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De novo main-chain modeling for EM maps using MAINMAST

An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4–5 Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automate...

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Detalles Bibliográficos
Autores principales: Terashi, Genki, Kihara, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5915429/
https://www.ncbi.nlm.nih.gov/pubmed/29691408
http://dx.doi.org/10.1038/s41467-018-04053-7
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author Terashi, Genki
Kihara, Daisuke
author_facet Terashi, Genki
Kihara, Daisuke
author_sort Terashi, Genki
collection PubMed
description An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4–5 Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map. The method directly traces the protein’s main-chain and identifies Cα positions as tree-graph structures in the EM map. MAINMAST performs significantly better than existing software in building global protein structure models on data sets of 40 simulated density maps at 5 Å resolution and 30 experimentally determined maps at 2.6–4.8 Å resolution. In another benchmark of building missing fragments in protein models for EM maps, MAINMAST builds fragments of 11–161 residues long with an average RMSD of 2.68 Å.
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spelling pubmed-59154292018-04-27 De novo main-chain modeling for EM maps using MAINMAST Terashi, Genki Kihara, Daisuke Nat Commun Article An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4–5 Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map. The method directly traces the protein’s main-chain and identifies Cα positions as tree-graph structures in the EM map. MAINMAST performs significantly better than existing software in building global protein structure models on data sets of 40 simulated density maps at 5 Å resolution and 30 experimentally determined maps at 2.6–4.8 Å resolution. In another benchmark of building missing fragments in protein models for EM maps, MAINMAST builds fragments of 11–161 residues long with an average RMSD of 2.68 Å. Nature Publishing Group UK 2018-04-24 /pmc/articles/PMC5915429/ /pubmed/29691408 http://dx.doi.org/10.1038/s41467-018-04053-7 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Terashi, Genki
Kihara, Daisuke
De novo main-chain modeling for EM maps using MAINMAST
title De novo main-chain modeling for EM maps using MAINMAST
title_full De novo main-chain modeling for EM maps using MAINMAST
title_fullStr De novo main-chain modeling for EM maps using MAINMAST
title_full_unstemmed De novo main-chain modeling for EM maps using MAINMAST
title_short De novo main-chain modeling for EM maps using MAINMAST
title_sort de novo main-chain modeling for em maps using mainmast
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5915429/
https://www.ncbi.nlm.nih.gov/pubmed/29691408
http://dx.doi.org/10.1038/s41467-018-04053-7
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