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

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

1.7K
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
1.7K
Local Anesthetics: Chemistry and Structure-Activity Relationship01:30

Local Anesthetics: Chemistry and Structure-Activity Relationship

6.5K
Local anesthetics (LAs) are drugs that induce a temporary loss of sensation in a limited body area, preventing pain. Cocaine was the first local anesthetic discovered in the late 19th century. Cocaine is a benzoic acid ester obtained from the leaves of coca shrubs and was often used for its psychotropic effects. Cocaine was first isolated in 1860 by Albert Niemann. Sigmund Freud studied the physiological actions of cocaine. Carl Koller later introduced it into clinical practice in 1884 as a...
6.5K
Cholinergic Antagonists: Chemistry and Structure-Activity Relationship01:29

Cholinergic Antagonists: Chemistry and Structure-Activity Relationship

2.7K
Cholinergic antagonists bind to cholinergic receptors and limit the effects of acetylcholine and other cholinergic agonists. Based on the specific cholinergic receptor affinity, these antagonists are classified as muscarinic or nicotinic. Anticholinergics interrupt parasympathetic innervations while sympathetic innervations remain uninterrupted. Muscarinic antagonists are also called 'muscarinic antagonists', 'antimuscarinics', or 'parasympatholytics'. Nicotinic...
2.7K
Adrenergic Agonists: Chemistry and Structure-Activity Relationship01:16

Adrenergic Agonists: Chemistry and Structure-Activity Relationship

3.9K
Adrenergic agonists' structure-activity relationship (SAR) determines their selectivity and efficacy. These agonists comprise a phenylethylamine moiety with an aromatic ring and an ethylamine side chain.
Aromatic ring substitutions: Substituting the aromatic ring with –OH groups at positions 3 and 4 yields catecholamines (e.g., epinephrine), which have a high affinity for adrenoceptors. Hydrogen bonding between –OH groups and receptors enhances adrenergic activity.
Separation of...
3.9K
Indirect-Acting Cholinergic Agonists: Chemistry and Structure-Activity Relationship01:29

Indirect-Acting Cholinergic Agonists: Chemistry and Structure-Activity Relationship

942
Indirect-acting cholinergic agonists are agents that interact with the acetylcholinesterase enzyme in the synaptic cleft, preventing the breakdown of acetylcholine into choline and acetate. Consequently, the concentration of acetylcholine in the synaptic cleft increases. These agonists can be classified into reversible and irreversible inhibitors based on their duration of action.
Reversible inhibitors display short to medium durations of action. Short-acting agents include simple alcohols with...
942
Direct-Acting Cholinergic Agonists: Chemistry and Structure-Activity Relationship01:22

Direct-Acting Cholinergic Agonists: Chemistry and Structure-Activity Relationship

2.1K
Cholinergic agonists or cholinomimetics mimic the action of acetylcholine to stimulate the parasympathetic nervous system. They are categorized into direct-acting and indirect-acting agents. The direct-acting cholinergic drugs induce the parasympathetic response by directly binding to the muscarinic or nicotine receptors. In comparison, the indirect-acting cholinergic drugs prevent acetylcholine hydrolysis, indirectly contributing to the extended parasympathetic response.
The direct-acting...
2.1K

You might also read

Related Articles

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

Sort by
Same author

Drug Repurposing Against Cestode Fatty Acid Binding Proteins Through Integrated Virtual Screening and In Vitro Validation.

ChemMedChem·2026
Same author

Lipid Nanoparticles with Stiripentol and Cannabidiol Oil: From Rational Optimization to Preclinical Characterization.

Pharmaceutics·2026
Same author

Advancing AI-driven drug discovery: an interview with Professor Alan Talevi.

Expert opinion on drug discovery·2026
Same author

Advancing <i>Trypanosoma cruzi</i> N-myristoyltransferase as a drug target for Chagas disease through <i>in silico</i> discovery and biochemical evaluation.

Frontiers in molecular biosciences·2026
Same author

In vitro and in vivo studies on the activity and selectivity of butoconazole in experimental infection by Trypanosoma cruzi.

Memorias do Instituto Oswaldo Cruz·2026
Same author

Application of Data-Centric Supervised Machine Learning to Predict Phenotypic Activity Against Clinically Relevant Stages of <i>Trypanosoma cruzi</i>.

