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Updated: May 3, 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

Fragment-based lead discovery and design.

Diane Joseph-McCarthy¹, Arthur J Campbell, Gunther Kern

¹Infection Innovative Medicines Unit, AstraZeneca, R&D Boston , 35 Gatehouse Drive, Waltham, Massachusetts 02451, United States.

Journal of Chemical Information and Modeling

|February 5, 2014

Summary

This summary is machine-generated.

Fragment-based lead discovery offers a promising approach in drug development. This review details fragment screening, design strategies, and library evolution for identifying high-quality chemical matter.

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Last Updated: May 3, 2026

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Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

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Area of Science:

Medicinal Chemistry
Drug Discovery
Computational Chemistry

Background:

Fragment-based lead discovery and design (FBLD) is a rapidly advancing field in pharmaceutical research.
Key aspects include hot-spot characterization, fragment screening methodologies, and fragment-based design principles.

Purpose of the Study:

To provide a comprehensive overview of the current state-of-the-art in fragment-based drug discovery.
To explore various fragment-based lead generation strategies and the evolution of fragment libraries.
To highlight the integration of computational approaches with experimental data for efficient chemical matter discovery.

Main Methods:

Discussion of hot-spot characterization techniques.
Review of diverse fragment screening methods.
Exploration of fragment-based design strategies and library development.

Main Results:

Three primary fragment-based lead generation strategies are presented: target characterization via screening, complementary screening to high-throughput screening, and direct fragment-based discovery.
The evolution and development of fragment libraries are detailed.
Integration of computational and experimental data accelerates the discovery of high-quality chemical matter.

Conclusions:

Fragment-based approaches are crucial for modern drug discovery.
Strategic integration of computational and experimental methods enhances lead identification.
The review emphasizes AstraZeneca's successful application of these integrated strategies.