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X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b

We present the data used for an integrative approach to computational modeling of proteins with large variable domains, specifically applied in this context to model HIV Env glycoprotein gp120 in its CD4 and 17b bound state. The initial data involved X-ray structure PDBID:1GC1 and electron microscop...

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Autores principales: Rasheed, Muhibur, Bettadapura, Radhakrishna, Bajaj, Chandrajit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749890/
https://www.ncbi.nlm.nih.gov/pubmed/26937457
http://dx.doi.org/10.1016/j.dib.2016.01.001
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author Rasheed, Muhibur
Bettadapura, Radhakrishna
Bajaj, Chandrajit
author_facet Rasheed, Muhibur
Bettadapura, Radhakrishna
Bajaj, Chandrajit
author_sort Rasheed, Muhibur
collection PubMed
description We present the data used for an integrative approach to computational modeling of proteins with large variable domains, specifically applied in this context to model HIV Env glycoprotein gp120 in its CD4 and 17b bound state. The initial data involved X-ray structure PDBID:1GC1 and electron microscopy image EMD:5020. Other existing X-ray structures were used as controls to validate and hierarchically refine partial and complete computational models. A summary of the experiment protocol and data was published (Rasheed et al., 2015) [26], along with detailed analysis of the final model (PDBID:3J70) and its implications.
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spelling pubmed-47498902016-03-02 X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b Rasheed, Muhibur Bettadapura, Radhakrishna Bajaj, Chandrajit Data Brief Data Article We present the data used for an integrative approach to computational modeling of proteins with large variable domains, specifically applied in this context to model HIV Env glycoprotein gp120 in its CD4 and 17b bound state. The initial data involved X-ray structure PDBID:1GC1 and electron microscopy image EMD:5020. Other existing X-ray structures were used as controls to validate and hierarchically refine partial and complete computational models. A summary of the experiment protocol and data was published (Rasheed et al., 2015) [26], along with detailed analysis of the final model (PDBID:3J70) and its implications. Elsevier 2016-01-12 /pmc/articles/PMC4749890/ /pubmed/26937457 http://dx.doi.org/10.1016/j.dib.2016.01.001 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Rasheed, Muhibur
Bettadapura, Radhakrishna
Bajaj, Chandrajit
X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title_full X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title_fullStr X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title_full_unstemmed X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title_short X-ray, Cryo-EM, and computationally predicted protein structures used in integrative modeling of HIV Env glycoprotein gp120 in complex with CD4 and 17b
title_sort x-ray, cryo-em, and computationally predicted protein structures used in integrative modeling of hiv env glycoprotein gp120 in complex with cd4 and 17b
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749890/
https://www.ncbi.nlm.nih.gov/pubmed/26937457
http://dx.doi.org/10.1016/j.dib.2016.01.001
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