ANALYSES OF SUBNANOMETER RESOLUTION CRYO-EM DENSITY MAPS

被引:16
|
作者
Baker, Matthew L. [1 ]
Baker, Mariah R. [1 ]
Hryc, Corey F. [1 ]
DiMaio, Frank [2 ]
机构
[1] Baylor Coll Med, Natl Ctr Macromol Imaging, Verna & Marrs McLean Dept Biochem & Mol Biol, Houston, TX 77030 USA
[2] Univ Washington, Dept Biochem, Seattle, WA 98195 USA
关键词
PARTICLE ELECTRON CRYOMICROSCOPY; STRUCTURAL-INFORMATICS APPROACH; PROTEIN-STRUCTURE PREDICTION; X-RAY CRYSTALLOGRAPHY; FITTING ATOMIC MODELS; GROUP-II CHAPERONIN; RICE-DWARF-VIRUS; CRYOELECTRON MICROSCOPY; SECONDARY STRUCTURE; STRUCTURE REFINEMENT;
D O I
10.1016/S0076-6879(10)83001-0
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Today, electron cryomicroscopy (cryo-EM) can routinely achieve subnanometer resolutions of complex macromolecular assemblies. From a density map, one can extract key structural and functional information using a variety of computational analysis tools. At subnanometer resolution, these tools make it possible to isolate individual subunits, identify secondary structures, and accurately fit atomic models. With several cryo-EM studies achieving resolutions beyond 5 angstrom, computational modeling and feature recognition tools have been employed to construct backbone and atomic models of the protein components directly from a density map. In this chapter, we describe several common classes of computational tools that can be used to analyze and model subnanometer resolution reconstructions from cryo-EM. A general protocol for analyzing subnanometer resolution density maps is presented along with a full description of steps used in analyzing the 4.3 angstrom resolution structure of Mm-cpn.
引用
收藏
页码:1 / 29
页数:29
相关论文
共 50 条
  • [1] Quantifying the local resolution of cryo-EM density maps
    Kucukelbir A.
    Sigworth F.J.
    Tagare H.D.
    Nature Methods, 2014, 11 (1) : 63 - 65
  • [2] A New Algorithm for Improving the Resolution of Cryo-EM Density Maps
    Hirsch, Michael
    Schoelkopf, Bernhard
    Habeck, Michael
    RESEARCH IN COMPUTATIONAL MOLECULAR BIOLOGY, PROCEEDINGS, 2010, 6044 : 174 - 188
  • [3] Density modification of cryo-EM maps
    Terwilliger, Thomas C.
    Sobolev, Oleg V.
    Afonine, Pavel V.
    Adams, Paul D.
    Read, Randy J.
    ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY, 2020, 76 : 912 - 925
  • [4] A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps
    Hirsch, Michael
    Schoelkopf, Bernhard
    Habeck, Michael
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2011, 18 (03) : 335 - 346
  • [6] Improvement of cryo-EM maps by density modification
    Terwilliger, Thomas C.
    Ludtke, Steven J.
    Read, Randy J.
    Adams, Paul D.
    Afonine, Pavel, V
    NATURE METHODS, 2020, 17 (09) : 923 - +
  • [7] Improvement of cryo-EM maps by density modification
    Thomas C. Terwilliger
    Steven J. Ludtke
    Randy J. Read
    Paul D. Adams
    Pavel V. Afonine
    Nature Methods, 2020, 17 : 923 - 927
  • [8] CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning
    Dai, Muzhi
    Dong, Zhuoer
    Xu, Kui
    Zhang, Qiangfeng Cliff
    JOURNAL OF MOLECULAR BIOLOGY, 2023, 435 (09)
  • [9] A Pattern Recognition Tool for Medium-Resolution Cryo-EM Density Maps and Low-Resolution Cryo-ET Density Maps
    Haslam, Devin
    Sazzed, Salim
    Wriggers, Willy
    Kovcas, Julio
    Song, Junha
    Auer, Manfred
    He, Jing
    BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2018, 2018, 10847 : 233 - 238
  • [10] Quality vs. Resolution in Cryo-EM Maps
    Stagg, Scott M.
    ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, 2019, 75 : A412 - A412