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Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra
Automated methods for NMR structure determination of proteins are continuously becoming more robust. However, current methods addressing larger, more complex targets rely on analyzing 6–10 complementary spectra, suggesting the need for alternative approaches. Here, we describe 4D-CHAINS/autoNOE-Rose...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5786013/ https://www.ncbi.nlm.nih.gov/pubmed/29374165 http://dx.doi.org/10.1038/s41467-017-02592-z |
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author | Evangelidis, Thomas Nerli, Santrupti Nováček, Jiří Brereton, Andrew E. Karplus, P. Andrew Dotas, Rochelle R. Venditti, Vincenzo Sgourakis, Nikolaos G. Tripsianes, Konstantinos |
author_facet | Evangelidis, Thomas Nerli, Santrupti Nováček, Jiří Brereton, Andrew E. Karplus, P. Andrew Dotas, Rochelle R. Venditti, Vincenzo Sgourakis, Nikolaos G. Tripsianes, Konstantinos |
author_sort | Evangelidis, Thomas |
collection | PubMed |
description | Automated methods for NMR structure determination of proteins are continuously becoming more robust. However, current methods addressing larger, more complex targets rely on analyzing 6–10 complementary spectra, suggesting the need for alternative approaches. Here, we describe 4D-CHAINS/autoNOE-Rosetta, a complete pipeline for NOE-driven structure determination of medium- to larger-sized proteins. The 4D-CHAINS algorithm analyzes two 4D spectra recorded using a single, fully protonated protein sample in an iterative ansatz where common NOEs between different spin systems supplement conventional through-bond connectivities to establish assignments of sidechain and backbone resonances at high levels of completeness and with a minimum error rate. The 4D-CHAINS assignments are then used to guide automated assignment of long-range NOEs and structure refinement in autoNOE-Rosetta. Our results on four targets ranging in size from 15.5 to 27.3 kDa illustrate that the structures of proteins can be determined accurately and in an unsupervised manner in a matter of days. |
format | Online Article Text |
id | pubmed-5786013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57860132018-01-29 Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra Evangelidis, Thomas Nerli, Santrupti Nováček, Jiří Brereton, Andrew E. Karplus, P. Andrew Dotas, Rochelle R. Venditti, Vincenzo Sgourakis, Nikolaos G. Tripsianes, Konstantinos Nat Commun Article Automated methods for NMR structure determination of proteins are continuously becoming more robust. However, current methods addressing larger, more complex targets rely on analyzing 6–10 complementary spectra, suggesting the need for alternative approaches. Here, we describe 4D-CHAINS/autoNOE-Rosetta, a complete pipeline for NOE-driven structure determination of medium- to larger-sized proteins. The 4D-CHAINS algorithm analyzes two 4D spectra recorded using a single, fully protonated protein sample in an iterative ansatz where common NOEs between different spin systems supplement conventional through-bond connectivities to establish assignments of sidechain and backbone resonances at high levels of completeness and with a minimum error rate. The 4D-CHAINS assignments are then used to guide automated assignment of long-range NOEs and structure refinement in autoNOE-Rosetta. Our results on four targets ranging in size from 15.5 to 27.3 kDa illustrate that the structures of proteins can be determined accurately and in an unsupervised manner in a matter of days. Nature Publishing Group UK 2018-01-26 /pmc/articles/PMC5786013/ /pubmed/29374165 http://dx.doi.org/10.1038/s41467-017-02592-z 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 Evangelidis, Thomas Nerli, Santrupti Nováček, Jiří Brereton, Andrew E. Karplus, P. Andrew Dotas, Rochelle R. Venditti, Vincenzo Sgourakis, Nikolaos G. Tripsianes, Konstantinos Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title | Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title_full | Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title_fullStr | Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title_full_unstemmed | Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title_short | Automated NMR resonance assignments and structure determination using a minimal set of 4D spectra |
title_sort | automated nmr resonance assignments and structure determination using a minimal set of 4d spectra |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5786013/ https://www.ncbi.nlm.nih.gov/pubmed/29374165 http://dx.doi.org/10.1038/s41467-017-02592-z |
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