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Title: Cryo‐EM map interpretation and protein model‐building using iterative map segmentation

Abstract

A procedure for building protein chains into maps produced by single-particle electron cryo-microscopy (cryo-EM) is described. The procedure is similar to the way an experienced structural biologist might analyze a map, focusing first on secondary structure elements such as helices and sheets, then varying the contour level to identify connections between these elements. Since the high density in a map typically follows the main-chain of the protein, the main-chain connection between secondary structure elements can often be identified as the unbranched path between them with the highest minimum value along the path. This chain-tracing procedure is then combined with finding side-chain positions based on the presence of density extending away from the main path of the chain, allowing generation of a Cα model. The Cα model is converted to an all-atom model and is refined against the map. We show that this procedure is as effective as other existing methods for interpretation of cryo-EM maps and that it is considerably faster and produces models with fewer chain breaks than our previous methods that were based on approaches developed for crystallographic maps.

Authors:
ORCiD logo [1];  [2];  [3];  [3]
  1. Los Alamos National Laboratory Los Alamos New Mexico, New Mexico Consortium Los Alamos New Mexico
  2. Molecular Biophysics &, Integrated Bioimaging DivisionLawrence Berkeley National Laboratory Berkeley California, Department of BioengineeringUniversity of California Berkeley Berkeley California
  3. Molecular Biophysics &, Integrated Bioimaging DivisionLawrence Berkeley National Laboratory Berkeley California
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC); Phenix Industrial Consortium; National Institutes of Health (NIH)
OSTI Identifier:
1571696
Alternate Identifier(s):
OSTI ID: 1571697; OSTI ID: 1615287; OSTI ID: 1630869
Report Number(s):
LA-UR-19-31493
Journal ID: ISSN 0961-8368
Grant/Contract Number:  
AC02‐05CH11231; AC02-05CH11231; 89233218CNA000001; AC52-06NA25396; GM063210
Resource Type:
Published Article
Journal Name:
Protein Science
Additional Journal Information:
Journal Name: Protein Science Journal Volume: 29 Journal Issue: 1; Journal ID: ISSN 0961-8368
Publisher:
The Protein Society
Country of Publication:
United Kingdom
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Biological Science; cryo-electron microscopy; map interpretation; map segmentation; model-building

Citation Formats

Terwilliger, Thomas C., Adams, Paul D., Afonine, Pavel V., and Sobolev, Oleg V. Cryo‐EM map interpretation and protein model‐building using iterative map segmentation. United Kingdom: N. p., 2019. Web. doi:10.1002/pro.3740.
Terwilliger, Thomas C., Adams, Paul D., Afonine, Pavel V., & Sobolev, Oleg V. Cryo‐EM map interpretation and protein model‐building using iterative map segmentation. United Kingdom. doi:10.1002/pro.3740.
Terwilliger, Thomas C., Adams, Paul D., Afonine, Pavel V., and Sobolev, Oleg V. Thu . "Cryo‐EM map interpretation and protein model‐building using iterative map segmentation". United Kingdom. doi:10.1002/pro.3740.
@article{osti_1571696,
title = {Cryo‐EM map interpretation and protein model‐building using iterative map segmentation},
author = {Terwilliger, Thomas C. and Adams, Paul D. and Afonine, Pavel V. and Sobolev, Oleg V.},
abstractNote = {A procedure for building protein chains into maps produced by single-particle electron cryo-microscopy (cryo-EM) is described. The procedure is similar to the way an experienced structural biologist might analyze a map, focusing first on secondary structure elements such as helices and sheets, then varying the contour level to identify connections between these elements. Since the high density in a map typically follows the main-chain of the protein, the main-chain connection between secondary structure elements can often be identified as the unbranched path between them with the highest minimum value along the path. This chain-tracing procedure is then combined with finding side-chain positions based on the presence of density extending away from the main path of the chain, allowing generation of a Cα model. The Cα model is converted to an all-atom model and is refined against the map. We show that this procedure is as effective as other existing methods for interpretation of cryo-EM maps and that it is considerably faster and produces models with fewer chain breaks than our previous methods that were based on approaches developed for crystallographic maps.},
doi = {10.1002/pro.3740},
journal = {Protein Science},
number = 1,
volume = 29,
place = {United Kingdom},
year = {2019},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
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DOI: 10.1002/pro.3740

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Cited by: 6 works
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Works referenced in this record:

The Buccaneer software for automated model building. 1. Tracing protein chains
journal, August 2006


A note on two problems in connexion with graphs
journal, December 1959


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

RosettaES: a sampling strategy enabling automated interpretation of difficult cryo-EM maps
journal, June 2017

  • Frenz, Brandon; Walls, Alexandra C.; Egelman, Edward H.
  • Nature Methods, Vol. 14, Issue 8
  • DOI: 10.1038/nmeth.4340

Bridging the information gap: computational tools for intermediate resolution structure interpretation
journal, May 2001

  • Jiang, Wen; Baker, Matthew L.; Ludtke, Steven J.
  • Journal of Molecular Biology, Vol. 308, Issue 5
  • DOI: 10.1006/jmbi.2001.4633

