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LERLIC-MS/MS for In-depth Characterization and Quantification of Glutamine and Asparagine Deamidation in Shotgun Proteomics
Published on: April 9, 2017
Impact of Amidination on Peptide Fragmentation and Identification in Shotgun Proteomics
Sujun Li1, Aditi Dabir2, Santosh A Misal2
1School of Informatics and Computing, Indiana University , Bloomington, Indiana 47405, United States.
Abstract:
Peptide amidination labeling using S-methyl thioacetimidate (SMTA) is investigated in an attempt to increase the number and types of peptides that can be detected in a bottom-up proteomics experiment. This derivatization method affects the basicity of lysine residues and is shown here to significantly impact the idiosyncracies of peptide fragmentation and peptide detectability. The unique and highly reproducible fragmentation properties of SMTA-labeled peptides, such as the strong propensity for forming b1 fragment ions, can be further exploited to modify the scoring of peptide-spectrum pairs and improve peptide identification. To this end, we have developed a supervised postprocessing algorithm to exploit these characteristics of peptides labeled by SMTA. Our experiments show that although the overall number of identifications are similar, the SMTA modification enabled the detection of 16-26% peptides not previously observed in comparable CID/HCD tandem mass spectrometry experiments without SMTA labeling.
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