A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes

Rebecca Beveridge, Johannes Stadlmann, Josef M. Penninger, Karl Mechtler

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)
22 Downloads (Pure)

Abstract

Crosslinking-mass spectrometry (XL-MS) serves to identify interaction sites between proteins. Numerous search engines for crosslink identification exist, but lack of ground truth samples containing known crosslinks has precluded their systematic validation. Here we report on XL-MS data arising from measuring synthetic peptide libraries that provide the unique benefit of knowing which identified crosslinks are true and which are false. The data are analysed with the most frequently used search engines and the results filtered to an estimated false discovery rate of 5%. We find that the actual false crosslink identification rates range from 2.4 to 32%, depending on the analysis strategy employed. Furthermore, the use of MS-cleavable crosslinkers does not reduce the false discovery rate compared to non-cleavable crosslinkers. We anticipate that the datasets acquired during this research will further drive optimisation and development of XL-MS search engines, thereby advancing our understanding of vital biological interactions.
Original languageEnglish
Article number742
Number of pages9
JournalNature Communications
Volume11
Issue number1
DOIs
Publication statusPublished - 6 Feb 2020

Keywords

  • chemical crosslinking
  • protein interactions
  • synthetic peptides

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