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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...
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...
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.
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 its...
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...
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...

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Related Experiment Video

Updated: May 20, 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

Systems biology visualization tools for drug target discovery.

Tianxiao Huan1, Xiaogang Wu, Jake Y Chen

  • 1Shandong University, College of Life Sciences, Shandong, JN 250100, PR China.

Expert Opinion on Drug Discovery
|July 25, 2012
PubMed
Summary

Systems biology visualization tools aid drug discovery by revealing patterns in complex Omics data. These tools help model diseases, identify targets, and improve drug development success rates.

Related Experiment Videos

Last Updated: May 20, 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

Area of Science:

  • Computational biology
  • Bioinformatics
  • Drug discovery

Background:

  • Post-genome era necessitates molecular systems-level analysis for drug development.
  • Complex Omics data requires advanced tools for pattern extraction and biological insight.
  • Systems biology visualization aids in understanding disease mechanisms and drug profiles.

Purpose of the Study:

  • To review the development and application of information visualization tools in systems biology for drug discovery.
  • To provide a framework and data representation schemes for visual data analysis in systems biology.
  • To highlight the utility of visualization tools in early-stage drug discovery tasks.

Main Methods:

  • Review of existing literature on visualization tools for systems biology.
  • Description of a framework for visual data analysis.
  • Focus on applications in disease modeling, target identification, and lead identification.
  • Inclusion of case studies and practical lessons learned.

Main Results:

  • Readers will gain an understanding of available visualization tools for systems biology.
  • Readers will learn how these tools can accelerate drug development processes.
  • The review demonstrates the practical application of visualization in drug discovery.

Conclusions:

  • Information visualization tools are crucial for navigating the complexity of systems biology.
  • These tools can uncover hidden properties within data, enhancing drug discovery success.
  • Effective use of visualization tools improves the identification of drug targets and leads.