Prediction of disordered regions in proteins based on the meta approach

被引:200
作者
Ishida, Takashi [1 ]
Kinoshita, Kengo [1 ,2 ]
机构
[1] Univ Tokyo, Inst Med Sci, Minato Ku, Tokyo 1088639, Japan
[2] SORST JST, Kawaguchi, Saitama 3320012, Japan
关键词
D O I
10.1093/bioinformatics/btn195
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: Intrinsically disordered regions in proteins have no unique stable structures without their partner molecules, thus these regions sometimes prevent high-quality structure determination. Furthermore, proteins with disordered regions are often involved in important biological processes, and the disordered regions are considered to play important roles in molecular interactions. Therefore, identifying disordered regions is important to obtain high-resolution structural information and to understand the functional aspects of these proteins. Results: We developed a new prediction method for disordered regions in proteins based on the meta approach and implemented a web-server for this prediction method named metaPrDOS. The method predicts the disorder tendency of each residue using support vector machines from the prediction results of the seven independent predictors. Evaluation of the meta approach was performed using the CASP7 prediction targets to avoid an overestimation due to the inclusion of proteins used in the training set of some component predictors. As a result, the meta approach achieved higher prediction accuracy than all methods participating in CASP7.
引用
收藏
页码:1344 / 1348
页数:5
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