XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data

Area of Science:

• Biochemistry
• Structural Biology
• Bioinformatics

Background:

• Chemical cross-linking with mass spectrometry (XL-MS) is a high-throughput method for determining protein structure and interactions.
• Existing XL-MS studies generate vast amounts of data, but a lack of integrated tools hinders comprehensive analysis.
• Effective compilation and network/structural knowledge access for large-scale XL-MS data remain challenging.

Purpose of the Study:

• To present XLinkDB 2.0, a novel integrated platform for analyzing XL-MS data.
• To provide tools for network analysis, Protein Data Bank queries, and protein structure modeling.
• To enable holistic analysis of XL-MS protein interaction data regardless of the cross-linker or analytical system.

Main Methods:

• Integration of network analysis tools.
• Incorporation of Protein Data Bank (PDB) querying capabilities.
• Implementation of predicted and docked protein structure modeling.

Main Results:

• XLinkDB 2.0 offers a unified approach to XL-MS data analysis.
• The platform supports comprehensive analysis without limitations on cross-linking agents or systems.
• Facilitates the exploration of protein structural information and protein-protein interactions.

Conclusions:

• XLinkDB 2.0 addresses the need for effective data compilation and knowledge access in large-scale XL-MS studies.
• The integrated approach allows for a holistic understanding of protein interaction networks.
• This tool enhances the utility of XL-MS data for structural biology and systems biology research.