Exhaustive Cross-Linking Search with Protein Feedback

Improving the sensitivity of protein–protein interaction
detection and protein structure probing is a principal challenge in
cross-linking mass spectrometry (XL-MS) data analysis. In this paper,
we propose an exhaustive cross-linking search method with protein
feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts
an optimized α/β mass detection scheme and establishes
protein–peptide association during the identification of cross-linked
peptides. Existing major scoring functions can all benefit from the
ECL-PF workflow to a great extent. In comparisons using synthetic
data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher
sensitivity over standard techniques. In experiments using real data
sets, it also identified 65.6% more cross-link spectrum matches and
48.7% more unique cross-links.