Retrieving Backbone String Neighbors Provides Insights Into Structural Modeling of Membrane Proteins

被引:1
作者
Sun, Jiang-Ming [1 ]
Li, Tong-Hua [1 ]
Cong, Pei-Sheng [1 ]
Tang, Sheng-Nan [1 ]
Xiong, Wen-Wei [1 ]
机构
[1] Tongji Univ, Dept Chem, Shanghai 200092, Peoples R China
基金
中国国家自然科学基金;
关键词
STRUCTURE PREDICTION; FOLD-RECOGNITION; STRUCTURE ALIGNMENT; SIMILARITY SEARCHES; SHAPE STRINGS; INFORMATION; SEQUENCES; DATABASE; SERVER; SCORE;
D O I
10.1074/mcp.M111.016808
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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. Molecular & Cellular Proteomics 11: 10.1074/mcp.M111.016808, 1-7, 2012.
引用
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页数:7
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