EVA: Large-scale analysis of secondary structure prediction

被引:90
作者
Rost, B
Eyrich, VA
机构
[1] Columbia Univ, CUBIC, Dept Biochem & Mol Biophys, New York, NY 10032 USA
[2] Columbia Univ, Dept Chem, New York, NY 10027 USA
关键词
automatic evaluation; large-scale assessment; protein structure prediction;
D O I
10.1002/prot.10051
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
EVA is a web-based server that evaluates automatic structure prediction servers continuously and objectively. Since June 2000, EVA collected more than 20,000 secondary structure predictions. The EVA sets sufficed to conclude that the field of secondary structure prediction has advanced again. Accuracy increased substantially in the 1990s through using evolutionary information taken from the divergence of proteins in the same structural family. Recently, the evolutionary information resulting from improved searches and larger databases has again boosted prediction accuracy by more than 4% to its current height around 76% of all residues predicted correctly in one of the three states: helix, strand, or other. The best current methods solved most of the problems raised at earlier CASP meetings: All good methods now get segments right and perform well on strands. Is the recent increase in accuracy significant enough to make predictions even more useful? We believe the answer is affirmative. What is the limit of prediction accuracy? We shall see. All data are available through the EVA web site at {cubic.bioc.columbia. edu/eva/). The raw data for the results presented are available at {eva}/sec/bup common/2001 02 22/. (C) 2002 Wiley-Liss, Inc.
引用
收藏
页码:192 / 199
页数:8
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