Your browser doesn't support javascript.
loading
MUFOLD-DB: a processed protein structure database for protein structure prediction and analysis.
BMC Genomics ; 15 Suppl 11: S2, 2014.
Article en En | MEDLINE | ID: mdl-25559128
ABSTRACT

BACKGROUND:

Protein structure data in Protein Data Bank (PDB) are widely used in studies of protein function and evolution and in protein structure prediction. However, there are two main barriers in large-scale usage of PDB data 1) PDB data are highly redundant in terms of sequence and structure similarity; and 2) many PDB files have issues due to inconsistency of data and standards as well as missing residues, so that automated retrieval and analysis are often difficult. DESCRIPTION To address these issues, we have created MUFOLD-DB http//mufold.org/mufolddb.php, a web-based database, to collect and process the weekly PDB files thereby providing users with non-redundant, cleaned and partially-predicted structure data. For each of the non-redundant sequences, we annotate the SCOP domain classification and predict structures of missing regions by loop modelling. In addition, evolutional information, secondary structure, disorder region, and processed three-dimensional structure are computed and visualized to help users better understand the protein.

CONCLUSIONS:

MUFOLD-DB integrates processed PDB sequence and structure data and multiple computational results, provides a friendly interface for users to retrieve, browse and download these data, and offers several useful functionalities to facilitate users' data operation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2014 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2014 Tipo del documento: Article
...