Structure-Templated Predictions of Novel Protein Interactions from Sequence Information

Doron Betel, Kevin E Breitkreuz, Ruth Isserlin, Danielle Dewar-Darch, Mike Tyers and Christopher W V Hogue

PLOS Computational Biology, 2007, vol. 3, issue 9, 1-7

Abstract: The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.: Many functions performed within a living cell are mediated by specific interactions between proteins. Precise geometric and chemical matches between segments of the protein structures facilitate those interactions. Such binding surfaces are often evolutionarily conserved elements of protein structures known as conserved domains that recognize specific binding elements on the interacting proteins. Binding domains and their corresponding interacting profiles constitute basic interacting modules that are replicated in multiple protein pairs, where they mediate similar interactions. Although many conserved domains are identified, only a handful have known, well-characterized binding elements. This paper describes a computational method that aims to elucidate the binding specificity of many domains. The utility of the derived binding specificity is demonstrated by predicting new interactions between yeast proteins. The predictions are based solely on sequence information by identifying the conserved domains and their corresponding binding sequences. A number of the predicted interactions were confirmed experimentally, demonstrating the feasibility of this approach.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:0030182

DOI: 10.1371/journal.pcbi.0030182

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