A Roadmap for Improving Reliability and Data Sharing in Crosslinking Mass Spectrometry

Juri Rappsilber*, James Bruce, Colin Combe, Stephen Fried, Andrea Graziadei, Albert J R Heck, Claudio Iacobucci, Alexander Leitner, Karl Mechtler, Petr Novak, Francis O'Reilly, David C Schriemer, Andrea Sinz, Florian Stengel, Konstantinos Thalassinos

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Crosslinking Mass Spectrometry (MS) can uncover protein-protein interactions and provide structural information on proteins in their native cellular environments. Despite its promise, the field remains hampered by inconsistent data formats, variable approaches to error control, and insufficient interoperability with global data repositories. Recent advances, especially in false discovery rate (FDR) models and pipeline benchmarking, show that Crosslinking MS data can reach a reliability that matches the demand of integrative structural biology. To drive meaningful progress, however, the community must agree on error estimation, open data formats, and streamlined repository submissions. This perspective highlights these challenges, clarifies remaining barriers, and frames practical next steps. Successful field harmonisation will enhance the acceptance of Crosslinking MS in the broader biological community and is critical for the dependability of the data, no matter where it is produced.

Original languageEnglish
Article number101024
JournalMolecular and Cellular Proteomics
DOIs
Publication statusE-pub ahead of print - 26 Jun 2025

Bibliographical note

Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.

Fingerprint

Dive into the research topics of 'A Roadmap for Improving Reliability and Data Sharing in Crosslinking Mass Spectrometry'. Together they form a unique fingerprint.

Cite this