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

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 its...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower Kd...
Evolution of New Traits in Microbes01:24

Evolution of New Traits in Microbes

Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.

You might also read

Related Articles

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

Sort by
Same author

Viral Sentry AI-Automated zoonotic surveillance and drug repurposing agent.

Biology methods & protocols·2026
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Integrated Transcriptomic Analysis of S100A8/A9 as a Key Biomarker and Therapeutic Target in Sepsis Pathogenesis and AI Drug Repurposing.

International journal of molecular sciences·2025
Same author

IL-1R2 as a Precision Therapeutic Target in Sepsis: Molecular Insights into Immune Regulation.

Current issues in molecular biology·2025
Same author

Rampant Interkingdom Horizontal Gene Transfer in Pezizomycotina? An Updated Inspection of Anomalous Phylogenies.

International journal of molecular sciences·2025
Same author

Drug Release Nanoparticle System Design: Data Set Compilation and Machine Learning Modeling.

ACS applied materials & interfaces·2025
Same journal

Bioactive Compounds and Mechanistic Insights of Chuanxiong Rhizoma and Angelicae Sinensis Radix in Endometriosis Treatment: A Network Pharmacology and Experimental Validation Study.

Current computer-aided drug design·2026
Same journal

Identification of Potential Compounds from Medicinal Plants using Molecular Docking and Molecular Dynamics Simulation with Special Reference to Autism Spectrum Disorder.

Current computer-aided drug design·2026
Same journal

Molecular Docking, Molecular Dynamics Simulation, DFT, and ADMET Prediction of 3-Carbonyl-3-Hydroxyl-Isoindolin-1-ones, Revealing Potential Inhibitors of MAO-B.

Current computer-aided drug design·2026
Same journal

Drug Repurposing Using Machine Learning and Deep Learning: A Systematic Literature Review.

Current computer-aided drug design·2026
Same journal

Augmented Chemical Language Meets Descriptor Space: A Hybrid Deep-learning Pipeline for Predicting Blood-brain Barrier Penetration of Drug-like Molecules.

Current computer-aided drug design·2026
Same journal

Integrating Network Pharmacology and Molecular Docking to Decipher the Anti-fibrotic Role of Fuzheng Xiezhuo Decoction via NLRP3/TNF-α/IL-6 Pathway in Renal Fibrosis.

Current computer-aided drug design·2026
See all related articles

Related Experiment Video

Updated: May 11, 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

Evolutionary computation and QSAR research.

Vanessa Aguiar-Pulido1, Marcos Gestal, Maykel Cruz-Monteagudo

  • 1Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elvina S/N, 15071 A Coruña, Spain. vaguiar@udc.es

Current Computer-Aided Drug Design
|May 25, 2013
PubMed
Summary
This summary is machine-generated.

Quantitative structure-activity relationship (QSAR) models accelerate drug discovery by predicting molecular activity. This review highlights evolutionary computation methods for building reliable QSAR models and selecting relevant molecular descriptors.

More Related Videos

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

Related Experiment Videos

Last Updated: May 11, 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

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

Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Drug discovery

Background:

  • High throughput screening is crucial for drug discovery.
  • Quantitative structure-activity relationship (QSAR) analysis models molecular activity using descriptors.
  • QSAR models can reduce drug candidate failure by predicting toxicity and pharmacokinetic profiles.

Purpose of the Study:

  • To review evolutionary computation methods for QSAR model development.
  • To focus on variable selection and model building in QSAR.
  • To discuss current and future trends in QSAR feature selection.

Main Methods:

  • Review of evolutionary computation techniques, including genetic algorithms and genetic programming.
  • Exploration of variable selection methods for high-dimensional QSAR data.
  • Analysis of QSAR model building approaches using artificial intelligence and machine learning.

Main Results:

  • Evolutionary computation offers powerful tools for QSAR variable selection and model optimization.
  • Current methods effectively address high-dimensional data challenges in QSAR.
  • Future trends point towards joint and multi-task feature selection for enhanced QSAR models.

Conclusions:

  • Evolutionary computation is vital for developing predictive and reliable QSAR models.
  • Advanced feature selection techniques improve the efficiency and accuracy of QSAR analysis.
  • The integration of evolutionary computation in QSAR is key to accelerating drug discovery.