Sensitive detection of sequence similarity using combinatorial pattern discovery: A challenging study of two distantly related protein families

被引:6
作者
Darzentas, N
Rigoutsos, I
Ouzounis, CA [1 ]
机构
[1] European Bioinformat Inst, Computat Genom Grp, EMBL Cambridge Outstn, Cambridge CB10 1SD, England
[2] IBM Corp, Thomas J Watson Res Ctr, Bioinformat & Pattern Discovery Grp, Yorktown Hts, NY 10598 USA
[3] MIT, Dept Chem Engn, Cambridge, MA 02139 USA
关键词
sensitivity detection; sequence similarity; protein families;
D O I
10.1002/prot.20608
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
We investigate the performance of combinatorial pattern discovery to detect remote sequence similarities in terms of both biological accuracy and computational efficiency for a pair of distantly related families, as a case study. The two families represent the cupredoxins and multicopper oxidases, both containing blue copper-binding domains. These families present a challenging case due to low sequence similarity, different local structure, and variable sequence conservation at their copper-binding active sites. In this study, we investigate a new approach for automatically identifying weak sequence similarities that is based on combinatorial pattern discovery. We compare its performance with a traditional, HMM-based scheme and obtain estimates for sensitivity and specificity of the two approaches. Our analysis suggests that pattern discovery methods can be substantially more sensitive in detecting remote protein relationships while at the same time guaranteeing high specificity.
引用
收藏
页码:926 / 937
页数:12
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