Minimalist models for biopolymers: Open problems, latest advances and perspectives (Articolo in rivista)

Type
Label
  • Minimalist models for biopolymers: Open problems, latest advances and perspectives (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1063/1.4730659 (literal)
Alternative label
  • Trovato, F.; Tozzini, V (2012)
    Minimalist models for biopolymers: Open problems, latest advances and perspectives
    in AIP conference proceedings
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Trovato, F.; Tozzini, V (literal)
Pagina inizio
  • 187 (literal)
Pagina fine
  • 200 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 1456 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • NEST-Ist. Nanoscienze, Pisa, Italy. (literal)
Titolo
  • Minimalist models for biopolymers: Open problems, latest advances and perspectives (literal)
Abstract
  • Simplified models representing biopolymers at less than atomic resolution (Coarse Grained) have recently become popular due to the need of reaching the mu-scale (in space and time domains) in simulations. The reduction of the internal degrees of freedom of the system brings a potentially unlimited saving of computational cost, at the expenses of the introduction of two main class of problems: (i) those related to the representability of the system and back-mapping to atomistic representation, (ii) those related to the parameterization of an accurate and predictive, yet simple enough, force field for the interactions. In this paper we illustrate these two issues focusing on the representative sub-class of the \"minimalist\" models, namely those with a single interacting center for amino-acid or nucleotide. We describe their features and the different available parameterization methodologies, illustrating their positive and negative aspects, with the aim of giving guiding lines for a general parameterization strategy. (literal)
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