Pharmaceutics·2025

Related Experiment Video

Updated: Jan 25, 2026

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

2.2K

Quantitative structure-activity relationship models for compounds with anticonvulsant activity.

Carolina L Bellera1,2, Alan Talevi1,2

  • 1a Laboratory of Bioactive Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences , University of La Plata (UNLP) , La Plata, Buenos Aires , Argentina.

Expert Opinion on Drug Discovery
|May 11, 2019
PubMed
Summary

Quantitative structure-activity relationships (QSAR) offer promising avenues for discovering novel antiepileptic drugs, as current treatments remain largely symptomatic. Advanced QSAR approaches can guide the development of more effective epilepsy therapies.

Keywords:
Antiepileptic drugsDrug DiscoveryDrug designEpilepsyMolecular DescriptorsPhenotypic Virtual ScreeningPhenotypic responseQSARSystemic QSARTarget-focused approximationsVirtual Screening

More Related Videos

Quantitative Methods to Study Protein Arginine Methyltransferase 1-9 Activity in Cells
08:11

Quantitative Methods to Study Protein Arginine Methyltransferase 1-9 Activity in Cells

Published on: August 7, 2021

4.6K
NMR-Based Activity Assays for Determining Compound Inhibition, IC50 Values, Artifactual Activity, and Whole-Cell Activity of Nucleoside Ribohydrolases
10:24

NMR-Based Activity Assays for Determining Compound Inhibition, IC50 Values, Artifactual Activity, and Whole-Cell Activity of Nucleoside Ribohydrolases

Published on: June 30, 2019

10.5K

Related Experiment Videos

Last Updated: Jan 25, 2026

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

2.2K
Quantitative Methods to Study Protein Arginine Methyltransferase 1-9 Activity in Cells
08:11

Quantitative Methods to Study Protein Arginine Methyltransferase 1-9 Activity in Cells

Published on: August 7, 2021

4.6K
NMR-Based Activity Assays for Determining Compound Inhibition, IC50 Values, Artifactual Activity, and Whole-Cell Activity of Nucleoside Ribohydrolases
10:24

NMR-Based Activity Assays for Determining Compound Inhibition, IC50 Values, Artifactual Activity, and Whole-Cell Activity of Nucleoside Ribohydrolases

Published on: June 30, 2019

10.5K

Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Pharmacology

Background:

  • Third-generation antiepileptic drugs (AEDs) have not significantly improved global seizure control rates, indicating a need for novel therapeutic strategies.
  • Current AEDs are primarily symptomatic treatments, highlighting the necessity for disease-modifying or more efficacious seizure control agents.
  • Quantitative Structure-Activity Relationships (QSAR) provide a computational framework for drug discovery and optimization.

Purpose of the Study:

  • To review and analyze existing Quantitative Structure-Activity Relationship (QSAR) models for antiepileptic drugs (AEDs) and their targets in epilepsy research.
  • To assess whether reported QSAR studies employ classic or non-classic approaches and utilize descriptive or predictive methodologies.
  • To focus on predictive QSAR studies with experimental validation, specifically those identifying and testing novel active compounds in vitro and/or in vivo.

Main Methods:

  • Systematic review of literature reporting QSAR models for antiepileptic drug discovery.
  • Categorization of QSAR models based on methodology (classic vs. non-classic) and application (descriptive vs. predictive).
  • In-depth analysis of predictive QSAR studies with experimental validation, including in vitro and in vivo testing of identified novel compounds.

Main Results:

  • The review identifies various QSAR models applied to antiepileptic drug discovery, with varying degrees of methodological sophistication and validation.
  • A subset of studies demonstrates the successful application of predictive QSAR in identifying novel AED candidates with experimentally confirmed activity.
  • Significant opportunities exist for enhancing AED discovery through advanced QSAR applications.

Conclusions:

  • Quantitative Structure-Activity Relationship (QSAR) methodology holds substantial potential for accelerating the discovery of more efficacious antiepileptic drugs.
  • Future QSAR applications should incorporate advanced techniques like systemic, multi-target, and multi-scale QSAR, alongside ensemble and deep learning methods.
  • Focusing QSAR efforts on novel drug targets and modern screening tools is crucial for advancing epilepsy treatment.