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Large-scale prediction and testing of drug activity on side-effect targets

Abstract

Discovering the unintended ‘off-targets’ that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended ‘side-effect’ targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug–target–adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.

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Figure 1: Predicting off-targets, and their novelty.
Figure 2: Off-target networks.
Figure 3: Target and drug promiscuity.

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Acknowledgements

E.L. is a presidential postdoctoral fellow supported by the Education Office of the Novartis Institutes for Biomedical Research (co-mentors L.U. and B.K.S.). Supported by US National Institutes of Health grants GM71896 (to B.K.S. and J. Irwin), AG002132 (to S. Prusiner and B.K.S.), and GM93456 (to M.J.K.), and by QB3 Rogers Family Foundation ‘Bridging-the-Gap’ Award (to M.J.K.).

Author information

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Authors

Contributions

SEA calculations were undertaken by M.J.K. Target–ADR associations, networks and promiscuity analysis were by E.L. In vitro assays were directed by S.W., J.H. and L.U. PK and PD experiments were conducted by E.W. and P.L. Platelet aggregation study was designed and carried out by L.U. and S.C. Chlorotrianisene solubility and aggregation were conducted by A.K.D. The project was conceived and planned by B.K.S., J.J., D.M. and L.U. Overall analysis and writing was largely by E.L., M.J.K., B.K.S. and L.U. All authors contributed to the manuscript.

Corresponding authors

Correspondence to Jeremy L. Jenkins, Brian K. Shoichet or Laszlo Urban.

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Competing interests

B.K.S. is a founder of SeaChange Pharmaceuticals Inc, a company that uses the SEA technology. The other authors have no competing interests to declare.

Supplementary information

Supplementary Information

This file contains Supplementary Methods, Supplementary Results, Supplementary References, Supplementary Figure 1 and legends for Supplementary Tables 1-8 (see separate file for tables). (PDF 824 kb)

Supplementary Tables

This file contains Supplementary Tables 1-8 (see Supplementary Information file for legends). Each sheet in the workbook corresponds to one table. (XLS 832 kb)

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Lounkine, E., Keiser, M., Whitebread, S. et al. Large-scale prediction and testing of drug activity on side-effect targets. Nature 486, 361–367 (2012). https://doi.org/10.1038/nature11159

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