2. Academic Validation
  3. Towards a proteome-scale map of the human protein-protein interaction network

Towards a proteome-scale map of the human protein-protein interaction network

  • Nature. 2005 Oct 20;437(7062):1173-8. doi: 10.1038/nature04209.
Jean-François Rual 1,  Kavitha Venkatesan,  Tong Hao,  Tomoko Hirozane-Kishikawa,  Amélie Dricot,  Ning Li,  Gabriel F Berriz,  Francis D Gibbons,  Matija Dreze,  Nono Ayivi-Guedehoussou,  Niels Klitgord,  Christophe Simon,  Mike Boxem,  Stuart Milstein,  Jennifer Rosenberg,  Debra S Goldberg,  Lan V Zhang,  Sharyl L Wong,  Giovanni Franklin,  Siming Li,  Joanna S Albala,  Janghoo Lim,  Carlene Fraughton,  Estelle Llamosas,  Sebiha Cevik,  Camille Bex,  Philippe Lamesch,  Robert S Sikorski,  Jean Vandenhaute,  Huda Y Zoghbi,  Alex Smolyar,  Stephanie Bosak,  Reynaldo Sequerra,  Lynn Doucette-Stamm,  Michael E Cusick,  David E Hill,  Frederick P Roth,  Marc Vidal
Affiliations

Affiliation

  • 1 Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA.
PMID: 16189514 DOI: 10.1038/nature04209
Abstract

Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with Other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.

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