Accurate Retention Time Prediction Based on Monolinked Peptide Information to Confidently Identify Cross-Linked Peptides

J Am Soc Mass Spectrom. 2021 Sep 1;32(9):2410-2416. doi: 10.1021/jasms.1c00120. Epub 2021 Jul 28.

Abstract

Cross-linking mass spectrometry methods have not been successfully applied to protein-protein interaction discovery at a proteome-wide level mainly due to the computation complexity (O (n2)) issue. In a previous report, we proposed a decision tree searching strategy (DTSS), which can reduce complexity by orders of magnitude. In this study, we further found that the monolinked peptides carry out the information on the retention time of the corresponding cross-linked pairs; therefore, the retention time of cross-linked peptide pairs can be predicted accurately. By utilizing the retention time as an extra filter, the false positive rate can be reduced by around 86% with a sensitivity loss of 10%. The method combined with DTSS (T-DTSS) not only benefits improving identification confidence but also leads to lower cutoff scores and facilitates substantially increasing inter-cross-link identification. T-DTSS was successfully applied to the identification of inter-cross-links obtained from Escherichia coli cell lysate cross-linked by a newly synthesized enrichable cross-linker, pDSBE. The approach can be applicable to both cleavable and noncleavable methods.

Keywords: cross-linking mass spectrometry; identification; monolinked peptides; retention time prediction.

MeSH terms

  • Cross-Linking Reagents / chemistry*
  • Databases, Protein*
  • Decision Trees
  • Escherichia coli / chemistry
  • Escherichia coli / metabolism
  • Mass Spectrometry / methods*
  • Organophosphonates / chemistry
  • Peptides* / analysis
  • Peptides* / chemistry
  • Protein Interaction Maps
  • Proteomics

Substances

  • Cross-Linking Reagents
  • Organophosphonates
  • Peptides