title: Applying molecular crowding models to simulations of virus capsid assembly in vitro.
abstract: Virus capsid assembly has been widely studied as a biophysical system, both for its biological and medical significance and as an important model for complex self-assembly processes. No current technology can monitor assembly in detail and what information we have on assembly kinetics comes exclusively from in vitro studies. There are many differences between the intracellular environment and that of an in vitro assembly assay, however, that might be expected to alter assembly pathways. Here, we explore one specific feature characteristic of the intracellular environment and known to have large effects on macromolecular assembly processes: molecular crowding. We combine prior particle simulation methods for estimating crowding effects with coarse-grained stochastic models of capsid assembly, using the crowding models to adjust kinetics of capsid simulations to examine possible effects of crowding on assembly pathways. Simulations suggest a striking difference depending on whether or not a system uses nucleation-limited assembly, with crowding tending to promote off-pathway growth in a nonnucleation-limited model but often enhancing assembly efficiency at high crowding levels even while impeding it at lower crowding levels in a nucleation-limited model. These models may help us understand how complicated assembly systems may have evolved to function with high efficiency and fidelity in the densely crowded environment of the cell.
authors.affiliation: Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania.
authors.forename: Gregory R
authors.initials: GR
authors.lastname: Smith
authors.affiliation: Joint Carnegie Mellon/University of Pittsburgh Ph.D. Program in Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania; Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania.
authors.forename: Lu
authors.initials: L
authors.lastname: Xie
authors.affiliation: Department of Mathematics and Statistics, Georgia State University, Atlanta, Georgia.
authors.forename: Byoungkoo
authors.initials: B
authors.lastname: Lee
authors.affiliation: Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania; Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania. Electronic address: russells@andrew.cmu.edu.
authors.forename: Russell
authors.initials: R
authors.lastname: Schwartz
mesh_terms: D036022:Capsid Proteins / Q000737:chemistry / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological; D019065:Virus Assembly
chemical_list: D036022:Capsid Proteins