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A graph-based filtering method for top-down mass spectral identification.

Runmin Yang1, Daming Zhu2

  • 1School of Computer Science and Technology, Shandong University, 1500, Shun Hua Lu, Jinan, 250101, China.

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|September 27, 2018
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Summary
This summary is machine-generated.

A new spectrum graph matching (SGM) method speeds up proteoform identification in top-down mass spectrometry. This approach enhances sensitivity and increases the number of identified proteoform spectrum-matches compared to tag-based methods.

Keywords:
Filtering algorithmMass spectrometrySpectrum graph

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Top-down tandem mass spectrometry relies on database searching for proteoform identification.
  • Identifying proteoforms with post-translational modifications (PTMs) or mutations is time-consuming due to extensive database comparisons.
  • Efficient filtering algorithms are crucial for accelerating database searches in proteoform identification.

Purpose of the Study:

  • To develop a novel and efficient filtering method for top-down mass spectral identification.
  • To improve the speed and sensitivity of proteoform identification in large-scale proteomics studies.
  • To simplify data processing by circumventing traditional tag-based preprocessing steps.

Main Methods:

  • A spectrum graph matching (SGM) based filtering method was proposed.
  • Subspectra from query spectra are used to generate spectrum graphs.
  • These graphs are searched against a protein database to identify candidate proteoforms.

Main Results:

  • The SGM filtering method demonstrates high sensitivity in protein sequence filtration.
  • It effectively bypasses the need for preprocessing steps required by sequence tag and gaped tag methods.
  • Performance was evaluated on Escherichia coli and MCF-7 cell line datasets.

Conclusions:

  • The SGM method significantly enhances the efficiency of proteoform identification.
  • When integrated with spectral alignment, SGM increases the number of identified proteoform spectrum-matches.
  • This approach offers a more streamlined and sensitive alternative to tag-based filtering methods in top-down mass spectrometry.