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Quantifying the chemical beauty of drugs

Nature Chemistry volume 4, pages 90–98 (2012)Cite this article

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Abstract

Drug-likeness is a key consideration when selecting compounds during the early stages of drug discovery. However, evaluation of drug-likeness in absolute terms does not reflect adequately the whole spectrum of compound quality. More worryingly, widely used rules may inadvertently foster undesirable molecular property inflation as they permit the encroachment of rule-compliant compounds towards their boundaries. We propose a measure of drug-likeness based on the concept of desirability called the quantitative estimate of drug-likeness (QED). The empirical rationale of QED reflects the underlying distribution of molecular properties. QED is intuitive, transparent, straightforward to implement in many practical settings and allows compounds to be ranked by their relative merit. We extended the utility of QED by applying it to the problem of molecular target druggability assessment by prioritizing a large set of published bioactive compounds. The measure may also capture the abstract notion of aesthetics in medicinal chemistry.

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Figure 1: Histograms of eight selected molecular properties for a set of 771 orally absorbed small molecule drugs.
Figure 2: Benchmarking of QED against other measures of drug-likeness.
Figure 3: Chemical aesthetics.
Figure 4: Structural diversity networks.

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Acknowledgements

This research received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement N° 223461 and the Scottish Universities Life Sciences Alliance. We thank J. Overington for providing the DrugStore data, R. Brenk for the provision of SMARTS for structural alerts and I. Carruthers for assistance with DrugStore database queries. We also thank the chemistry community of AstraZeneca for participating in the chemistry survey.

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Authors and Affiliations

  1. Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dundee, DD1 5EH, UK

    G. Richard Bickerton, Jérémy Besnard & Andrew L. Hopkins

  2. Gaia Paolini Ltd, 29 High Street, Bridge, CT4 5JZ, Canterbury, UK

    Gaia V. Paolini

  3. DECS Computational Compound Sciences, Computational Chemistry, AstraZeneca R&D Mölndal, Mölndal, S-431 83, Sweden

    Sorel Muresan

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  1. G. Richard Bickerton
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Contributions

A.L.H. conceived the approach and designed the algorithm. G.R.B. implemented the algorithm, performed the calculations, identified the functions and performed the analysis. G.V.P. developed the use of Shannon entropy as the weighting scheme, J.B. wrote the Pipeline Pilot implementation, S.M. coordinated the survey of AstraZeneca chemists, A.L.H and G.R.B. co-wrote the manuscript and G.R.B. produced the figures. All authors commented on the manuscript.

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Correspondence to Andrew L. Hopkins.

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The authors declare no competing financial interests.

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Bickerton, G., Paolini, G., Besnard, J. et al. Quantifying the chemical beauty of drugs. Nature Chem 4, 90–98 (2012). https://doi.org/10.1038/nchem.1243

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