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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Nature Reviews Drug ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Nature Reviews Drug Discovery
Article . 2004 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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Fragment-based lead discovery

Authors: David C, Rees; Miles, Congreve; Christopher W, Murray; Robin, Carr;

Fragment-based lead discovery

Abstract

Fragment-based lead discovery is gaining momentum in both large pharmaceutical companies and biotechnology laboratories as a complementary approach to traditional screening. This is because fragment-based approaches require significantly fewer compounds to be screened and synthesized, and are showing a high success rate in generating chemical series with lead-like properties. Compared with traditional screening hits, the starting fragments have considerably lower molecular mass, and although the binding interactions of these fragments with a target protein are weak, they are structurally understood through X-ray crystallography or NMR, and they exhibit high 'ligand efficiency'. Here, we use examples from 25 different protein targets to describe chemical strategies that exploit this structural knowledge to rapidly develop fragments into high-affinity leads.

Keywords

Structure-Activity Relationship, Chemistry, Pharmaceutical, Drug Evaluation, Preclinical, Technology, Pharmaceutical, Peptide Fragments

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
704
Top 1%
Top 0.1%
Top 0.1%
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