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The roles of structural dynamics in the cellular functions of RNAs

Nature Reviews Molecular Cell Biology volume 20, pages 474–489 (2019)Cite this article

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Abstract

RNAs fold into 3D structures that range from simple helical elements to complex tertiary structures and quaternary ribonucleoprotein assemblies. The functions of many regulatory RNAs depend on how their 3D structure changes in response to a diverse array of cellular conditions. In this Review, we examine how the structural characterization of RNA as dynamic ensembles of conformations, which form with different probabilities and at different timescales, is improving our understanding of RNA function in cells. We discuss the mechanisms of gene regulation by microRNAs, riboswitches, ribozymes, post-transcriptional RNA modifications and RNA-binding proteins, and how the cellular environment and processes such as liquid–liquid phase separation may affect RNA folding and activity. The emerging RNA-ensemble–function paradigm is changing our perspective and understanding of RNA regulation, from in vitro to in vivo and from descriptive to predictive.

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Fig. 1: RNA structural changes enable biological functions.
Fig. 2: Dynamic ensembles describe the roles of RNA structural changes.
Fig. 3: Organizing principles of RNA ensembles.
Fig. 4: Ensemble-based modelling of RNA activity in vitro.
Fig. 5: The effect of cellular environments on RNA behaviour.
Fig. 6: RNA ensembles in cells.

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Acknowledgements

The authors thank A. Mustoe, B. Liu, A. K. Rangadurai, N. Orlovsky and other members of the Al-Hashimi laboratory for critical input and help in making figures, and R. Das (Stanford University, CA, USA), P. Z. Qin (USC, Los Angeles, CA, USA)), Q. Zhang (UNC Chapel Hill, NC, USA), A. Bartesaghi (Duke University, NC, USA), S. Bonilla (Stanford University, CA, USA) and T. Oas (Duke University, NC, USA) for critical input. This work was supported by the US National Institutes of Health (P50 GM103297 and P01 GM0066275 to H.M.A. and D.H.; F31 GM119306 to L.R.G.).

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Nature Reviews Molecular Cell Biology thanks A. Laederach, J. Lucks and K. Weeks for their contribution to the peer review of this work.

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Authors and Affiliations

  1. Department of Biochemistry, Duke University School of Medicine, Durham, NC, USA

    Laura R. Ganser, Megan L. Kelly & Hashim M. Al-Hashimi

  2. Department of Biochemistry, Stanford ChEM-H Chemistry, Engineering, and Medicine for Human Health, Stanford University, Stanford, CA, USA

    Daniel Herschlag

  3. Department of Chemical Engineering, Stanford ChEM-H Chemistry, Engineering, and Medicine for Human Health, Stanford University, Stanford, CA, USA

    Daniel Herschlag

  4. Department of Chemistry, Stanford ChEM-H Chemistry, Engineering, and Medicine for Human Health, Stanford University, Stanford, CA, USA

    Daniel Herschlag

  5. Department of Chemistry, Duke University, Durham, NC, USA

    Hashim M. Al-Hashimi

Authors
  1. Laura R. Ganser
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  2. Megan L. Kelly
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  3. Daniel Herschlag
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  4. Hashim M. Al-Hashimi
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Contributions

All authors made substantial contributions to the discussion of content and the editing of the manuscript before submission. L.R.G. and H.M.A. wrote the manuscript.

Corresponding author

Correspondence to Hashim M. Al-Hashimi.

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Competing interests

H.M.A. is an adviser to and holds an ownership interest in Nymirum Inc., an RNA-based drug discovery company. Some of the technology used to generate ensembles described in this Review has been licensed to Nymirum, Inc. The other authors declare no competing interests.

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Supplementary information

Glossary

Secondary structures

RNA structures described in terms of nucleotide pairing.

Ribozymes

RNA structures capable of catalysing specific biochemical reactions such as cleaving the RNA phosphodiester backbone.

Riboswitches

RNA structures typically found in 5′-untranslated regions of bacterial mRNAs, which regulate transcription or translation through a ligand-induced conformational change.

Tertiary structures

Typically long-range interactions between distal RNA structural elements or nucleotides involved in base pairing.

Quaternary assemblies

Higher-order organizations of RNA molecules in complex with other molecules, including with other RNAs, proteins and DNA.

Boltzmann distribution

A probability distribution that describes the likelihood that a system will be in a specific state based on the relative energy of that state and the temperature of the system.

Dynamic ensembles

The many conformations adopted by an RNA molecule over time and their abundance or probabilities of formation as described by the Boltzmann distribution.

Free energy landscape

A depiction of the free energy of every conformational state in a macromolecule.

Ground state

The lowest-energy and therefore most populated structural conformation of an RNA molecule.

RNA junction topology

In a structured RNA molecule, the lengths of the different single strands that adjoin helices.

Four-way junction

A structural element in which four helices come together.

Native secondary structure

The lowest-energy and therefore most populated secondary structure adopted by a particular RNA molecule.

Non-native secondary structures

Alternative secondary structures of RNA that are of higher energy than the native structure, but still form in solution with non-negligible probability.

Apical loop

A single-stranded RNA loop of variable length at the end of a helical region.

Coaxial conformations

Conformations in which two helices stack on each other across inter-helical junctions.

Base triple

A structural element in which three nucleotides are hydrogen bonded to one another.

Inter-helical dynamics

Conformational changes at junctions between two helices that lead to changes in the bend and twist angles between the two helices, thus greatly affecting the global conformation of the RNA.

Tetraloops

Apical loops composed of four nucleotides.

Sugar pucker

A conformational description of the ribose sugar ring in nucleic acids. The sugar pucker tends to be predominately C3′-endo for the helical A-form RNA conformation.

Computational docking

The use of computational algorithms to predict the lowest-energy conformation for the binding of a small molecule to a receptor molecule (RNA or protein).

Ensemble redistribution

Changes in the abundance of two or more conformations in the RNA ensemble, which are induced by a cellular cue such as the binding of a protein or ligand or by post-transcriptional modifications.

Tertiary receptors

Regions of RNA molecules that are involved in tertiary, long-range interactions.

Nucleic acid force fields

The physical models used to computationally predict nucleic acid dynamics in molecular dynamics simulations.

Tautomerization

The interconversion between two molecules with the same molecular formula but different connectivity.

Metastable conformations

RNA conformations that are only stable within a short range of nucleotide lengths during co-transcriptional folding.

SHAPE

Selective 1′-hydroxyl acylation analysed by primer extension (SHAPE) is a common chemical-probing technique used to elucidate RNA secondary structures.

Click chemistry

Simple and robust chemical reactions commonly used to covalently join specific substrates.

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Ganser, L.R., Kelly, M.L., Herschlag, D. et al. The roles of structural dynamics in the cellular functions of RNAs. Nat Rev Mol Cell Biol 20, 474–489 (2019). https://doi.org/10.1038/s41580-019-0136-0

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