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Bioinformatics Advance Access published online on March 15, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti386
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received November 4, 2004
Revised February 16, 2005
Accepted March 9, 2005

Article

The properties of protein family space depend on experimental design

Victor Kunin 1*, Sarah A. Teichmann 2, Martijn A. Huynen 3, and Christos A. Ouzounis 1

1 Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK
2 MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, UK
3 Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, University of Nijmegen, Nijmegen, The Netherlands

* To whom correspondence should be addressed.
Victor Kunin, E-mail: kunin{at}ebi.ac.uk


  Abstract

Motivation: Databases of protein families often exhibit drastically different properties of the protein family space.

Results: We compared the properties of protein family space as reflected by exhaustive protein family databases and databases with predefined families. We used TRIBES, Protomap, ProDom and COGs as representatives of the exhaustive databases, and Pfam-A and Superfamily as databases that predefine families. We observe a power-law distribution of family sizes in all these databases, albeit in predefined databases the power law line collapses before reaching smaller-sized families. We discuss future trends of this power-law distribution and suggest that saturation in the sampling of protein family space will result in a distortion of the power law at small family sizes. For larger genome sizes, predefined databases show logarithmic growth of number of families per genome, whereas exhaustive databases exhibit a virtually linear relationship. All databases consistently differ in the proportion of protein families shared between taxa. Pre-defined databases have a larger number of protein families shared between the three domains of life, while exhaustive databases show a much more fragmented distribution. We argue that these discrepancies reflect alternative approaches to the trade-off issue of sensitivity vs. specificity in detection of homologous proteins. We conclude that these properties are complementary rather than contradictory, describing the protein universe from different perspectives.


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