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Crystal-C: A Computational Tool for Refinement of Open Search Results

  • Hui-Yin Chang
    Hui-Yin Chang
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
  • Andy T. Kong
    Andy T. Kong
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
    More by Andy T. Kong
  • Felipe da Veiga Leprevost
    Felipe da Veiga Leprevost
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
  • Dmitry M. Avtonomov
    Dmitry M. Avtonomov
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
  • Sarah E. Haynes
    Sarah E. Haynes
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
  • , and 
  • Alexey I. Nesvizhskii*
    Alexey I. Nesvizhskii
    Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States
    Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States
    *Tel: +1-734-764-3516. Email: [email protected]
Cite this: J. Proteome Res. 2020, 19, 6, 2511–2515
Publication Date (Web):April 27, 2020
https://doi.org/10.1021/acs.jproteome.0c00119
Copyright © 2020 American Chemical Society

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    Abstract

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    Shotgun proteomics using liquid chromatography coupled to mass spectrometry (LC-MS) is commonly used to identify peptides containing post-translational modifications. With the emergence of fast database search tools such as MSFragger, the approach of enlarging precursor mass tolerances during the search (termed “open search”) has been increasingly used for comprehensive characterization of post-translational and chemical modifications of protein samples. However, not all mass shifts detected using the open search strategy represent true modifications, as artifacts exist from sources such as unaccounted missed cleavages or peptide co-fragmentation (chimeric MS/MS spectra). Here, we present Crystal-C, a computational tool that detects and removes such artifacts from open search results. Our analysis using Crystal-C shows that, in a typical shotgun proteomics data set, the number of such observations is relatively small. Nevertheless, removing these artifacts helps to simplify the interpretation of the mass shift histograms, which in turn should improve the ability of open search-based tools to detect potentially interesting mass shifts for follow-up investigation.

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    Cited By

    This article is cited by 13 publications.

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    13. Daniel J. Geiszler, Andy T. Kong, Dmitry M. Avtonomov, Fengchao Yu, Felipe da Veiga Leprevost, Alexey I. Nesvizhskii. PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results. Molecular & Cellular Proteomics 2021, 20 , 100018. https://doi.org/10.1074/mcp.TIR120.002216

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