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Related Experiment Video

Updated: Jun 4, 2026

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Virtual screening for lead discovery.

Yat T Tang¹, Garland R Marshall

¹Center for Computational Biology, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA. yattang@wustl.edu

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

|February 15, 2011

Summary

This summary is machine-generated.

Virtual screening offers a cost-effective alternative to high-throughput screening for identifying potential drug compounds. This method uses molecular docking to accurately predict drug-target interactions and binding conformations for drug discovery.

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Area of Science:

Drug discovery and development
Computational chemistry
Chemical biology

Background:

Small drug-like compounds are crucial for probing biological pathways and designing new drugs.
High-throughput screening (HTS) is common but resource-intensive for identifying lead compounds.
Virtual screening (VS) provides an effective alternative to HTS for prioritizing chemical libraries.

Purpose of the Study:

To provide a practical guide for performing virtual screening.
To demonstrate the use of freely available tools for structure-based lead discovery.
To highlight VS as an efficient method for identifying potential drug candidates.

Main Methods:

Utilizing virtual screening methodologies, including molecular docking and scoring.
Employing freely available software tools for computational drug discovery.
Focusing on structure-based lead discovery approaches.

Main Results:

Virtual screening successfully prioritizes large chemical libraries to identify active compounds.
Molecular docking accurately predicts native binding conformations of compounds to biological targets.
This approach serves as a practical and effective alternative to traditional high-throughput screening.

Conclusions:

Virtual screening is a powerful and accessible tool for identifying drug-like compounds.
The described methods enable efficient structure-based lead discovery.
This approach accelerates the drug discovery process by reducing costs and time.