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

Toxicity Testing in Animals01:23

Toxicity Testing in Animals

195
Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
195
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

1.8K
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...
1.8K
Toxicokinetics: Overview01:21

Toxicokinetics: Overview

299
Studies that assess how a drug is absorbed, distributed, metabolized, and excreted (ADME) at toxic doses are termed toxicokinetics. Understanding toxicokinetics helps predict adverse drug reactions (ADRs) and manage toxicity in humans.Toxicokinetics differs from pharmacokinetics mainly in the dose levels studied, with toxicokinetics focusing on higher toxic doses. The kinetics at these levels can be non-linear due to altered physiological processes. Toxicodynamics examines the relationship...
299
Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

2.0K
Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
2.0K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

479
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
479

You might also read

Related Articles

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

Sort by
Same author

Design of Hyperporous Molecularly Imprinted Thin Films for Ultrasensitive Antibody-Free QCM Detection of a Small-Cell Lung Cancer Biomarker.

ACS sensors·2026
Same author

Untargeted <sup>1</sup>H NMR metabolomics to distinguish milk from different feeding systems for haymilk authentication.

Food research international (Ottawa, Ont.)·2026
Same author

Multivariate analysis of the label-declared nutritional composition of plant-based milk alternatives compared to milk in the Ecuadorian market.

Journal of the science of food and agriculture·2026
Same author

De novo design of anticancer 4-thiazolidinone derivatives: a generative framework shaped by activity cliffs.

Journal of cheminformatics·2026
Same author

Data Fusion Combining High-Resolution Mass Spectrometry and <sup>1</sup>H-NMR Metabolomic Data with Gluten Protein Content to Assess the Impact of Agro-Sustainable Treatments on Durum Wheat.

Molecules (Basel, Switzerland)·2026
Same author

Kolbe radical-initiated electrochemical desulfurization of thioamides under aerobic conditions.

Chemical communications (Cambridge, England)·2026

Related Experiment Video

Updated: Apr 22, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
05:47

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

16.3K

Towards global QSAR model building for acute toxicity: Munro database case study.

Swapnil Chavan1, Ian A Nicholls2, Björn C G Karlsson3

  • 1Bioorganic & Biophysical Chemistry Laboratory, Linnaeus University Centre for Biomaterials Chemistry and Department of Chemistry & Biomedical Sciences, Linnaeus University, Kalmar SE-391 82, Sweden. swapnil.chavan@lnu.se.

International Journal of Molecular Sciences
|October 11, 2014
PubMed
Summary

This study explored developing a global Quantitative Structure-Activity Relationship (QSAR) model for acute toxicity using 436 chemicals. While classification accuracy was moderate, it advanced understanding of toxicity prediction.

More Related Videos

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
14:34

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

247
High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC
11:38

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC

Published on: May 10, 2016

12.4K

Related Experiment Videos

Last Updated: Apr 22, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
05:47

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

16.3K
A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
14:34

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

247
High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC
11:38

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC

Published on: May 10, 2016

12.4K

Area of Science:

  • Computational toxicology
  • Medicinal chemistry
  • Environmental science

Background:

  • Acute toxicity assessment is crucial for chemical safety.
  • Developing global Quantitative Structure-Activity Relationship (QSAR) models aids in predicting chemical hazards.
  • Existing QSAR models often lack broad applicability across diverse chemical structures.

Purpose of the Study:

  • To investigate the feasibility of a global QSAR model for acute toxicity.
  • To classify chemicals into toxicity categories based on experimental LD50 values.
  • To identify molecular descriptors relevant to acute toxicity prediction.

Main Methods:

  • Utilized a dataset of 436 chemicals from the Munro database with experimental LD50 values.
  • Employed Dragon molecular descriptors for QSAR model development.
  • Applied genetic algorithms for descriptor selection.
  • Classified toxicity into three levels (highly toxic, intermediate toxic, low to non-toxic) based on the Globally Harmonized Scheme.
  • Used the k-nearest neighbor (k-NN) classification method.

Main Results:

  • The k-NN model, using 25 molecular descriptors, achieved a non-error rate (NER) of 0.66 for internal prediction and 0.57 for external prediction.
  • The classification performance, while not optimal, provided insights into descriptor-toxicity relationships.
  • Identified specific molecular descriptors correlated with different toxicity levels.

Conclusions:

  • The study represents a step towards developing a global QSAR model for acute toxicity.
  • Further refinement of QSAR models is needed for improved predictive accuracy.
  • Analysis of selected descriptors offers valuable information for understanding the mechanisms of acute toxicity.