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Related Concept Videos

RNA Structure01:23

RNA Structure

78.8K
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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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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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
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Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

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The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
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Related Experiment Video

Updated: Jan 15, 2026

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
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When does molecular dynamics improve RNA models? Insights from CASP15 and practical guidelines.

Chandran Nithin1, Smita P Pilla1, Sebastian Kmiecik1

  • 1University of Warsaw, Biological and Chemical Research Centre, Faculty of Chemistry, Laboratory of Computational Biology, Zwirki i Wigury 101, Warsaw 02-089, Poland.

Computational and Structural Biotechnology Journal
|October 13, 2025
PubMed
Summary
This summary is machine-generated.

Molecular dynamics (MD) simulations offer modest improvements for refining high-quality RNA structure models, particularly by stabilizing base pairs. However, poorly predicted models rarely benefit and longer simulations can reduce accuracy.

Keywords:
CASP 15Molecular DynamicsRNA Structure predictionRNA modeling

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Area of Science:

  • Biomolecular modeling
  • Computational biology
  • Structural bioinformatics

Background:

  • Molecular dynamics (MD) simulations are increasingly used for refining biomolecular models.
  • The utility of MD for RNA structure prediction requires systematic evaluation.

Purpose of the Study:

  • To benchmark the impact of MD simulations on RNA models within the CASP15 framework.
  • To determine optimal MD simulation parameters for RNA structure refinement.

Main Methods:

  • Systematic benchmarking of MD simulation effects on 61 RNA models from CASP15.
  • Utilized Amber software with the RNA-specific χOL3 force field.
  • Evaluated models subjected to short (10-50 ns) and long (>50 ns) simulations.

Main Results:

  • Short MD simulations (10-50 ns) provided modest improvements for high-quality starting models, enhancing stability of stacking and non-canonical base pairs.
  • Poorly predicted models showed little to no benefit and often deteriorated after MD simulations.
  • Longer simulations (>50 ns) generally led to structural drift and reduced model fidelity.

Conclusions:

  • MD simulations are most effective for fine-tuning reliable RNA models and assessing their stability.
  • MD is not a universal corrective method for RNA structure prediction errors.
  • Guidelines are provided for selecting input models and optimal simulation lengths for RNA refinement.