ArticleNature communications2020
A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- To cleave or not to cleave: a systemic evaluation of DSS versus DSSO for cross-linking mass spectrometry analysis.Molecular systems biology · 2026Article
- Towards a universal cross-linking mass spectrometry approach for protein structure analysis with homo-bi-functional photo-activatable cross-linkers.Communications biology · 2025Article
- Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study protein interactions and structures.Nature communications · 2025Article
- Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex.Communications chemistry · 2024Article
- Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics.Nature methods · 2024Article
- High-Performance Workflow for Identifying Site-Specific Crosslinks Originating from a Genetically Incorporated, Photoreactive Amino Acid.Journal of proteome research · 2024Article
- Denaturing mass photometry for rapid optimization of chemical protein-protein cross-linking reactions.Nature communications · 2024Article
- Article
- New advances in cross-linking mass spectrometry toward structural systems biology.Current opinion in chemical biology · 2023Review
- ECL 3.0: a sensitive peptide identification tool for cross-linking mass spectrometry data analysis.BMC bioinformatics · 2023Article
- MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity.Journal of proteome research · 2023Article
- High-Sensitivity Proteome-Scale Searches for Crosslinked Peptides Using CRIMP 2.0.Analytical chemistry · 2023Article
- Cross-linking mass spectrometry for mapping protein complex topologies in situ.Essays in biochemistry · 2023Article
- Real-Time Library Search Increases Cross-Link Identification Depth across All Levels of Sample Complexity.Analytical chemistry · 2023Article
- Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline.Journal of proteome research · 2023Article
- The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data.Journal of proteome research · 2023Article
- Mono- and Intralink Filter (Mi-Filter) To Reduce False Identifications in Cross-Linking Mass Spectrometry Data.Analytical chemistry · 2022Article
- Deep Proteome Profiling with Reduced Carryover Using Superficially Porous Microfabricated nanoLC Columns.Analytical chemistry · 2022Article
- Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.Nature communications · 2022Article
- Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry.Chemical reviews · 2022Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Crosslinking-mass spectrometry (XL-MS) serves to identify interaction sites between proteins. Numerous search engines for crosslink identification exist, but lack of ground truth samples containing known crosslinks has precluded their systematic validation. Here we report on XL-MS data arising from measuring synthetic peptide libraries that provide the unique benefit of knowing which identified crosslinks are true and which are false. The data are analysed with the most frequently used search engines and the results filtered to an estimated false discovery rate of 5%. We find that the actual false crosslink identification rates range from 2.4 to 32%, depending on the analysis strategy employed. Furthermore, the use of MS-cleavable crosslinkers does not reduce the false discovery rate compared to non-cleavable crosslinkers. We anticipate that the datasets acquired during this research will further drive optimisation and development of XL-MS search engines, thereby advancing our understanding of vital biological interactions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.