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SBIR Phase I: Electron Capture Dissociation for Radiofrequency Ion Trap MS

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0810794
Agency Tracking Number: 0810794
Amount: $99,991.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: EO
Solicitation Number: NSF 07-586
Solicitation Year: N/A
Award Year: 2008
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
TUSTIN, CA 92780
United States
DUNS: 939007852
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jack Syage
 (714) 258-4400
Business Contact
 Jack Syage
Title: PhD
Phone: (714) 258-4400
Research Institution

This Small Business Innovation Research Phase I project will test the feasibility of an electron capture dissociation (ECD) method for radio-frequency (RF) ion trap mass spectrometers. ECD has emerged as a powerful means to fragment peptide and protein bonds in a manner that can reveal details of post-translational modifications (PTMs). ECD is difficult to implement in RF driven mass analyzers, such as quadrupole and linear ion traps, because the RF fields drive electrons to excess energy and out of the trap. This research demonstrates the feasibility for an ECD method for ion traps using a method of gating the RF off for short periods of time, while introducing low-energy electrons to achieve ECD. The broader impacts of this research are in healthcare and disease control. Studying the entire complement of proteins expressed by a particular cell, organism or tissue at a given time and under a specific set of environmental conditions will require developing new automated and high-speed methods for analyzing the protein content of cell lines. The proposed ECD method for ion traps will lead to accurate identification of protein structure including PTM sites. This diagnostic capability has the potential to provide systematic searches for biomarkers. Studies of cancer cell lines can reveal signatures of cancerous cells that can serve as biomarkers for actual diagnosis. The economic impacts in terms of increased productivity and decreased burden on the health care system are substantial.

* Information listed above is at the time of submission. *

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