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      Tools for Model Building and Optimization into Near-Atomic Resolution Electron Cryo-Microscopy Density Maps

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      Author(s): * , † , 1 , ‡ , 1
      Publication date (Electronic):
      Journal: Methods in Enzymology
      Publisher: Elsevier Inc.
      Keywords: CryoEM map-derived model, Model optimization, Model validation

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          Abstract

          Electron cryo-microscopy (cryoEM) has advanced dramatically to become a viable tool for high-resolution structural biology research. The ultimate outcome of a cryoEM study is an atomic model of a macromolecule or its complex with interacting partners. This chapter describes a variety of algorithms and software to build a de novo model based on the cryoEM 3D density map, to optimize the model with the best stereochemistry restraints and finally to validate the model with proper protocols. The full process of atomic structure determination from a cryoEM map is described. The tools outlined in this chapter should prove extremely valuable in revealing atomic interactions guided by cryoEM data.

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          Biochemistry. The resolution revolution.

          W Kühlbrandt (2014)
          Article 0 comments Cited 369 times – based on 0 reviews     Review now
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            Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics.

            Leonardo Trabuco, Elizabeth Villa, Kakoli Mitra … (2008)
            A novel method to flexibly fit atomic structures into electron microscopy (EM) maps using molecular dynamics simulations is presented. The simulations incorporate the EM data as an external potential added to the molecular dynamics force field, allowing all internal features present in the EM map to be used in the fitting process, while the model remains fully flexible and stereochemically correct. The molecular dynamics flexible fitting (MDFF) method is validated for available crystal structures of protein and RNA in different conformations; measures to assess and monitor the fitting process are introduced. The MDFF method is then used to obtain high-resolution structures of the E. coli ribosome in different functional states imaged by cryo-EM.
            Article 0 comments Cited 324 times – based on 0 reviews     Review now
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              Protein structure fitting and refinement guided by cryo-EM density.

              Andrej Sali, Maya Topf, Keren Lasker … (2008)
              For many macromolecular assemblies, both a cryo-electron microscopy map and atomic structures of its component proteins are available. Here we describe a method for fitting and refining a component structure within its map at intermediate resolution (<15 A). The atomic positions are optimized with respect to a scoring function that includes the crosscorrelation coefficient between the structure and the map as well as stereochemical and nonbonded interaction terms. A heuristic optimization that relies on a Monte Carlo search, a conjugate-gradients minimization, and simulated annealing molecular dynamics is applied to a series of subdivisions of the structure into progressively smaller rigid bodies. The method was tested on 15 proteins of known structure with 13 simulated maps and 3 experimentally determined maps. At approximately 10 A resolution, Calpha rmsd between the initial and final structures was reduced on average by approximately 53%. The method is automated and can refine both experimental and predicted atomic structures.
              Article 0 comments Cited 131 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                F. DiMaio
                W. Chiu
                Journal
                Journal ID (nlm-ta): Methods Enzymol
                Journal ID (iso-abbrev): Meth. Enzymol
                Title: Methods in Enzymology
                Publisher: Elsevier Inc.
                ISSN (Print): 0076-6879
                ISSN (Electronic): 1557-7988
                Publication date PMC-release: 12 August 2016
                Publication date (Print): 2016
                Publication date (Electronic): 12 August 2016
                Volume: 579
                Pages: 255-276
                Affiliations
                [* ]University of Washington, Seattle, WA, United States
                [† ]Institute for Protein Design, University of Washington, Seattle, WA, United States
                [‡ ]National Center for Macromolecular Imaging, Baylor College of Medicine, Houston, TX, United States
                Author notes
                Article
                Publisher ID: S0076-6879(16)30113-6
                DOI: 10.1016/bs.mie.2016.06.003
                PMC ID: 5103630
                PubMed ID: 27572730
                SO-VID: e724d2f7-82b9-4541-8148-503e0c975029
                Copyright © Copyright © 2016 Elsevier Inc. All rights reserved.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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                Subject: Article

                Keywords: cryoem map-derived model,model optimization,model validation
                Data availability:
                Keywords: cryoem map-derived model, model optimization, model validation

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