Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Predicting new molecular targets for known drugs

Nature volume 462, pages 175–181 (2009)Cite this article

Abstract

Although drugs are intended to be selective, at least some bind to several physiological targets, explaining side effects and efficacy. Because many drug–target combinations exist, it would be useful to explore possible interactions computationally. Here we compared 3,665 US Food and Drug Administration (FDA)-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-hydroxytryptamine (5-HT) transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug–target associations were confirmed, five of which were potent (<100 nM). The physiological relevance of one, the drug N,N-dimethyltryptamine (DMT) on serotonergic receptors, was confirmed in a knockout mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Drug–target networks, before and after predicting off-targets.
Figure 2: Testing new off-target activities.
Figure 3: Discovered off-targets network.

Similar content being viewed by others

References

  1. Ehrlich, P. The theory and practice of chemotherapy. Folia Serologica 7, 697–714 (1911)

    CAS  Google Scholar 

  2. Peterson, R. T. Chemical biology and the limits of reductionism. Nature Chem. Biol. 4, 635–638 (2008)

    Article  CAS  Google Scholar 

  3. Nobeli, I., Favia, A. D. & Thornton, J. M. Protein promiscuity and its implications for biotechnology. Nature Biotechnol. 27, 157–167 (2009)

    Article  CAS  Google Scholar 

  4. Marona-Lewicka, D. & Nichols, D. E. Further evidence that the delayed temporal dopaminergic effects of LSD are mediated by a mechanism different than the first temporal phase of action. Pharmacol. Biochem. Behav. 87, 453–461 (2007)

    Article  CAS  Google Scholar 

  5. Marona-Lewicka, D. & Nichols, D. E. WAY 100635 produces discriminative stimulus effects in rats mediated by dopamine D4 receptor activation. Behav. Pharmacol. 20, 114–118 (2009)

    Article  CAS  Google Scholar 

  6. Roth, B. L., Sheffler, D. J. & Kroeze, W. K. Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia. Nature Rev. Drug Discov. 3, 353–359 (2004)

    Article  CAS  Google Scholar 

  7. Rix, U. et al. Chemical proteomic profiles of the BCR-ABL inhibitors imatinib, nilotinib, and dasatinib reveal novel kinase and nonkinase targets. Blood 110, 4055–4063 (2007)

    Article  CAS  Google Scholar 

  8. Hopkins, A. L. Network pharmacology. Nature Biotechnol. 25, 1110–1111 (2007)

    Article  CAS  Google Scholar 

  9. Roth, B. L. Drugs and valvular heart disease. N. Engl. J. Med. 356, 6–9 (2007)

    Article  CAS  Google Scholar 

  10. Bajorath, J. Computational analysis of ligand relationships within target families. Curr. Opin. Chem. Biol. 12, 352–358 (2008)

    Article  CAS  Google Scholar 

  11. Oprea, T. I., Tropsha, A., Faulon, J. L. & Rintoul, M. D. Systems chemical biology. Nature Chem. Biol. 3, 447–450 (2007)

    Article  CAS  Google Scholar 

  12. Newman, D. J. Natural products as leads to potential drugs: an old process or the new hope for drug discovery? J. Med. Chem. 51, 2589–2599 (2008)

    Article  CAS  Google Scholar 

  13. Siegel, M. G. & Vieth, M. Drugs in other drugs: a new look at drugs as fragments. Drug Discov. Today 12, 71–79 (2007)

    Article  CAS  Google Scholar 

  14. Miller, J. R. et al. A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore. Proc. Natl Acad. Sci. USA 106, 1737–1742 (2009)

    Article  ADS  CAS  Google Scholar 

  15. Walsh, C. T. & Fischbach, M. A. Repurposing libraries of eukaryotic protein kinase inhibitors for antibiotic discovery. Proc. Natl Acad. Sci. USA 106, 1689–1690 (2009)

    Article  ADS  CAS  Google Scholar 

  16. Young, D. W. et al. Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nature Chem. Biol. 4, 59–68 (2008)

    Article  ADS  CAS  Google Scholar 

  17. Wagner, B. K. et al. Large-scale chemical dissection of mitochondrial function. Nature Biotechnol. 26, 343–351 (2008)

