Scalable discovery of homomeric protein–protein interactions from cross‐linking mass spectrometry data with <scp>CLAUDIO</scp> 2.0

Cross-linking mass spectrometry (XL-MS) is a powerful biochemical approach for residue-level characterization of protein structures and interactions under near-native conditions. The growing scale of XL-MS datasets demands scalable analysis pipelines that capture signals often overlooked in conventional workflows, including homomeric interactions. Here, we present CLAUDIO 2.0, a next-generation framework for structural analysis of large-scale XL-MS data. CLAUDIO 2.0 identifies homomeric interactions using overlapping peptide sequences and structural evaluation. Our optimized workflow improves computational efficiency, enabling scalable analysis and expanding structural coverage. Applied to a human mitochondrial XL-MS dataset, CLAUDIO 2.0 evaluates over 75% of cross-links using available high-confidence structural models, reduces runtime by over 95% (averaging 5 s per cross-link) compared to its predecessor, and identifies 205 proteins with homomeric interaction signals. CLAUDIO 2.0 is freely available under the MIT License at (https://github.com/ElhabashyLab/CLAUDIO) and as a web server at (https://elhabashylab.org/claudio), providing an accessible platform for scalable structural proteomics.