Computational Approaches for RNA Structure Ensemble Deconvolution from Structure Probing Data.
RNA structure ensemble
SHAPE
clustering
partition function
thermodynamics
Journal
Journal of molecular biology
ISSN: 1089-8638
Titre abrégé: J Mol Biol
Pays: Netherlands
ID NLM: 2985088R
Informations de publication
Date de publication:
30 09 2022
30 09 2022
Historique:
received:
14
03
2022
revised:
29
04
2022
accepted:
05
05
2022
pubmed:
21
5
2022
medline:
16
9
2022
entrez:
20
5
2022
Statut:
ppublish
Résumé
RNA structure probing experiments have emerged over the last decade as a straightforward way to determine the structure of RNA molecules in a number of different contexts. Although powerful, the ability of RNA to dynamically interconvert between, and to simultaneously populate, alternative structural configurations, poses a nontrivial challenge to the interpretation of data derived from these experiments. Recent efforts aimed at developing computational methods for the reconstruction of coexisting alternative RNA conformations from structure probing data are paving the way to the study of RNA structure ensembles, even in the context of living cells. In this review, we critically discuss these methods, their limitations and possible future improvements.
Identifiants
pubmed: 35595163
pii: S0022-2836(22)00215-7
doi: 10.1016/j.jmb.2022.167635
pii:
doi:
Substances chimiques
RNA
63231-63-0
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
167635Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.