Researchers built pyXLMS, a Python package and public web application designed to link crosslinking mass spectrometry search results directly to downstream analysis programs, Nature Communications reported on September 4, 2026. Crosslinking mass spectrometry identifies protein-protein interactions and maps protein structures in living cells. Connecting search engine outputs to subsequent biological interpretation previously required manual handling and specialized bioinformatics expertise.
The pyXLMS application accepts inputs from more than seven crosslink search engines, as well as the mzIdentML format maintained by the HUPO Proteomics Standards Initiative. The tool processes datasets internally, offering features for data aggregation, validation, annotation, filtering, and visualization. Once processed, datasets export directly into more than ten downstream analysis formats and tools. The researchers tested the software by re-analyzing a publicly available crosslink dataset across multiple search engines using a single unified workflow.
Micha J. Birklbauer and Viktoria Dorfer led the work at the University of Applied Sciences Upper Austria alongside colleagues Louise M. Buur, Sabrina Kaser, and Stephan Winkler. Team members also held affiliations with Johannes Kepler University Linz, the Institute of Molecular Pathology, the Institute of Molecular Biotechnology, and the Gregor Mendel Institute at the Vienna BioCenter. Martina A. Höllwarth, Eva Rauch, and Dennis Dannecker tested pyXLMS, while Melanie E. Birklbauer designed the software logo.
Funding for the project came from the Austrian Research Promotion Agency under grant 4795911, alongside the Vienna Science and Technology Fund, the Austrian Science Fund, and the European Union’s Horizon 2020 Marie Skłodowska-Curie grant number 956148. The authors submitted the peer-reviewed manuscript on January 7, 2026, and the journal accepted it on August 20, 2026 before publishing it under an open-access Creative Commons Attribution 4.0 International license.
