Functional Centrality: Detecting Lethality of Proteins in Protein Interaction Networks

Kar Leong Tew[1] (kltew@i2r.a-star.edu.sg)
Xiao-Li Li[1] (xlli@i2r.a-star.edu.sg)
Soon-Heng Tan[1],[2],[3] (chris.tan@utoronto.ca)

[1]Knowledge Discovery Department, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613
[2]Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada*
[3]Department of Molecular and Medical Genetics, University of Toronto, Toronto, Ontario, Canada*
*Present Affiliation

Abstract

Identifying lethal proteins is important for understanding the intricate mechanism governing life. Researchers have shown that the lethality of a protein can be computed based on its topological position in the protein-protein interaction (PPI) network. Performance of current approaches has been less than satisfactory as the lethality of a protein is a functional characteristic that cannot be determined solely by network topology. Furthermore, a significant number of lethal proteins have low connectivity in the interaction networks but are overlooked by most current methods.
Our work reveals that a protein's lethality correlates more strongly with its “functional centrality” than pure topological centrality. We define functional centrality as the topological centrality within a subnetwork of proteins with similar functions. Evaluation experiments on four Saccharomyces cerevisiae PPI datasets showed that NFC performed significantly better than all the other existing computational techniques. Our method was able to detect low connectivity lethal proteins that were previously undetected by conventional methods. The results and an online version of NFC is available at http://lethalproteins.i2r.a-star.edu.sg

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