Log on / register
Feedback | Support | My details
Open AccessResearch article

An evolutionary and structural characterization of mammalian protein complex organization

Philip Wong1 email, Sonja Althammer1* email, Andrea Hildebrand1* email, Andreas Kirschner2* email, Philipp Pagel1,2* email, Bernd Geissler2 email, Pawel Smialowski1,2 email, Florian Blöchl1 email, Matthias Oesterheld1 email, Thorsten Schmidt1,2 email, Normann Strack1 email, Fabian J Theis1,3 email, Andreas Ruepp1 email and Dmitrij Frishman1,2 email

Helmholtz Center Munich – German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Ingolstädter Landstraße 1 D-85764 Neuherberg, Germany

Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftzentrum Weihenstephan, 85350 Freising, Germany

Max-Planck-Institute for Dynamics and Self-Organization, Bunsenstrasse 10, 37073 Göttingen, Germany

author email corresponding author email* Contributed equally

BMC Genomics 2008, 9:629doi:10.1186/1471-2164-9-629

Published: 23 December 2008

Abstract

Background

We have recently released a comprehensive, manually curated database of mammalian protein complexes called CORUM. Combining CORUM with other resources, we assembled a dataset of over 2700 mammalian complexes. The availability of a rich information resource allows us to search for organizational properties concerning these complexes.

Results

As the complexity of a protein complex in terms of the number of unique subunits increases, we observed that the number of such complexes and the mean non-synonymous to synonymous substitution ratio of associated genes tend to decrease. Similarly, as the number of different complexes a given protein participates in increases, the number of such proteins and the substitution ratio of the associated gene also tends to decrease. These observations provide evidence relating natural selection and the organization of mammalian complexes. We also observed greater homogeneity in terms of predicted protein isoelectric points, secondary structure and substitution ratio in annotated versus randomly generated complexes. A large proportion of the protein content and interactions in the complexes could be predicted from known binary protein-protein and domain-domain interactions. In particular, we found that large proteins interact preferentially with much smaller proteins.

Conclusion

We observed similar trends in yeast and other data. Our results support the existence of conserved relations associated with the mammalian protein complexes.


© 1999-2009 BioMed Central Ltd unless otherwise stated. Part of Springer Science+Business Media.