Advertisement

Journal of Computer-Aided Molecular Design

, Volume 23, Issue 8, pp 541–554 | Cite as

Energetic analysis of fragment docking and application to structure-based pharmacophore hypothesis generation

  • Kathryn Loving
  • Noeris K. Salam
  • Woody Sherman
Article

Abstract

We have developed a method that uses energetic analysis of structure-based fragment docking to elucidate key features for molecular recognition. This hybrid ligand- and structure-based methodology uses an atomic breakdown of the energy terms from the Glide XP scoring function to locate key pharmacophoric features from the docked fragments. First, we show that Glide accurately docks fragments, producing a root mean squared deviation (RMSD) of <1.0 Å for the top scoring pose to the native crystal structure. We then describe fragment-specific docking settings developed to generate poses that explore every pocket of a binding site while maintaining the docking accuracy of the top scoring pose. Next, we describe how the energy terms from the Glide XP scoring function are mapped onto pharmacophore sites from the docked fragments in order to rank their importance for binding. Using this energetic analysis we show that the most energetically favorable pharmacophore sites are consistent with features from known tight binding compounds. Finally, we describe a method to use the energetically selected sites from fragment docking to develop a pharmacophore hypothesis that can be used in virtual database screening to retrieve diverse compounds. We find that this method produces viable hypotheses that are consistent with known active compounds. In addition to retrieving diverse compounds that are not biased by the co-crystallized ligand, the method is able to recover known active compounds from a database screen, with an average enrichment of 8.1 in the top 1% of the database.

Keywords

Fragments Virtual screening Docking accuracy Enrichment Fragment-based drug design 

Supplementary material

10822_2009_9268_MOESM1_ESM.gz (1.7 mb)
(GZ 1755 kb)
10822_2009_9268_MOESM2_ESM.gz (143 kb)
(GZ 143 kb)
10822_2009_9268_MOESM3_ESM.pdf (5 kb)
(PDF 6 kb)

