Evidence map›Paper›PMID 25726468›Full record

ArticleMethods in enzymology2015

Using simulations and kinetic network models to reveal the dynamics and functions of riboswitches.

Jong-Chin Lin, Jeseong Yoon, Changbong Hyeon, D Thirumalai

Open access · greenAbstract read
In one paragraph

Article in Methods in enzymology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Riboswitches as Drug Targets for Antibiotics.Antibiotics (Basel, Switzerland) · 2021
    Review
  2. Article
  3. Evaluating riboswitch optimality.Methods in enzymology · 2019
    Article
  4. Predicting Cotranscriptional Folding Kinetics For Riboswitch.The journal of physical chemistry. B · 2018
    Article
  5. Review
  6. Article
  7. Review
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

4 authors at 2 institutions in 2 countries.

Jong-Chin LinInstitute for Physical Science and Technology, University of Maryland, College Park, MD, USA; Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA.
Jeseong YoonSchool of Computational Sciences, Korea Institute for Advanced Study, Seoul Republic of Korea.
Changbong HyeonSchool of Computational Sciences, Korea Institute for Advanced Study, Seoul Republic of Korea. Electronic address: hyeoncb@kias.re.kr.
D ThirumalaiInstitute for Physical Science and Technology, University of Maryland, College Park, MD, USA; Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA.
Korea Institute for Advanced Study · KRUniversity of Maryland, College Park · US

Funding

Computational Approaches to Single Molecule Force SpectroscopyR01GM089685 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI THIRUMALAI, DEVARAJAN · 2010 to 2020
$2.9M
NIGMS NIH HHS GM 089685NIGMS NIH HHS R01 GM089685
6 · The paper itself

Abstract

Riboswitches, RNA elements found in the untranslated region, regulate gene expression by binding to target metaboloites with exquisite specificity. Binding of metabolites to the conserved aptamer domain allosterically alters the conformation in the downstream expression platform. The fate of gene expression is determined by the changes in the downstream RNA sequence. As the metabolite-dependent cotranscriptional folding and unfolding dynamics of riboswitches are the key determinant of gene expression, it is important to investigate both the thermodynamics and kinetics of riboswitches both in the presence and absence of metabolite. Single molecule force experiments that decipher the free energy landscape of riboswitches from their mechanical responses, theoretical and computational studies have recently shed light on the distinct mechanism of folding dynamics in different classes of riboswitches. Here, we first discuss the dynamics of water around riboswitch, highlighting that water dynamics can enhance the fluctuation of nucleic acid structure. To go beyond native state fluctuations, we used the Self-Organized Polymer model to predict the dynamics of add adenine riboswitch under mechanical forces. In addition to quantitatively predicting the folding landscape of add-riboswitch, our simulations also explain the difference in the dynamics between pbuE adenine- and add adenine-riboswitches. In order to probe the function in vivo, we use the folding landscape to propose a system level kinetic network model to quantitatively predict how gene expression is regulated for riboswitches that are under kinetic control.

Indexed as

Gene Expression RegulationModels, MolecularNucleic Acid ConformationRiboswitchAdenineBase SequenceFeedback, PhysiologicalHydrogen BondingKineticsModels, BiologicalMolecular Sequence DataRNA FoldingThermodynamicsWaterAdenineRiboswitchWaterForce spectroscopy of riboswitchesGene expressionKinetic and thermodynamic controlNegative feedback controlPurine and SAM riboswitchesRNA hydration dynamics

Identifiers

PMID25726468
PMCPMC5580269
OpenAlexW2964257097

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.