Literature DB >> 19261595

How perfect can protein interactomes be?

Emmanuel D Levy1, Christian R Landry, Stephen W Michnick.   

Abstract

Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with "junk" DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes-that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term "noisy." We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.

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Year:  2009        PMID: 19261595     DOI: 10.1126/scisignal.260pe11

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  31 in total

Review 1.  Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.

Authors:  Bram Stynen; Hélène Tournu; Jan Tavernier; Patrick Van Dijck
Journal:  Microbiol Mol Biol Rev       Date:  2012-06       Impact factor: 11.056

2.  DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila.

Authors:  William W Fisher; Jingyi Jessica Li; Ann S Hammonds; James B Brown; Barret D Pfeiffer; Richard Weiszmann; Stewart MacArthur; Sean Thomas; John A Stamatoyannopoulos; Michael B Eisen; Peter J Bickel; Mark D Biggin; Susan E Celniker
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-10       Impact factor: 11.205

3.  Protein abundance is key to distinguish promiscuous from functional phosphorylation based on evolutionary information.

Authors:  Emmanuel D Levy; Stephen W Michnick; Christian R Landry
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-09-19       Impact factor: 6.237

4.  ComPPI: a cellular compartment-specific database for protein-protein interaction network analysis.

Authors:  Daniel V Veres; Dávid M Gyurkó; Benedek Thaler; Kristóf Z Szalay; Dávid Fazekas; Tamás Korcsmáros; Peter Csermely
Journal:  Nucleic Acids Res       Date:  2014-10-27       Impact factor: 16.971

Review 5.  Noise in cellular signaling pathways: causes and effects.

Authors:  John E Ladbury; Stefan T Arold
Journal:  Trends Biochem Sci       Date:  2012-02-15       Impact factor: 13.807

Review 6.  Protein-protein interaction networks: how can a hub protein bind so many different partners?

Authors:  Chung-Jung Tsai; Buyong Ma; Ruth Nussinov
Journal:  Trends Biochem Sci       Date:  2009-12       Impact factor: 13.807

Review 7.  Strategies for protein synthetic biology.

Authors:  Raik Grünberg; Luis Serrano
Journal:  Nucleic Acids Res       Date:  2010-04-12       Impact factor: 16.971

8.  Protein networks reveal detection bias and species consistency when analysed by information-theoretic methods.

Authors:  Luis P Fernandes; Alessia Annibale; Jens Kleinjung; Anthony C C Coolen; Franca Fraternali
Journal:  PLoS One       Date:  2010-08-18       Impact factor: 3.240

Review 9.  Proteome-Scale Human Interactomics.

Authors:  Katja Luck; Gloria M Sheynkman; Ivy Zhang; Marc Vidal
Journal:  Trends Biochem Sci       Date:  2017-03-08       Impact factor: 13.807

10.  Expanding the substantial interactome of NEMO using protein microarrays.

Authors:  Beau J Fenner; Michael Scannell; Jochen H M Prehn
Journal:  PLoS One       Date:  2010-01-20       Impact factor: 3.240

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