Evidence map›Paper›PMID 29072147›Full record

ArticleBMC bioinformatics2017

Tractable RNA-ligand interaction kinetics.

Felix Kühnl, Peter F Stadler, Sebastian Will

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding.Journal of chemical theory and computation · 2022
    Article
  2. Design of Artificial Riboswitches as Biosensors.Sensors (Basel, Switzerland) · 2017
    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

3 authors.

Felix KühnlDepartment of Computer Science and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstr. 16-18, Leipzig, D-04107, Germany.
Peter F StadlerDepartment of Computer Science and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstr. 16-18, Leipzig, D-04107, Germany.
Sebastian WillDepartment of Computer Science and Interdisciplinary Center for Bioinformatics, University Leipzig, Härtelstr. 16-18, Leipzig, D-04107, Germany. will@bioinf.uni-leipzig.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe binding of small ligands to RNA elements can cause substantial changes in the RNA structure. This constitutes an important, fast-acting mechanism of ligand-controlled transcriptional and translational gene regulation implemented by a wide variety of riboswitches. The associated refolding processes often cannot be explained by thermodynamic effects alone. Instead, they are governed by the kinetics of RNA folding. While the computational analysis of RNA folding can make use of well-established models of the thermodynamics of RNA structures formation, RNA-RNA interaction, and RNA-ligand interaction, kinetic effects pose fundamentally more challenging problems due to the enormous size of the conformation space. The analysis of the combined process of ligand binding and structure formation even for small RNAs is plagued by intractably large state spaces. Moreover, the interaction is concentration-dependent and thus is intrinsically non-linear. This precludes the direct transfer of the strategies previously used for the analysis of RNA folding kinetics.

resultsIn our novel, computationally tractable approach to RNA-ligand kinetics, we overcome the two main difficulties by applying a gradient-based coarse graining to RNA-ligand systems and solving the process in a pseudo-first order approximation. The latter is well-justified for the most common case of ligand excess in RNA-ligand systems. We present the approach rigorously and discuss the parametrization of the model based on empirical data. The method supports the kinetic study of RNA-ligand systems, in particular at different ligand concentrations. As an example, we apply our approach to analyze the concentration dependence of the ligand response of the rationally designed, artificial theophylline riboswitch RS3.

conclusionThis work demonstrates the tractability of the computational analysis of RNA-ligand interaction. Naturally, the model will profit as more accurate measurements of folding and binding parameters become available. Due to this work, computational analysis is available to support tasks like the design of riboswitches; our analysis of RS3 suggests strong co-transcriptional effects for this riboswitch. The method used in this study is available online, cf. Section "Availability of data and materials".

Indexed as

DimerizationKineticsLigandsModels, TheoreticalNucleic Acid ConformationProbabilityRNAThermodynamicsLigandsRNARiboswitchesRNA interaction kineticsRNA–ligand interactionRNA secondary structure prediction

Identifiers

PMID29072147
PMCPMC5657077

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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.