skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Automated map sharpening by maximization of detail and connectivity

Abstract

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a modelmore » withBfactors (atomic displacement factors; ADPs) set to zero. This model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

Authors:
; ; ORCiD logo;
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
National Institutes of Health (NIH); USDOE
OSTI Identifier:
1437712
Alternate Identifier(s):
OSTI ID: 1440481; OSTI ID: 1461163
Report Number(s):
LA-UR-17-30952
Journal ID: ISSN 2059-7983; ACSDAD; PII: S2059798318004655
Grant/Contract Number:  
AC52-06NA25396; P01GM063210; AC02-05CH11231
Resource Type:
Published Article
Journal Name:
Acta Crystallographica. Section D. Structural Biology
Additional Journal Information:
Journal Name: Acta Crystallographica. Section D. Structural Biology Journal Volume: 74 Journal Issue: 6; Journal ID: ISSN 2059-7983
Publisher:
IUCr
Country of Publication:
United Kingdom
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats

Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., and Adams, Paul D. Automated map sharpening by maximization of detail and connectivity. United Kingdom: N. p., 2018. Web. doi:10.1107/S2059798318004655.
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., & Adams, Paul D. Automated map sharpening by maximization of detail and connectivity. United Kingdom. doi:10.1107/S2059798318004655.
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., and Adams, Paul D. Fri . "Automated map sharpening by maximization of detail and connectivity". United Kingdom. doi:10.1107/S2059798318004655.
@article{osti_1437712,
title = {Automated map sharpening by maximization of detail and connectivity},
author = {Terwilliger, Thomas C. and Sobolev, Oleg V. and Afonine, Pavel V. and Adams, Paul D.},
abstractNote = {An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. This model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.},
doi = {10.1107/S2059798318004655},
journal = {Acta Crystallographica. Section D. Structural Biology},
number = 6,
volume = 74,
place = {United Kingdom},
year = {2018},
month = {5}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1107/S2059798318004655

Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Metrics for comparison of crystallographic maps
journal, September 2014

  • Urzhumtsev, Alexandre; Afonine, Pavel V.; Lunin, Vladimir Y.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 70, Issue 10
  • DOI: 10.1107/S1399004714016289

Optimal Determination of Particle Orientation, Absolute Hand, and Contrast Loss in Single-particle Electron Cryomicroscopy
journal, October 2003


EMDataBank unified data resource for 3DEM
journal, November 2015

  • Lawson, Catherine L.; Patwardhan, Ardan; Baker, Matthew L.
  • Nucleic Acids Research, Vol. 44, Issue D1
  • DOI: 10.1093/nar/gkv1126

Electron Density Sharpening as a General Technique in Crystallographic Studies
journal, February 2014


Atomic structure of the innexin-6 gap junction channel determined by cryo-EM
journal, December 2016

  • Oshima, Atsunori; Tani, Kazutoshi; Fujiyoshi, Yoshinori
  • Nature Communications, Vol. 7, Issue 1
  • DOI: 10.1038/ncomms13681

The Resolution Revolution
journal, March 2014


Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard
journal, December 2007

  • Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 64, Issue 1
  • DOI: 10.1107/S090744490705024X

Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment
journal, May 2016


Features and development of Coot
journal, March 2010

  • Emsley, P.; Lohkamp, B.; Scott, W. G.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 66, Issue 4
  • DOI: 10.1107/S0907444910007493

Big data in cryoEM: automated collection, processing and accessibility of EM data
journal, June 2018


Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes
journal, March 1977

  • Ryckaert, Jean-Paul; Ciccotti, Giovanni; Berendsen, Herman J. C.
  • Journal of Computational Physics, Vol. 23, Issue 3
  • DOI: 10.1016/0021-9991(77)90098-5

Structural basis for gating the high-conductance Ca2+-activated K+ channel
journal, December 2016

  • Hite, Richard K.; Tao, Xiao; MacKinnon, Roderick
  • Nature, Vol. 541, Issue 7635
  • DOI: 10.1038/nature20775

PHENIX: a comprehensive Python-based system for macromolecular structure solution
journal, January 2010

  • Adams, Paul D.; Afonine, Pavel V.; Bunkóczi, Gábor
  • Acta Crystallographica Section D Biological Crystallography, Vol. 66, Issue 2, p. 213-221
  • DOI: 10.1107/S0907444909052925

Breaking Cryo-EM Resolution Barriers to Facilitate Drug Discovery
journal, June 2016


Atomic Structure of the Cystic Fibrosis Transmembrane Conductance Regulator
journal, December 2016


Recent developments in the CCP-EM software suite
journal, May 2017

  • Burnley, Tom; Palmer, Colin M.; Winn, Martyn
  • Acta Crystallographica Section D Structural Biology, Vol. 73, Issue 6
  • DOI: 10.1107/S2059798317007859

Decision-making in structure solution using Bayesian estimates of map quality: the PHENIX AutoSol wizard
journal, May 2009

  • Terwilliger, Thomas C.; Adams, Paul D.; Read, Randy J.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 65, Issue 6
  • DOI: 10.1107/S0907444909012098

Structure of the TRPV1 ion channel determined by electron cryo-microscopy
journal, December 2013


The 13Å Structure of a Chaperonin GroEL–Protein Substrate Complex by Cryo-electron Microscopy
journal, April 2005

  • Falke, Scott; Tama, Florence; Brooks, Charles L.
  • Journal of Molecular Biology, Vol. 348, Issue 1
  • DOI: 10.1016/j.jmb.2005.02.027

Atomic structure of anthrax protective antigen pore elucidates toxin translocation
journal, March 2015

  • Jiang, Jiansen; Pentelute, Bradley L.; Collier, R. John
  • Nature, Vol. 521, Issue 7553
  • DOI: 10.1038/nature14247

Model-based local density sharpening of cryo-EM maps
journal, October 2017


The Protein Data Bank
journal, January 2000


FEM: feature-enhanced map
journal, February 2015

  • Afonine, Pavel V.; Moriarty, Nigel W.; Mustyakimov, Marat
  • Acta Crystallographica Section D Biological Crystallography, Vol. 71, Issue 3
  • DOI: 10.1107/S1399004714028132

Considerations for the refinement of low-resolution crystal structures
journal, July 2006

  • DeLaBarre, Byron; Brunger, Axel T.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 62, Issue 8
  • DOI: 10.1107/S0907444906012650

Improved Fourier coefficients for maps using phases from partial structures with errors
journal, May 1986

  • Read, R. J.
  • Acta Crystallographica Section A Foundations of Crystallography, Vol. 42, Issue 3
  • DOI: 10.1107/S0108767386099622

UCSF Chimera?A visualization system for exploratory research and analysis
journal, January 2004

  • Pettersen, Eric F.; Goddard, Thomas D.; Huang, Conrad C.
  • Journal of Computational Chemistry, Vol. 25, Issue 13
  • DOI: 10.1002/jcc.20084

The protein data bank: A computer-based archival file for macromolecular structures
journal, May 1977

  • Bernstein, Frances C.; Koetzle, Thomas F.; Williams, Graheme J. B.
  • Journal of Molecular Biology, Vol. 112, Issue 3
  • DOI: 10.1016/S0022-2836(77)80200-3

Reciprocal-space solvent flattening
journal, November 1999

  • Terwilliger, Thomas C.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 55, Issue 11
  • DOI: 10.1107/S0907444999010033

Low-resolution refinement tools in REFMAC 5
journal, March 2012

  • Nicholls, Robert A.; Long, Fei; Murshudov, Garib N.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 68, Issue 4
  • DOI: 10.1107/S090744491105606X