    Article  CAS  Google Scholar 

  18. Krejsa, C. M. et al. Predicting ADME properties and side effects: the BioPrint approach. Curr. Opin. Drug Discov. Dev. 6, 470–480 (2003)

    CAS  Google Scholar 

  19. Campillos, M., Kuhn, M., Gavin, A. C., Jensen, L. J. & Bork, P. Drug target identification using side-effect similarity. Science 321, 263–266 (2008)

    Article  ADS  CAS  Google Scholar 

  20. Paolini, G. V., Shapland, R. H. B., van Hoorn, W. P., Mason, J. S. & Hopkins, A. L. Global mapping of pharmacological space. Nature Biotechnol. 24, 805–815 (2006)

    Article  CAS  Google Scholar 

  21. Keiser, M. J. et al. Relating protein pharmacology by ligand chemistry. Nature Biotechnol. 25, 197–206 (2007)

    Article  CAS  Google Scholar 

  22. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990)

    Article  CAS  Google Scholar 

  23. Hert, J., Keiser, M. J., Irwin, J. J., Oprea, T. I. & Shoichet, B. K. Quantifying the relationships among drug classes. J. Chem. Inf. Model. 48, 755–765 (2008)

    Article  CAS  Google Scholar 

  24. Nigsch, F., Bender, A., Jenkins, J. L. & Mitchell, J. B. Ligand-target prediction using Winnow and naive Bayesian algorithms and the implications of overall performance statistics. J. Chem. Inf. Model. 48, 2313–2325 (2008)

    Article  CAS  Google Scholar 

  25. Schuffenhauer, A. et al. An ontology for pharmaceutical ligands and its application for in silico screening and library design. J. Chem. Inf. Comput. Sci. 42, 947–955 (2002)

    Article  CAS  Google Scholar 

  26. Olah, M. et al. in Chemical Biology: From Small Molecules to Systems Biology and Drug Design (eds Schreiber, S. L., Kapoor, T. M. & Wess, G.) 760–786 (Wiley-VCH, 2007)

    Book  Google Scholar 

  27. Lomasney, J. W. et al. Molecular cloning and expression of the cDNA for the α1A-adrenergic receptor. The gene for which is located on human chromosome 5. J. Biol. Chem. 266, 6365–6369 (1991)

    CAS  PubMed  Google Scholar 

  28. Fontanilla, D. et al. The hallucinogen N,N-dimethyltryptamine (DMT) is an endogenous sigma-1 receptor regulator. Science 323, 934–937 (2009)

    Article  ADS  CAS  Google Scholar 

  29. Su, T. P., Hayashi, T. & Vaupel, D. B. When the endogenous hallucinogenic trace amine N,N-dimethyltryptamine meets the sigma-1 receptor. Sci. Signal. 2, pe12 (2009)

    Article  Google Scholar 

  30. Roth, B. L., Lopez, E., Patel, S. & Kroeze, W. K. The multiplicity of serotonin receptors: uselessly diverse molecules or an embarrasment of riches? Neuroscientist 6, 252–262 (2000)

    Article  CAS  Google Scholar 

  31. Smith, R. L., Canton, H., Barrett, R. J. & Sanders-Bush, E. Agonist properties of N,N-dimethyltryptamine at serotonin 5-HT2A and 5-HT2C receptors. Pharmacol. Biochem. Behav. 61, 323–330 (1998)

    Article  CAS  Google Scholar 

  32. Kohen, R. et al. Cloning, characterization, and chromosomal localization of a human 5-HT6 serotonin receptor. J. Neurochem. 66, 47–56 (1996)

    Article  CAS  Google Scholar 

  33. Pierce, P. A. & Peroutka, S. J. Hallucinogenic drug interactions with neurotransmitter receptor binding sites in human cortex. Psychopharmacology (Berl.) 97, 118–122 (1989)

    Article  CAS  Google Scholar 

  34. Abbas, A. I. et al. PSD-95 is essential for hallucinogen and atypical antipsychotic drug actions at serotonin receptors. J. Neurosci. 29, 7124–7136 (2009)

    Article  CAS  Google Scholar 

  35. Kurland, A. A., Mc, C. K. & Michaux, W. W. Clinical trial of haloanisone (R-2028) with hospitalized psychiatric patients. J. New Drugs 2, 352–360 (1962)

