The detection and quantitation of protein-ligand binding interactions is critical for understanding protein function and drug action. Current assays for the analysis of protein-ligand binding interactions do not have the combination of throughput, generality, and quantitative capabilities necessary for characterizing protein-ligand binding interactions on the proteomic scale. This ultimately precludes a complete understanding of protein function and drug action. Proposed here is the development of a protein-ligand binding platform that is amenable to quantitative analyses on the proteomic scale and that is useful with a wide range of ligand types including small molecules, DNA, peptides, and proteins. The platform exploits an H/D exchange- and mass spectrometry-based technique, termed SUPREX, for the high-throughput and quantitative thermodynamic analysis of protein-ligand binding interactions.
The specific aims of this work are focused on the platform's development, validation and initial application to analysis of the protein network in the 55-protein Escherichia coli (E. coli) bacteriophage T7 proteome, to analysis of protein-protein interactions in a subset of 11 proteins involved in a yeast cell-signaling pathway, and to drug mode-of-action studies using selected proteins in the yeast proteome. In the proposed work we will (1) characterize the thermodynamic properties of each model protein in this study using three different protocols;(2) optimize and evaluate the different protocols in (1) in terms of their throughput and multiplex cababilities;(3) use the optimized protocols to detect and quantify the protein-protein interactions between the 55 proteins T7 proteome and between 11 yeast proteins in involved in a Camediated cell-signaling pathway;(4) demonstrate the platform's ability to identify the on-target and off-target interactions of the immunosuppressive drug, cyclosporin A (CsA), with the 11 cell-signaling proteins in yeast;and (5) utilize the platform in a drug mode-of-action study in which tamoxifen will be screened for binding to a set of 1427 yeast proteins in order to better understand the pleiotropic activities of this breast cancer drug.

Public Health Relevance

Current assays for protein-ligand binding do not have the combination of throughput, generality, and quantitative capabilities necessary for characterizing protein function and drug action on the proteomic scale. Proposed here is the development of a protein-ligand binding platform that is amenable to quantitative analyses on the proteomic scale. The work will focus on the platform's optimization, validation, and initial application to analysis of the protein network in the 55-protein E. coli bacteriophage T7 proteome, to analysis of protein-protein interactions in a subset of 11 proteins involved in a yeast cell-signaling pathway, and to drug mode-of-action studies using proteins in the yeast proteome;but, the platform will be scaleable and directly applicable to the quantitative analysis of protein-ligand binding in other proteomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM084174-03
Application #
8118907
Study Section
Enabling Bioanalytical and Biophysical Technologies Study Section (EBT)
Program Officer
Edmonds, Charles G
Project Start
2009-08-01
Project End
2013-07-31
Budget Start
2011-08-01
Budget End
2012-07-31
Support Year
3
Fiscal Year
2011
Total Cost
$321,081
Indirect Cost
Name
Duke University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Meng, He; Fitzgerald, Michael C (2018) Proteome-Wide Characterization of Phosphorylation-Induced Conformational Changes in Breast Cancer. J Proteome Res 17:1129-1137
Ogburn, Ryenne N; Jin, Lorrain; Meng, He et al. (2017) Discovery of Tamoxifen and N-Desmethyl Tamoxifen Protein Targets in MCF-7 Cells Using Large-Scale Protein Folding and Stability Measurements. J Proteome Res 16:4073-4085
Liu, Fang; Meng, He; Fitzgerald, Michael C (2017) Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using SILAC-SPROX. J Proteome Res 16:3277-3286
Ogburn, Ryenne N; Randall, Thomas A; Xu, Yingrong et al. (2017) Are dust mite allergens more abundant and/or more stable than other Dermatophagoides pteronyssinus proteins? J Allergy Clin Immunol 139:1030-1032.e1
Roberts, Julia H; Liu, Fang; Karnuta, Jaret M et al. (2016) Discovery of Age-Related Protein Folding Stability Differences in the Mouse Brain Proteome. J Proteome Res 15:4731-4741
Liu, Fang; Fitzgerald, Michael C (2016) Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis. J Proteome Res 15:4666-4674
Geer Wallace, M Ariel; Kwon, Do-Yeon; Weitzel, Douglas H et al. (2016) Discovery of Manassantin A Protein Targets Using Large-Scale Protein Folding and Stability Measurements. J Proteome Res 15:2688-96
Adhikari, Jagat; West, Graham M; Fitzgerald, Michael C (2015) Global analysis of protein folding thermodynamics for disease state characterization. J Proteome Res 14:2287-97
Tran, Duc T; Adhikari, Jagat; Fitzgerald, Michael C (2014) StableIsotope Labeling with Amino Acids in Cell Culture (SILAC)-based strategy for proteome-wide thermodynamic analysis of protein-ligand binding interactions. Mol Cell Proteomics 13:1800-13
Strickland, Erin C; Geer, M Ariel; Hong, Jiyong et al. (2014) False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform. J Am Soc Mass Spectrom 25:132-40

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