The research described in the current proposal has the long-range goals of enabling the prediction of protein-protein interactions and the application of this knowledge to problems of biomedical relevance. An additional long-term goal is the fuller integration of Structural and Systems Biology.
Specific Aims i nclude: a) The development of three-dimensional structure-based methods to predict, on a genome-wide scale, whether and how two proteins interact. b) The integration of structural information with other sources of evidence as to protein-protein interactions. c) The application of the methods being developed to important biomedical problems. These research goals are motivated by a number of factors. First, cellular function is mediated by tens or even hundreds of thousands of protein-protein interactions yet these are generally hard to predict in advance or to measure accurately with high-throughput experimental techniques. A method that allows the computational prediction of such interactions would thus be of significant impact. Second, there are many more protein sequences than protein structures so it is necessary to find ways to amplify the information in protein databases if structure is to be fully integrated in genome scale research. The proposed research is intended to bridge this gap. A central element of the approach to be taken is the use of structural alignments to reveal novel functional relationships between proteins. Since structure is better conserved than sequence, these alignments can reveal new information. A novel structure-based method is introduced which exploits homology models and remote geometric relationships to amplify structural information. The evidence that is obtained is then combined with non-structural sources of evidence using Bayesian networks to yield a probability of whether two proteins interact. An important element in the proposed research strategy is the recognition that structural modeling on a large scale is necessarily imprecise so that it is necessary to use low resolution "scoring functions for a given model that do not depend sensitively on atomic detail. Bayesian methods then allow the extraction of a clear signal from the underlying noise. The biological impact of the research will be enhanced through computational/experimental applications in areas where structural clues have the potential of discovering truly novel interactions. Validated predictions on adhesion proteins, nuclear hormone receptors and cytokine signaling proteins demonstrate the efficacy of the methodology. New applications to viral host interactions and to cancer signaling pathways are described.

Public Health Relevance

The health relatedness of the proposed research arises from the fact that a better understanding of protein- protein interactions opens the way to a better understanding of the biology underlying human disease. Applications to interactions involved in viral-host interactions, and in cancer-related pathways serve to highlight this aspect of the proposed research.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Columbia University (N.Y.)
Schools of Medicine
New York
United States
Zip Code
Kim, Dae Heon; Park, Mi-Jeong; Gwon, Gwang Hyeon et al. (2014) An ankyrin repeat domain of AKR2 drives chloroplast targeting through coincident binding of two chloroplast lipids. Dev Cell 30:598-609
Petrey, Donald; Honig, Barry (2014) Structural bioinformatics of the interactome. Annu Rev Biophys 43:193-210
Chen, Brian Y (2014) VASP-E: specificity annotation with a volumetric analysis of electrostatic isopotentials. PLoS Comput Biol 10:e1003792
Dey, Fabian; Cliff Zhang, Qiangfeng; Petrey, Donald et al. (2013) Toward a "structural BLAST": using structural relationships to infer function. Protein Sci 22:359-66
Zhang, Qiangfeng Cliff; Petrey, Donald; Garzon, Jose Ignacio et al. (2013) PrePPI: a structure-informed database of protein-protein interactions. Nucleic Acids Res 41:D828-33
Kuziemko, Andrew; Honig, Barry; Petrey, Donald (2011) Using structure to explore the sequence alignment space of remote homologs. PLoS Comput Biol 7:e1002175
Bishop, Eric P; Rohs, Remo; Parker, Stephen C J et al. (2011) A map of minor groove shape and electrostatic potential from hydroxyl radical cleavage patterns of DNA. ACS Chem Biol 6:1314-20
Fischer, Markus; Zhang, Qiangfeng Cliff; Dey, Fabian et al. (2011) MarkUs: a server to navigate sequence-structure-function space. Nucleic Acids Res 39:W357-61
Slattery, Matthew; Riley, Todd; Liu, Peng et al. (2011) Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins. Cell 147:1270-82
Zhu, Jiang; Yu, Yong; Ulbrich, Maximilian H et al. (2011) Structural model of the TRPP2/PKD1 C-terminal coiled-coil complex produced by a combined computational and experimental approach. Proc Natl Acad Sci U S A 108:10133-8

Showing the most recent 10 out of 65 publications