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Visualizing the ai5γ group IIB intron

It has become apparent that much of cellular metabolism is controlled by large well-folded noncoding RNA molecules. In addition to crystallographic approaches, computational methods are needed for visualizing the 3D structure of large RNAs. Here, we modeled the molecular structure of the ai5γ group...

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Detalles Bibliográficos
Autores principales: Somarowthu, Srinivas, Legiewicz, Michal, Keating, Kevin S., Pyle, Anna Marie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
RNA
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919574/
https://www.ncbi.nlm.nih.gov/pubmed/24203709
http://dx.doi.org/10.1093/nar/gkt1051
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author Somarowthu, Srinivas
Legiewicz, Michal
Keating, Kevin S.
Pyle, Anna Marie
author_facet Somarowthu, Srinivas
Legiewicz, Michal
Keating, Kevin S.
Pyle, Anna Marie
author_sort Somarowthu, Srinivas
collection PubMed
description It has become apparent that much of cellular metabolism is controlled by large well-folded noncoding RNA molecules. In addition to crystallographic approaches, computational methods are needed for visualizing the 3D structure of large RNAs. Here, we modeled the molecular structure of the ai5γ group IIB intron from yeast using the crystal structure of a bacterial group IIC homolog. This was accomplished by adapting strategies for homology and de novo modeling, and creating a new computational tool for RNA refinement. The resulting model was validated experimentally using a combination of structure-guided mutagenesis and RNA structure probing. The model provides major insights into the mechanism and regulation of splicing, such as the position of the branch-site before and after the second step of splicing, and the location of subdomains that control target specificity, underscoring the feasibility of modeling large functional RNA molecules.
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spelling pubmed-39195742014-02-10 Visualizing the ai5γ group IIB intron Somarowthu, Srinivas Legiewicz, Michal Keating, Kevin S. Pyle, Anna Marie Nucleic Acids Res RNA It has become apparent that much of cellular metabolism is controlled by large well-folded noncoding RNA molecules. In addition to crystallographic approaches, computational methods are needed for visualizing the 3D structure of large RNAs. Here, we modeled the molecular structure of the ai5γ group IIB intron from yeast using the crystal structure of a bacterial group IIC homolog. This was accomplished by adapting strategies for homology and de novo modeling, and creating a new computational tool for RNA refinement. The resulting model was validated experimentally using a combination of structure-guided mutagenesis and RNA structure probing. The model provides major insights into the mechanism and regulation of splicing, such as the position of the branch-site before and after the second step of splicing, and the location of subdomains that control target specificity, underscoring the feasibility of modeling large functional RNA molecules. Oxford University Press 2014-02 2013-11-06 /pmc/articles/PMC3919574/ /pubmed/24203709 http://dx.doi.org/10.1093/nar/gkt1051 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle RNA
Somarowthu, Srinivas
Legiewicz, Michal
Keating, Kevin S.
Pyle, Anna Marie
Visualizing the ai5γ group IIB intron
title Visualizing the ai5γ group IIB intron
title_full Visualizing the ai5γ group IIB intron
title_fullStr Visualizing the ai5γ group IIB intron
title_full_unstemmed Visualizing the ai5γ group IIB intron
title_short Visualizing the ai5γ group IIB intron
title_sort visualizing the ai5γ group iib intron
topic RNA
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919574/
https://www.ncbi.nlm.nih.gov/pubmed/24203709
http://dx.doi.org/10.1093/nar/gkt1051
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