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RNA Structure

RNA Structure

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...

RNA Structure

RNA Structure

RNA Structure

RNA Structure

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.
Different Types of RNA Have the Same Basic Structure
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...

Nucleic Acid Structure

Nucleic Acid Structure

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...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

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Related Experiment Video

Updated: Mar 27, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Building RNA coarse-grained force fields: Design principles and training strategies.

Wenfei Li¹, Shi-Jie Chen¹

¹Department of Physics, Department of Biochemistry, and Institute of Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.

Biophysical Journal

|March 25, 2026

Summary

This summary is machine-generated.

Coarse-grained (CG) models enhance computational efficiency for RNA structure analysis. This review covers CG model development, force field design, and the integration of structural information, highlighting machine learning

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Area of Science:

Computational biology
Biophysics
Structural biology

Background:

All-atom models for RNA are computationally expensive for large systems.
Coarse-grained (CG) models offer enhanced efficiency while preserving accuracy.
Understanding RNA structures and biological pathways requires efficient computational tools.

Purpose of the Study:

To review force field development for RNA coarse-grained models.
To discuss design principles and training strategies for RNA CG force fields.
To explore integrating structural information into CG models.

Main Methods:

Discussion of force field development considerations for RNA CG models.
Analysis of design principles and training strategies for CG force fields.
Exploration of integrating sequence-dependent effects, secondary, and tertiary structures.

Main Results:

Identified key considerations in RNA CG force field development.
Highlighted strategies for building accurate and efficient RNA CG models.
Showcased the integration of diverse structural features into CG models.

Conclusions:

Coarse-grained models are crucial for studying large RNA systems.
Machine learning presents a promising avenue for future RNA CG model development.
Enhanced CG models will advance RNA structure and pathway research.