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Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field.
Leonarski, Filip; Trovato, Fabio; Tozzini, Valentina; Les, Andrzej; Trylska, Joanna.
Afiliação
  • Leonarski F; Centre of New Technologies, University of Warsaw , Zwirki i Wigury 93, Warsaw 02-089, Poland.
  • Trovato F; Faculty of Chemistry, University of Warsaw , Pasteura 1, Warsaw 02-093, Poland.
  • Tozzini V; NEST, Istituto Nanoscienze - Cnr, Scuola Normale Superiore and Center of Nanotechnology and Innovation, IIT, Piazza San Silvestro 12, 56127 Pisa, Italy.
  • Les A; NEST, Istituto Nanoscienze - Cnr and Scuola Normale Superiore, Piazza San Silvestro 12, 56127 Pisa, Italy.
  • Trylska J; Faculty of Chemistry, University of Warsaw , Pasteura 1, Warsaw 02-093, Poland.
J Chem Theory Comput ; 9(11): 4874-89, 2013 Nov 12.
Article em En | MEDLINE | ID: mdl-26583407
Simulations using residue-scale coarse-grained models of biomolecules are less computationally demanding than simulations employing full-atomistic force fields. However, the coarse-grained models are often difficult and tedious to parametrize for certain applications. Therefore, a systematic and objective method to help develop or adapt the coarse-grained models is needed. We present an automatic method that implements an evolutionary algorithm to find a set of optimal force field parameters for a one-bead coarse-grained model. In addition to an optimized force field, parameter correlations and significance of the potential energy terms can be determined. The method is applied to two classes of problems: the dynamics of an RNA helix and the RNA structure prediction.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2013 Tipo de documento: Article