    Article  CAS  Google Scholar 

  36. Gankina, E. M. et al. Effect of some antihistamine preparations on binding of 3H-mepyramine and 3H-cimetidine to histamine receptors in rat brain. Pharm. Chem. J 26, 373–376 (1992)

    Article  Google Scholar 

  37. Gankina, E. M. et al. The effect of antihistaminic preparations on the binding of labelled mepyramine, ketanserin and quinuclidinyl benzilate in the rat brain [in Russian with English abstract]. Eksp. Klin. Farmakol. 56, 22–24 (1993)

    CAS  PubMed  Google Scholar 

  38. Heykants, J. et al. On the pharmacokinetics of domperidone in animals and man. IV. The pharmacokinetics of intravenous domperidone and its bioavailability in man following intramuscular, oral and rectal administration. Eur. J. Drug Metab. Pharmacokinet. 6, 61–70 (1981)

    Article  CAS  Google Scholar 

  39. FDA. Talk Paper: FDA Warns Against Women Using Unapproved Drug, Domperidone, to Increase Milk Production &lt; http://www.fda.gov/Drugs/DrugSafety/InformationbyDrugClass/ucm173886.htm&gt; (7 June 2004)

  40. Stork, D. et al. State dependent dissociation of HERG channel inhibitors. Br. J. Pharmacol. 151, 1368–1376 (2007)

    Article  CAS  Google Scholar 

  41. Michelson, D. et al. Interruption of selective serotonin reuptake inhibitor treatment. Double-blind, placebo-controlled trial. Br. J. Psychiatry 176, 363–368 (2000)

    Article  CAS  Google Scholar 

  42. Berger, M., Gray, J. A. & Roth, B. L. The extended pharmacology of serotonin. Annu. Rev. Med. 60, 355–366 (2009)

    Article  CAS  Google Scholar 

  43. Waldinger, M. D., Hengeveld, M. W., Zwinderman, A. H. & Olivier, B. Effect of SSRI antidepressants on ejaculation: a double-blind, randomized, placebo-controlled study with fluoxetine, fluvoxamine, paroxetine, and sertraline. J. Clin. Psychopharmacol. 18, 274–281 (1998)

    Article  CAS  Google Scholar 

  44. Peters, J. U., Schnider, P., Mattei, P. & Kansy, M. Pharmacological promiscuity: dependence on compound properties and target specificity in a set of recent Roche compounds. ChemMedChem 4, 680–686 (2009)

    Article  CAS  Google Scholar 

  45. Scott, L. J. & Perry, C. M. Delavirdine: a review of its use in HIV infection. Drugs 60, 1411–1444 (2000)

    Article  CAS  Google Scholar 

  46. Dijkstra, D. et al. Human inflammatory dendritic epidermal cells express a functional histamine H4 receptor. J. Invest. Dermatol. 128, 1696–1703 (2008)

    Article  CAS  Google Scholar 

  47. Mehvar, R., Jamali, F., Watson, M. W. & Skelton, D. Pharmacokinetics of tetrabenazine and its major metabolite in man and rat. Bioavailability and dose dependency studies. Drug Metab. Dispos. 15, 250–255 (1987)

    CAS  PubMed  Google Scholar 

  48. Masanori, I., Tetsuya, T., Tomihiro, I., Taku, N. & Shigeyuki, T. β1-adrenergic selectivity of the new cardiotonic agent denopamine in its stimulating effects on adenylate cyclase. Biochem. Pharmacol. 36, 1947–1954 (1987)

    Article  Google Scholar 

  49. Jensen, N. H. et al. N-desalkylquetiapine, a potent norepinephrine reuptake inhibitor and partial 5-HT1A agonist, as a putative mediator of quetiapine’s antidepressant activity. Neuropsychopharmacology 33, 2303–2312 (2008)

    Article  CAS  Google Scholar 

  50. Irwin, J. J. & Shoichet, B. K. ZINC–a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model. 45, 177–182 (2005)

    Article  CAS  Google Scholar 

  51. James, C., Weininger, D. & Delany, J. Daylight Theory Manual (Daylight Chemical Information Systems Inc., 1992–, 2005)

    Google Scholar 

  52. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003)

    Article  CAS  Google Scholar 

  53. Roth, B. L. et al. Salvinorin A: a potent naturally occurring nonnitrogenous κ opioid selective agonist. Proc. Natl Acad. Sci. USA 99, 11934–11939 (2002)

