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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 18, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

On setting up and assessing docking simulations for virtual screening.

Jacek Biesiada¹, Aleksey Porollo, Jaroslaw Meller

¹Biomedical Informatics, Children's Hospital Research Foundation, Cincinnati, OH, USA.

Methods in Molecular Biology (Clifton, N.J.)

|September 8, 2012

Summary

This summary is machine-generated.

This chapter details computational screening methods for drug discovery using small molecule docking. It covers software, protocols, and hit re-ranking strategies for efficient virtual screening pipelines.

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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Area of Science:

Computational chemistry
Drug discovery
cheminformatics

Background:

Small molecule docking and virtual screening are crucial in modern drug discovery.
These computational methods complement and accelerate experimental drug development pipelines.

Purpose of the Study:

To describe software packages and protocols for setting up computational screening.
To discuss methods for assessing and re-ranking screening results.
To focus on public domain software for drug development.

Main Methods:

Utilizing specific software packages for virtual screening.
Implementing docking programs with compound libraries.
Applying consensus- and clustering-based approaches for hit assessment.

Main Results:

Efficient setup of computational screening pipelines is achievable.
Tailored implementation of virtual screening may be needed for different platforms.
Public domain packages offer viable solutions for drug development.

Conclusions:

The described methods streamline virtual screening in drug discovery.
Effective assessment and re-ranking of docked compounds enhance hit identification.
Focus on accessible tools supports broader application in drug development.