CLMSVault: A Software Suite for Protein Cross-Linking Mass-Spectrometry Data Analysis and Visualization

Protein cross-linking mass spectrometry
(CL–MS) enables
the sensitive detection of protein interactions and the inference
of protein complex topology. The detection of chemical cross-links
between protein residues can identify intra- and interprotein contact
sites or provide physical constraints for molecular modeling of protein
structure. Recent innovations in cross-linker design, sample preparation,
mass spectrometry, and software tools have significantly improved
CL–MS approaches. Although a number of algorithms now exist
for the identification of cross-linked peptides from mass spectral
data, a dearth of user-friendly analysis tools represent a practical
bottleneck to the broad adoption of the approach. To facilitate the
analysis of CL–MS data, we developed CLMSVault, a software
suite designed to leverage existing CL–MS algorithms and provide
intuitive and flexible tools for cross-platform data interpretation.
CLMSVault stores and combines complementary information obtained from
different cross-linkers and search algorithms. CLMSVault provides
filtering, comparison, and visualization tools to support CL–MS
analyses and includes a workflow for label-free quantification of
cross-linked peptides. An embedded 3D viewer enables the visualization
of quantitative data and the mapping of cross-linked sites onto PDB
structural models. We demonstrate the application of CLMSVault for
the analysis of a noncovalent Cdc34–ubiquitin protein complex
cross-linked under different conditions. CLMSVault is open-source
software (available at https://gitlab.com/courcelm/clmsvault.git), and a live demo is available at http://democlmsvault.tyerslab.com/.