A comprehensive overview of computational protein disorder prediction methods

被引:84
作者
Deng, Xin [1 ]
Eickholt, Jesse [1 ]
Cheng, Jianlin [1 ,2 ,3 ]
机构
[1] Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA
[2] Univ Missouri, Inst Informat, Columbia, MO 65211 USA
[3] Univ Missouri, C Bond Life Sci Ctr, Columbia, MO 65211 USA
关键词
INTRINSICALLY UNSTRUCTURED PROTEINS; SEQUENCE-BASED PREDICTION; MODEL QUALITY ASSESSMENT; AMINO-ACID-COMPOSITION; SECONDARY STRUCTURE; FOLD RECOGNITION; MODFOLD SERVER; ENERGY CONTENT; REGIONS; COMPLEXITY;
D O I
10.1039/c1mb05207a
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Over the past decade there has been a growing acknowledgement that a large proportion of proteins within most proteomes contain disordered regions. Disordered regions are segments of the protein chain which do not adopt a stable structure. Recognition of disordered regions in a protein is of great importance for protein structure prediction, protein structure determination and function annotation as these regions have a close relationship with protein expression and functionality. As a result, a great many protein disorder prediction methods have been developed so far. Here, we present an overview of current protein disorder prediction methods including an analysis of their advantages and shortcomings. In order to help users to select alternative tools under different circumstances, we also evaluate 23 disorder predictors on the benchmark data of the most recent round of the Critical Assessment of protein Structure Prediction (CASP) and assess their accuracy using several complementary measures.
引用
收藏
页码:114 / 121
页数:8
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