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Retrieving backbone string neighbors provides insights into structural modeling of membrane proteins.
Sun, Jiang-Ming; Li, Tong-Hua; Cong, Pei-Sheng; Tang, Sheng-Nan; Xiong, Wen-Wei.
Afiliación
  • Sun JM; Department of Chemistry, Tongji University, 1239 Siping Road, Shanghai 200092, China.
Mol Cell Proteomics ; 11(7): M111.016808, 2012 Jul.
Article en En | MEDLINE | ID: mdl-22415040
Identification of protein structural neighbors to a query is fundamental in structure and function prediction. Here we present BS-align, a systematic method to retrieve backbone string neighbors from primary sequences as templates for protein modeling. The backbone conformation of a protein is represented by the backbone string, as defined in Ramachandran space. The backbone string of a query can be accurately predicted by two innovative technologies: a knowledge-driven sequence alignment and encoding of a backbone string element profile. Then, the predicted backbone string is employed to align against a backbone string database and retrieve a set of backbone string neighbors. The backbone string neighbors were shown to be close to native structures of query proteins. BS-align was successfully employed to predict models of 10 membrane proteins with lengths ranging between 229 and 595 residues, and whose high-resolution structural determinations were difficult to elucidate both by experiment and prediction. The obtained TM-scores and root mean square deviations of the models confirmed that the models based on the backbone string neighbors retrieved by the BS-align were very close to the native membrane structures although the query and the neighbor shared a very low sequence identity. The backbone string system represents a new road for the prediction of protein structure from sequence, and suggests that the similarity of the backbone string would be more informative than describing a protein as belonging to a fold.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional / Proteínas de la Membrana Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2012 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Biología Computacional / Proteínas de la Membrana Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2012 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos