Understanding the pathways by which viral capsid proteins assemble around their genomes could identify key intermediates as potential drug targets. In this work we use computer simulations to characterize assembly over a wide range of capsid protein-protein interaction strengths and solution ionic strengths. We find that assembly pathways can be categorized into two classes, in which intermediates are either predominantly ordered or disordered. Our results suggest that estimating the protein-protein and the protein-genome binding affinities may be sufficient to predict which pathway occurs. Furthermore, the calculated phase diagrams suggest that knowledge of the dominant assembly pathway and its relationship to control parameters could identify optimal strategies to thwart or redirect assembly to block infection. Finally, analysis of simulation trajectories suggests that the two classes of assembly pathways can be distinguished in single molecule fluorescence correlation spectroscopy or bulk time resolved small angle x-ray scattering experiments.

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude. © 2014 AIP Publishing LLC.

The CRISPR-Cas9 system has been utilized for large-scale, loss-of-function screens mainly using lentiviral pooled formats and cell-survival phenotypic assays. Screening in an arrayed format expands the types of phenotypic readouts that can be used to now include high-content, morphology-based assays, and with the recent availability of synthetic crRNA libraries, new studies are emerging. Here, we use a cell cycle reporter cell line to perform an arrayed, synthetic crRNA:tracrRNA screen targeting 169 genes (>600 crRNAs) and used high content analysis (HCA) to identify genes that regulate the cell cycle. Seven parameters were used to classify cells into cell cycle categories and multiple parameters were combined using a new analysis technique to identify hits. Comprehensive hit follow-up experiments included target gene expression analysis, confirmation of DNA insertions/deletions, and validation with orthogonal reagents. Our results show that most hits had three or more independent crRNAs per gene that demonstrated a phenotype with consistent individual parameters, indicating that our screen produced high-confidence hits with low off-target effects and allowed us to identify hits with more subtle phenotypes. The results of our screen demonstrate the power of using arrayed, synthetic crRNAs for functional phenotypic screening using multiparameter HCA assays.

We use all-atom simulations to elucidate the mechanisms underlying conformational switching and allostery within the coat protein of the bacteriophage MS2. Assembly of most icosahedral virus capsids requires that the capsid protein adopts different conformations at precise locations within the capsid. It has been shown that a 19 nucleotide stem loop (TR) from the MS2 genome acts as an allosteric effector, guiding conformational switching of the coat protein during capsid assembly. Since the principal conformational changes occur far from the TR binding site, it is important to understand the molecular mechanism underlying this allosteric communication. To this end, we use all-atom simulations with explicit water combined with a path sampling technique to sample the MS2 coat protein conformational transition, in the presence and absence of TR-binding. The calculations find that TR binding strongly alters the transition free energy profile, leading to a switch in the favored conformation. We discuss changes in molecular interactions responsible for this shift. We then identify networks of amino acids with correlated motions to reveal the mechanism by which effects of TR binding span the protein. We find that TR binding strongly affects residues located at the 5-fold and quasi-sixfold interfaces in the assembled capsid, suggesting a mechanism by which the TR binding could direct formation of the native capsid geometry. The analysis predicts amino acids whose substitution by mutagenesis could alter populations of the conformational substates or their transition rates.

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