Algorithmic Determinations of Disulfide Bonding Patterns

Description:

Disulfide bonds play an important role in understanding protein folding, evolution, and in studies related to determining structural and functional properties of specific proteins. At the state-of-the-art, liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) can produce spectra of the peptides in a protein that are putatively joined by a disulfide bond. In this setting, efficient algorithms are required for matching the theoretical mass spaces of all possible bonded peptide fragments to the experimentally derived spectra to determine the number and location of the disulfide bonds. The algorithmic solution must also account for issues associated with interpreting experimental data from mass spectrometry, such as noise, isotopic variation, neutral loss, and charge state uncertainty. 

The research under this project seeks to develop algorithms to address the above challenges. Our work is being conducted in collaboration with the Mass Spectrometry Laboratory of the department of Chemistry and Biochemistry at SFSU. This research is supported in part by the National Science Foundation (grants IIS-0644418 and CHE-0619163), the National Institute of Health (P20MD000262) and a grant from the Center for Computing in Life Sciences of SFSU.

Publications

• R. Singh "A Review of Algorithmic Techniques for Disulfide-Bond Determination", Briefings in Functional Genomics and Proteomics, 2008, Vol. 7, pp. 157-172, 2008. Available online at: http://bfgp.oxfordjournals.org/cgi/content/abstract/7/2/157

 

• T. Lee and R. Singh, Comparative Analysis of Disulfide Bond Determination Using Computational-Predictive Methods and Mass Spectrometry-Based Algorithmic Analysis, International Conference on Bioinformatics Research and Development (BIRD), Communications in Computer and Information Science, Vol. 13, pp. 140-153, Springer Verlag, 2008
 
• T. Lee, R. Singh, R. Yen, and B. Macher, An Algorithmic Approach to Automated High-Throughput Identification of Disulfide Connectivity in Proteins Using Tandem Mass Spectrometry, Computational Systems Bioinformatics Conference (CSB), pp. 41-51, 2007
 
• T. Lee, R. Singh, R. Yen, and B. Macher, MS2DB: A Mass-Based Hashing Algorithm for the Identification of Disulfide Linkage Patterns in Protein Utilizing Mass Spectrometric Data, IEEE International Symposium on Computer-Based Medical Systems (CBMS), pp. 397-402, 2007
 
• T. Lee, R. Singh, R. Yen, and B. Macher, MS2DB: An Algorithmic Approach to Determine Disulfide Linkage Patterns in Proteins by Utilizing Tandem Mass Spectrometric Data, IEEE International Symposium on Computer-Based Medical Systems (CBMS), pp. 947-952, 2006

Software

• Please go to http://tintin.sfsu.edu:33191/ms2db/

See Also

• Molecular Query Retrieval
 
• Designing Systems for Molecular Query-Retrieval and Molecular Informatics