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

12.9K
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...
12.9K
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

76
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...
76
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

2.0K
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...
2.0K
Genetic Screens02:46

Genetic Screens

5.9K
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...
5.9K
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

87
The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
87
Pharmacogenetics of Drug Metabolism: Overview01:27

Pharmacogenetics of Drug Metabolism: Overview

106
Genetic polymorphism in drug metabolism is crucial to the inter-individual variability observed in drug responses. Drug metabolism primarily involves the chemical modification of drugs and other xenobiotics to enhance their elimination by increasing their polarity. Two main classes of enzymes mediate this biotransformation process: Phase I enzymes, primarily cytochrome P450s, catalyze oxidation and reduction reactions, while other enzymes, such as esterases, mediate hydrolysis, and Phase II...
106

You might also read

Related Articles

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

Sort by
Same author

Additive value of polygenic risk and family history for coronary heart disease risk stratification in two diverse US cohorts.

American journal of human genetics·2026
Same author

Implementing a Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease in a Diverse Cohort.

Genetics in medicine : official journal of the American College of Medical Genetics·2026
Same author

Predicting Psychiatric Readmission of Children and Adolescents Using Machine Learning.

Journal of child and adolescent psychopharmacology·2026
Same author

Serum Isolevuglandin IgG Antibody Concentrations Are Increased in Patients with Systemic Lupus Erythematosus and Associated with Lower 24-Hour Blood Pressure.

Frontiers in lupus·2026
Same author

GWAS analysis of a depression cohort defined by an EHR-phenotyping algorithm reveals the role of immune regulations in depression risk.

Frontiers in genetics·2026
Same author

Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.

NPJ digital medicine·2026

Related Experiment Video

Updated: Mar 24, 2026

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

A Mendelian randomization-based drug repurposing pipeline: application to lipid traits and coronary artery disease.

Sergio Mundo1, Monika Grabowska1, Alyson Dickson2

  • 1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.

Medrxiv : the Preprint Server for Health Sciences
|March 23, 2026
PubMed
Summary

We developed a flexible, high-throughput Mendelian randomization (MR) pipeline for drug repurposing. This approach identified six proteins interacting with approved drugs, offering new therapeutic opportunities for atherosclerotic cardiovascular disease.

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
Using Human Induced Pluripotent Stem Cell-derived Hepatocyte-like Cells for Drug Discovery
12:40

Using Human Induced Pluripotent Stem Cell-derived Hepatocyte-like Cells for Drug Discovery

Published on: May 19, 2018

10.8K

Related Experiment Videos

Last Updated: Mar 24, 2026

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
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
Using Human Induced Pluripotent Stem Cell-derived Hepatocyte-like Cells for Drug Discovery
12:40

Using Human Induced Pluripotent Stem Cell-derived Hepatocyte-like Cells for Drug Discovery

Published on: May 19, 2018

10.8K

Area of Science:

  • Genetics and Bioinformatics
  • Pharmacology and Drug Discovery
  • Cardiovascular Disease Research

Background:

  • Drug repurposing accelerates the identification of novel therapeutics by leveraging existing drug data.
  • Current high-throughput drug repurposing methods often lack versatility and rigorous validation.
  • There is a need for robust, flexible, and high-throughput approaches to drug target identification.

Purpose of the Study:

  • To develop and validate a flexible, high-throughput Mendelian randomization (MR)-based pipeline for drug repurposing.
  • To identify and prioritize potential drug targets for atherosclerotic cardiovascular disease (ASCVD).
  • To highlight opportunities for repurposing existing drugs for ASCVD treatment.

Main Methods:

  • A three-stage pipeline was developed: MR-based identification, MR-based validation and prioritization, and drug target application.
  • Stage 1 involved MR analyses to identify proteins (exposures) causally linked to a trait/condition (outcome), with quality control for heterogeneity, pleiotropy, and colocalization.
  • Stage 2 conducted further MR analyses for validation using external cohorts, followed by Stage 3 querying the Drug-Gene Interaction database (DGIdb) for druggable targets.

Main Results:

  • The pipeline was applied to identify drug targets for atherosclerotic cardiovascular disease, using UKB-PPP cis-pQTLs for 2,923 proteins.
  • Causal effects on LDL-C and triglycerides were assessed, with lipid-associated targets validated against a coronary artery disease genome-wide association study.
  • Six proteins interacting with approved drugs were identified, demonstrating significant drug repurposing potential.

Conclusions:

  • The developed MR pipeline offers a versatile and rigorous high-throughput approach for drug repurposing across various clinical traits.
  • The study successfully identified potential drug repurposing candidates for atherosclerotic cardiovascular disease.
  • This methodology facilitates the efficient discovery of novel therapeutic strategies by connecting genetic associations to druggable targets.