A family of evolution-entropy hybrid methods for ranking protein residues by importance

被引：241

作者：

Mihalek, I ^{[1
]}

Res, I ^{[1
]}

Lichtarge, O ^{[1
]}

机构：

[1] Baylor Coll Med, Dept Mol & Human Genet, Houston, TX 77030 USA

来源：

JOURNAL OF MOLECULAR BIOLOGY | 2004年 / 336卷 / 05期

关键词：

bioinformatics; evolutionary trace; information entropy; functional site; binding interaction;

D O I：

10.1016/j.jmb.2003.12.078

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：

In order to identify the amino acids that determine protein structure and function it is useful to rank them by their relative importance. Previous approaches belong to two groups; those that rely on statistical inference, and those that focus on phylogenetic analysis. Here, we introduce a class of hybrid methods that combine evolutionary and entropic information from multiple sequence alignments. A detailed analysis in insulin receptor kinase domain and tests on proteins that are well-characterized experimentally show the hybrids' greater robustness with respect to the input choice of sequences, as well as improved sensitivity and specificity of prediction. This is a further step toward proteome scale analysis of protein structure and function. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：1265 / 1282

页数：18

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