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Review
. 2013 Dec;12(12):948-62.
doi: 10.1038/nrd4128.

Chemical predictive modelling to improve compound quality

John G Cumming  1 , Andrew M Davis, Sorel Muresan, Markus Haeberlein, Hongming Chen
Affiliations
Review

Chemical predictive modelling to improve compound quality

John G Cumming et al. Nat Rev Drug Discov. 2013 Dec.

Abstract

The 'quality' of small-molecule drug candidates, encompassing aspects including their potency, selectivity and ADMET (absorption, distribution, metabolism, excretion and toxicity) characteristics, is a key factor influencing the chances of success in clinical trials. Importantly, such characteristics are under the control of chemists during the identification and optimization of lead compounds. Here, we discuss the application of computational methods, particularly quantitative structure-activity relationships (QSARs), in guiding the selection of higher-quality drug candidates, as well as cultural factors that may have affected their use and impact.

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