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Related Concept Videos

Riboswitches01:56

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Riboswitches are non-coding mRNA domains that regulate the transcription and translation of downstream genes without the help of proteins. Riboswitches bind directly to a metabolite and can form unique stem-loop or hairpin structures in response to the amount of the metabolite present. They have two distinct regions – a metabolite-binding aptamer and an expression platform.
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The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
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Related Experiment Video

Updated: Feb 8, 2026

Preparation of Multifunctional Silk-Based Microcapsules Loaded with DNA Plasmids Encoding RNA Aptamers and Riboswitches
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Predicting Cotranscriptional Folding Kinetics For Riboswitch.

Ting-Ting Sun1,2, Chenhan Zhao2, Shi-Jie Chen2

  • 1Department of Physics , Zhejiang University of Science and Technology , Hangzhou 310023 , P. R. China.

The Journal of Physical Chemistry. B
|July 10, 2018
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Summary

This study introduces a new helix-based model for predicting RNA folding during transcription. The model accurately forecasts RNA folding pathways and kinetics, validated by experiments with E. coli SRP RNA and pbuE riboswitch.

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Area of Science:

  • Computational Biology
  • Molecular Biology
  • Biophysics

Background:

  • RNA folding is crucial for gene regulation and function.
  • Cotranscriptional folding, occurring during RNA synthesis, presents unique kinetic challenges.
  • Predicting these dynamic processes requires sophisticated computational models.

Purpose of the Study:

  • To develop a novel helix-based transition rate model for sampling cotranscriptional RNA conformational ensembles.
  • To predict cotranscriptional folding kinetics and pathways accurately.
  • To provide a new computational tool for understanding RNA folding dynamics.

Main Methods:

  • Development of a helix-based transition rate model.
  • Application of the model to E. coli Signal Recognition Particle (SRP) RNA and pbuE riboswitch.
  • Comparison of model predictions with experimental data, including SHAPE-seq and single-molecule pulling experiments.

Main Results:

  • The model reliably predicts cotranscriptional folding pathways and population kinetics for E. coli SRP RNA, aligning with SHAPE-seq data.
  • For the pbuE riboswitch, the model predicts force-dependent transcriptional termination and distinct folding pathways with and without adenine.
  • The model identified force-induced structural transitions and conformational switches, with residence times matching experimental observations.

Conclusions:

  • The developed model offers a reliable method for predicting cotranscriptional RNA folding kinetics and pathways.
  • Results provide insights into RNA functions, such as gene expression regulation by riboswitches.
  • The model serves as a valuable tool for quantitative predictions in RNA biophysics and molecular biology.