Algorithm for Mining MS-MS Spectra to Detect Specific Chemical Species in Complex Mixtures

University of Arizona
posted on 10/19/2009

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Background: Mass spectrometry (MS) is one of the most widely used techniques in chemistry.  Its enormous utility and is derived from its speed and convenience and it is especially useful for high-throughput analysis of proteins. With appropriate automation, the data collection and sample preparation required for MS becomes trivial for routine samples and the speed of a research project is determined by the amount of time it takes to interpret the enormous amount of data generated.  Automated algorithms exist that allow computers to quickly and accurately interpret various kinds of MS data. These have found particular utility in the rapid identification of proteins.  The chemical properties of proteins and peptides provide both challenges and opportunities for the practice of MS. The modular nature of amino acids joined by peptide bonds to form proteins facilitates their automated identification by MS but the process is complicated by the existence of post-translational modifications and splice variants.  This technology comprises a method for the automated identification of proteins and peptides that may include post-translational modifications and splice variants.

Applications:

*The identification of proteins and peptides from their mass spectra.

Advantages:

*The technique is rapid and automated making it ideal for high-throughput projects.

The Technology: The system consists of an algorithm which compares spectra from unknown samples to known spectra stored in a database.  Each potential match is assigned a score based on its similarity and possible matches are ranked.

Patent: US 7,158,862 Jan. 2, 2007