Protein-nucleic acid (protein-Nu) interactions are crucial for many cellular processes and biological functions. Crosslinking mass spectrometry (XL-MS) has emerged as a powerful method for identifying these interactions. However, the analysis of protein-Nu XL-MS data requires an integrated workflow from raw data processing to results inspection and validation. Existing workflows for protein-Nu XL-MS often require switching between tools and considerable manual processing. Here, we introduce NuXLApp, an interactive web-based application for data processing and results visualization in protein-Nu XL-MS studies. NuXLApp integrates the protein-Nu crosslink search engine "NuXL," machine-learning models for peptide property prediction, and interactive result visualization within a reproducible workflow. It enables rapid validation of false discovery rate-controlled crosslink spectrum match-level identifications and facilitates collaboration and intuitive exploration of experimental results. In addition, NuXLApp generates a spectral library from identified protein-Nu crosslinks to enable quantitative analysis of crosslinks using data-independent acquisition (DIA). NuXLApp supports discovery-driven identification of protein-nucleic acid crosslinks and enables DIA-based follow-up experiments for their quantitative analysis. NuXLApp is open-source and available via the OpenMS WebApps platform at https://nuxl.webapps.openms.de/.
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Siraj et al. (2026) studied this question.
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