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Predicting protein interaction sites from residue spatial sequence profile and evolution rate.
Wang, Bing; Chen, Peng; Huang, De-Shuang; Li, Jing-jing; Lok, Tat-Ming; Lyu, Michael R.
Afiliação
  • Wang B; Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui 230031, China.
FEBS Lett ; 580(2): 380-4, 2006 Jan 23.
Article em En | MEDLINE | ID: mdl-16376878
ABSTRACT
This paper proposes a novel method that can predict protein interaction sites in heterocomplexes using residue spatial sequence profile and evolution rate approaches. The former represents the information of multiple sequence alignments while the latter corresponds to a residue's evolutionary conservation score based on a phylogenetic tree. Three predictors using a support vector machines algorithm are constructed to predict whether a surface residue is a part of a protein-protein interface. The efficiency and the effectiveness of our proposed approach is verified by its better prediction performance compared with other models. The study is based on a non-redundant data set of heterodimers consisting of 69 protein chains.
Assuntos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conformação Proteica / Algoritmos / Proteínas / Mapeamento de Interação de Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: FEBS Lett Ano de publicação: 2006 Tipo de documento: Article
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conformação Proteica / Algoritmos / Proteínas / Mapeamento de Interação de Proteínas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: FEBS Lett Ano de publicação: 2006 Tipo de documento: Article