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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...

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Related Experiment Video

Updated: May 30, 2026

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

A Fluorescence-based Lymphocyte Assay Suitable for High-throughput Screening of Small Molecules

Published on: March 10, 2017

Virtual high throughput screening in new lead identification.

Preethi Badrinarayan¹, G Narahari Sastry

¹Molecular Modeling Group, Organic Chemical Sciences, Indian Institute of Chemical Technology, Tarnaka, Hyderabad- 500 607, India.

Combinatorial Chemistry & High Throughput Screening

|August 17, 2011

Summary

This summary is machine-generated.

Molecular modeling and virtual high throughput screening (VHTS) accelerate drug discovery by identifying potential lead compounds. Combining computational methods with experimental validation is key for efficient lead optimization and new drug design.

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Area of Science:

Computational chemistry and drug discovery.

Background:

Drug discovery is a significant challenge requiring efficient methods for identifying lead compounds.
Molecular modeling and computational approaches are crucial for rational drug design.

Purpose of the Study:

To review the relevance of molecular modeling and virtual screening in drug discovery.
To highlight the importance of lead optimization and new lead identification strategies.

Main Methods:

Discusses virtual high throughput screening (VHTS) as an efficient approach.
Explains the application of various screening filters: pharmacophore mapping, shape-based, ligand-based, and molecular similarity.
Emphasizes the role of reliable scoring functions for non-bonded interactions.

Main Results:

VHTS and computational methods identify potential lead compounds from large databases.
Integration of computational and experimental approaches facilitates lead identification and optimization.
Examples illustrate lead optimization and new lead design.

Conclusions:

Molecular modeling and VHTS are vital for efficient lead identification.
A combination of screening protocols enhances the reliability of drug discovery efforts.
Developing robust scoring functions is critical for successful drug design.