Abstract
A major challenge in proteomics is to fully identify and characterize posttranslational modification (PTM) patterns present at any given time in cells, tissues, and organisms. Currently, the most frequently used method for identifying PTMs is tandem mass spectrometry combined with searching a protein sequence database. Although, database searching has been highly successful for the identification of proteins, it has a number of significant drawbacks for identification of modifications. The user needs to specify all expected modifications, and the search engine needs to consider all possible combinations of these modifications for all peptide sequences. If several potential modifications are considered, the search can take much longer than the data acquisition, creating a bottleneck in high-throughput analysis. In addition, the many possible assignments that need to be tested increase the noise and require better quality data for confident identification of modifications. Here, we describe a method for identifying both known and unknown PTM using mass spectrometry that does not suffer from these problems. The method is based on the observation that, in many samples, peptides are usually present both with and without modifications. By identifying the unmodified peptide with conventional database searches, the modified species of the peptide can be identified by searching for peptides with common and similar fragments as the unmodified peptide. After identifying both the modified and unmodified peptide, the elemental composition of the modification can be deduced if the mass accuracy of the precursor ion is sufficiently high.
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Savitski, M.F., Savitski, M.M. (2010). Unbiased Detection of Posttranslational Modifications Using Mass Spectrometry. In: Fenyö, D. (eds) Computational Biology. Methods in Molecular Biology, vol 673. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-842-3_12
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DOI: https://doi.org/10.1007/978-1-60761-842-3_12
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