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

Area of Science:

• Biochemistry
• Structural Biology
• Computational Biology

Background:

• Protein cross-linking mass spectrometry (CL-MS) is vital for identifying protein interactions and mapping protein complex structures.
• Advancements in CL-MS technologies have improved sensitivity and data generation, but analysis remains a bottleneck.
• Existing algorithms for cross-linked peptide identification lack user-friendly interfaces, hindering broader CL-MS adoption.

Purpose of the Study:

• To develop a user-friendly software suite, CLMSVault, for streamlined analysis and interpretation of CL-MS data.
• To integrate existing CL-MS algorithms and provide flexible, cross-platform data interpretation tools.
• To facilitate the visualization and quantification of cross-linking data for protein structure modeling.

Main Methods:

• Development of CLMSVault, a software suite integrating various CL-MS analysis algorithms.
• Implementation of tools for data filtering, comparison, and visualization of cross-linked peptides.
• Inclusion of a label-free quantification workflow and an embedded 3D viewer for mapping cross-links onto protein structures.

Main Results:

• CLMSVault successfully stores and combines information from different cross-linkers and search algorithms.
• The software provides intuitive filtering, comparison, and visualization capabilities for CL-MS data.
• Demonstrated application of CLMSVault for analyzing a Cdc34-ubiquitin protein complex, showcasing its utility.

Conclusions:

• CLMSVault addresses the practical bottleneck in CL-MS data analysis by providing an intuitive and flexible software solution.
• The suite enhances the interpretation of protein interaction and topology data derived from CL-MS.
• CLMSVault promotes broader adoption of CL-MS techniques in structural biology and proteomics research.