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RNA 3D Structure Prediction Using Coarse-Grained Models
The three-dimensional (3D) structures of Ribonucleic acid (RNA) molecules are essential to understanding their various and important biological functions. However, experimental determination of the atomic structures is laborious and technically difficult. The large gap between the number of sequence...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283274/ https://www.ncbi.nlm.nih.gov/pubmed/34277713 http://dx.doi.org/10.3389/fmolb.2021.720937 |
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author | Li, Jun Chen, Shi-Jie |
author_facet | Li, Jun Chen, Shi-Jie |
author_sort | Li, Jun |
collection | PubMed |
description | The three-dimensional (3D) structures of Ribonucleic acid (RNA) molecules are essential to understanding their various and important biological functions. However, experimental determination of the atomic structures is laborious and technically difficult. The large gap between the number of sequences and the experimentally determined structures enables the thriving development of computational approaches to modeling RNAs. However, computational methods based on all-atom simulations are intractable for large RNA systems, which demand long time simulations. Facing such a challenge, many coarse-grained (CG) models have been developed. Here, we provide a review of CG models for modeling RNA 3D structures, compare the performance of the different models, and offer insights into potential future developments. |
format | Online Article Text |
id | pubmed-8283274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82832742021-07-17 RNA 3D Structure Prediction Using Coarse-Grained Models Li, Jun Chen, Shi-Jie Front Mol Biosci Molecular Biosciences The three-dimensional (3D) structures of Ribonucleic acid (RNA) molecules are essential to understanding their various and important biological functions. However, experimental determination of the atomic structures is laborious and technically difficult. The large gap between the number of sequences and the experimentally determined structures enables the thriving development of computational approaches to modeling RNAs. However, computational methods based on all-atom simulations are intractable for large RNA systems, which demand long time simulations. Facing such a challenge, many coarse-grained (CG) models have been developed. Here, we provide a review of CG models for modeling RNA 3D structures, compare the performance of the different models, and offer insights into potential future developments. Frontiers Media S.A. 2021-07-02 /pmc/articles/PMC8283274/ /pubmed/34277713 http://dx.doi.org/10.3389/fmolb.2021.720937 Text en Copyright © 2021 Li and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Li, Jun Chen, Shi-Jie RNA 3D Structure Prediction Using Coarse-Grained Models |
title | RNA 3D Structure Prediction Using Coarse-Grained Models |
title_full | RNA 3D Structure Prediction Using Coarse-Grained Models |
title_fullStr | RNA 3D Structure Prediction Using Coarse-Grained Models |
title_full_unstemmed | RNA 3D Structure Prediction Using Coarse-Grained Models |
title_short | RNA 3D Structure Prediction Using Coarse-Grained Models |
title_sort | rna 3d structure prediction using coarse-grained models |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283274/ https://www.ncbi.nlm.nih.gov/pubmed/34277713 http://dx.doi.org/10.3389/fmolb.2021.720937 |
work_keys_str_mv | AT lijun rna3dstructurepredictionusingcoarsegrainedmodels AT chenshijie rna3dstructurepredictionusingcoarsegrainedmodels |