsid Assembly In Vitro

Abstract

Viral capsid assembly has been widely studied as a biophysical system both for its biological and medical significance and as an important model system for complex self-assembly processes. One important and largely unresolved question is how viruses select among the potential pathways by which a capsid might assemble. Sources of experimental data to resolve assembly pathways are limited in scope to in vitro studies. We have previously applied numerical optimization methods to fit kinetic rate parameters of assembly simulations to light scattering data in order to more accurately model the in vitro viral capsid assembly process, making it possible to predict detailed patterns of interaction and pathways of assembly of specific viruses. There is substantial reason, however, to suspect the interaction patterns inferred in vitro might be altered in a very different in vivo environment. We examine here one aspect of this difference, effects of intracellular molecular crowding on assembly kinetics and pathways. We have applied regression models developed from Green's function reaction dynamic simulations to adjust inferred reaction kinetics of capsid models to reflect likely differences in crowded systems. We then examined how such adjustments affect computer models of the capsid assembly process. We applied these methods to three icosahedral viruses: human papillomavirus (HPV), hepatitis B virus (HBV), and cowpea chlorotic mottle virus (CCMV). Preliminary results show complicated effects on pathway dynamics, with increased cellular crowding increasing the nucleation rate of CCMV and HBV capsids while slowing the nucleation rate for HPV capsids and increasing a propensity to kinetic trapping in all viruses studied. Future work will explore how additional features of the cellular environment may act synergistically to lead to rapid, robust growth in living cells.