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

Drug Discovery: Overview01:26

Drug Discovery: Overview

7.9K
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...
7.9K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

720
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...
720
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

6.3K
Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
6.3K
Principles of Drug Action01:24

Principles of Drug Action

6.0K
Drugs are chemical substances that modify biological responses by interacting with macromolecular targets such as receptors, ion channels, transporters, and enzymes. Pharmacodynamics describes the course of action of drugs leading to the physiological effect at a specific site in the body.
Drugs can be agonists or antagonists. Like the endogenous ligands, agonists always bind and activate the target to produce a cellular response. Agonist binding induces a conformational change which in turn...
6.0K
Drug Biotransformation: Overview01:16

Drug Biotransformation: Overview

2.4K
Pharmaceutical substances known as xenobiotics are predominantly lipophilic and nonionized. This enables them to permeate lipid bilayers, such as cell membranes, and interact with intracellular target receptors. Lipophilic drugs have an advantage in crossing biological barriers and reaching their intended sites of action. However, lipophilic drugs often have a restricted capacity for renal expulsion or elimination from the body. When these drugs enter the kidneys and undergo glomerular...
2.4K
Pharmacodynamics: Overview and Principles01:21

Pharmacodynamics: Overview and Principles

1.1K
Pharmacodynamics is a scientific field that delves into drugs' intricate biochemical, cellular, and physiological effects on the human body. The study of pharmacodynamics helps us understand how drugs interact with the body and elicit various responses.
Most drugs' effects result from their interactions with drug receptors or targets within the body. These interactions trigger specific responses at the cellular or systemic level. Drug receptors can be found on the surfaces of cells or...
1.1K

You might also read

Related Articles

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

Sort by
Same author

Sodium Ions Affect GPR17 Conformational States and Functionality.

Proteins·2026
Same author

Structure-Guided Prioritization and Synthesis of New Ligands for GPR17 Receptor.

ACS omega·2026
Same author

Extracellular vesicles (EVs) in neurodevelopment: The emerging role of lipids.

Biochemical pharmacology·2026
Same author

Systems biology-based drug repurposing for neuroinflammation treatment in activated human microglia.

Scientific reports·2026
Same author

Mild Cognitive Impairment Associated with Obstructive Sleep Apnoea: A Pilot Study on Oxygen-Related Plasma Biomarkers and Network Analysis.

Molecular neurobiology·2026
Same author

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

Phytotherapy research : PTR·2026

Related Experiment Video

Updated: Jul 2, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.0K

Drug Mechanism: A bioinformatic update.

Martina Cirinciani1, Eleonora Da Pozzo2, Maria Letizia Trincavelli2

  • 1Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy.

Biochemical Pharmacology
|February 25, 2024
PubMed
Summary

Understanding drug Mechanism of Action (MoA) is key to drug discovery. This review highlights bioinformatics methods, integrating omics data and Machine Learning (ML), for effective MoA analysis.

Keywords:
BioinformaticsDrug Mechanism of ActionDrug developmentMachine LearningOmics dataSystems Biology

More Related Videos

Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease
08:15

Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease

Published on: May 10, 2024

570
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.2K

Related Experiment Videos

Last Updated: Jul 2, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

5.0K
Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease
08:15

Author Spotlight: Network Pharmacology and Molecular Docking to Decipher the Action of Jiawei Shengjiang San Against Diabetic Kidney Disease

Published on: May 10, 2024

570
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

4.2K

Area of Science:

  • Bioinformatics
  • Pharmacology
  • Computational Biology

Background:

  • Drug Mechanism of Action (MoA) elucidation is critical for understanding drug activity.
  • Traditional experimental methods generate vast amounts of data.
  • Increasing omics data and computational power necessitate advanced analytical approaches.

Purpose of the Study:

  • To provide an updated review of bioinformatics methods for drug MoA analysis.
  • To focus on in silico solutions integrating multi-omics data and Machine Learning (ML).
  • To analyze the advantages, disadvantages, and applications of these methods.

Main Methods:

  • Review of bioinformatics methodologies for drug MoA studies.
  • Focus on multi-omics data integration within biochemical networks.
  • Application of Machine Learning (ML) algorithms.

Main Results:

  • Analysis of various input data types for MoA studies.
  • Evaluation of the strengths and weaknesses of different bioinformatics approaches.
  • Discussion of applications in cancer drug development, antibiotics discovery, and drug repurposing.

Conclusions:

  • Bioinformatics approaches, particularly those using multi-omics data and ML, are essential for modern drug MoA studies.
  • These methods offer productive avenues for drug discovery in key research areas.
  • Continued development of in silico solutions is vital for advancing pharmacological research.