Grigorieff, N. FREALIGN: high-resolution refinement of single particle structures. J. Struct. Biol. 157, 117-125

Howard Hughes Medical Institute, Department of Biochemistry, Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, MA 02454, USA.
Journal of Structural Biology (Impact Factor: 3.23). 02/2007; 157(1):117-25. DOI: 10.1016/j.jsb.2006.05.004
Source: PubMed


The refinement of three-dimensional reconstructions and correction for the contrast transfer function of the microscope are important steps in the determination of macromolecular structures by single particle electron microscopy. The algorithms implemented in the computer program FREALIGN are optimized to perform these tasks efficiently. A general overview and details on how to use FREALIGN are provided. The program is free and available for download on the author's web page.

Download full-text


Available from: Nikolaus Grigorieff
    • "higher defocus. For this reason, information restoration from cryoEM image is quite challenging, especially at high frequency, which makes accurate CTF determination an important factor for near-atomic 3D reconstructions. There are currently several programs available for CTF determination ( Ludtke et al., 1999 ; Mallick et al., 2005 ; Mindell and Grigorieff , 2003 ; Penczek et al., 2014 ; Shaikh et al . , 2008 ; Sorzano et al . , 2004 ; Tang et al . , 2007 ; Vargas et al . , 2013 ; Voortman et al . , 2011 ) . In a recent work , researchers systematically studied the performance of different programs ( Marabini et al . , 2015 ) . Each of the programs has its own advantages for certain purposes . The popular program CTFFIND3 ( Mindell and Grigorieff , 2003 ) shows the most self - consistent"
    [Show abstract] [Hide abstract]
    ABSTRACT: Accurate estimation of the contrast transfer function (CTF) is critical for a near-atomic resolution cryo electron microscopy (cryoEM) reconstruction. Here, I present a GPU-accelerated computer program, Gctf, for accurate and robust, real-time CTF determination. Similar to alternative programs, the main target of Gctf is to maximize the cross-correlation of a simulated CTF with the power spectra of observed micrographs after background reduction. However, novel approaches in Gctf improve both speed and accuracy. In addition to GPU acceleration, a fast ‘1-dimensional search plus 2-dimensional refinement (1S2R)’ procedure significantly speeds up Gctf. Based on the global CTF determination, the local defocus for each particle and for single frames of movies is accurately refined, which improves CTF parameters of all particles for subsequent image processing. Novel diagnosis method using equiphase averaging(EFA) and self-consistency verification procedures have also been implemented in the program for practical use, especially for aims of near-atomic reconstruction. Gctf is an independent program and the outputs can be easily imported into other cryoEM software such as Relion and Frealign. The results from several representative datasets are shown and discussed in this paper.
    No preview · Article · Jul 2015 · Journal of Structural Biology
  • Source
    • "Structures of the Rotated/Nonrotated Yeast 80S previously (Brilot et al., 2013; Grigorieff, 2007). The initial data set consisted of 86,866 particles. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The structural understanding of eukaryotic translation lags behind that of translation on bacterial ribosomes. Here, we present two subnanometer resolution structures of S. cerevisiae 80S ribosome complexes formed with either one or two tRNAs and bound in response to an mRNA fragment containing the Kozak consensus sequence. The ribosomes adopt two globally different conformations that are related to each other by the rotation of the small subunit. Comparison with bacterial ribosome complexes reveals that the global structures and modes of intersubunit rotation of the yeast ribosome differ significantly from those in the bacterial counterpart, most notably in the regions involving the tRNA, small ribosomal subunit, and conserved helix 69 of the large ribosomal subunit. The structures provide insight into ribosome dynamics implicated in tRNA translocation and help elucidate the role of the Kozak fragment in positioning an open reading frame during translation initiation in eukaryotes.
    Full-text · Article · Aug 2014 · Structure
  • Source
    • "In single particle EM, two dimensional (2D) projection images of biological specimens are recorded in an electron microscope, their relative orientations are determined using one of a number of alignment algorithms, and finally one or more 3D reconstructions are calculated (Frank et al., 1996; Van Heel et al., 1996; Marabini et al., 1996; Grigorieff, 2007; Tang et al., 2007; Scheres, 2012). With favourable datasets (high signal-to-noise, even particle distributions , homogeneous conformation, etc.), iterative refinement of the orientations assigned to each particle image will converge to the true 3D density map. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Determining the structure of a protein complex using electron microscopy requires the calculation of a 3D density map from 2D images of single particles. Since the individual images are taken at low electron dose to avoid radiation damage, they are noisy and difficult to align with each other. This can result in incorrect maps, making validation essential. Pairs of electron micrographs taken at known angles to each other (tilt-pairs) can be used to measure the accuracy of assigned projection orientations and verify the soundness of calculated maps. Here we establish a statistical framework for evaluating images and density maps using tilt-pairs. The directional distribution of such angular data is modelled using a Fisher distribution on the unit sphere. This provides a simple, quantitative and easily comparable metric, the concentration parameter κ , for evaluating the quality of datasets and density maps that is independent of the data collection and analysis methods. A large κ is indicative of good agreement between the particle images and the 3D density map. For structure validation, we recommend κ>10κ>10 and a p-value<0.01p-value<0.01. The statistical framework herein allows one to objectively answer the question: Is a reconstructed density map correct within a particular confidence interval?
    Full-text · Article · Aug 2014 · Journal of Structural Biology
Show more