Journal of Computer-Aided Molecular Design

, Volume 25, Issue 10, pp 931–945 | Cite as

De novo design by pharmacophore-based searches in fragment spaces

  • Tobias Lippert
  • Tanja Schulz-Gasch
  • Olivier Roche
  • Wolfgang Guba
  • Matthias Rarey
Article

Abstract

De novo ligand design supports the search for novel molecular scaffolds in medicinal chemistry projects. This search can either be based on structural information of the targeted active site (structure-based approach) or on similarity to known binders (ligand-based approach). In the absence of structural information on the target, pharmacophores provide a way to find topologically novel scaffolds. Fragment spaces have proven to be a valuable source for molecular structures in de novo design that are both diverse and synthetically accessible. They also offer a simple way to formulate custom chemical spaces. We have implemented a new method which stochastically constructs new molecules from fragment spaces under consideration of a three dimensional pharmacophore. The program has been tested on several published pharmacophores and is shown to be able to reproduce scaffold hops from the literature, which resulted in new chemical entities.

Keywords

De novo design Pharmacophores Fragment-based design 

References

  1. 1.
    Schneider G, Fechner U (2005) Nat Rev Drug Discov 4(8):649CrossRefGoogle Scholar
  2. 2.
    Mauser H, Guba W (2008) Curr Opin Drug Discov Dev 11(3):365Google Scholar
  3. 3.
    Kutchukian P, Shakhnovich E (2010) Expert Opin Drug Discov 5(8):789CrossRefGoogle Scholar
  4. 4.
    Dobson C (2004) Nature 432(7019):824CrossRefGoogle Scholar
  5. 5.
    Schneider P, Schneider G (2003) QSAR Comb Sci 22(7):713CrossRefGoogle Scholar
  6. 6.
    Degen J, Wegscheid-Gerlach C, Zaliani A, Rarey M (2008) ChemMedChem 3(10):1503CrossRefGoogle Scholar
  7. 7.
    Mauser H, Stahl M (2007) J Chem Inf Model 47(2):318CrossRefGoogle Scholar
  8. 8.
    Lewell X, Judd D, Watson S, Hann M (1998) J Chem Inf Comput Sci 38(3):511CrossRefGoogle Scholar
  9. 9.
    Rotstein S, Murcko M (1993) J Comput Aided Mol Des 7(1):23CrossRefGoogle Scholar
  10. 10.
    Pearlman D, Murcko M (1993) J Comput Chem 14(10):1184CrossRefGoogle Scholar
  11. 11.
    Boehm H (1992) J Comput Aided Mol Des 6(1):61CrossRefGoogle Scholar
  12. 12.
    Todorov N, Dean P (1998) J Comput Aided Mol Des 12(4):335CrossRefGoogle Scholar
  13. 13.
    Degen J, Rarey M (2006) ChemMedChem 1(8):854CrossRefGoogle Scholar
  14. 14.
    Pierce A, Rao G, Bemis G (2004) J Med Chem 47(11):2768CrossRefGoogle Scholar
  15. 15.
    Pearce B, Langley D, Kang J, Huang H, Kulkarni A (2009) J Chem Inf Model 49(7):1797CrossRefGoogle Scholar
  16. 16.
    Fechner U, Schneider G (2006) J Chem Inf Model 46(2):699CrossRefGoogle Scholar
  17. 17.
    Viswanadhan V, Ghose A, Revankar G, Robins R (1989) J Chem Inf Model 29(3):163CrossRefGoogle Scholar
  18. 18.
    Rarey M, Stahl M (2001) J Comput Aided Mol Des 15(6):497CrossRefGoogle Scholar
  19. 19.
