From static structures to dynamic landscapes: cryo-EM redefines RNA biology
Abstract
RNA molecules perform diverse biological functions by dynamically exploring multiple conformational states rather than adopting a single static structure. Capturing these ensembles is a challenge in molecular biology. Recent advances in cryoEM are now transforming this landscape by enabling the visualization of RNA molecules across a broad spectrum of functionally relevant conformations at near atomic resolution. Here, we examine how cryoEM is reshaping RNA structural biology changing focus from the analysis of static structures to dynamic conformational landscapes. Through 8 representative case studies we illustrate how cryoEM has revealed previously inaccessible mechanisms of RNA motion, including folding processes, ligand-dependent switching, and cooperative assembly. We specifically discuss emerging experimental and computational approaches that address and overcome the challenges associated with studying dynamic RNAs, particularly in construct design, sample preparation, vitrification, and data analysis. These novel methods resolve conformational variability and enable the reconstruction of discrete and continuous RNA conformational landscapes from cryoEM data, highlighting how structural heterogeneity can be harnessed to extract functional insights. Looking forward, the integration of cryoEM with complementary biophysical techniques and time resolved methodologies promises to bridge structural and temporal resolution, to routinely derive experimental molecular movies of RNA in action. These advances will not only deepen our understanding of RNA biology but also provide new opportunities for RNA targeted therapeutics and the rational design of dynamic RNA-based nanodevices. By connecting structural snapshots into coherent dynamic models, cryoEM is establishing a framework for quantitative descriptions of RNA energy landscapes and their functional roles.
Versions
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BibTeX
@misc{jadhav2026from,
title = {{From static structures to dynamic landscapes: cryo-EM redefines RNA biology}},
author = {Shekhar Jadhav and Spandan Saha and Qingbin Shang and Marco Marcia},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.01132},
eprint = {2609.01132},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.01132},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - From static structures to dynamic landscapes: cryo-EM redefines RNA biology
AU - Shekhar Jadhav
AU - Spandan Saha
AU - Qingbin Shang
AU - Marco Marcia
PY - 2026
DA - 2026/10/27
PB - arXiv
DO - 10.48550/arxiv.2609.01132
UR - https://arxiv.org/abs/2609.01132
AB - RNA molecules perform diverse biological functions by dynamically exploring multiple conformational states rather than adopting a single static structure. Capturing these ensembles is a challenge in molecular biology. Recent advances in cryoEM are now transforming this landscape by enabling the visualization of RNA molecules across a broad spectrum of functionally relevant conformations at near atomic resolution. Here, we examine how cryoEM is reshaping RNA structural biology changing focus from the analysis of static structures to dynamic conformational landscapes. Through 8 representative case studies we illustrate how cryoEM has revealed previously inaccessible mechanisms of RNA motion, including folding processes, ligand-dependent switching, and cooperative assembly. We specifically discuss emerging experimental and computational approaches that address and overcome the challenges associated with studying dynamic RNAs, particularly in construct design, sample preparation, vitrification, and data analysis. These novel methods resolve conformational variability and enable the reconstruction of discrete and continuous RNA conformational landscapes from cryoEM data, highlighting how structural heterogeneity can be harnessed to extract functional insights. Looking forward, the integration of cryoEM with complementary biophysical techniques and time resolved methodologies promises to bridge structural and temporal resolution, to routinely derive experimental molecular movies of RNA in action. These advances will not only deepen our understanding of RNA biology but also provide new opportunities for RNA targeted therapeutics and the rational design of dynamic RNA-based nanodevices. By connecting structural snapshots into coherent dynamic models, cryoEM is establishing a framework for quantitative descriptions of RNA energy landscapes and their functional roles.
ER -