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Computational Biology Branch, National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland 20894, USA
(RECEIVED August 9, 2005; FINAL REVISION October 12, 2005; ACCEPTED October 27, 2005)
Proteins evolved through the shuffling of functional domains, and therefore, the same domain can be found in different proteins and species. Interactions between such conserved domains often involve specific, well-determined binding surfaces reflecting their important biological role in a cell. To find biologically relevant interactions we developed a method of systematically comparing and classifying protein domain interactions from the structural data. As a result, a set of conserved binding modes (CBMs) was created using the atomic detail of structure alignment data and the protein domain classification of the Conserved Domain Database. A conserved binding mode is inferred when different members of interacting domain families dock in the same way, such that their structural complexes superimpose well. Such domain interactions with recurring structural themes have greater significance to be biologically relevant, unlike spurious crystal packing interactions. Consequently, this study gives lower and upper bounds on the number of different types of interacting domain pairs in the structure database on the order of 10002000. We use CBMs to create domain interaction networks, which highlight functionally significant connections by avoiding many infrequent links between highly connected nodes. The CBMs also constitute a library of docking templates that may be used in molecular modeling to infer the characteristics of an unknown binding surface, just as conserved domains may be used to infer the structure of an unknown protein. The methods ability to sort through and classify large numbers of putative interacting domain pairs is demonstrated on the oligomeric interactions of globins.
Keywords: proteinprotein interactions; conserved binding modes; homology modeling; protein structure; protein domain families
Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi/doi/10.1110/ps.051760806.
Reprint requests to: Benjamin A. Shoemaker, Computational Biology Branch, National Center for Biotechnology Information, Building 38A, National Institutes of Health, Bethesda, MD 20894, USA; e-mail: shoemake{at}mail.nih.gov; fax: (301) 480-4637.
Supplemental material: www.proteinscience.org
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