    Damewood J, Lerman C, Masek B (2010) J Chem Inf Model 50(7):1296CrossRefGoogle Scholar
  20. 20.
    Fechner U, Franke L, Renner S, Schneider P, Schneider G (2003) J Comput Aided Mol Des 17(10):687CrossRefGoogle Scholar
  21. 21.
    Renner S, Hechenberger M, Noeske T, Bocker A, Jatzke C, Schmuker M, Parsons C, Weil T, Schneider G (2007) Angew Chem (International ed. in English) 46(28):5336CrossRefGoogle Scholar
  22. 22.
    Todorov N, Dean P (1997) J Comput Aided Mol Des 11(2):175CrossRefGoogle Scholar
  23. 23.
    Lloyd D, Buenemann C, Todorov N, Manallack D, Dean P (2004) J Med Chem 47(3):493CrossRefGoogle Scholar
  24. 24.
    Grant J, Gallardo M, Pickup B (1996) J Comput Chem 17(14):1653CrossRefGoogle Scholar
  25. 25.
    Kirkpatrick S, Gelatt C, Vecchi M (1983) Science (New York) 220(4598):671CrossRefGoogle Scholar
  26. 26.
    Schneider G, Hartenfeller M, Reutlinger M, Tanrikulu Y, Proschak E, Schneider P (2009) Trends Biotechnol 27(1):18CrossRefGoogle Scholar
  27. 27.
    Maass P, Schulz-Gasch T, Stahl M, Rarey M (2007) J Chem Inf Model 47(2):390CrossRefGoogle Scholar
  28. 28.
    Leach A, Gillet V, Lewis R, Taylor R (2010) J Med Chem 53(2):539CrossRefGoogle Scholar
  29. 29.
    Spitzer G, Heiss M, Mangold M, Markt P, Kirchmair J, Wolber G, Liedl K (2010) J Chem Inf Model 50(7):1241CrossRefGoogle Scholar
  30. 30.
    Gmespie R (1970) J Chem Edu 47(1):18CrossRefGoogle Scholar
  31. 31.
    Gillet V, Willett P, Bradshaw J (2003) J Chem Inf Comput Sci 43(2):338CrossRefGoogle Scholar
  32. 32.
    Stahl M, Rarey M (2001) J Med Chem 44(7):1035CrossRefGoogle Scholar
  33. 33.
    Kurumbail R, Stevens A, Gierse J, McDonald J, Stegeman R, Pak J, Gildehaus D, Miyashiro J, Penning T, Seibert K, Isakson P, Stallings W (1996) Nature 384(6610):644CrossRefGoogle Scholar
  34. 34.
    Stahl M, Todorov N, James T, Mauser H, Boehm HJ, Dean P (2002) J Comput Aided Mol Des 16(7):459CrossRefGoogle Scholar
  35. 35.
    Bemis G, Murcko M (1996) J Med Chem 39(15):2887CrossRefGoogle Scholar
  36. 36.
    Wolber G, Langer T (2005) J Chem Inf Model 45(1):160CrossRefGoogle Scholar
  37. 37.
    Nagar B, Hantschel O, Young M, Scheffzek K, Veach D, Bornmann W, Clarkson B, Superti-Furga G, Kuriyan J (2003) Cell 112(6):859CrossRefGoogle Scholar
  38. 38.
    Nogrady T, Weaver D (2005) Medicinal Chemistry. 3rd edn. Oxford University Press, New YorkGoogle Scholar
  39. 39.
    Shoichet B (2004) Nature 432(7019):862CrossRefGoogle Scholar
  40. 40.
    Stahl M, Guba W, Kansy M (2006) Drug Discov Today 11(7–8):326CrossRefGoogle Scholar
  41. 41.
    Pettersen E, Goddard T, Huang C, Couch G, Greenblatt D, Meng E, Ferrin T (2004) J Comput Chem 25(13):1605CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Tobias Lippert
    • 1
  • Tanja Schulz-Gasch
    • 2
  • Olivier Roche
    • 2
  • Wolfgang Guba
    • 2
  • Matthias Rarey
    • 1
  1. 1.Center for BioinformaticsUniversity of HamburgHamburgGermany
  2. 2.Pharmaceutical DivisionF. Hoffmann-La Roche LtdBaselSwitzerland

Personalised recommendations