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Unraveling protein interaction networks with near-optimal efficiency

Nature Biotechnology volume 22, pages 98–103 (2004)Cite this article

Abstract

The functional characterization of genes and their gene products is the main challenge of the genomic era. Examining interaction information for every gene product is a direct way to assemble the jigsaw puzzle of proteins into a functional map. Here we demonstrate a method in which the information gained from pull-down experiments, in which single proteins act as baits to detect interactions with other proteins, is maximized by using a network-based strategy to select the baits. Because of the scale-free distribution of protein interaction networks, we were able to obtain fast coverage by focusing on highly connected nodes (hubs) first. Unfortunately, locating hubs requires prior global information about the network one is trying to unravel. Here, we present an optimized 'pay-as-you-go' strategy that identifies highly connected nodes using only local information that is collected as successive pull-down experiments are performed. Using this strategy, we estimate that 90% of the human interactome can be covered by 10,000 pull-down experiments, with 50% of the interactions confirmed by reciprocal pull-down experiments.

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Figure 1: Edge covering and the graph-weight of a node ordering.
Figure 2: Network coverage achieved by different strategies.
Figure 3: The effect of systematic error on the relative performance in confirming interactions of the pay-as-you-go versus the random strategies.

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Acknowledgements

We thank P. Akan, R. Apweiler, M. Ashburner, D. Bolser, D. Bray, G. Cesareni, A. Griffiths, A. Heger, H. Hermjacob, F. Hollfelder, V. Kunin, M. Louis, L. Montecchi-Palazzi, C. Ouzounis, K. Paszkiewicz, T. Schlitt, J. Schulz, E. Ukkonen, M. Vendruscolo, M. Vingron, C. Webber, N. Wyatt, I. Xenarios, Cellzome AG and the IntAct team at the European Bioinformatics Institute for providing resources, valuable feedback and insightful discussions. M.L. is supported by the EMBL International PhD program and Biotechnology and Biological Sciences Research Council (BBSRC) grant 8/C19399.

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  1. Michael Lappe

    Present address: Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1GA, UK

Authors and Affiliations

  1. EMBL Outstation, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, Cambridge, UK

    Michael Lappe

  2. Institute of Biotechnology, University of Helsinki, PO Box 56, Viikinkaari 5, FI-00014, Finland

    Liisa Holm

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  1. Michael Lappe
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Correspondence to Michael Lappe.

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Lappe, M., Holm, L. Unraveling protein interaction networks with near-optimal efficiency. Nat Biotechnol 22, 98–103 (2004). https://doi.org/10.1038/nbt921

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