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Related Concept Videos

Drug Discovery: Overview01:26

Drug Discovery: Overview

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...
Drug Biotransformation: Overview01:16

Drug Biotransformation: Overview

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...
Drug Biotransformation: Overview01:28

Drug Biotransformation: Overview

Biotransformation, also known as drug metabolism, is a vital physiological process that chemically alters drugs, facilitating their elimination from the body and terminating their action. This process involves two main phases: phase I and phase II reactions. Phase I reactions, including oxidation, reduction, and hydrolysis, introduce or unmask polar functional groups on the drug molecule, thereby increasing its water solubility. By enhancing water solubility, the drug becomes more hydrophilic...
Prodrugs01:30

Prodrugs

Prodrugs are a class of pharmaceutical compounds that undergo a biotransformation process within the body to be converted into a pharmacologically active drug. Prodrugs are designed to improve the therapeutic properties of the parent drug, such as enhancing bioavailability, increasing stability, or reducing toxicity. The concept of prodrugs revolves around modifying the chemical structure of the original drug to make it more effective or convenient for administration.
Prodrugs help overcome...
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

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.
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Drug Nomenclature01:17

Drug Nomenclature

During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that the same...

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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

Network-based drug repositioning.

Zikai Wu1, Yong Wang, Luonan Chen

  • 1Business School, University of Shanghai for Science and Technology, Shanghai, China.

Molecular Biosystems
|March 16, 2013
PubMed
Summary
This summary is machine-generated.

This study unifies drug repositioning and drug combination using network biology. It highlights how omics data and network analysis reveal new drug roles and synergistic combinations for drug discovery.

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

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Last Updated: May 13, 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

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

Area of Science:

  • Computational Biology
  • Network Science
  • Pharmacology

Background:

  • Network-based computational biology, integrating biomolecular interactions and omics data, has advanced drug development, including drug repositioning and combination therapies.
  • Drug repositioning addresses high failure rates and long development times in drug discovery by identifying new therapeutic uses for existing drugs.
  • Drug combination therapies aim to overcome drug resistance and exploit synergistic effects against diseases.

Purpose of the Study:

  • To unify drug repositioning and drug combination under a network perspective, treating combination therapy as a form of repositioning.
  • To emphasize the role of high-throughput genome-wide data in large-scale drug repositioning.
  • To organize and analyze existing network-based computational methods for single drug repositioning and drug combination.

Main Methods:

  • Utilizing high-throughput genome-wide data to capture molecular interplay and network structures.
  • Developing network-based computational methods to bridge molecular profiles and phenotypes.
  • Categorizing existing methods into single drug repositioning and drug combination based on data sources.

Main Results:

  • Demonstrated that omics data integration and network analysis can uncover novel drug interactions and therapeutic strategies.
  • Provided a structured overview of network-based computational methods for drug repositioning and combination.
  • Identified key data sources driving these computational approaches.

Conclusions:

  • Network-based approaches offer a powerful framework for both drug repositioning and combination therapy discovery.
  • Integrating diverse omics data is crucial for understanding complex drug-target interactions.
  • Further research into network-based methods holds significant promise for accelerating drug discovery and development.