Evidence map›Paper›PMID 40319045›Full record

ArticleNature communications2025

Labelizer: systematic selection of protein residues for covalent fluorophore labeling.

Christian Gebhardt, Pascal Bawidamann, Anna-Katharina Spring, Robin Schenk, Konstantin Schütze, Gabriel G Moya Muñoz, Nicolas D Wendler, Douglas A Griffith, Jan Lipfert, Thorben Cordes

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Christian GebhardtPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany. gebhardt.christian@gmx.net.ORCID http://orcid.org/0000-0002-5834-6579
Pascal BawidamannPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.
Anna-Katharina SpringPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.
Robin SchenkKlinikum rechts der Isar, Technische Universität München, Klinik und Poliklinik für Innere Medizin II, München, Germany.ORCID http://orcid.org/0000-0001-6823-8128
Konstantin SchützePhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.ORCID http://orcid.org/0000-0002-3957-412X
Gabriel G Moya MuñozPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.ORCID http://orcid.org/0000-0003-2797-2005
Nicolas D WendlerPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.ORCID http://orcid.org/0000-0002-5436-3929
Douglas A GriffithPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany.
Jan LipfertDepartment of Physics and Center for NanoScience, Ludwig-Maximilians-Universität München, Amalienstr. 54, München, Germany. j.lipfert@uu.nl.ORCID http://orcid.org/0000-0003-3613-7896
Thorben CordesPhysical and Synthetic Biology, Faculty of Biology, Ludwig-Maximilians-Universität München, Großhadernerstr. 2-4, Planegg-Martinsried, Germany. thorben.cordes@tu-dortmund.de.ORCID http://orcid.org/0000-0002-8598-5499

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attaching fluorescent dyes to biomolecules is essential for assays in biology, biochemistry, biophysics, biomedicine and imaging. A systematic approach for the selection of suitable labeling sites in macromolecules, particularly proteins, is missing. We present a quantitative strategy to identify such protein residues using a naïve Bayes classifier. Analysis of >100 proteins with ~400 successfully labeled residues allows to identify four parameters, which can rank residues via a single metric (the label score). The approach is tested and benchmarked by inspection of literature data and experiments on the expression level, degree of labelling, and success in FRET assays of different bacterial substrate binding proteins. With the paper, we provide a python package and webserver ( https://labelizer.bio.lmu.de/ ), that performs an analysis of a pdb-structure (or model), label score calculation, and FRET assay scoring. The approach can facilitate to build up a central open-access database to continuously refine the label-site selection in proteins.

Indexed as

Fluorescent DyesProteinsSoftwareStaining and LabelingBayes TheoremDatabases, ProteinFluorescence Resonance Energy TransferFluorescent DyesProteins

Identifiers

PMID40319045
PMCPMC12049551

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.