Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Experimental RNAi02:15

Experimental RNAi

6.2K
RNA interference (RNAi) is a cellular mechanism that inhibits gene expression by suppressing its transcription or activating the RNA degradation process. The mechanism was discovered by Andrew Fire and Craig Mello in 1998 in plants. Today, it is observed in almost all eukaryotes, including protozoa, flies, nematodes, insects, parasites, and mammals. This precise cellular mechanism of gene silencing has been developed into a technique that provides an efficient way to identify and determine the...
6.2K
RNA Interference01:23

RNA Interference

26.1K
RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
26.1K
Nonsense-mediated mRNA Decay02:27

Nonsense-mediated mRNA Decay

10.7K
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,...
10.7K
Types of RNA01:23

Types of RNA

64.0K
Overview
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in the regulation of gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA...
64.0K
Drug Discovery: Overview01:26

Drug Discovery: Overview

8.1K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
8.1K
Riboswitches01:56

Riboswitches

8.2K
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.
The aptamer has high specificity for a particular metabolite which allows riboswitches to specifically regulate...
8.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Polypharmacology-Driven Approach to Alzheimer's Disease and Tauopathies: Rational Design, Synthesis and Characterization of Amino-Pyrazole-Based Multikinase (GSK-3β/FYN-α/DYRK1A) Inhibitors.

Journal of medicinal chemistry·2026
Same author

Critical Assessment of a Structure-Based Pipeline for Targeting the Long Noncoding RNA MALAT1.

Journal of chemical information and modeling·2026
Same author

Targeting RAD51-BRCA2 Interaction to Enhance Synthetic Lethality with Olaparib in Pancreatic Cancer: Development of a Novel Phenyl Furan-Quinoline-Carboxylic Acid Series.

ACS medicinal chemistry letters·2026
Same author

A Metabolites' Interplay Can Modulate DNA Repair by Homologous Recombination.

International journal of molecular sciences·2026
Same author

GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis.

Briefings in bioinformatics·2026
Same author

Correction: Chronic administration of Metformin exerts cytostatic and cytotoxic effects via the PP2A-GSK3β-MCL-1 pathway by inhibiting the tmCLIC1 membrane protein in glioblastoma-initiating cells.

Journal of experimental & clinical cancer research : CR·2026

Related Experiment Video

Updated: Jul 20, 2025

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
07:55

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

3.8K

Computational drug discovery under RNA times.

Mattia Bernetti1,2, Riccardo Aguti1,2, Stefano Bosio1,2

  • 1Computational and Chemical Biology, Italian Institute of Technology, 16152 Genova, Italy.

QRB Discovery
|August 2, 2023
PubMed
Summary

Computational chemists are exploring structure-based drug discovery for RNA targets. This approach faces challenges in RNA-small molecule recognition, selectivity, and ligand properties.

Keywords:
Molecular DockingMolecular Dynamics simulationsRNA selectivityRNA-binding drugsnon-coding RNA

More Related Videos

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes
11:58

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

Published on: January 30, 2019

8.4K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

1.3K

Related Experiment Videos

Last Updated: Jul 20, 2025

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
07:55

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

3.8K
Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes
11:58

Using In Vitro and In-cell SHAPE to Investigate Small Molecule Induced Pre-mRNA Structural Changes

Published on: January 30, 2019

8.4K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

1.3K

Area of Science:

  • Biochemistry and Molecular Biology
  • Medicinal Chemistry
  • Drug Discovery

Background:

  • Ribonucleic acid (RNA) molecules are increasingly recognized for their diverse functional and regulatory roles within cells.
  • RNA-based therapeutics are gaining significant attention in modern medicine.
  • Structure-based approaches have proven successful in identifying small-molecule drugs for protein targets.

Purpose of the Study:

  • To discuss the challenges of applying traditional structure-based drug discovery methods to RNA targets.
  • To explore the specific considerations for small-molecule recognition and binding to RNA.
  • To address the critical aspects of selectivity and the anticipated properties of RNA-targeting ligands.

Main Methods:

  • Computational chemistry perspectives on structure-based drug design.
  • Analysis of molecular recognition principles between small molecules and RNA.
  • Evaluation of selectivity challenges in RNA-targeted drug discovery.
  • Prediction and characterization of potential RNA ligand properties.

Main Results:

  • Extending structure-based approaches to RNA presents unique challenges compared to protein targets.
  • Understanding RNA-small molecule interactions requires specialized considerations for RNA structure and dynamics.
  • Achieving selectivity for specific RNA structures or sequences is a key hurdle.

Conclusions:

  • Computational chemists face distinct challenges when adapting structure-based drug discovery for RNA targets.
  • Further research is needed to refine methods for RNA-small molecule recognition, selectivity, and ligand design.
  • Successful development of RNA-targeted therapeutics will rely on overcoming these computational and chemical hurdles.