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Related Concept Videos

RNA Structure01:23

RNA Structure

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The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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Related Experiment Video

Updated: Feb 26, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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FRET-guided selection of RNA 3D structures.

Mirko Weber1, Felix Erichson1, Maciej Antczak2,3

  • 1Laserinstitut Hochschule Mittweida, University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany.

Nucleic Acids Research
|February 25, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a Förster resonance energy transfer (FRET)-guided method to predict RNA 3D structures. The approach successfully identifies RNA conformational states by integrating computational modeling with single-molecule FRET experiments.

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Area of Science:

  • Biomolecular modeling
  • Structural biology
  • RNA biophysics

Background:

  • Predicting RNA structures is challenging due to complex energy landscapes and conformational diversity.
  • Accurate RNA structural collections are crucial for understanding binding and folding.
  • Existing computational methods struggle with the heterogeneity of large RNA molecules.

Purpose of the Study:

  • To develop and validate a Förster resonance energy transfer (FRET)-guided strategy for predicting RNA 3D structures.
  • To identify RNA conformational states consistent with single-molecule FRET (smFRET) experimental data.
  • To integrate computational RNA modeling with experimental biophysical techniques.

Main Methods:

  • Predicted 3D RNA structures using RNAComposer, FARFAR2, and AlphaFold3.
  • Validated models based on Watson-Crick base-pairing and an eRMSD threshold.
  • Computed dye pair accessible contact volumes using FRETraj to predict FRET distributions.
  • Compared predicted FRET distributions with experimental smFRET data to identify compatible states.

Main Results:

  • Successfully predicted RNA 3D structures that are consistent with experimental smFRET data.
  • Demonstrated that in silico predicted RNA structures can reproduce experimental transfer efficiencies.
  • Identified specific RNA conformational states compatible with observed FRET states.
  • Validated the utility of a FRET-guided workflow for analyzing flexible RNA motifs.

Conclusions:

  • The FRET-guided workflow enables accurate prediction of RNA conformational states.
  • This integrative approach enhances the study of RNA folding and dynamics.
  • The method provides a foundation for capturing diverse conformational states in flexible RNA motifs.