Abstract
Single-molecule Forster resonance energy transfer (FRET) is a powerful tool to study conformational dynamics of biomolecules. Using solution-based single-pair FRET by burst analysis, conformational heterogeneities and fluctuations of fluorescently labeled proteins or nucleic acids can be studied by monitoring a single distance at a time. Three-color FRET is sensitive to three distances simultaneously and can thus elucidate complex coordinated motions within single molecules. While three-color FRET has been applied on the single-molecule level before, a detailed quantitative description of the obtained FRET efficiency distributions is still missing. Direct interpretation of three-color FRET data is additionally complicated by an increased shot noise contribution when converting photon counts to FRET efficiencies. However, to address the question of coordinated motion, it is of special interest to extract information about the underlying distance heterogeneity, which is not easily extracted from the FRET efficiency histograms directly. Here, we present three-color photon distribution analysis (3C-PDA), a method to extract distributions of interdye distances from three- color FRET measurements. We present a model for diffusion-based three-color FRET experiments and apply Bayesian inference to extract information about the physically relevant distance heterogeneity in the sample. The approach is verified using simulated data sets and experimentally applied to triple-labeled DNA duplexes. Finally, three-color FRET experiments on the Hsp70 chaperone BiP reveal conformational coordinated changes between individual domains. The possibility to address the co-occurrence of intramolecular distances makes 3C-PDA a powerful method to study the coordination of domain motions within biomolecules undergoing conformational dynamics.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Chemie und Pharmazie > Department Chemie |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 540 Chemie |
ISSN: | 1520-6106 |
Sprache: | Englisch |
Dokumenten ID: | 83331 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 15:07 |
Letzte Änderungen: | 15. Dez. 2021, 15:07 |