The discovery of unanticipated protein modifications is one of the most challenging problems in proteomics. Whereas widely used algorithms such as Sequest and Mascot enable mapping of modifications when the mass and amino acid specificity are known, unexpected modifications cannot be identified with these tools. We have developed an algorithm and software called P-Mod, which enables discovery and sequence mapping of modifications to target proteins known to be represented in the analysis or identified by Sequest. P-Mod matches MS/MS spectra to peptide sequences in a search list. For spectra of modified peptides, P-Mod calculates mass differences between search peptide sequences and MS/MS precursors and localizes the mass shift to a sequence position in the peptide. Because modifications are detected as mass shifts, P-Mod does not require the user to guess at masses or sequence locations of modifications. P-Mod uses extreme value statistics to assign p value estimates to sequence-to-spectrum matches. The reported p values are scaled to account for the number of comparisons, so that error rates do not increase with the expanded search lists that result from incorporating potential peptide modifications. Combination of P-Mod searches from multiple LC-MS/MS analyses and multiple samples revealed previously unreported BSA modifications, including a novel decarboxymethylation or D-->G substitution at position 579 of the protein. P-Mod can serve a unique role in the identification of protein modifications both from exogenous and endogenous sources and may be useful for identifying modified protein forms as biomarkers for toxicity and disease processes.
A pattern recognition algorithm called SALSA (scoring algorithm for spectral analysis) has been developed to rapidly screen large numbers of peptide MS-MS spectra for fragmentation characteristics indicative of specific peptide modifications. The algorithm facilitates sensitive and specific detection of modified peptides at low abundance in an enzymatic protein digest. SALSA can simultaneously score multiple user-specified search criteria, including product ions, neutral losses, charged losses, and ion pairs that are diagnostic of specific peptide modifications. Application of SALSA to the detection of peptide adducts of the electrophiles dehydromonocrotaline, benzoquinone, and iodoacetic acid permitted their detection in a complex tryptic peptide digest mixture. SALSA provides superior detection of adducted peptides compared to conventional tandem MS precursor ion or neutral loss scans.
We have developed a pattern recognition algorithm called SALSA (scoring algorithm for spectral analysis) for the detection of specific features in tandem MS (MS-MS) spectra. Application of the SALSA algorithm to the detection of peptide MS-MS ion series enables identification of MS-MS spectra displaying characteristics of specific peptide sequences. SALSA analysis scores MS-MS spectra based on correspondence between theoretical ion series for peptide sequence motifs and actual MS-MS product ion series, regardless of their absolute positions on the m/z axis. Analyses of tryptic digests of bovine serum albumin (BSA) by LC-MS-MS followed by SALSA analysis detected MS-MS spectra for both unmodified and multiple modified forms of several BSA tryptic peptides. SALSA analysis of MS-MS data from mixtures of BSA and human serum albumin (HSA) tryptic digests indicated that ion series searches with BSA peptide sequence motifs identified MS-MS spectra for both BSA and closely related HSA peptides. Optimal discrimination between MS-MS spectra of variant peptide forms is achieved when the SALSA search criteria are optimized to the target peptide. Application of SALSA to LC-MS-MS proteome analysis will facilitate the characterization of modified and sequence variant proteins.
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