Skip to main content

Advertisement

Log in

Leadlikeness and structural diversity of synthetic screening libraries

  • Full–length Paper
  • Published:
Molecular Diversity Aims and scope Submit manuscript

Summary

High program failure rates in the pharmaceutical industry have prompted the development of predictive software that can profile compound libraries as being ‘druglike’ (resembling existing drugs) and/or ‘leadlike’ (possessing the structural and physicochemical profile of a quality lead). In recent years, these two notions prompted pharmaceutical companies to clean up their corporate libraries of screening compounds. In order to maintain and expand the size and diversity of these corporate libraries, pharmaceutical companies still continue to add compounds to these, mainly by the acquisition of screening libraries. In this paper, we have analyzed 45 commercially available libraries, offered by suppliers of screening chemistry, for leadlikeness and diversity of the offered structures. To this end we have used a set of structural and physicochemical filters for leadlikeness that was developed in-house. These 45 supplier libraries contained a total of 5.3 million structures, of which 49% (2,592,778 structures) turned out to be unique, and only 12% (677,328 structures) were found to be both unique and leadlike. A diversity analysis revealed that big differences exist between the various offered libraries.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Milne, G.M.,Pharmaceutical productivity — The Imperative for New Paradigms, Ann. Rep. Med. Chem., 38 (2002) 383–396.

    Article  Google Scholar 

  2. Lipinski, C.A., Lombardo, F., Dominy, B.W. and Feeny, P.J.,Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Delivery Rev., 23 (1997) 3–25.

    Article  CAS  Google Scholar 

  3. Proudfoot, J.R.,Drugs, leads, and drug-likeness: An analysis of some recently launched drugs, Bioorg. Med. Chem. Lett., 12 (2002) 1647–1650.

    Article  PubMed  CAS  Google Scholar 

  4. Teague, S.J., Davis, A.M., Leeson, P.D. and Oprea, T.I.,The design of leadlike combinatorial libraries, Angew. Chem. Int. Ed., 38 (1999) 3743–3748.

    Article  CAS  Google Scholar 

  5. Hann, M.M., Leach, A.R. and Harper, G.,Molecular complexity and its impact on the probability of finding leads for drug discovery, J. Chem. Inf. Comput. Sci., 41 (2001) 856–864.

    Article  PubMed  CAS  Google Scholar 

  6. Oprea, T.I., Davis, A.M., Teague, S.J. and Leeson, P.D.,Is there a difference between leads and drugs? A historical perspective, J. Chem. Inf. Comput. Sci., 41 (2001) 1308–1315.

    Article  PubMed  CAS  Google Scholar 

  7. Oprea, T.I.,Current trends in lead discovery: Are we looking for the appropriate properties?, J. Comp. Aid. Mol. Des., 16 (2002) 325–334.

    Article  CAS  Google Scholar 

  8. Lipinski, C.A.,Drug-like properties and the causes of poor solubility and poor permeability, J. Pharm. Tox. Methods, 44 (2000) 235–249.

    Article  CAS  Google Scholar 

  9. Blake, J.F.,Examiniation of the computed molecular properties of compounds selected for clinical development, Biotechniques, 34 (2003) S16–S20.

    Google Scholar 

  10. Rishton, G.M.,Reactive compounds and in vitro false positives in HTS, Drug Discovery Today, 2 (1997) 382–384.

    Article  CAS  Google Scholar 

  11. Huth, J.R., Mendoza, R., Olejniczak, E.T., Johnson, R.W., Cothron, D.A., Liu, Y., Lerner, C.G., Chen, J. and Hajduk, P.J.,ALARM NMR: A rapid and robust experimental method to detect reactive false positives in biochemical screens, J. Am. Chem. Soc., 127 (2005) 217–224.

    Article  PubMed  CAS  Google Scholar 

  12. (a) McGovern, S.L., Caselli, E., Grigorieff, N. and Shoichet, B.K.,A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening, J. Med. Chem., 45 (2002) 1712–1722. (b) Seidler, J., McGovern, S.L., Doman, T.N. and Shoichet, B.K.,Identification and prediction of promiscuous aggregating inhibitors among known drugs, J. Med. Chem., 46 (2003) 4477–4486.

    Article  PubMed  CAS  Google Scholar 

  13. Roche, O., Schneider, P., Zuegge, J., Guba, W., Kansy, M., Alanine, A., Bleicher, K., Danel, F., Gutknecht, E-M., Rogers-Evans, M., Neidhart, W., Stalder, H., Dillon, M., Sjögren, E., Fotouhi, N., Gillespie, P., Goodnow, R., Harris, W., Jones, P., Taniguchi, M., Tsujii, S., von der Saal, W., Zimmerman, G. and Schneider, G.,Development of a virtual screening method for identification of ‘frequent hitters’ in compound libraries, J. Med. Chem., 45 (2002) 137–142.

    Article  PubMed  CAS  Google Scholar 

  14. (a) Oprea, T.I., Gottfries, J., Sherbukhin, V., Svensson, P. and Kuhler, T.C.,Chemical information management in drug discovery: Optimizing the computational and combinatorial chemistry interfaces, J. Mol. Graph. Mol., 18 (2000) 512–524. (b) Oprea, T.I., Zamora, I. and Ungell, A.,Pharmacokinetically Based Mapping Device for Chemical Space Navigation, J. Comb. Chem., 4 (2002) 258–266.

