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Issue 12, 2009
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Towards inferring time dimensionality in protein–protein interaction networks by integrating structures: the p53 example

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Abstract

Inspection of protein–protein interaction maps illustrates that a hub protein can interact with a very large number of proteins, reaching tens and even hundreds. Since a single protein cannot interact with such a large number of partners at the same time, this presents a challenge: can we figure out which interactions can occur simultaneously and which are mutually excluded? Addressing this question adds a fourth dimension into interaction maps: that of time. Including the time dimension in structural networks is an immense asset; time dimensionality transforms network node-and-edge maps into cellular processes, assisting in the comprehension of cellular pathways and their regulation. While the time dimensionality can be further enhanced by linking protein complexes to time series of mRNA expression data, current robust, network experimental data are lacking. Here we outline how, using structural data, efficient structural comparison algorithms and appropriate datasets and filters can assist in getting an insight into time dimensionality in interaction networks; in predicting which interactions can and cannot co-exist; and in obtaining concrete predictions consistent with experiment. As an example, we present p53-linked processes.

Graphical abstract: Towards inferring time dimensionality in protein–protein interaction networks by integrating structures: the p53 example

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Publication details

The article was received on 20 Mar 2009, accepted on 28 May 2009 and first published on 30 Jun 2009


Article type: Paper
DOI: 10.1039/B905661K
Citation: Mol. BioSyst., 2009,5, 1770-1778
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    Towards inferring time dimensionality in protein–protein interaction networks by integrating structures: the p53 example

    N. Tuncbag, G. Kar, A. Gursoy, O. Keskin and R. Nussinov, Mol. BioSyst., 2009, 5, 1770
    DOI: 10.1039/B905661K

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