NuXLApp : Interactive data analysis and visualization for protein‐nucleic acid crosslinking mass spectrometry
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/.
Authors
- Sergei A. Moshkovskii (ORCID: https://orcid.org/0000-0003-1697-9201)
- Timo T. Sachsenberg (ORCID: https://orcid.org/0000-0002-2833-6070)
- Oliver Kohlbacher (ORCID: https://orcid.org/0000-0003-1739-4598)
- Arslan Siraj (ORCID: https://orcid.org/0009-0006-5748-0027)
- Henning Urlaub (ORCID: https://orcid.org/0000-0003-1837-5233)
- Tom David Müller (ORCID: https://orcid.org/0000-0003-0118-9434)
Institutions
- Universitätsklinikum Tübingen (DE)
- Universitätsmedizin Göttingen (DE)
- Max Planck Institute for Biophysical Chemistry (DE)
- University of Göttingen (DE)
- University of Tübingen (DE)
Publication Details
- Journal
- Protein Science
- Published
- 2026-10-15
- DOI
- https://doi.org/10.1002/pro.70820
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00