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Molecular & Cellular Proteomics 7:2048-2060, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Targeting the Human Cancer Pathway Protein Interaction Network by Structural Genomics^*

Yuanpeng Janet Huang, Dehua Hang, Long Jason Lu^,¶, Liang Tong^||, Mark B. Gerstein^,** and Gaetano T. Montelione^,

From the Department of Molecular Biology and Biochemistry, Center for Advanced Biotechnology and Medicine, and Northeast Structural Genomics Consortium, Rutgers University, Piscataway, New Jersey 08854, Department of Molecular Biophysics and Biochemistry and ^** Department of Computer Science and Northeast Structural Genomics Consortium, Yale University, New Haven, Connecticut 06520, and ^|| Department of Biological Sciences and Northeast Structural Genomics Consortium, Columbia University, New York, New York 10027

Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as "hubs" or "bottlenecks" in the HCPIN. At least half of HCPIN proteins are either directly associated with or interact with multiple signaling pathways. Although some 45% of residues in these proteins are in sequence segments that meet criteria sufficient for approximate homology modeling (Basic Local Alignment Search Tool (BLAST) E-value <10^–6), only 20% of residues in these proteins are structurally covered using high accuracy homology modeling criteria (i.e. BLAST E-value <10^–6 and at least 80% sequence identity) or by actual experimental structures. The HCPIN Website provides a comprehensive description of this biomedically important multipathway network together with experimental and homology models of HCPIN proteins useful for cancer biology research. To complement and enrich cancer systems biology, the Northeast Structural Genomics Consortium is targeting >1000 human proteins and protein domains from the HCPIN for sample production and 3D structure determination. The long range goal of this effort is to provide a comprehensive 3D structure-function database for human cancer-associated proteins and protein complexes in the context of their interaction networks. The network-based target selection (BioNet) approach described here is an example of a general strategy for targeting co-functioning proteins by structural genomics projects.

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