Single molecule Förster resonance energy transfer (smFRET) is a popular tool to study biological systems that undergo topological transitions on the nanometer scale. smFRET experiments typically require recording of long smFRET trajectories and subsequent statistical analysis to extract parameters such as the states’ lifetimes. Alternatively, analysis of probability distributions exploits the shapes of smFRET distributions at well chosen exposure times and hence works without the acquisition of time traces. Here, we describe a variant that utilizes statistical tests to compare experimental datasets with Monte Carlo simulations. For a given model, parameters are varied to cover the full realistic parameter space. As output, the method yields p-values which quantify the likelihood for each parameter setting to be consistent with the experimental data. The method provides suitable results even if the actual lifetimes differ by an order of magnitude. We also demonstrated the robustness of the method to inaccurately determine input parameters. As proof of concept, the new method was applied to the determination of transition rate constants for Holliday junctions.
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28 March 2018
Research Article|
February 07 2018
Kinetic analysis of single molecule FRET transitions without trajectories
Special Collection:
Single Molecule Biophysics
Lukas Schrangl;
Lukas Schrangl
1
Institute of Applied Physics, TU Wien
, Wiedner Hauptstraße 8–10, 1040 Wien, Vienna, Austria
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Janett Göhring;
Janett Göhring
2
Institute for Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna
, Lazarettgasse 19, 1090 Wien, Vienna, Austria
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Gerhard J. Schütz
Gerhard J. Schütz
a)
1
Institute of Applied Physics, TU Wien
, Wiedner Hauptstraße 8–10, 1040 Wien, Vienna, Austria
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J. Chem. Phys. 148, 123328 (2018)
Article history
Received:
September 21 2017
Accepted:
January 22 2018
Citation
Lukas Schrangl, Janett Göhring, Gerhard J. Schütz; Kinetic analysis of single molecule FRET transitions without trajectories. J. Chem. Phys. 28 March 2018; 148 (12): 123328. https://doi.org/10.1063/1.5006038
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