The overarching goal of the thesis project is to develop technologies to infer pathways implicated in periodontal diseases and tissue regeneration. Specifically, we will use methods to computationally annotate and predict protein interactions to investigate sub-networks within the human interactome that comprise these pathways. The thesis research will have two phases: (1) Development of a periodontal protein interaction database (PPID) and automated interaction predictions. The PPID will include known protein interactions, automated prediction of interactions using state of the art computational methods, and integration into visualized interaction networks. Automating interaction predictions will require integration of the phylogenetic profile, domain fusion, interolog, and gene neighbor techniques. Access to the database and prediction tools will be developed within the lab servers. (2) Experimental verification of predicted interactions. To evaluate prediction methods, proteins with high probability of interaction will be tested for functional interactions. Experiments will focus on protein pairs predicted to exist in a pathway with the NH2-propeptide of procollagen type I (N-propeptide). N-propeptide provides feedback for extracellular matrix production [1], an important aspect of bone formation. Verification of physical interactions will include co-immunoprecipitation, yeast two hybrid, and cell-based binding studies. Co-expression testing will include quantitative RT-PCR, SAGE, and/or gene array methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of Dental & Craniofacial Research (NIDCR)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
5F30DE017522-04
Application #
7616719
Study Section
NIDCR Special Grants Review Committee (DSR)
Program Officer
Frieden, Leslie A
Project Start
2006-05-01
Project End
2011-04-30
Budget Start
2009-05-01
Budget End
2010-04-30
Support Year
4
Fiscal Year
2009
Total Cost
$34,943
Indirect Cost
Name
University of Washington
Department
Dentistry
Type
Schools of Dentistry
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Martinez-Avila, Olga; Wu, Shenping; Kim, Seung Joong et al. (2012) Self-assembly of filamentous amelogenin requires calcium and phosphate: from dimers via nanoribbons to fibrils. Biomacromolecules 13:3494-502
Horst, Orapin V; Horst, Jeremy A; Samudrala, Ram et al. (2011) Caries induced cytokine network in the odontoblast layer of human teeth. BMC Immunol 12:9
Cunningham, Michael L; Horst, Jeremy A; Rieder, Mark J et al. (2011) IGF1R variants associated with isolated single suture craniosynostosis. Am J Med Genet A 155A:91-7
Horst, Jeremy A; Wang, Kai; Horst, Orapin V et al. (2010) Disease risk of missense mutations using structural inference from predicted function. Curr Protein Pept Sci 11:573-88
Dibble, Christopher F; Horst, Jeremy A; Malone, Michael H et al. (2010) Defining the functional domain of programmed cell death 10 through its interactions with phosphatidylinositol-3,4,5-trisphosphate. PLoS One 5:e11740
Horst, Jeremy A; Samudrala, Ram (2010) A protein sequence meta-functional signature for calcium binding residue prediction. Pattern Recognit Lett 31:2103-2112
Horst, Jeremy; Samudrala, Ram (2009) Diversity of protein structures and difficulties in fold recognition: the curious case of protein G. F1000 Biol Rep 1:69
Michino, Mayako; Abola, Enrique; GPCR Dock 2008 participants et al. (2009) Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008. Nat Rev Drug Discov 8:455-63
Horst, Jeremy A; Clark, Matthew D; Lee, Andrew H (2009) Observation, assisting, apprenticeship: cycles of visual and kinesthetic learning in dental education. J Dent Educ 73:919-33
Liu, Tianyun; Horst, Jeremy A; Samudrala, Ram (2009) A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction. Proteins 77:220-34

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