    Article  CAS  Google Scholar 

  15. (a) Rishton, G.M.,Nonleadlikeness and leadlikeness in biochemical screening, Drug Discovery Today, 8 (2003) 86–96. (b) Rishton, G.M.,Failure and Success in Modern Drug Discovery: Guiding Principles in the Establishment of High Probability of Success Drug Discovery Organizations, Medicinal Chemistry, 1 (2005) 519–527.

    Article  PubMed  CAS  Google Scholar 

  16. Lipinski, C.A.,Lead- and drug-like compounds: The rule-of-five revolution, Drug Discovery Today: Technologies, 1 (2004) 337–341.

    Article  CAS  Google Scholar 

  17. Lipinski, C.A., Presentation ‘Combinatorial chemistry and HTS: Causes of or solutions to the innovation gap’, 4th Symposium on Drug Discovery, April 7–8, 2005, Antwerp, Belgium.

  18. Hemmerle, H., Presentation ‘Platform library science and compound collection enhancement as the base for successful medicinal chemistry’, DDT Conference, August 9–11, 2005, Boston, U.S.A.

  19. Blower, P.E., Cross, K.P., Fligner, M.A., Myatt, G.J., Verducci, J.S. and Yang, C.,Systematic Analysis of Large Screening Sets in Drug Discovery, Curr. Drug Disc. Technol., 1 (2004) 37.

    Article  CAS  Google Scholar 

  20. Voigt, J.H., Bienfait, B., Wang, S. and Nicklaus, M.C.,Comparison of the NCI open database with seven large chemical structural databases, J. Chem. Inf. Comput. Sci., 41 (2001) 702–712.

    Article  PubMed  CAS  Google Scholar 

  21. Baurin, N., Baker, R., Richardson, C., Chen, I., Foloppe, N., Potter, A., Jordan, A., Roughley, S., Parratt, M., Greany, P., Morley, D. and Hubbard, R.E.,Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7\ million compounds, J. Chem. Inf. Comput. Sci., 44 (2004) 643–651.

    Article  PubMed  CAS  Google Scholar 

  22. MDL Information Systems, Inc., 14600 Catalina Street, San Leandro, CA 94577, U.S.A. http://www.mdli.com/.

  23. Chemical Computing Group, Inc. 1010 Sherbrooke St. West, Suite 910, Montreal, H3A 2R7 Canada. http://www.chemcomp.com/

  24. Syracuse Research Corporation, 6225 Running Ridge Road, North Syracuse, NY 13212, U.S.A. KOWWIN and WSKOWWIN are part of the EPI suite (V3.12), available from http://www.epa.gov/oppt/-exposure/docs/episuitedl.htm

  25. Xu, J.,A New Approach to finding natural chemical structure classes, J. Med. Chem., 45 (2002) 5311–5320.

    Article  PubMed  CAS  Google Scholar 

  26. Trepalin, S.V. and Yarkov, A.V.,Ched—Chemical databases compilation tool, internet server and client for SQL servers, J. Chem. Inf. Comput. Sci., 41 (2001) 100–107., http://ched.ipac.ac.ru.

    Article  PubMed  CAS  Google Scholar 

  27. Congreve, M., Carr, R., Murray, C. and Jhoti, H.,A ‘rule of three’ for fragment-based lead discovery?, Drug Discovery Today, 8 (2003) 876–877.

    Article  PubMed  Google Scholar 

  28. Veber, D.F., Johnson, S.R., Cheng, H., Smith, B.R., Ward, K.W. and Kopple, K.D.,Molecular properties that influence the oral bioavailability of drug candidates, J. Med. Chem., 45 (2002) 2615–2623.

    Article  PubMed  CAS  Google Scholar 

  29. Fichert, T., Yazdanian, M. and Proudfoot, J.R.,A structure-permeability study of samll drug-like molecules, Bioorg. Med. Chem. Lett., 13 (2003) 719–722.

    Article  PubMed  CAS  Google Scholar 

  30. Clark, D.E. and Pickett, S.D.,Computational methods for the prediction of drug-likeness, Drug Discovery Today 5 (2000) 49–58.

    Article  PubMed  CAS  Google Scholar 

  31. Kelder, J., Grootenhuis, P.J.D., Bayada, D.M., Delbressine, L.P.C. and Bloemen, J.,Polar molecular surface as a dominating determinant fororal absorption and brain penetration of drugs, Pharm. Res., 16 (1999) 1514–1519.

    Article  PubMed  CAS  Google Scholar 

  32. Xu, J. and Stevenson, J.,Drug-like index: A new approach to measure drug-like compounds and their diversity, J. Chem. Inf. Comput. Sci., 40 (2000) 1177–1187.

    Article  PubMed  CAS  Google Scholar 

  33. Bemis, G.W. and Murcko, M.A.,The properties of known drugs. 1. Molecular frameworks, J. Med. Chem., 39 (1996) 2887–2893.

    Article  PubMed  CAS  Google Scholar 

  34. Maybridge PLC., Trevillett, Tintagel, Cornwall PL34 OHW, England. http://www.maybridge.com/.

  35. Hann, M.M. and Oprea, T.I.,Pursuing the leadlikeness concept in pharmaceutical research, Curr. Opin. Chem. Biol., 8 (2004) 255–263.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Herman J. Verheij.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Verheij, H.J. Leadlikeness and structural diversity of synthetic screening libraries. Mol Divers 10, 377–388 (2006). https://doi.org/10.1007/s11030-006-9040-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11030-006-9040-6

Key words

Navigation