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Internal organization of large protein families: Relationship between the sequence, structure, and function‐based clustering
Author(s) -
Cai XiaoHui,
Jaroszewski Lukasz,
Wooley John,
Godzik Adam
Publication year - 2011
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.23049
Subject(s) - sequence (biology) , computational biology , cluster analysis , similarity (geometry) , function (biology) , protein family , protein structure database , structural classification of proteins database , protein structure , biology , cluster (spacecraft) , protein function prediction , evolutionary biology , genetics , computer science , protein function , artificial intelligence , gene , sequence database , biochemistry , image (mathematics) , programming language
The protein universe can be organized in families that group proteins sharing common ancestry. Such families display variable levels of structural and functional divergence, from homogenous families, where all members have the same function and very similar structure, to very divergent families, where large variations in function and structure are observed. For practical purposes of structure and function prediction, it would be beneficial to identify sub‐groups of proteins with highly similar structures (iso‐structural) and/or functions (iso‐functional) within divergent protein families. We compared three algorithms in their ability to cluster large protein families and discuss whether any of these methods could reliably identify such iso‐structural or iso‐functional groups. We show that clustering using profile‐sequence and profile–profile comparison methods closely reproduces clusters based on similarities between 3D structures or clusters of proteins with similar biological functions. In contrast, the still commonly used sequence‐based methods with fixed thresholds result in vast overestimates of structural and functional diversity in protein families. As a result, these methods also overestimate the number of protein structures that have to be determined to fully characterize structural space of such families. The fact that one can build reliable models based on apparently distantly related templates is crucial for extracting maximal amount of information from new sequencing projects. Proteins 2011; © 2011 Wiley‐Liss, Inc.