Protein folding studied by single-molecule FRET

Abstract

A complete understanding of a protein-folding mechanism requires description of the distribution of microscopic pathways that connect the folded and unfolded states. This distribution can, in principle, be described by computer simulations and theoretical models of protein folding, but is hidden in conventional experiments on large ensembles of molecules because only average properties are measured. A long-term goal of single-molecule fluorescence studies is to time-resolve the structural events as individual molecules make transitions between folded and unfolded states. Although such studies are still in their infancy, the work till now shows great promise and has already produced novel and important information on current issues in protein folding that has been impossible or difficult to obtain from ensemble measurements.

Figure 1

Two-state folding dynamics of an individual protein molecule illustrated as a diffusive process on a two-dimensional free energy surface (left) with a corresponding equilibrium folding/unfolding trajectory (white). An intramolecular distance (corresponding to the distance between a donor and an acceptor fluorophore in a single molecule FRET experiment) is plotted as a function of time (right), showing rapid jumps between folded and unfolded state. An ultimate goal of single molecule experiments is to time-resolve these transitions (expanded scale, top right).

Figure 2

Overview of instrumentation and data reduction in confocal single molecule spectroscopy. The scheme on the right illustrates the main components of a 4-channel confocal single molecule instrument, such as the one commercially available [85], that collects fluorescence photons separated by polarization and wavelength and records their individual arrival times. (a) Sample of a trajectory of detected photons recorded from molecules freely diffusing in solution (in this example CspTm in 1.5 M GdmCl [37,38]), where every burst corresponds to an individual molecule traversing the diffraction-limited confocal volume (see upper right of the scheme). (b) 2-dimensional histogram of donor fluorescence lifetime τ_D versus transfer efficiency E calculated from individual bursts, resulting in subpopulations that can be assigned to the folded and unfolded protein and molecules without active acceptor at E ≈ 0 (shaded in grey). (c) Projection of the histogram onto the E axis. (d) Subpopulation-specific time-correlated single photon counting histograms from donor and acceptor photons from all bursts assigned to unfolded molecules that can be used to extract distance distributions [31,36,38]. (e) Subpopulation-specific donor intensity correlation function, in this case reporting on the nanosecond reconfiguration dynamics of the unfolded protein [58].

Figure 3

Protein folding kinetics measured with single molecule spectroscopy in a microfluidic mixing device [43]. Starting from CspTm unfolded at high denaturant concentration (top), transfer efficiency histograms are measured at different positions along the channel, corresponding to different times after mixing. The fits to Gaussians having the same peak position and width at all times illustrate the redistribution of populations expected for a two-state system after the initial chain collapse.

Figure 4

Transfer efficiency distribution p(E | t) for a Gaussian chain with different ratios of observation time t and chain reconfiguration time τ_r, with t/τ_r = 0 (dark blue), 0.1 (light blue), 1 (green), 5 (yellow), and 10 (red) (assuming R₀ = 〈r²〉), illustrating the sensitivity of transfer efficiency distributions to chain dynamics. Gopich and Szabo [33] showed that for a Gaussian chain and t >> τ_r, τ_r ≈ 10 t σ², with ${\sigma }^2={\sigma }_{obs}^2-{\sigma }_{noise}^2$, where ${\sigma }_{obs}^2$ is the observed variance in E, and ${\sigma }_{noise}^2$ is the variance due to noise and other effects not dependent on the interdye distance.

Box. Förster resonance energy transfer