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Deformable complex network for refining low-resolution X-ray structures

In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the deve...

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Detalles Bibliográficos
Autores principales: Zhang, Chong, Wang, Qinghua, Ma, Jianpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631475/
https://www.ncbi.nlm.nih.gov/pubmed/26527134
http://dx.doi.org/10.1107/S139900471501528X
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author Zhang, Chong
Wang, Qinghua
Ma, Jianpeng
author_facet Zhang, Chong
Wang, Qinghua
Ma, Jianpeng
author_sort Zhang, Chong
collection PubMed
description In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint with the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.
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spelling pubmed-46314752015-11-20 Deformable complex network for refining low-resolution X-ray structures Zhang, Chong Wang, Qinghua Ma, Jianpeng Acta Crystallogr D Biol Crystallogr Research Papers In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint with the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination. International Union of Crystallography 2015-10-27 /pmc/articles/PMC4631475/ /pubmed/26527134 http://dx.doi.org/10.1107/S139900471501528X Text en © Zhang et al. 2015 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Zhang, Chong
Wang, Qinghua
Ma, Jianpeng
Deformable complex network for refining low-resolution X-ray structures
title Deformable complex network for refining low-resolution X-ray structures
title_full Deformable complex network for refining low-resolution X-ray structures
title_fullStr Deformable complex network for refining low-resolution X-ray structures
title_full_unstemmed Deformable complex network for refining low-resolution X-ray structures
title_short Deformable complex network for refining low-resolution X-ray structures
title_sort deformable complex network for refining low-resolution x-ray structures
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631475/
https://www.ncbi.nlm.nih.gov/pubmed/26527134
http://dx.doi.org/10.1107/S139900471501528X
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