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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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The DNA Helix01:07

The DNA Helix

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Deoxyribonucleic acid, or DNA, is the genetic material responsible for passing traits from generation to generation in all organisms and most viruses. DNA is composed of two strands of nucleotides that wind around each other to form a spring-like structure called a double helix. However, the double helix is not perfectly symmetrical. Instead, there are regularly occurring grooves in the structure. The major groove occurs where the sugar-phosphate backbones are relatively far apart. This space...
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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.
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Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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Related Experiment Video

Updated: Nov 30, 2025

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Advances in RNA 3D Structure Modeling Using Experimental Data.

Bing Li1, Yang Cao1, Eric Westhof2

  • 1Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, China.

Frontiers in Genetics
|November 16, 2020
PubMed
Summary
This summary is machine-generated.

Computational modeling enhances RNA structure determination by integrating experimental data. This approach improves accuracy, aiding the understanding of RNA's diverse biological roles.

Keywords:
3D shapeRNA structureRNA-puzzleschemical probingstructure prediction

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Structural Biology

Background:

  • Ribonucleic acid (RNA) is crucial for genetic information storage and diverse biological functions.
  • RNA's function is dictated by its specific three-dimensional conformations.
  • Experimental RNA structure determination is challenging, limiting structural biology insights.

Purpose of the Study:

  • To review experimental methods integrated into RNA structure modeling.
  • To summarize computational approaches utilizing experimental data for RNA structure prediction.
  • To highlight how computational modeling aids experimental RNA structure determination.

Main Methods:

  • Integration of diverse experimental data into computational models.
  • Application of computational modeling techniques for RNA structure prediction.
  • Utilizing high-throughput experimental data for enhanced modeling accuracy.

Main Results:

  • Computational modeling accuracy is dependent on RNA length and structural complexity.
  • Integration of experimental data significantly increases the credibility of computational models.
  • Recent advances enable reliable RNA structure models using high-throughput experimental data.

Conclusions:

  • Computational modeling, augmented by experimental data, is vital for advancing RNA structural biology.
  • This integrated approach overcomes limitations of purely experimental or computational methods.
  • Future research can leverage these advancements for a deeper understanding of RNA functions.