BBMB Research Seminars
October 18, 2007
Dr. Sachdev Sidhu
Genentech
"“Phage peptide and antibody libraries in protein engineering and ligand selection”
1414 Molecular Biology Buidling
4:10 p.m.
Abstract:
Specificity Map for the PDZ Domain Family
Sachdev S. Sidhu1, Raffi Tonikian2, Yingnan Zhang1, Stephen L. Sazinsky1, Bridget Currell1, Jung-Hua Yeh1, Boris Reva3, Heike A. Held1, Brent A. Appleton1, Marie Evangelista1, Yan Wu1, Andrew C. Chan1, Somasekar Seshagiri1, Chris Sander3, Laurence A. Lasky1, Charles Boone2 & Gary D. Bader2
1)Genentech, Inc., South San Francisco, CA
2) University of Toronto, Canada
3) Memorial Sloan-Kettering Cancer Center, New York, NY
PDZ domains are protein-protein interaction modules that recognize specific C-terminal sequences to assemble protein complexes in multicellular organisms. Using large-scale peptide scannining, we accurately map binding specificity for approximately half of the over 330 PDZ domains identified in the human and Caenorhabditis elegans proteomes. We cluster PDZ domains by binding specificity and reveal novel distinct classes which recognize features of the last seven ligand positions. Thus, most PDZ domains are not promiscuous, but rather are fine-tuned for specific interactions. We use the domain-specific sequence distributions to construct a predicted human PDZ protein interaction network, correctly identifying proteins known to bind to PDZ domains and predicting many previously unknown interactions. One particular set of predicted interactions indicates that viruses have evolved PDZ-binding motifs able to disrupt host protein complexes and that highly pathogenic strains appear to use this mechanism to target PDZ domains involved in cell polarity and growth. Using the knowledge gained from the analysis of natural PDZ domains, we subsequently generated and analyzed hundreds of mutant PDZ domains to explore the evolution of novel specificities. Taken together, our results reveal that the PDZ domain is an extremely robust scaffold that can rapidly evolve new specificities that could readily lead to the evolution of novel networks and biological functions.
