A Software for Top-Down Spectral Deconvolution and Protein Identification
UC San Diego researchers compared MS-Align+ with various tools for top-down protein identification on two data sets from Saccharomyces cerevisiae (SC) and Salmonella typhimurium (ST). The results demonstrate that MS-Align+ significantly increase the number of identified spectra as compared to MASCOT and OMSSA on both data sets. While MS-Align+ and ProSightPC have similar performance on the ST data set, MS-Align+ outperforms ProSightPC on the more complex SC data set.
UC San Diego researchers have developed MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications (PTMs). The first step in top-down spectral interpretation is usually spectral deconvolution, which converts a complex top-down spectrum to a list of monoisotopic masses (a deconvoluted spectrum). Every protein (possibly with modifications) can be scored against a top-down deconvoluted spectrum, resulting in a protein-spectrum-match (PrSM). MS-Align+ shares the spectral alignment approach with MS-TopDown, but greatly improves on speed, statistical analysis (providing E-values of PrSMs), and the number of identified PrSMs (e.g., by finding spectral alignments between spectra and truncated proteins).
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