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What is the Likelihood of an Active Compound to Be Promiscuous? Systematic Assessment of Compound Promiscuity on the Basis of PubChem Confirmatory Bioassay Data

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Abstract

Compound promiscuity refers to the ability of small molecules to specifically interact with multiple targets, which represents the origin of polypharmacology. Promiscuity is thought to be a widespread characteristic of pharmaceutically relevant compounds. Yet, the degree of promiscuity among active compounds from different sources remains uncertain. Here, we report a thorough analysis of compound promiscuity on the basis of more than 1,000 PubChem confirmatory bioassays, which yields an upper-limit assessment of promiscuity among active compounds. Because most PubChem compounds have been tested in large numbers of assays, data sparseness has not been a limiting factor for the current analysis. We have determined that there is an overall likelihood of ∼50% of an active PubChem compound to interact with two or more targets. The probability to interact with more than five targets is reduced to 7.6%. On average, an active PubChem compound was found to interact with ∼2.5 targets. Moreover, if only activities consistently detected in all assays available for a given target were considered, this ratio was further reduced to ∼2.3 targets per compound. For comparison, we have also analyzed high-confidence activity data from ChEMBL, the major public repository of compounds from medicinal chemistry, and determined that an active ChEMBL compound interacted on average with only ∼1.5 targets. Taken together, our results indicate that the degree of compound promiscuity is lower than often assumed.

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REFERENCES

  1. Paolini GV, Shapland RHB, van Hoorn WP, Mason JS, Hopkins AL. Global mapping of pharmacological space. Nat Biotechnol. 2006;24(7):805–15. doi:10.1038/nbt1228.

    Article  PubMed  CAS  Google Scholar 

  2. Keiser MJ, Roth BL, Armbruster BN, Ernsberger P, Irwin JJ, Shoichet BK. Relating protein pharmacology by ligand chemistry. Nat Biotechnol. 2007;25(2):197–206. doi:10.1038/nbt1284.

    Article  PubMed  CAS  Google Scholar 

  3. Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol. 2008;4(11):682–90. doi:10.1038/nchembio.118.

    Article  PubMed  CAS  Google Scholar 

  4. Mestres J, Gregori-Puigjane E, Valverde S, Sole RV. Data completeness—the achilles heel of drug–target networks. Nat Biotechnol. 2008;26(9):983–4. doi:10.1038/nbt0908-983.

    Article  PubMed  CAS  Google Scholar 

  5. Knight ZA, Lin H, Shokat KM. Targeting the cancer kinome through polypharmacology. Nat Rev Cancer. 2010;10(2):130–7. doi:10.1038/nrc2787.

    Article  PubMed  CAS  Google Scholar 

  6. Merino A, Bronowska AK, Jackson DB, Cahill DJ. Drug profiling: knowing where it hits. Drug Discov Today. 2010;15(17–18):749–56. doi:10.1016/j.drudis.2010.06.006.

    Article  PubMed  Google Scholar 

  7. Xie L, Xie L, Kinnings SL, Bourne PE. Novel computational approaches to polypharmacology as a means to define responses to individual drugs. Annu Rev Pharmacol Toxicol. 2012;52:361–79. doi:10.1146/annurev-pharmtox-010611-134630.

    Article  PubMed  CAS  Google Scholar 

  8. Jalencas X, Mestres J. On the origins of drug polypharmacology. Med Chem Commun. 2013;4(1):80–7. doi:10.1039/C2MD20242E.

    Article  CAS  Google Scholar 

  9. Campillos M, Kuhn M, Gavin AC, Jensen LJ, Bork P. Drug target identification using side-effect similarity. Science. 2008;321(5886):263–6. doi:10.1126/science.1158140.

    Article  PubMed  CAS  Google Scholar 

  10. Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J, Jenkins JL, et al. Large-scale prediction and testing of drug activity on side-effect targets. Nature. 2012;486(7403):361–7. doi:10.1038/nature11159.

    PubMed  CAS  Google Scholar 

  11. Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Zhou Z, et al. PubChem’s BioAssay database. Nucleic Acids Res. 2012;40(Database issue):D400–12. doi:10.1093/nar/gkr1132.

    Article  PubMed  CAS  Google Scholar 

  12. Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, et al. ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2012;40(D1):D1100–7. doi:10.1093/nar/gkr777.

    Article  PubMed  CAS  Google Scholar 

  13. Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, et al. DrugBank 3.0: a comprehensive resource for ‘omics’ research on drugs. Nucleic Acids Res. 2011;39(Database issue):D1035–41. doi:10.1093/nar/gkq1126.

    Article  PubMed  CAS  Google Scholar 

  14. Hu Y, Bajorath J. Many structurally related drugs bind different targets whereas distinct drugs display significant target overlap. RSC Adv. 2012;2(8):3481–9. doi:10.1039/C2RA01345B.

    Article  CAS  Google Scholar 

  15. Hu Y, Bajorath J. Growth of ligand-target interaction data in ChEMBL is associated with increasing and activity measurement-dependent compound promiscuity. J Chem Inf Model. 2012;52(10):2550–8. doi:10.1021/ci3003304.

    Article  PubMed  CAS  Google Scholar 

  16. Hu Y, Bajorath J. How promiscuous are pharmaceutically relevant compounds? a data-driven assessment. AAPS J. 2013;15(1):104–11. doi:10.1208/s12248-012-9421-y.

    Article  PubMed  CAS  Google Scholar 

  17. Bemis GW, Murcko MA. The properties of known drugs. 1. Molecular frameworks. J Med Chem. 1996;39(15):2887–93. doi:10.1021/jm9602928.

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Jürgen Bajorath.

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Hu, Y., Bajorath, J. What is the Likelihood of an Active Compound to Be Promiscuous? Systematic Assessment of Compound Promiscuity on the Basis of PubChem Confirmatory Bioassay Data. AAPS J 15, 808–815 (2013). https://doi.org/10.1208/s12248-013-9488-0

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  • DOI: https://doi.org/10.1208/s12248-013-9488-0

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