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Physics-based RNA structure prediction
Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. L...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4762127/ https://www.ncbi.nlm.nih.gov/pubmed/26942214 http://dx.doi.org/10.1007/s41048-015-0001-4 |
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author | Xu, Xiaojun Chen, Shi-Jie |
author_facet | Xu, Xiaojun Chen, Shi-Jie |
author_sort | Xu, Xiaojun |
collection | PubMed |
description | Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. Low-resolution structural modeling enables us to estimate the conformational entropies for a number of tertiary folds through rigorous statistical mechanical calculations. The models lead to 3D tertiary folds at coarse-grained level. The coarse-grained structures serve as the initial structures for all-atom molecular dynamics refinement to build the final all-atom 3D structures. In this paper, we present an overview of RNA computational models for secondary and tertiary structures’ predictions and then focus on a recently developed RNA statistical mechanical model—the Vfold model. The main emphasis is placed on the physics behind the models, including the treatment of the non-canonical interactions in secondary and tertiary structure modelings, and the correlations to RNA functions. |
format | Online Article Text |
id | pubmed-4762127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-47621272016-03-01 Physics-based RNA structure prediction Xu, Xiaojun Chen, Shi-Jie Biophys Rep Methods Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. Low-resolution structural modeling enables us to estimate the conformational entropies for a number of tertiary folds through rigorous statistical mechanical calculations. The models lead to 3D tertiary folds at coarse-grained level. The coarse-grained structures serve as the initial structures for all-atom molecular dynamics refinement to build the final all-atom 3D structures. In this paper, we present an overview of RNA computational models for secondary and tertiary structures’ predictions and then focus on a recently developed RNA statistical mechanical model—the Vfold model. The main emphasis is placed on the physics behind the models, including the treatment of the non-canonical interactions in secondary and tertiary structure modelings, and the correlations to RNA functions. Springer Berlin Heidelberg 2015-07-09 2015 /pmc/articles/PMC4762127/ /pubmed/26942214 http://dx.doi.org/10.1007/s41048-015-0001-4 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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. |
spellingShingle | Methods Xu, Xiaojun Chen, Shi-Jie Physics-based RNA structure prediction |
title | Physics-based RNA structure prediction |
title_full | Physics-based RNA structure prediction |
title_fullStr | Physics-based RNA structure prediction |
title_full_unstemmed | Physics-based RNA structure prediction |
title_short | Physics-based RNA structure prediction |
title_sort | physics-based rna structure prediction |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4762127/ https://www.ncbi.nlm.nih.gov/pubmed/26942214 http://dx.doi.org/10.1007/s41048-015-0001-4 |
work_keys_str_mv | AT xuxiaojun physicsbasedrnastructureprediction AT chenshijie physicsbasedrnastructureprediction |