Publicação: Using genetic algorithm to design protein sequence
dc.contributor.author | Scott, Luis P. B. | |
dc.contributor.author | Chahine, Jorge [UNESP] | |
dc.contributor.author | Ruggiero, José Roberto [UNESP] | |
dc.contributor.institution | Universidade Federal do ABC (UFABC) | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2014-05-20T14:02:39Z | |
dc.date.available | 2014-05-20T14:02:39Z | |
dc.date.issued | 2008-06-15 | |
dc.description.abstract | In this work, genetic algorithms concepts along with a rotamer library for proteins side chains are used to optimize the tertiary structure of the hydrophobic core of Cytochrome b(562) starting from the known PDB structure of its backbone which is kept fixed while the side chains of the hydrophobic core are allowed to adopt the conformations present in the rotamer library. The atoms of the side chains forming the core interact via van der Waals energy. Besides the prediction of the native core structure, it is also suggested a set of different amino acid sequences for this core. Comparison between these new cores and the native are made in terms of their volumes, van der Waals energies values and the numbers of contacts made by the side chains forming the cores. This paper proves that genetic algorithms area efficient to design new sequence for the protein core. (C) 2007 Elsevier B.V. All rights reserved. | en |
dc.description.affiliation | Universidade Federal do ABC (UFABC), CMCC, BR-09090400 Santo Andre, SP, Brazil | |
dc.description.affiliation | IBILCE, Dept Phys, São Paulo, Brazil | |
dc.description.affiliationUnesp | IBILCE, Dept Phys, São Paulo, Brazil | |
dc.identifier | http://dx.doi.org/10.1016/j.amc.2007.09.033 | |
dc.identifier.citation | Applied Mathematics and Computation. New York: Elsevier B.V., v. 200, n. 1, p. 1-9, 2008. | |
dc.identifier.doi | 10.1016/j.amc.2007.09.033 | |
dc.identifier.issn | 0096-3003 | |
dc.identifier.lattes | 1518826294347383 | |
dc.identifier.uri | http://hdl.handle.net/11449/22089 | |
dc.identifier.wos | WOS:000255728600001 | |
dc.language.iso | eng | |
dc.publisher | Elsevier B.V. | |
dc.relation.ispartof | Applied Mathematics and Computation | |
dc.relation.ispartofjcr | 2.300 | |
dc.relation.ispartofsjr | 1,065 | |
dc.rights.accessRights | Acesso restrito | |
dc.source | Web of Science | |
dc.subject | genetic algorithms | en |
dc.subject | Optimization | en |
dc.subject | Protein structure | en |
dc.subject | prediction | en |
dc.subject | Bioinformatics | en |
dc.title | Using genetic algorithm to design protein sequence | en |
dc.type | Artigo | |
dcterms.license | http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy | |
dcterms.rightsHolder | Elsevier B.V. | |
dspace.entity.type | Publication | |
unesp.author.lattes | 1518826294347383 | |
unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Biociências, Letras e Ciências Exatas, São José do Rio Preto | pt |
unesp.department | Física - IBILCE | pt |
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