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Swellix: a computational tool to explore RNA conformational space
BACKGROUND: The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697422/ https://www.ncbi.nlm.nih.gov/pubmed/29157200 http://dx.doi.org/10.1186/s12859-017-1910-7 |
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author | Sloat, Nathan Liu, Jui-Wen Schroeder, Susan J. |
author_facet | Sloat, Nathan Liu, Jui-Wen Schroeder, Susan J. |
author_sort | Sloat, Nathan |
collection | PubMed |
description | BACKGROUND: The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. RESULTS: The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures. CONCLUSIONS: Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1910-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5697422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56974222017-12-01 Swellix: a computational tool to explore RNA conformational space Sloat, Nathan Liu, Jui-Wen Schroeder, Susan J. BMC Bioinformatics Methodology Article BACKGROUND: The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. RESULTS: The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures. CONCLUSIONS: Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-017-1910-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-21 /pmc/articles/PMC5697422/ /pubmed/29157200 http://dx.doi.org/10.1186/s12859-017-1910-7 Text en © The Author(s). 2017 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Article Sloat, Nathan Liu, Jui-Wen Schroeder, Susan J. Swellix: a computational tool to explore RNA conformational space |
title | Swellix: a computational tool to explore RNA conformational space |
title_full | Swellix: a computational tool to explore RNA conformational space |
title_fullStr | Swellix: a computational tool to explore RNA conformational space |
title_full_unstemmed | Swellix: a computational tool to explore RNA conformational space |
title_short | Swellix: a computational tool to explore RNA conformational space |
title_sort | swellix: a computational tool to explore rna conformational space |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697422/ https://www.ncbi.nlm.nih.gov/pubmed/29157200 http://dx.doi.org/10.1186/s12859-017-1910-7 |
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