MS Annika: A New Cross-Linking Search Engine

Georg J. Pirklbauer, Christian E. Stieger, Manuel Matzinger, Stephan Winkler, Karl Mechtler, Viktoria Dorfer

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Cross-linking mass spectrometry (XL-MS) has become a powerful technique that enables insights into protein structures and protein interactions. The development of cleavable cross-linkers has further promoted XL-MS through search space reduction, thereby allowing for proteome-wide studies. These new analysis possibilities foster the development of new cross-linkers, which not every search engine can deal with out of the box. In addition, some search engines for XL-MS data also struggle with the validation of identified cross-linked peptides, that is, false discovery rate (FDR) estimation, as FDR calculation is hampered by the fact that not only one but two peptides in a single spectrum have to be correct. We here present our new search engine, MS Annika, which can identify cross-linked peptides in MS2 spectra from a wide variety of cleavable cross-linkers. We show that MS Annika provides realistic estimates of FDRs without the need of arbitrary score cutoffs, being able to provide on average 44% more identifications at a similar or better true FDR than comparable tools. In addition, MS Annika can be used on proteome-wide studies due to fast, parallelized processing and provides a way to visualize the identified cross-links in protein 3D structures.

Original languageEnglish
Pages (from-to)2560-2569
Number of pages10
JournalJournal of Proteome Research
Volume20
Issue number5
DOIs
Publication statusPublished - 7 May 2021

Keywords

  • bioinformatics
  • cross-linking
  • MS/MS
  • PPI
  • protein-protein-interaction
  • search engine
  • tandem mass spectrometry
  • XL-MS
  • Cross-Linking Reagents
  • Peptides
  • Proteome
  • Mass Spectrometry
  • Search Engine

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