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

Modified-Release Drug Delivery Systems: Site-Targeted01:24

Modified-Release Drug Delivery Systems: Site-Targeted

Site-targeted drug delivery systems enhance therapeutic efficacy while minimizing systemic toxicity and treatment costs. Unlike conventional methods, these systems ensure precise drug delivery, improving bioavailability and reducing side effects. Targeted drug delivery is classified into three levels. First-order targeting directs drugs to the capillary beds of specific organs or tissues. Second-order targets specific cell types, such as tumor cells, using receptor-mediated interactions.
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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...
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

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...
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...
Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase01:11

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...

You might also read

Related Articles

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

Sort by
Same author

Reliable quantification of renal function from frozen blood samples.

medRxiv : the preprint server for health sciences·2026
Same author

Comorbidity sequence, sex, and APOE-genotype forecast Alzheimer's disease diagnosis.

Frontiers in medicine·2026
Same author

Twelve-year trends in sex and age of patients with COPD and chronic respiratory failure undergoing pulmonary rehabilitation.

European journal of internal medicine·2026
Same author

Why almost all ML models for medicine are wrong-and what we need for evidence-based medical AI.

International journal of medical informatics·2026
Same author

Cost effectiveness of routine utilization of atypically-pronucleated zygotes in in vitro fertilization cycles with preimplantation genetic testing.

Fertility and sterility·2026
Same author

A Quantitative Assessment of Upper Limb Motor Function Across Disease Stages in Hereditary Transthyretin Amyloidosis.

Journal of the peripheral nervous system : JPNS·2026

Related Experiment Video

Updated: May 9, 2026

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

Network-based target ranking for polypharmacological therapies.

Francesca Vitali1, Francesca Mulas, Pietro Marini

  • 1Dipartimento di Ingegneria Industriale e dell'Informazione, University of Pavia, Pavia, Italy.

Journal of Biomedical Informatics
|July 16, 2013
PubMed
Summary

This study introduces a novel network-based computational method to identify synergistic drug combinations for complex diseases. It effectively ranks potential multi-target therapeutic strategies using protein-protein interaction networks.

Keywords:
Drug discoveryNetwork-based bioinformaticsPPI networkPolypharmacologyTarget ranking

Related Experiment Videos

Last Updated: May 9, 2026

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

Area of Science:

  • Computational biology
  • Systems pharmacology
  • Drug discovery

Background:

  • The shift towards multi-target drug discovery for complex diseases necessitates new methods for evaluating synergistic combinations.
  • Polypharmacology offers a paradigm to address declining pharmaceutical research productivity.
  • Protein-protein interaction (PPI) networks are valuable for integrating and analyzing complex disease data.

Purpose of the Study:

  • To propose a novel computational network-based approach for identifying multicomponent synergistic agents.
  • To develop an efficient method for evaluating and ranking synergistic drug combinations.
  • To demonstrate the application of the method in identifying novel therapeutic targets for Type 2 Diabetes Mellitus.

Main Methods:

  • Utilizing topological features of protein-protein interaction (PPI) networks specific to a given complex disease.
  • Developing a computational approach to identify potential combinations of hit targets within the PPI network.
  • Ranking identified target combinations based on a calculated synergistic score.

Main Results:

  • The proposed method successfully identified novel target candidates for complex diseases.
  • The efficacy of the identified targets was validated through literature analysis.
  • The approach demonstrated feasibility and efficiency in identifying multicomponent synergistic agents.

Conclusions:

  • The network-based computational approach provides a feasible and efficient strategy for identifying synergistic drug combinations.
  • This method aids in discovering novel therapeutic targets for complex diseases, exemplified by Type 2 Diabetes Mellitus.
  • The approach supports the transition to multi-target, multi-drug strategies in modern drug discovery.