Milestones towards smFRET Empirically-Restrained Structural Modeling of Conformations
Structural modeling using empirical spatial restraints is gaining slow yet steady populrity in the study of the ensemble structures of conformations. Bringing the Förster Resonance Energy Transfer (smFRET) ruler to the single-molecule level allows distinguishing different conformations according to specific inter-residue distances. Performing such single-molecule FRET (smFRET) experiments probing multiple pairs of residues provides enough spatial restraints for the structural modeling of the ensemble of structures that define a given conformation. It is therefore clear that the retrieval of accurate inter-residue distance information is of the utmost important. The structural assessment is based on the Förster relation between the efficiency of energy transfer between two dyes and the distance between them. It is known, however, that inter-dye distance fluctuations, on the timescale of the fluorescence lifetime (or shorter), can increase the observed FRET efficiency and thus give the impression of an overall decreased inter-dye distance. Although the information on diffusion-enhancement of FRET could in principle be retrieved from model fitting to fluorescence decays, in single-molecule fluorescence measurements fluorescence decays are too noisy to be accurately fitted with such complex models. Here we introduce Monte-Carlo diffusion-enhanced photon inference (MC-DEPI). MC-DEPI recolors photons of smFRET measurements taking into account dynamics of inter-dye distance fluctuations, multiple interconverting states and photoblinking. Using this approach, we show that the distance interpretation of smFRET experiments of even molecules as simple as doubly-labeled dsDNA is nontrivial and requires decoupling the effects of rapid inter-dye distance fluctuations on FRET in order to avoid systematic biases in the estimation of the inter-dye distance distribution. MC-DEPI can hence be used for the retrieval of accurate and unbiased distance information that is required for proper structural modeling.
Eitan Lerner ist Senior Lecturer am Department für Biologische Chemie der Hebrew University in Jerusalem und derzeit Visiting Fellow am CAS.
Ort und Anmeldung
2. August 2019, 15.30 Uhr: Center for NanoScience (CeNS), Schellingstraße 4 // Kleiner Physikhörsaal, 80799 München
6. August 2019, 17.15 Uhr: Biozentrum, Großhaderner Straße 2 // Raum B01.019, 82152 Planegg-Martinsried