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Drug Discovery: Overview

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 Targets

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: Overview

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...

Structure-Activity Relationships and Drug Design

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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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Updated: Jun 12, 2026

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

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

Published on: December 11, 2016

Discovering drug targets through the web.

David S Wishart¹

¹Departments of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8.

Comparative Biochemistry and Physiology. Part D, Genomics & Proteomics

|May 21, 2010

Summary

Computer-based in silico drug-target discovery is revolutionizing traditional experimental methods. This review highlights freely available bioinformatics tools for identifying drug targets for various diseases.

Area of Science:

Bioinformatics
Computational Biology
Genomics and Proteomics

Background:

Traditional drug-target discovery relies on labor-intensive wet-bench experiments.
Advances in high-throughput sequencing and profiling generate vast amounts of disease-associated data.
The data deluge necessitates computational approaches for efficient drug-target identification.

Purpose of the Study:

To review in silico methods for drug-target discovery.
To highlight freely available web-based bioinformatics resources.
To demonstrate the application of these tools for identifying targets for endogenous and exogenous diseases.

Main Methods:

Utilizing web-accessible sequence databases.
Employing automated genome annotation tools.

More Related Videos

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

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

Published on: December 1, 2020

Related Experiment Videos

Last Updated: Jun 12, 2026

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

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

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

Published on: December 1, 2020

Leveraging text mining and integrated drug/sequence databases.

Main Results:

Demonstrated the feasibility of computer-based drug-target identification.
Showcased a variety of accessible bioinformatics tools.
Provided a framework for identifying drug targets for genetic, epigenetic, and infectious diseases.

Conclusions:

In silico drug-target discovery offers a powerful complement to traditional experimental approaches.
Freely available bioinformatics resources enable efficient identification of potential drug targets.
Computational methods are increasingly vital for modern drug discovery pipelines.