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Related Concept Videos

RNA Structure01:23

RNA Structure

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Overview
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.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
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RNA Structure01:19

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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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There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
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Nucleic Acid Structure01:25

Nucleic Acid Structure

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The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
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RNA Stability01:53

RNA Stability

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Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
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Updated: Jan 13, 2026

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

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Decoding RNA Structural Ensembles: Energy Landscape Exploration of the TAR Stemloop.

Konstantin Röder1

  • 1Randall Centre for Cell and Molecular Biophysics, King's College London, London WC2R 2LS, United Kingdom.

Journal of Chemical Theory and Computation
|January 6, 2026
PubMed
Summary
This summary is machine-generated.

Discrete path sampling effectively maps complex RNA structural ensembles and activation pathways, aiding therapeutic development. This computational method captures mutational effects without experimental data, revealing transient binding pockets.

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Area of Science:

  • Molecular Biology
  • Computational Biology
  • Biophysics

Background:

  • RNA structural ensembles are challenging to study due to dynamic polymorphism.
  • Current computational and experimental methods have limitations in fully characterizing RNA dynamics.
  • RNA force fields require further development for accurate modeling.

Purpose of the Study:

  • To demonstrate discrete path sampling for comprehensive RNA structural ensemble mapping.
  • To validate the method's ability to capture mutational effects.
  • To reveal complexities in RNA activation pathways and identify novel binding sites.

Main Methods:

  • Energy landscape exploration using discrete path sampling.
  • Computational modeling of RNA structural ensembles (TAR stem-loop and ES2).
  • Validation against experimental observations without incorporating external data.

Main Results:

  • Discrete path sampling successfully mapped complex RNA structural ensembles.
  • The method accurately reproduced experimental findings for TAR stem-loop and ES2.
  • Significant complexity in structural ensembles and activation pathways was revealed.
  • A transient binding pocket emerging during the activation pathway was identified.

Conclusions:

  • Discrete path sampling is a powerful tool for elucidating RNA structural ensembles and dynamics.
  • The approach provides insights into RNA function and can guide therapeutic interventions.
  • Accurate computational modeling of RNA is achievable with advanced sampling techniques.