A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules.

Amy Hin Yan Tong, Becky Drees, Giuliano Nardelli, Gary D Bader, Barbara Brannetti, Luisa Castagnoli, Marie Evangelista, Silvia Ferracuti, Bryce Nelson, Serena Paoluzi, Michele Quondam, Adriana Zucconi, Christopher W V Hogue, Stanley Fields, Charles Boone, Gianni Cesareni

Journal: Science (New York, N.Y.) 2002;295(5553):321-4

PMID: 11743162

Abstract

Peptide recognition modules mediate many protein-protein interactions critical for the assembly of macromolecular complexes. Complete genome sequences have revealed thousands of these domains, requiring improved methods for identifying their physiologically relevant binding partners. We have developed a strategy combining computational prediction of interactions from phage-display ligand consensus sequences with large-scale two-hybrid physical interaction tests. Application to yeast SH3 domains generated a phage-display network containing 394 interactions among 206 proteins and a two-hybrid network containing 233 interactions among 145 proteins. Graph theoretic analysis identified 59 highly likely interactions common to both networks. Las17 (Bee1), a member of the Wiskott-Aldrich Syndrome protein (WASP) family of actin-assembly proteins, showed multiple SH3 interactions, many of which were confirmed in vivo by coimmunoprecipitation.

Address: Banting and Best Department of Medical Research and Department of Molecular and Medical Genetics, University of Toronto, Toronto, Ontario, Canada M5G 1L6.
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