Proteomic Phosphopeptide Chip Technology for Protein Profiling

University Of Houston, Houston TX

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Abstract

[unreadable] DESCRIPTION (provided by applicant): [unreadable] This R21/R33 grant application is in response to NIH/NCI RFA-CA-07-005 for "Advanced Proteomic Platforms and Computational Sciences for the NCI Clinical Proteomic Technologies Initiative". Cancers are malignant growths caused by misregulated and uncontrolled cell division; these abnormal cellular activities are typically accompanied by unusual protein expression profiles1. Existing proteomics technologies cannot meet the demand of reliable, sensitive, accurate determinations of these disease-related molecular profiles; to achieve reproducible quality, high throughput, and affordable proteomic analyses, many challenging technological hurdles must first be addressed. We propose developing a proteomic phosphopeptide (PPEP) microchip technology platform that profiles proteins carrying phosphopeptide binding domains (PPBDs); using profiles generated in these experiments, along with predicative computational modeling based on both experimental data and a comprehensive PPEP and PPBD interaction database, we will demonstrate specific and quantitative measurements related to protein functions for proteins of significant biological importance. The strength of our proposed work lies in the integration of an already established array technology and a highly promising bioinformatics platform. The methods developed will enable many researchers to rapidly and vigorously develop peptide arrays for quantitative measurement of the proteins in the biological systems of their own interest or to use standard domain-optimized peptide arrays to systematically profile biological samples of basic research or clinical importance. Over the long term, the methods we develop will be used to establish domain-recognition systems for other types of domain-carrying proteins measurements. These capabilities of reliable measurement of proteins as a function of disease states are essential for cancer research, diagnosis and treatment. [unreadable] [unreadable] [unreadable] [unreadable]