Evidence map›Paper›PMID 42517710›Full record

ArticleProtein science : a publication of the Protein Society2026

Scalable discovery of homomeric protein-protein interactions from cross-linking mass spectrometry data with CLAUDIO 2.0.

Tobias Löser, Alexander Röhl, Markus Baier, Andrei Lupas, Oliver Kohlbacher, Hadeer Elhabashy

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tobias LöserApplied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
Alexander RöhlApplied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
Markus BaierApplied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
Andrei LupasDepartment of Protein Evolution, Max-Planck-Institute for Biology, Tübingen, Germany.
Oliver KohlbacherApplied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
Hadeer ElhabashyDepartment of Protein Evolution, Max-Planck-Institute for Biology, Tübingen, Germany.ORCID 0000-0002-4677-7064

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cross-linking mass spectrometry (XL-MS) is a powerful biochemical approach for residue-level characterization of protein structures and interactions under near-native conditions. The growing scale of XL-MS datasets demands scalable analysis pipelines that capture signals often overlooked in conventional workflows, including homomeric interactions. Here, we present CLAUDIO 2.0, a next-generation framework for structural analysis of large-scale XL-MS data. CLAUDIO 2.0 identifies homomeric interactions using overlapping peptide sequences and structural evaluation. Our optimized workflow improves computational efficiency, enabling scalable analysis and expanding structural coverage. Applied to a human mitochondrial XL-MS dataset, CLAUDIO 2.0 evaluates over 75% of cross-links using available high-confidence structural models, reduces runtime by over 95% (averaging 5 s per cross-link) compared to its predecessor, and identifies 205 proteins with homomeric interaction signals. CLAUDIO 2.0 is freely available under the MIT License at (https://github.com/ElhabashyLab/CLAUDIO) and as a web server at (https://elhabashylab.org/claudio), providing an accessible platform for scalable structural proteomics.

Indexed as

Cross-Linking ReagentsMass SpectrometryProtein Interaction MappingProteinsSoftwareHumansModels, MolecularCross-Linking ReagentsProteinscross‐linking mass spectrometryhomomeric interaction

Identifiers

PMID42517710
PMCPMC13410943

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.