Evidence map›Paper›PMID 22359488›Full record

ArticlePLoS computational biology2012

Dynamic energy landscapes of riboswitches help interpret conformational rearrangements and function.

Giulio Quarta, Ken Sin, Tamar Schlick

Abstract read
In one paragraph

Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. RNA Modeling with the Computational Energy Landscape Framework.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  6. Article
  7. Article
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  11. Article
  12. Article
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  14. Article
  15. Single-molecule studies of riboswitch folding.Biochimica et biophysica acta · 2014
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Network Theory Tools for RNA Modeling.WSEAS transactions on mathematics · 2013
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Giulio QuartaDepartment of Chemistry, New York University, New York, New York, United States of America.
Ken Sin
Tamar Schlick

Funding

INSTITUTIONAL CLINICAL AND TRANSLATIONAL SCIENCE AWARDUL1RR029893 · NCRR · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CRONSTEIN, BRUCE NEIL · 2009 to 2011
$17.7M
Modeling RNA Tertiary Structure Folding by a Hierarchical FrameworkR01GM100469 · NIGMS · NEW YORK UNIVERSITY · PI SCHLICK, TAMAR · 2011 to 2014
$1.5M
Computational studies of in vitro selection of RNAsR01GM081410 · NIGMS · NEW YORK UNIVERSITY · PI SCHLICK, TAMAR · 2009 to 2012
$1.2M
Howard Hughes Medical InstituteNCRR NIH HHS 1UL1RR029893NCRR NIH HHS UL1 RR029893NIGMS NIH HHS R01 GM081410NIGMS NIH HHS R01GM081410NIGMS NIH HHS R01 GM100469
6 · The paper itself

Abstract

Riboswitches are RNAs that modulate gene expression by ligand-induced conformational changes. However, the way in which sequence dictates alternative folding pathways of gene regulation remains unclear. In this study, we compute energy landscapes, which describe the accessible secondary structures for a range of sequence lengths, to analyze the transcriptional process as a given sequence elongates to full length. In line with experimental evidence, we find that most riboswitch landscapes can be characterized by three broad classes as a function of sequence length in terms of the distribution and barrier type of the conformational clusters: low-barrier landscape with an ensemble of different conformations in equilibrium before encountering a substrate; barrier-free landscape in which a direct, dominant "downhill" pathway to the minimum free energy structure is apparent; and a barrier-dominated landscape with two isolated conformational states, each associated with a different biological function. Sharing concepts with the "new view" of protein folding energy landscapes, we term the three sequence ranges above as the sensing, downhill folding, and functional windows, respectively. We find that these energy landscape patterns are conserved in various riboswitch classes, though the order of the windows may vary. In fact, the order of the three windows suggests either kinetic or thermodynamic control of ligand binding. These findings help understand riboswitch structure/function relationships and open new avenues to riboswitch design.

Indexed as

Gene Expression RegulationBacterial ProteinsComputational BiologyKineticsLigandsNucleic Acid ConformationNucleotidesProtein BindingProtein ConformationProtein Structure, SecondaryProtein Structure, TertiaryRNAThermodynamicsBacterial ProteinsLigandsNucleotidesRNA

Identifiers

PMID22359488
PMCPMC3280964

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.