Labelizer: systematic selection of protein residues for covalent fluorophore labeling

dc.contributor.authorGebhardt, Christian
dc.contributor.authorBawidamann, Pascal
dc.contributor.authorSpring, Anna-Katharina
dc.contributor.authorSchenk, Robin
dc.contributor.authorSchütze, Konstantin
dc.contributor.authorMoya Muñoz, Gabriel G.
dc.contributor.authorWendler, Nicolas D.
dc.contributor.authorGriffith, Douglas A.
dc.contributor.authorLipfert, Jan
dc.contributor.authorCordes, Thorben
dc.date.accessioned2025-06-18T13:04:24Z
dc.date.available2025-06-18T13:04:24Z
dc.date.issued2025-05-04
dc.description.abstractAttaching 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.en
dc.identifier.urihttp://hdl.handle.net/2003/43760
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-25534
dc.language.isoen
dc.relation.ispartofseriesNature communications; 16
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc540
dc.titleLabelizer: systematic selection of protein residues for covalent fluorophore labelingen
dc.typeText
dc.type.publicationtypeArticle
dcterms.accessRightsopen access
eldorado.secondarypublicationtrue
eldorado.secondarypublication.primarycitationGebhardt, C., Bawidamann, P., Spring, A.-K., Schenk, R., Schütze, K., Moya Muñoz, G. G., Wendler, N. D., Griffith, D. A., Lipfert, J., & Cordes, T. (2025). Labelizer: systematic selection of protein residues for covalent fluorophore labeling. Nature Communications, 16, Article 4147. https://doi.org/10.1038/s41467-025-58602-y
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1038/s41467-025-58602-y

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