Introducing Protein Intrinsic Disorder

被引:564
作者
Habchi, Johnny [1 ,2 ]
Tompa, Peter [3 ,4 ]
Longhi, Sonia [1 ,2 ]
Uversky, Vladimir N. [5 ,6 ]
机构
[1] Aix Marseille Univ, AFMB, UMR 7257, F-13288 Marseille, France
[2] CNRS, AFMB, UMR 7257, F-13288 Marseille, France
[3] Vrije Univ Brussel VIB, Dept Biol Struct, B-1050 Ixelles, Belgium
[4] Hungarian Acad Sci, Inst Enzymol, Res Ctr Nat Sci, H-1113 Budapest, Hungary
[5] Univ S Florida, Morsani Coll Med, Dept Mol Med, Tampa, FL 33620 USA
[6] Russian Acad Sci, Inst Biol Instrumentat, Pushchino, Moscow Region, Russia
关键词
C-TERMINAL DOMAIN; MOLECULAR RECOGNITION FEATURES; MEASLES-VIRUS NUCLEOPROTEIN; NATIVELY UNFOLDED PROTEINS; STRUCTURAL DISORDER; UNSTRUCTURED PROTEINS; POSTTRANSLATIONAL MODIFICATIONS; ALPHA-SYNUCLEIN; VIRAL-PROTEINS; CONFORMATIONAL ENSEMBLES;
D O I
10.1021/cr400514h
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Proteins are the major component of the living cell. They play crucial roles in the maintenance of life, and their dysfunctions are known to cause different pathologies. Simple amino acid propensities reflect some basic physical or sequence features. Such propensity-based predictors rely on simple statistics of amino acid propensity, on the physical/chemical features of amino acids, or on a preliminary concept on the physical background of disorder. Regions of missing electron density in the PDB are generally short, as long regions prevent crystallization. As such, short disorder is overrepresented in the database of disordered regions, and hence these predictors tend to perform better in predicting short disorder than long disorder. Predictors can also be classified based on the binary nature of the prediction. Examples of binary predictors are the CH plot and the cumulative distribution function (CDF) analysis.
引用
收藏
页码:6561 / 6588
页数:28
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