TY - JOUR
T1 - Computational approaches for RNA structure ensemble deconvolution from structure probing data
AU - Aviran, Sharon
AU - Incarnato, Danny
N1 - Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.
PY - 2022/9/30
Y1 - 2022/9/30
N2 - 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.
AB - 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.
U2 - 10.1016/j.jmb.2022.167635
DO - 10.1016/j.jmb.2022.167635
M3 - Review article
C2 - 35595163
SN - 0022-2836
VL - 434
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
IS - 18
M1 - 167635
ER -