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

12.6K
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...
12.6K
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

59
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
59
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

1.9K
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...
1.9K
Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

109
Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
109
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.9K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
14.9K
Biopharmaceutics and Pharmacokinetics: Overview01:28

Biopharmaceutics and Pharmacokinetics: Overview

4.8K
Understanding drugs, drug products, and their performance in pharmaceutical science is pivotal. Drugs, whether simple molecules or complex compounds, are designed to interact with the body's biological systems to diagnose, treat, or prevent diseases. Drug products include various delivery systems such as tablets, capsules, injections, and inhalers. The performance of these drug products is gauged by their ability to deliver the active ingredient to the desired site of action at the...
4.8K

You might also read

Related Articles

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

Sort by
Same author

Retroviruses and Cancer: Coevolution and Genetic Exchanges Between the Viral and the Host Genomes.

Biology·2026
Same author

Stoichiometry-induced differential selection on codon optimization among ribosomal protein genes in bacterial species.

Molecular biology and evolution·2026
Same author

Evolution of Translational Machinery in Fast- and Slow-Growing Bacteria.

Microorganisms·2026
Same author

The Branching Process: A General Conceptual Framework for Addressing Current Ecological and Evolutionary Questions.

Life (Basel, Switzerland)·2025
Same author

Clinical characteristics of nephrocalcinosis in a tertiary children's hospital.

Frontiers in pediatrics·2025
Same author

On Rooting and Dating Viral Trees With a Changing Evolutionary Rate Following Host-Switching.

Genome biology and evolution·2025

Related Experiment Video

Updated: Mar 12, 2026

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

5.6K

Bioinformatics and Drug Discovery.

Xuhua Xia1

  • 1Department of Biology, Faculty of Science, University of Ottawa, Ottawa, Ontario, Canada.

Current Topics in Medicinal Chemistry
|November 17, 2016
PubMed
Summary
This summary is machine-generated.

Bioinformatics accelerates drug discovery by analyzing high-throughput data for target identification and screening. It aids in understanding side effects and predicting resistance, enhancing drug repurposing and development.

Keywords:
Drug candidateDrug screeningDrug targetEpigeneticsGenomicsProteomicsStructureTranscriptomics

More Related Videos

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

1.1K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.3K

Related Experiment Videos

Last Updated: Mar 12, 2026

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

5.6K
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

1.1K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.3K

Area of Science:

  • Computational biology and bioinformatics
  • Genomics and transcriptomics
  • Structural biology and cheminformatics

Background:

  • Bioinformatic analysis is crucial for advancing drug discovery and repurposing.
  • High-throughput data types (genomic, transcriptomic, proteomic) are vital for mechanism-based drug development.
  • Advancements in structural biology and databases enable realistic protein-ligand docking and virtual screening.

Purpose of the Study:

  • To present a conceptual framework for collecting high-throughput data in drug discovery.
  • To summarize the utility and potential of mining diverse biological data for drug development.
  • To outline limitations and propose refined analysis methods for bioinformatic data in drug discovery.

Main Methods:

  • Leveraging high-throughput data (genomic, epigenetic, transcriptomic, proteomic, etc.).
  • Utilizing structural biology tools like homology modeling and protein structure simulation.
  • Employing large databases of small molecules and metabolites for virtual screening and docking.

Main Results:

  • Bioinformatics significantly accelerates drug target identification, screening, and refinement.
  • High-throughput data analysis aids in characterizing drug side effects and predicting resistance.
  • Integrated analysis of diverse data types enhances mechanism-based drug discovery and repurposing.

Conclusions:

  • Bioinformatic analysis of high-throughput data is indispensable for modern drug discovery.
  • Continued refinement of data analysis methods and software is essential for maximizing potential.
  • The integration of structural and chemical data with omics data offers promising avenues for future drug development.