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Mechanical and Assembly Units of Viral Capsids Identified via Quasi-Rigid Domain Decomposition
Author(s) -
Guido Polles,
Giuliana Indelicato,
Raffaello Potestio,
Paolo Cermelli,
Reidun Twarock,
Cristian Micheletti
Publication year - 2013
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1003331
Subject(s) - capsid , viral life cycle , domain decomposition methods , domain (mathematical analysis) , mesoscopic physics , computer science , biological system , salient , computational biology , viral replication , physics , biology , mathematics , virology , artificial intelligence , virus , mathematical analysis , quantum mechanics , finite element method , thermodynamics
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.

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