We present a comprehensive toolkit for Förster resonance energy transfer (FRET)-restrained modeling of biomolecules and their complexes for quantitative applications in structural biology. A dramatic improvement in the precision of FRET-derived structures is achieved by explicitly considering spatial distributions of dye positions, which greatly reduces uncertainties due to flexible dye linkers. The precision and confidence levels of the models are calculated by rigorous error estimation. The accuracy of this approach is demonstrated by docking a DNA primer-template to HIV-1 reverse transcriptase. The derived model agrees with the known X-ray structure with an r.m.s. deviation of 0.5 Å. Furthermore, we introduce FRET-guided 'screening' of a large structural ensemble created by molecular dynamics simulations. We used this hybrid approach to determine the formerly unknown configuration of the flexible single-strand template overhang.

In Förster resonance energy transfer (FRET) experiments, the donor (D) and acceptor (A) fluorophores are usually attached to the macromolecule of interest via long flexible linkers of up to 15 Å in length. This causes significant uncertainties in quantitative distance measurements and prevents experiments with short distances between the attachment points of the dyes due to possible dye-dye interactions. We present two approaches to overcome the above problems as demonstrated by FRET measurements for a series of dsDNA and dsRNA internally labeled with Alexa488 and Cy5 as D and A dye, respectively. First, we characterize the influence of linker length and flexibility on FRET for different dye linker types (long, intermediate, short) by analyzing fluorescence lifetime and anisotropy decays. For long linkers, we describe a straightforward procedure that allows for very high accuracy of FRET-based structure determination through proper consideration of the position distribution of the dye and of linker dynamics. The position distribution can be quickly calculated with geometric accessible volume (AV) simulations, provided that the local structure of RNA or DNA in the proximity of the dye is known and that the dye diffuses freely in the sterically allowed space. The AV approach provides results similar to molecular dynamics simulations (MD) and is fully consistent with experimental FRET data. In a benchmark study for ds A-RNA, an rmsd value of 1.3 Å is achieved. Considering the case of undefined dye environments or very short DA distances, we introduce short linkers with a propargyl or alkenyl unit for internal labeling of nucleic acids to minimize position uncertainties. Studies by ensemble time correlated single photon counting and single-molecule detection show that the nature of the linker strongly affects the radius of the dye's accessible volume (6-16 Å). For short propargyl linkers, heterogeneous dye environments are observed on the millisecond time scale. A detailed analysis of possible orientation effects (κ(2) problem) indicates that, for short linkers and unknown local environments, additional κ(2)-related uncertainties are clearly outweighed by better defined dye positions.

Which comes first, the deformation or the binding? High specificity of protein-DNA interaction is often related with specific deformation of the binding site. B-Z transition is the most dramatic structural change induced by protein-DNA interaction, where some segment of DNA abruptly changes from the right-handed B-DNA to the left-handed Z-DNA by the help of specific proteins. Here, we report single-molecule FRET studies on protein-induced Z-DNA formation. DNA duplexes with six CG-repeats were prepared. To monitor the conformational dynamics of the CG-repeat, we labeled Cy3 and Cy5 at each end of the CG-repeat. Surface-immobilized DNA molecules did not show any structural dynamics in normal physiological conditions. When a Z-DNA inducing protein, Za, was added to the buffer solution, however, fluorescence intensity increased abruptly without any accompanying FRET change. Abrupt FRET change occurred with time delay (~10 minute at 25 C on average). When the proteins were washed out, molecules didn't recover the original FRET value for more than 3 hours, but molecules without the FRET change readily recovered their original fluorescence intensity. From these result, we conclude that Za protein weakly interact with B-DNA, but the interaction becomes extremely strong once Z-DNA is formed. Next, we prepared a DNA duplex with methylated cytosine in the CG repeat. With millimolar Ni 2þ in the buffer solution, we observed the intrinsic B-Z transition dynamics, and Z-DNA stabilization by Za proteins. The transition time from B-DNA to Z-DNA, however, was not affected by the presence of Za proteins, which strongly support that Za protein induces Z-DNA by passively trapping Z-DNA structure transiently formed by the intrinsic B-Z transition dynamics. Even though we cannot directly observe Z-DNA, Z-DNA's are actually waiting there inside the cell to play their biological roles on time.

cryo-electron tomography. This technique ascertains that rhodopsin is preserved in a close-to-native state. Briefly: retina is fixed by high-pressure freezing, ultra-thin sectioned and visualized by cryo-electron tomography. In the reconstructed and processed tomograms the organization of rhodopsin molecules becomes visible. We identify three levels of hierarchical supramolecular organization. Rhodopsin forms dimers; the dimers form rows; and rows come in special pairs like rail tracks. Rows are aligned parallel to the disk incisure. A row is comprised of at least 10 dimers and is about 50 nm in length. The distance between rows within a track is 5 nm; and tracks are separated by 15 nm. We propose that rhodopsin tracks provide a template that organizes the spatio-temporal interaction of preassembled signalling components on the disk surface. Aligned rows of immobile rhodopsin renders photoreceptors highly dichroic and might provide the structural basis for detection of polarized light. We envisage that rhodopsin-like type A GPCRs, which are highly homologous, also entertain a supramolecular organization.

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Single particle tracking (SPT) is a powerful class of techniques for exploring the dynamics of single molecules moving inside living cells. In order to extract information about the biophysical processes under study, one desires both the trajectories of the tracked particles as well as the parameters of their motions, such as diffusion coefficients, confinement lengths, and similar values. Typically this information is determined in two steps, first through trajectory estimation from the image data and then parameter estimation from the trajectories In prior work, we have introduced a general algorithm known as Sequential Monte Carlo-Expectation Maximization (SMC-EM) that leverages nonlinear system identification tools using particle filters and particle smoothers to handle nonlinear models of motion as well as nonlinear models of observation, allowing us to incorporate camera models, varying point spread functions, and other experimental realities. These scheme does not separate the estimation of trajectory and motion parameters. SMC-EM is in fact a family of algorithms described by the choice of filter and smoother. In this work, we undertake a systematic study of the effect the choice of these different sub-algorithms, focusing on diffusion models as well as the simplest setting that is biologically relevant. The algorithms are compared with respect to a variety of measures, including speed of convergence, computational complexity, trajectory estimation accuracy, parameter estimation accuracy, and robustness to noise. We present a Bayesian approach to fluorescence correlation spectroscopy (FCS) parameter estimation. Traditionally, FCS data are analyzed by leastsquare fitting the autocorrelation function of the fluorescent intensity signal. We show by simulation that a least-square analysis of FCS autocorrelation functions is problematic both in the sense that the analysis results in an order-of-magnitude overestimation of confidence in the fitting parameters, but more importantly in systematic shifts of parameters away from the true value. This effect is more pronounced the shorter the data set is. Motivated by this result, we developed a Bayesian framework for the analysis of FCS data that takes single photon arrival times as input. So far, we have solved the time-independent probability distribution of photon arrival times for a 3d Gaussian beam shape and we are in the process of comparing our method to traditional photon counting histograms in FCS. In the future, we will incorporate the dynamics of fluorescent molecule diffusion into the model. 685-PosExperimental Dissection of Excluded Volume Effects from Quinary Interactions in Macromolecular Crowding . Current models of diffusion are, at best, approximations of what happens in vivo. Fick's Law and Stokes-Einstein approximate dilute solution behavior, but they do not account for in vivo environmental factors that modulate particle motion such as electrostatic forces, hydrophobic interactions, and excluded volume. Such factors represent the contributions f...