Structural similarity of genetically interacting proteins

Oranit Dror, Dina Schneidman-Duhovny, Alexandra Shulman-Peleg, Ruth Nussinov, Haim J. Wolfson*, Roded Sharan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Background: The study of gene mutants and their interactions is fundamental to understanding gene function and backup mechanisms within the cell. The recent availability of large scale genetic interaction networks in yeast and worm allows the investigation of the biological mechanisms underlying these interactions at a global scale. To date, less than 2% of the known genetic interactions in yeast or worm can be accounted for by sequence similarity. Results: Here, we perform a genome-scale structural comparison among protein pairs in the two species. We show that significant fractions of genetic interactions involve structurally similar proteins, spanning 7-10% and 14% of all known interactions in yeast and worm, respectively. We identify several structural features that are predictive of genetic interactions and show their superiority over sequence-based features. Conclusion: Structural similarity is an important property that can explain and predict genetic interactions. According to the available data, the most abundant mechanism for genetic interactions among structurally similar proteins is a common interacting partner shared by two genetically interacting proteins.

Original languageAmerican English
Article number69
JournalBMC Systems Biology
StatePublished - 31 Jul 2008
Externally publishedYes

Bibliographical note

Funding Information:
We thank Maxim Shatsky, Nir Yosef and Tomer Shlomi for their help with various stages of the analysis. RS was supported by an Alon Fellowship. The research of OD was supported by the Israeli Ministry of Science Eshkol Fellowship. The research of AS-P was supported by the Clore PhD Fellowship. The research of HJW has been supported in part by the Israel Science Foundation (grant no. 281/05), by the NIAID, NIH (grant No. 1UC1AI067231), by the Binational US-Israel Science Foundation (BSF) and by the Hermann Minkowski-Minerva Center for Geometry at TAU. This publication has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract NO1-CO-12400. This research was supported [in part] by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government.


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