Servers for protein structure prediction

被引:56
作者
Fischer, D [1 ]
机构
[1] SUNY Buffalo, Buffalo Ctr Excellence Bioinformat, Buffalo, NY 14260 USA
[2] SUNY Buffalo, Dept Comp Sci & Engn, Buffalo, NY 14260 USA
[3] Ben Gurion Univ Negev, Dept Comp Sci, IL-84105 Beer Sheva, Israel
关键词
D O I
10.1016/j.sbi.2006.03.004
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 [生物化学与分子生物学]; 081704 [应用化学];
摘要
The 1990s cultivated a generation of protein structure human predictors. As a result of structural genomics and genome sequencing projects, and significant improvements in the performance of protein structure prediction methods, a generation of automated servers has evolved in the past few years. Servers for close and distant homology modeling are now routinely used by many biologists, and have already been applied to the experimental structure determination process itself, and to the interpretation and annotation of genome sequences. Because dozens of servers are currently available, it is hard for a biologist to know which server(s) to use; however, the state of the art of these methods is now assessed through the LiveBench and CAFASP experiments. Meta-servers servers that use the results of other autonomous servers to produce a consensus prediction - have proven to be the best performers, and are already challenging all but a handful of expert human predictors. The difference in performance of the top ten autonomous (non-meta) servers is small and hard to assess using relatively small test sets. Recent experiments suggest that servers will soon free humans from most of the burden of protein structure prediction.
引用
收藏
页码:178 / 182
页数:5
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