References

  1. 1.
    Erlanson DA, McDowell RS, O’Brien T (2004) J Med Chem 47:3463. doi: 10.1021/jm040031v CrossRefGoogle Scholar
  2. 2.
    Boehm H-J, Boehringer M, Bur D, Gmuender H, Huber W, Klaus W, Kostrewa D, Kuehne H, Luebbers T, Meunier-Keller N, Mueller F (2000) J Med Chem 43:2664. doi: 10.1021/jm000017s CrossRefGoogle Scholar
  3. 3.
    Gill A (2004) Mini Rev Med Chem 4:301. doi: 10.2174/1389557043487385 CrossRefGoogle Scholar
  4. 4.
    Card GL, Blasdel L, England BP, Zhang C, Suzuki Y, Gillette S, Fong D, Ibrahim PN, Artis DR, Bollag G, Milburn MV, Kim S-H, Schlessinger J, Zhang KYJ (2005) Nat Biotechnol 23:201. doi: 10.1038/nbt1059 CrossRefGoogle Scholar
  5. 5.
    Hartshorn MJ, Murray CW, Cleasby A, Frederickson M, Tickle IJ, Jhoti H (2005) J Med Chem 48:403. doi: 10.1021/jm0495778 CrossRefGoogle Scholar
  6. 6.
    Nienaber VL, Richardson PL, Klighofer V, Bouska JJ, Giranda VL, Greer J (2000) Nat Biotechnol 18:1105. doi: 10.1038/80319 CrossRefGoogle Scholar
  7. 7.
    Tondi D, Morandi F, Bonnet R, Costi MP, Shoichet BK (2005) J Am Chem Soc 127:4632. doi: 10.1021/ja042984o CrossRefGoogle Scholar
  8. 8.
    Hajduk PJ, Greer J (2007) Nat Rev Drug Discov 6:211. doi: 10.1038/nrd2220 CrossRefGoogle Scholar
  9. 9.
    Tobias Fink HB, Reymond J (2005) Angew Chem 117:1528. doi: 10.1002/ange.200462457 CrossRefGoogle Scholar
  10. 10.
    Martin YC (1981) J Med Chem 24:229. doi: 10.1021/jm00135a001 CrossRefGoogle Scholar
  11. 11.
    Babaoglu K, Shoichet BK (2006) Nat Chem Biol 2:720. doi: 10.1038/nchembio831 CrossRefGoogle Scholar
  12. 12.
    Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) J Med Chem 49:534. doi: 10.1021/jm050540c CrossRefGoogle Scholar
  13. 13.
    Moitessier N, Therrien E, Hanessian S (2006) J Med Chem 49:5885CrossRefGoogle Scholar
  14. 14.
    Nabuurs SB, Wagener M, de Vlieg J (2007) J Med Chem 50:6507CrossRefGoogle Scholar
  15. 15.
    Zhou Z, Felts AK, Friesner RA, Levy RM (2007) J Chem Inf Model 47:1599CrossRefGoogle Scholar
  16. 16.
    Perola E, Walters WP, Charifson PS (2004) Proteins 56:235CrossRefGoogle Scholar
  17. 17.
    Marcou G, Rognan D (2007) J Chem Inf Model 47:195CrossRefGoogle Scholar
  18. 18.
    Cole JC, Murray CW, Nissink JW, Taylor RD, Taylor R (2005) Proteins 60:325CrossRefGoogle Scholar
  19. 19.
    Deng Z, Chuaqui C, Singh J (2004) J Med Chem 47:337CrossRefGoogle Scholar
  20. 20.
    Yusuf D, Davis AM, Kleywegt GJ, Schmitt S (2008) J Chem Inf Model 48:1411CrossRefGoogle Scholar
  21. 21.
    Friesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, Sanschagrin PC, Mainz DT (2006) J Med Chem 49:6177CrossRefGoogle Scholar
  22. 22.
    Schrödinger Fragment Library (2008) Schrödinger, Inc. http://www.schrodinger.com/ProductInfo.php?mID=6&sID=6&cID=53
  23. 23.
    Bemis GWM, Murcko MA (1996) J Med Chem 39:7CrossRefGoogle Scholar
  24. 24.
    Fejzo J, Lepre CA, Peng JW, Bemis GW, Ajay, Murcko MA, Moore JM (1999) Chem Biol 6:755CrossRefGoogle Scholar
  25. 25.
    Huth JR, Sun C (2002) Comb Chem High Throughput Screen 5:631Google Scholar
  26. 26.
    Hajduk PJ, Bures M, Praestgaard J, Fesik SW (2000) J Med Chem 43:3443CrossRefGoogle Scholar
  27. 27.
    Jacoby E, Davies J, Blommers MJJ (2003) Curr Top Med Chem 3:11CrossRefGoogle Scholar
  28. 28.
    Maestro v8.5, Schrödinger, Inc.: Portland, ORGoogle Scholar
  29. 29.
    Impact v5.0, Schrödinger, Inc.: Portland, ORGoogle Scholar
  30. 30.
    LigPrep v2.2, Schrödinger, Inc.: Portland, ORGoogle Scholar
  31. 31.
    Epik v1.6, Schrödinger, Inc.: Portland, ORGoogle Scholar
  32. 32.
    Glide v5.0, Schrödinger, Inc.: Portland, ORGoogle Scholar
  33. 33.
    Kuntz ID, Chen K, Sharp KA, Kollman PA (1999) Proc Natl Acad Sci USA 96:9997CrossRefGoogle Scholar
  34. 34.
    Volume_cluster.py from the Schrödinger ScriptCenter (2008) Schrödinger, Inc. http://www.schrodinger.com/ScriptCenter.php
  35. 35.
    Phase v3.0, Schrödinger, Inc.: Portland, ORGoogle Scholar
  36. 36.
    Eldridge MD, Murray CW, Auton TR, Paolini GV, Mee RP (1997) J Comput-Aided Mol Des 11:425CrossRefGoogle Scholar
  37. 37.
    Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, Banks JL (2004) J Med Chem 47:1750CrossRefGoogle Scholar
  38. 38.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) J Med Chem 47:1739CrossRefGoogle Scholar
  39. 39.
    Wang Z, Canagarajah BJ, Boehm JC, Kassisa S, Cobb MH, Young PR, Abdel-Meguid S, Adams JL, Goldsmith EJ (1998) Structure 39:12Google Scholar
  40. 40.
    Dixon S, Smondyrev A, Knoll E, Rao S, Shaw D, Friesner R (2006) J Comput-Aided Mol Des 20:647CrossRefGoogle Scholar
  41. 41.
    Congreve M, Chessari G, Tisi D, Woodhead AJ (2008) J Med Chem 51:3661CrossRefGoogle Scholar
  42. 42.
    Damm KL, Carlson HA (2006) Biophys J 90:4558CrossRefGoogle Scholar
  43. 43.
    Meyer EA, Furler M, Diederich F, Brenk R, Klebe G (2004) Helv Chim Acta 87:1333CrossRefGoogle Scholar
  44. 44.
    Wu Q, Gee CL, Lin F, Tyndall JD, Martin JL, Grunewald GL, McLeish MJ (2005) J Med Chem 48:7243CrossRefGoogle Scholar
  45. 45.
    Canvas v1.1, Schrödinger, Inc.: Portland, ORGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Kathryn Loving
    • 1
  • Noeris K. Salam
    • 1
  • Woody Sherman
    • 1
  1. 1.Schrödinger, Inc.New YorkUSA

Personalised recommendations