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

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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.
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Non-gated Ion Channels01:24

Non-gated Ion Channels

Ion channels are specialized proteins on the plasma membrane that allow charged ions to pass down their electrochemical gradient. Their main function is to maintain the membrane potential which is critical for cell viability. These channels are either gated or non-gated and can transport more than a thousand ions within milliseconds for the cellular event to occur.
Compared to the gated ion channels, the non-gated channels, also known as leakage or passive channels, have no gating mechanism.
Antiarrhythmic Drugs: Class III Agents as Potassium Channel Blockers01:12

Antiarrhythmic Drugs: Class III Agents as Potassium Channel Blockers

Class III antiarrhythmic drugs are a group of medications that can prolong action potentials in the heart. They achieve this by blocking potassium channels or enhancing inward currents from sodium channels. However, these drugs have a unique property of "reverse use-dependence," which is most pronounced at slower heart rates and can lead to torsades de pointes—a specific type of arrhythmia. However, it is essential to note that excessive QT interval prolongation—a measure of the heart's...
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion, mediated...

You might also read

Related Articles

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

Sort by
Same author

Case-malformed signal detection and prioritisation using EUROmediCAT data for pharmacovigilance in pregnancy.

British journal of clinical pharmacology·2026
Same author

Gabapentin and Pregabalin Use in First Trimester of Pregnancy and Risk of Specific Congenital Anomalies: An IMI ConcePTION European Case-Malformed Control Study.

Drug safety·2026
Same author

Glucoerucin, Glucosinolate From Brassicaceae Vegetables, Improves the Metabolic Profile in a Murine Model of Diet-Induced Obesity.

Phytotherapy research : PTR·2026
Same author

Dercum Disease: Exploratory Therapeutic Approaches in the Absence of Standardized Medical Treatment-A Single Center Case Series.

Life (Basel, Switzerland)·2026
Same author

The EUROmediCAT Network and Databases: A Resource for Pharmacovigilance in Pregnancy.

Pharmacoepidemiology and drug safety·2026
Same author

Hydroxyl carboxylic acid receptor-2 modulation as an emerging pathway for chronic pain management.

Neural regeneration research·2026

Related Experiment Video

Updated: Jun 21, 2026

High-throughput Screening for Small-molecule Modulators of Inward Rectifier Potassium Channels
10:07

High-throughput Screening for Small-molecule Modulators of Inward Rectifier Potassium Channels

Published on: January 27, 2013

Predictive models, based on classification algorithms, for compounds potentially active as mitochondrial

Alessio Coi1, Anna Maria Bianucci, Vincenzo Calderone

  • 1Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.

Bioorganic & Medicinal Chemistry
|July 15, 2009
PubMed
Summary

Researchers developed QSAR models to identify cardioprotective agents targeting heart mitochondrial ATP-sensitive potassium channels (mito-K(ATP) channels). These models aid in designing new drugs to prevent heart injury from ischemia/reperfusion events.

More Related Videos

A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors
10:28

A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors

Published on: August 17, 2019

Assessment of Open Probability of the Mitochondrial Permeability Transition Pore in the Setting of Coenzyme Q Excess
07:35

Assessment of Open Probability of the Mitochondrial Permeability Transition Pore in the Setting of Coenzyme Q Excess

Published on: June 1, 2022

Related Experiment Videos

Last Updated: Jun 21, 2026

High-throughput Screening for Small-molecule Modulators of Inward Rectifier Potassium Channels
10:07

High-throughput Screening for Small-molecule Modulators of Inward Rectifier Potassium Channels

Published on: January 27, 2013

A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors
10:28

A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors

Published on: August 17, 2019

Assessment of Open Probability of the Mitochondrial Permeability Transition Pore in the Setting of Coenzyme Q Excess
07:35

Assessment of Open Probability of the Mitochondrial Permeability Transition Pore in the Setting of Coenzyme Q Excess

Published on: June 1, 2022

Area of Science:

  • Cardiovascular Pharmacology
  • Medicinal Chemistry
  • Computational Chemistry

Background:

  • Heart mitochondrial ATP-sensitive potassium channels (mito-K(ATP) channels) are crucial for ischemic preconditioning's self-defense mechanism.
  • Activating these channels with exogenous molecules offers a promising strategy to mitigate myocardial injury from ischemia/reperfusion.

Purpose of the Study:

  • To develop Quantitative Structure-Activity Relationship (QSAR) models for classifying cardioprotective agents.
  • To identify novel benzopyran derivatives with potential anti-ischemic properties.

Main Methods:

  • Synthesis of 4-spiro-substituted benzopyran derivatives.
  • Computation of molecular descriptors using CODESSA and E-Dragon software.
  • Development of classification QSAR models using machine learning approaches.

Main Results:

  • Two distinct sets of validated QSAR models were generated.
  • Models demonstrated high accuracy in discriminating between cardioprotective and non-cardioprotective compounds.
  • Successful validation on training, test, and additional prediction sets.

Conclusions:

  • The developed QSAR models are reliable tools for designing new cardioprotective agents.
  • These models can effectively screen chemical libraries for novel therapeutic candidates.
  • The study supports the potential of benzopyran derivatives as anti-ischemic drugs.