Proteolytic enzymes play essential roles for all living organisms, from bacteria to higher eukaryotes. Understanding the function of the large numbers of proteases that have been uncovered by whole genome sequencing is a significant challenge, and novel methods are needed to rapidly provide functional information on a proteome-wide scale. Peptide libraries have been used over the last 15 years to determine cleavage site sequence motifs, which can be used to design model substrates, identify in vivo protein substrates, and generate potent and specific protease inhibitors. Recent advances in peptide microarray technology now allow higher throughput analysis of peptide cleavage specificity, but current approaches can only be applied to a subset of proteases and provides limited information. We propose to develop a novel platform that combines peptide microarrays with mass spectrometry to allow for rapid, general, and thorough analysis of protease cleavage selectivity. Dually-labeled fluorescence resonance energy transfer peptide substrates will be immobilized on modified glass slides at high density via their amino termini. Treatment of slides with a protease of interest results in site- specific cleavage of a subset of peptides. The resulting change in fluorescence will be detected on a microarray reader, allowing quantitative assessment of the extent of cleavage of each peptide on the array. The specific sites of cleavage within each substrate peptide will be determined by subjecting the released amino terminal fragments to liquid chromatography-electrospray mass spectrometry. Consensus cleavage motifs are subsequently derived from sequence alignments of the cleaved peptides. Because proteases have been implicated widely in human disease, this methodology has the potential to impact research and drug discovery in a number of areas, including cancer, arthritis, autoimmune disease, and infectious disease. ? ? Proteases, the enzymes that break down proteins, are essential for normal physiology yet can contribute to human disease in multiple contexts, including cancer, viral infection, autoimmune disease, and Alzheimer's disease. The proposed research will develop new micro-scale technology to rapidly analyze the way that proteases recognize their target proteins. This information will contribute to our understanding of how proteases function and will be applicable to the discovery of new protease inhibitor drugs. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21RR022859-01A1
Application #
7345165
Study Section
Special Emphasis Panel (ZRR1-BT-B (01))
Program Officer
Friedman, Fred K
Project Start
2007-12-15
Project End
2010-11-30
Budget Start
2007-12-15
Budget End
2008-11-30
Support Year
1
Fiscal Year
2008
Total Cost
$206,510
Indirect Cost
Name
Yale University
Department
Pharmacology
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Deng, Yang; Alicea-Velázquez, Nilda L; Bannwarth, Ludovic et al. (2014) Global analysis of human nonreceptor tyrosine kinase specificity using high-density peptide microarrays. J Proteome Res 13:4339-46
Caescu, Cristina I; Jeschke, Grace R; Turk, Benjamin E (2009) Active-site determinants of substrate recognition by the metalloproteinases TACE and ADAM10. Biochem J 424:79-88