    Article  ADS  CAS  Google Scholar 

Download references

Acknowledgements

Supported by grants from the National Institutes of Health (NIH) supporting chemoinformatics (to B.K.S. and J.J.I.) and NIH grants and contracts supporting drug discovery and receptor pharmacology (to B.L.R). M.J.K., J.H. and C.L. were supported by fellowships from the National Science Foundation, the 6th FP of the European Commission, and the Max Kade Foundation, respectively. B.L.R. was also supported by a Distinguished Investigator Award from the NARSAD and the Michael Hooker Chair. We thank T. Oprea of Sunset Molecular for WOMBAT, Elsevier MDL for the MDDR, Scitegic for PipelinePilot, J. Overington of the European Bioinformatics Institute (EMBL-EBI) for StARlite, Daylight Chemical Information Systems Inc. for the Daylight toolkit, and J. Gingrich for 5-HT2A knockout mice.

Author Contributions B.K.S., J.J.I. and M.J.K. developed the ideas for SEA. M.J.K. wrote the SEA algorithms, undertook the calculations, and identified the off-targets reported here, typically vetted with J.J.I. and B.K.S., unless otherwise noted below. M.J.K. wrote the naive Bayesian classifier algorithms with assistance from J.H. With assistance from B.K.S. and J.J.I., C.L. identified off-targets for Fabahistin, K.L.H.T. identified off-targets for Prozac and Paxil, and D.D.E. identified the off-target for Rescriptor. V.S. and B.L.R. designed empirical tests of the predictions, analysed and interpreted data, and performed experiments. V.S., T.B.T., R.W., R.C.M., A.A., N.H.J. and M.B.K. performed empirical testing of the predictions. V.S., S.J.H. and R.A.G. generated materials for the experiments. M.J.K., B.K.S. and B.L.R. wrote the manuscript with contributions and review from V.S. All authors discussed the results and commented on the manuscript.

Author information

Author notes

  1. Michael J. Keiser and Vincent Setola: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmaceutical Chemistry,,

    Michael J. Keiser, John J. Irwin, Christian Laggner, Jérôme Hert, Kelan L. H. Thomas, Douglas D. Edwards & Brian K. Shoichet

  2. Graduate Group in Bioinformatics, University of California San Francisco, 1700 4th Street, San Francisco, California 94143-2550, USA,

    Michael J. Keiser

  3. Department of Pharmacology,, NIMH Psychoactive Drug Screening Program,

    Vincent Setola, Michael B. Kuijer, Roberto C. Matos, Thuy B. Tran, Ryan Whaley & Bryan L. Roth

  4. Department of Biochemistry, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106, USA,

    Atheir I. Abbas

  5. Department of Pharmacology and Division of Medicinal Chemistry and Natural Products, The University of North Carolina Chapel Hill School of Medicine, Chapel Hill, North Carolina 27759, USA,

    Sandra J. Hufeisen, Niels H. Jensen & Bryan L. Roth

  6. Department of Medicinal Chemistry, School of Pharmacy, Medical College of Virginia Campus, Virginia Commonwealth University, 410 North 12th Street, PO Box 980540, Richmond, Virginia 23298-0540, USA,

    Richard A. Glennon

  7. University of Michigan Health System, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109, USA,

    Kelan L. H. Thomas

Authors
  1. Michael J. Keiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vincent Setola
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John J. Irwin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christian Laggner
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Atheir I. Abbas
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sandra J. Hufeisen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Niels H. Jensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael B. Kuijer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Roberto C. Matos
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Thuy B. Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ryan Whaley
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Richard A. Glennon
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jérôme Hert
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Kelan L. H. Thomas
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Douglas D. Edwards
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Brian K. Shoichet
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Bryan L. Roth
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Brian K. Shoichet or Bryan L. Roth.

Ethics declarations

Competing interests

B.K.S., M.J.K. and J.J.I. are founders of SeaChange Pharmaceuticals, Inc., a company that uses SEA technology.

Supplementary information

Supplementary Information

This file contains Supplementary Tables 1-3 and Supplementary Figures 1-10 with Legends. (PDF 1789 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Keiser, M., Setola, V., Irwin, J. et al. Predicting new molecular targets for known drugs. Nature 462, 175–181 (2009). https://doi.org/10.1038/nature08506

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature08506

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing