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DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model

MOTIVATION: Folding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5′ end can fold into metastable structures before potentially stronger interactions with the 3′ end become available. Thermodynamic RNA folding models are...

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Detalles Bibliográficos
Autores principales: Badelt, Stefan, Lorenz, Ronny, Hofacker, Ivo L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889959/
https://www.ncbi.nlm.nih.gov/pubmed/36655786
http://dx.doi.org/10.1093/bioinformatics/btad034
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author Badelt, Stefan
Lorenz, Ronny
Hofacker, Ivo L
author_facet Badelt, Stefan
Lorenz, Ronny
Hofacker, Ivo L
author_sort Badelt, Stefan
collection PubMed
description MOTIVATION: Folding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5′ end can fold into metastable structures before potentially stronger interactions with the 3′ end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences. RESULTS: We present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides. AVAILABILITY AND IMPLEMENTATION: This software is open-source and available at https://github.com/ViennaRNA/drtransformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-98899592023-02-02 DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model Badelt, Stefan Lorenz, Ronny Hofacker, Ivo L Bioinformatics Original Paper MOTIVATION: Folding during transcription can have an important influence on the structure and function of RNA molecules, as regions closer to the 5′ end can fold into metastable structures before potentially stronger interactions with the 3′ end become available. Thermodynamic RNA folding models are not suitable to predict structures that result from cotranscriptional folding, as they can only calculate properties of the equilibrium distribution. Other software packages that simulate the kinetic process of RNA folding during transcription exist, but they are mostly applicable for short sequences. RESULTS: We present a new algorithm that tracks changes to the RNA secondary structure ensemble during transcription. At every transcription step, new representative local minima are identified, a neighborhood relation is defined and transition rates are estimated for kinetic simulations. After every simulation, a part of the ensemble is removed and the remainder is used to search for new representative structures. The presented algorithm is deterministic (up to numeric instabilities of simulations), fast (in comparison with existing methods), and it is capable of folding RNAs much longer than 200 nucleotides. AVAILABILITY AND IMPLEMENTATION: This software is open-source and available at https://github.com/ViennaRNA/drtransformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2023-01-19 /pmc/articles/PMC9889959/ /pubmed/36655786 http://dx.doi.org/10.1093/bioinformatics/btad034 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Badelt, Stefan
Lorenz, Ronny
Hofacker, Ivo L
DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title_full DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title_fullStr DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title_full_unstemmed DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title_short DrTransformer: heuristic cotranscriptional RNA folding using the nearest neighbor energy model
title_sort drtransformer: heuristic cotranscriptional rna folding using the nearest neighbor energy model
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889959/
https://www.ncbi.nlm.nih.gov/pubmed/36655786
http://dx.doi.org/10.1093/bioinformatics/btad034
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