Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF,...

Full description

Bibliographic Details
Main Authors: Singharoy, Abhishek, Teo, Ivan, McGreevy, Ryan, Stone, John E, Zhao, Jianhua, Schulten, Klaus
Format: Online
Language:English
Published: eLife Sciences Publications, Ltd 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990421/
id pubmed-4990421
recordtype oai_dc
spelling pubmed-49904212016-08-19 Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps Singharoy, Abhishek Teo, Ivan McGreevy, Ryan Stone, John E Zhao, Jianhua Schulten, Klaus Biophysics and Structural Biology Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. eLife Sciences Publications, Ltd 2016-07-07 /pmc/articles/PMC4990421/ /pubmed/27383269 http://dx.doi.org/10.7554/eLife.16105 Text en © 2016, Singharoy et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Singharoy, Abhishek
Teo, Ivan
McGreevy, Ryan
Stone, John E
Zhao, Jianhua
Schulten, Klaus
spellingShingle Singharoy, Abhishek
Teo, Ivan
McGreevy, Ryan
Stone, John E
Zhao, Jianhua
Schulten, Klaus
Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
author_facet Singharoy, Abhishek
Teo, Ivan
McGreevy, Ryan
Stone, John E
Zhao, Jianhua
Schulten, Klaus
author_sort Singharoy, Abhishek
title Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
title_short Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
title_full Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
title_fullStr Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
title_full_unstemmed Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps
title_sort molecular dynamics-based refinement and validation for sub-5 å cryo-electron microscopy maps
description Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.
publisher eLife Sciences Publications, Ltd
publishDate 2016
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990421/
_version_ 1613630222046855168

Similar Items