MS Annika: A New Cross-Linking Search Engine

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.