Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2007 Jan;25(1):71-5.
doi: 10.1038/nbt1273.

Structure-based maximal affinity model predicts small-molecule druggability

Alan C Cheng  1 , Ryan G Coleman, Kathleen T Smyth, Qing Cao, Patricia Soulard, Daniel R Caffrey, Anna C Salzberg, Enoch S Huang
Affiliations

Structure-based maximal affinity model predicts small-molecule druggability

Alan C Cheng et al. Nat Biotechnol. 2007 Jan.

Abstract

Lead generation is a major hurdle in small-molecule drug discovery, with an estimated 60% of projects failing from lack of lead matter or difficulty in optimizing leads for drug-like properties. It would be valuable to identify these less-druggable targets before incurring substantial expenditure and effort. Here we show that a model-based approach using basic biophysical principles yields good prediction of druggability based solely on the crystal structure of the target binding site. We quantitatively estimate the maximal affinity achievable by a drug-like molecule, and we show that these calculated values correlate with drug discovery outcomes. We experimentally test two predictions using high-throughput screening of a diverse compound collection. The collective results highlight the utility of our approach as well as strategies for tackling difficult targets.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

Publication types

LinkOut - more resources