Conference proceeding
MS2DB: An algorithmic approach to determine disulfide linkage patterns in proteins by utilizing tandem mass spectrometric data
19TH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, Vol.2006, pp.947-952
IEEE International Symposium on Computer-Based Medical Systems
01/01/2006
DOI: 10.1109/CBMS.2006.119
Abstract
Determining the number and location of disulfide bonds within a protein provide valuable insight into the protein's three-dimensional structure. Purely computational methods that predict the bonded cysteine pairings given a protein's primary structure have limitations in both prediction correctness and the number of bonds that can be predicted. Our approach utilizes tandem mass spectrometric (MS/MS) experimental procedures that produce spectra of protein fragments joined by a disulfide bond This allows the limitations in correctness and scaling to be overcome. The algorithmic problem then becomes how to match a theoretical mass space of all possible bonded fragments against the MS/MS data. In our algorithm, which we call the Indexed approach, the regions of the mass space that contain masses comparable to the MS/MS spectrum masses are located before the match is determined We have developed a software package, MS2DB, which implements this approach. A performance study shows that the Indexed approach determines disulfide bond linkage patterns both correctly and efficiently.
Details
- Title: Subtitle
- MS2DB: An algorithmic approach to determine disulfide linkage patterns in proteins by utilizing tandem mass spectrometric data
- Creators
- Timothy Lee - San Francisco State UniversityRahul Singh - San Francisco State UniversityTen-Yang Yen - San Francisco State UniversityBruce Macher - San Francisco State University
- Contributors
- D J Lee (Editor)B Nutter (Editor)S Antani (Editor)S Mitra (Editor)J Archibald (Editor)
- Resource Type
- Conference proceeding
- Publication Details
- 19TH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, Vol.2006, pp.947-952
- Publisher
- IEEE
- Series
- IEEE International Symposium on Computer-Based Medical Systems
- DOI
- 10.1109/CBMS.2006.119
- ISSN
- 2372-9198
- eISSN
- 2372-9198
- Number of pages
- 2
- Grant note
- Center for Computing for Life Sciences at San Francisco State University
- Language
- English
- Date published
- 01/01/2006
- Academic Unit
- Computer Science
- Record Identifier
- 9984446521702771
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