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Title: Disruption of protein complexes
Authors: Taheri, G.
Habibi, M.
Wong, L. 
Eslahchi, C.
Keywords: disruption
Protein complexes
spectral bipartitioning
Issue Date: Jun-2013
Citation: Taheri, G., Habibi, M., Wong, L., Eslahchi, C. (2013-06). Disruption of protein complexes. Journal of Bioinformatics and Computational Biology 11 (3) : -. ScholarBank@NUS Repository.
Abstract: Protein complexes are a cornerstone of many biological processes and, together, they form various types of molecular machinery that perform a vast array of biological functions. Different complexes perform different functions and, the same complex can perform very different functions that depend on a variety of factors. Thus disruption of protein complexes can be lethal to an organism. It is interesting to identify a minimal set of proteins whose removal would lead to a massive disruption of protein complexes and, to understand the biological properties of these proteins. A method is presented for identifying a minimum number of proteins from a given set of complexes so that a maximum number of these complexes are disrupted when these proteins are removed. The method is based on spectral bipartitioning. This method is applied to yeast protein complexes. The identified proteins participate in a large number of biological processes and functional modules. A large proportion of them are essential proteins. Moreover, removing these identified proteins causes a large number of the yeast protein complexes to break into two fragments of nearly equal size, which minimizes the chance of either fragment being functional. The method is also superior in these aspects to alternative methods based on proteins with high connection degree, proteins whose neighbors have high average degree, and proteins that connect to lots of proteins of high connection degree. Our spectral bipartitioning method is able to efficiently identify a biologically meaningful minimal set of proteins whose removal causes a massive disruption of protein complexes in an organism. © Imperial College Press.
Source Title: Journal of Bioinformatics and Computational Biology
ISSN: 02197200
DOI: 10.1142/S0219720013410084
Appears in Collections:Staff Publications

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