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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Chemical predictive modelling to improve compound quality
John G Cumming1, Andrew M Davis, Sorel Muresan
1Chemistry Innovation Centre, Discovery Sciences, AstraZeneca R&D, Alderley Park, Macclesfield SK10 4TG, UK.
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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