Applying Automated Maximum Entropy Spectral Deconvolution for the Analysis of Complicated Protein LC/MS Datasets

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Scott J. Berger, Ignatius J. Kass, Kevin M. Millea, and John C. Gebler
Presented at: ABRF 2005; Association of Biomolecular Resource Facilities Annual Meeting; February 5-8; Savannah GA
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Analysis of proteins by electrospray ionization mass spectrometry is complicated by the need to deconvolute multiply charged m/z spectra to produce neutral masses for sample components. This deconvolution process becomes significantly more complicated when analyzing data from online LC/MS protein separations. TIC information can be used to identify regions of MS data for summation and deconvolution with well resolved protein mixtures, but the approach fails with more complex protein separations. In this poster we describe a methodology for automating mass spectral deconvolution of complicated LC/MS data sets. The resulting data is output in a tab-delimited text file, and can be represented with intuitive and visually informative displays. Proper selection of processing parameters permit accurate intact protein mass determination, and retention of chromatographic profiles of each component.

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