7 research outputs found
How simple can a model of an empty viral capsid be? Charge distributions in viral capsids
We investigate and quantify salient features of the charge distributions on
viral capsids. Our analysis combines the experimentally determined capsid
geometry with simple models for ionization of amino acids, thus yielding the
detailed description of spatial distribution for positive and negative charge
across the capsid wall. The obtained data is processed in order to extract the
mean radii of distributions, surface charge densities and dipole moment
densities. The results are evaluated and examined in light of previously
proposed models of capsid charge distributions, which are shown to have to some
extent limited value when applied to real viruses.Comment: 10 pages, 10 figures; accepted for publication in Journal of
Biological Physic
Mechanical and Assembly Units of Viral Capsids Identified via Quasi-Rigid Domain Decomposition
Key steps in a viral life-cycle, such as self-assembly of a protective protein container or in some cases also subsequent maturation events, are governed by the interplay of physico-chemical mechanisms involving various spatial and temporal scales. These salient aspects of a viral life cycle are hence well described and rationalised from a mesoscopic perspective. Accordingly, various experimental and computational efforts have been directed towards identifying the fundamental building blocks that are instrumental for the mechanical response, or constitute the assembly units, of a few specific viral shells. Motivated by these earlier studies we introduce and apply a general and efficient computational scheme for identifying the stable domains of a given viral capsid. The method is based on elastic network models and quasi-rigid domain decomposition. It is first applied to a heterogeneous set of well-characterized viruses (CCMV, MS2, STNV, STMV) for which the known mechanical or assembly domains are correctly identified. The validated method is next applied to other viral particles such as L-A, Pariacoto and polyoma viruses, whose fundamental functional domains are still unknown or debated and for which we formulate verifiable predictions. The numerical code implementing the domain decomposition strategy is made freely available