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• W2012914294 abstract "Electron transfer dissociation (ETD) is increasingly becoming popular for high-throughput experiments especially in the identification of the labile post-translational modifications. Most search algorithms that are currently in use for querying MS/MS data against protein databases have been optimized on the basis of matching fragment ions derived from collision induced dissociation of peptides, which are dominated by b and y ions. However, electron transfer dissociation of peptides generates completely different types of fragments: c and z ions. The goal of our study was to test the ability of different search algorithms to handle data from this fragmentation method. We compared four MS/MS search algorithms (OMSSA, Mascot, Spectrum Mill, and X!Tandem) using approximately 170,000 spectra generated from a standard protein mix, as well as from complex proteomic samples which included a large number of phosphopeptides. Our analysis revealed (1) greater differences between algorithms than has been previously reported for CID data, (2) a significant charge state bias resulting in >60-fold difference in the numbers of matched doubly charged peptides, and (3) identification of 70% more peptides by the best performing algorithm than the algorithm identifying the least number of peptides. Our results indicate that the search engines for analyzing ETD derived MS/MS spectra are still in their early days and that multiple search engines could be used to reduce individual biases of algorithms." @default.
• W2012914294 created "2016-06-24" @default.
• W2012914294 creator A5024268602 @default.
• W2012914294 creator A5026244741 @default.
• W2012914294 creator A5067407395 @default.
• W2012914294 date "2009-07-29" @default.
• W2012914294 modified "2023-09-24" @default.
• W2012914294 title "Evaluation of Several MS/MS Search Algorithms for Analysis of Spectra Derived from Electron Transfer Dissociation Experiments" @default.
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• W2012914294 doi "https://doi.org/10.1021/ac9006107" @default.
• W2012914294 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/19639959" @default.
• W2012914294 hasPublicationYear "2009" @default.
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