The Resolution Revolution
journal, March 2014


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

De novo protein structure determination from near-atomic-resolution cryo-EM maps
journal, February 2015

  • Wang, Ray Yu-Ruei; Kudryashev, Mikhail; Li, Xueming
  • Nature Methods, Vol. 12, Issue 4
  • DOI: 10.1038/nmeth.3287

Structure of  -galactosidase at 3.2-A resolution obtained by cryo-electron microscopy
journal, July 2014

  • Bartesaghi, A.; Matthies, D.; Banerjee, S.
  • Proceedings of the National Academy of Sciences, Vol. 111, Issue 32
  • DOI: 10.1073/pnas.1402809111

EM-Fold: De Novo Atomic-Detail Protein Structure Determination from Medium-Resolution Density Maps
journal, March 2012


The crystal structure of the bacterial chaperonln GroEL at 2.8 Å
journal, October 1994

  • Braig, Kerstin; Otwinowski, Zbyszek; Hegde, Rashmi
  • Nature, Vol. 371, Issue 6498
  • DOI: 10.1038/371578a0

Accurate model annotation of a near-atomic resolution cryo-EM map
journal, March 2017

  • Hryc, Corey F.; Chen, Dong-Hua; Afonine, Pavel V.
  • Proceedings of the National Academy of Sciences, Vol. 114, Issue 12
  • DOI: 10.1073/pnas.1621152114

Fast procedure for reconstruction of full-atom protein models from reduced representations
journal, January 2008

  • Rotkiewicz, Piotr; Skolnick, Jeffrey
  • Journal of Computational Chemistry, Vol. 29, Issue 9
  • DOI: 10.1002/jcc.20906

Tertiary templates for proteins
journal, February 1987


A Graph Based Method for the Prediction of Backbone Trace from Cryo-EM Density Maps
conference, January 2017

  • Collins, Peter; Si, Dong
  • Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics - ACM-BCB '17
  • DOI: 10.1145/3107411.3107501

A fully automatic method yielding initial models from high-resolution cryo-electron microscopy maps
journal, October 2018


Overview and future of single particle electron cryomicroscopy
journal, September 2015


A Structural-informatics Approach for Mining β-Sheets: Locating Sheets in Intermediate-resolution Density Maps
journal, September 2003


Subunit conformational variation within individual GroEL oligomers resolved by Cryo-EM
journal, July 2017

  • Roh, Soung-Hun; Hryc, Corey F.; Jeong, Hyun-Hwan
  • Proceedings of the National Academy of Sciences, Vol. 114, Issue 31
  • DOI: 10.1073/pnas.1704725114

Automated main-chain model building by template matching and iterative fragment extension
journal, December 2002

  • Terwilliger, Thomas C.
  • Acta Crystallographica Section D Biological Crystallography, Vol. 59, Issue 1
  • DOI: 10.1107/S0907444902018036

Cryo-EM structures of the human endolysosomal TRPML3 channel in three distinct states
journal, November 2017

  • Zhou, Xiaoyuan; Li, Minghui; Su, Deyuan
  • Nature Structural & Molecular Biology, Vol. 24, Issue 12
  • DOI: 10.1038/nsmb.3502

Modeling protein structure at near atomic resolutions with Gorgon
journal, May 2011

  • Baker, Matthew L.; Abeysinghe, Sasakthi S.; Schuh, Stephen
  • Journal of Structural Biology, Vol. 174, Issue 2
  • DOI: 10.1016/j.jsb.2011.01.015

The Protein Data Bank
journal, January 2000


A Multi-model Approach to Assessing Local and Global Cryo-EM Map Quality
journal, February 2019


De Novo modeling in cryo-EM density maps with Pathwalking
journal, December 2016

  • Chen, Muyuan; Baldwin, Philip R.; Ludtke, Steven J.
  • Journal of Structural Biology, Vol. 196, Issue 3
  • DOI: 10.1016/j.jsb.2016.06.004

Structure of the E. coli ribosome–EF-Tu complex at <3 Å resolution by Cs-corrected cryo-EM
journal, February 2015

  • Fischer, Niels; Neumann, Piotr; Konevega, Andrey L.
  • Nature, Vol. 520, Issue 7548
  • DOI: 10.1038/nature14275

De novo main-chain modeling for EM maps using MAINMAST
journal, April 2018


Advances in the molecular dynamics flexible fitting method for cryo-EM modeling
journal, May 2016


EMBuilder: A Template Matching-based Automatic Model-building Program for High-resolution Cryo-Electron Microscopy Maps
journal, June 2017


How Good Can Single-Particle Cryo-EM Become? What Remains Before It Approaches Its Physical Limits?
journal, May 2019


The development of cryo-EM into a mainstream structural biology technique
journal, December 2015


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

Identification of Secondary Structure Elements in Intermediate-Resolution Density Maps
journal, January 2007


A Structural-informatics Approach for Tracing β-Sheets: Building Pseudo-Cα Traces for β-Strands in Intermediate-resolution Density Maps
journal, May 2004