References

1. Walters, P.A., Stahl, M.T. and Murcko, M.A., Drug Discov. Today, 3 (1998) 160.

2. Armstrong, R.W., Combs, A.P., Tempest, P.A., Brown, S.D. and Keating, T.A., Acc. Chem. Res., 29 (1996) 123.

3. Koltermann, A., Kettling, U., Bieschke, J., Winkler, T. and Eigen, M., Proc. Natl. Acad. Sci. USA, 95 (1998) 1421.

4. VanDrie, J.H. and Lajiness, M.S., Drug Discov. Today, 3 (1998) 274.

5. Kubinyi, H., Curr. Opin. Drug Discov. Develop., 1 (1998) 16.

6. Ghose, A.K., Viswanadhan, V.N. and Wendoloski, J.J., In Parrill, A. and Reddy, M.R. (Eds.) Rational Drug Design, American Chemical Society, Washington, DC, 1998.

10. Böhm, H.-J., Curr. Opin. Biotechnol., 7 (1996) 433.

11. Kuntz, I.D., Blaney, J.M., Oatley, S.J., Langridge, R.L. and Femn, T.E., J. Mol. Biol., 161 (1982) 269.

12. Rarey, M., Kramer, B., Lengauer, T. and Klebe, G., J. Mol. Biol., 261 (1996) 470.

13. Welch, W., Ruppert, J. and Jain, A.N., Chem. Biol., 3 (1996) 449.

14. Jones, G., Willett, P., Glen, R.C., Leach, A.R. and Taylor, R., J. Mol. Biol., 267 (1997) 727.

15. Moms, G.M., Goodsell, D.S., Halliday, R.S., Huey, R., Hart, W.E., Belew, R.K. and Olson, A.J., J. Comput. Chem., 19 (1998) 1639.

16. Sun, Y., Ewing, T.J., Skillman, A.G. and Kuntz, I.D., J. Comput.-Aided Mol. Design, 12 (1998) 597.

17. Baxter, C.A., Murray, C.W., Clark, D.E., Westhead, D.R. and Eldridge, M.D. Proteins, 33 (1998) 367.

18. Wang, J., Kollman, P.A. and Kuntz, I.D., Proteins, 36 (1999) 1.

19. Trosset, J.Y. and Scheraga, H.A., J. Comput. Chem., 20 (1999) 412.

20. Fradera, X., Knegtel, R.M.A. and Mestres, J., Proteins Struct. Funct. Genet., 40 (2000) 623.

21. Ewing, T. and Kuntz, I.D., J. Comput. Chem., 18 (1997) 1175.

22. Vieth, M., Hirst, J.D., Dominy, B.N., Daigler, H. and Brooks 111, C.L., J. Comput. Chem., 19 (1998) 1623.

23. Bush, B.L. and McCammon, J.A., Biophys. J., 72 (1997) 1047.

24. Ajay and Murcko, M.A., J. Med. Chem., 38 (1996) 4953.

26. Friesner, R.A. and Beachy, M.D., Curr. Opin. Struct. Biol., 8 (1998) 257.

27. Monard, G. and Merz Jr., K.M., Acc. Chem. Res., 32 (1999) 904.

28. Vieth, M., Hirst, J.D., Kolinski, A. and Brooks III, C.L., J. Comput. Chem., 19 (1998) 1612.

29. Tame, J.R.H., J. Comput.-Aided Mol. Design, 13 (1999) 99.

30. Knegtel, R.M.A., Bayada, D.M., Engh, R.A., von der Saal, W., van Geerestein, V.J. and Grootenhuis, P.D.J. J. Comput.-Aided Mol. Design, 13 (1999) 167.

31. Muegge, I. and Martin, Y.C., J. Med. Chem., 42 (1999) 791.

32. Gschwend, D.A. and Kuntz, I.D., J. Comput.-Aided Mol. Design, 10 (1996) 123.

34. Knegtel, R.M.A., Kuntz, I.D. and Oshiro, C.M., J. Mol. Biol., 266 (1997) 424.

35. Apostolakis, J., Pluckthun, A. and Caflisch, A,, J. Comput. Chem., 19 (1998) 21.

36. Sandak, B., Wolfson, H.J. and Nussinov, R., Proteins, 32 (1998) 159.

37. Blaney, J.M. and Dixon, J.S., Perspect. Drug Discov. and Design, 1 (1993) 301.

38. Jones, G. and Willett, P., Curr. Opin. Biotech., 6 (1995) 652.

39. Lengauer, T. and Rarey, M., Curr. Opin. Struct. Biol., 6 (1996) 402.

41. Kirkpatrick, D.L., Watson, S. and Ulhaq, S., Comb. Chem. High-Through. Screen., 2 (1999) 211.

42. Knegtel, R.M.A. and Wagener, M., Proteins Struct. Funct. Genet., 37 (1999) 334.

43. Johnson, M.A. and Maggiora, G.M. (Eds.), Concepts and Applications of Molecular Similarity, Wiley, New York, NY, 1990.

44. Dean, P.M. (Ed.), Molecular Similarity in Drug Design, Blackie Academic, London, 1995.

45. Karelson, M., Lobanov, V.S. and Katritzky, A.R., Chem. Rev., 96 (1996) 1027.

46. Hansch, C., Hoekman, D. and Gao, H., Chem. Rev., 96 (1996) 1045.

47. Cramer III, R.D., Patterson, D.E. and Bunce, J.D., J. Am. Chem. Soc., 110 (1988) 5959.

48. Klebe, G., Perspect. Drug Discov. Design, 12/13/14 (1998) 87.

49. Kubinyi, H. (Ed.), 3D QSAR in Drug Design: Theory, Methods and Applications, ESCOM, Leiden, 1993.

50. Kubinyi, H., Folkers, G. and Martin, Y.C. (Eds.), 3D QSAR in Drug Design: Ligand-protein Interactions and Molecular Similarity, Perspect. Drug Discov. Design, 9/10/11 (1998).

51. Kubinyi, H., Folkers, G. and Martin, Y.C. (Eds.), 3D QSAR in Drug Design: Recent Advances, Perspect. Drug Discov. Design, 12/13/14 (1998).

52. Willett, P., Similarity and Clustering in Chemical Information Systems, Wiley, New York, NY, 1994.

53. Martin, E.J., Blaney, J.M., Siani, M.A., Spellmeyer, D.C., Wong, A.K. and Moos, W.K., J. Med. Chem., 38 (1995) 1431.

54. Hassan, M., Bielawaski, J.P., Hempel, J.C. and Waldman, M., Mol. Div., 2 (1996) 64.

55. Bayada, D.M., Hamersma, H. and van Geerestein, V.J., J. Chem. Inf. Comput. Sci., 39 (1999) 1.

56. Martin, E.J. and Critchlow, R.E., J. Comb. Chem., 1 (1999) 32.

57. Agrafiotis, D.K., Myslik, J.C. and Salemme, F.R., Mol. Div., 4 (1999) 1.

58. Barnard, J.M. and Downs, G.M., J. Chem. Inf. Comput. Sci., 32 (1992) 644.

59. Brown, R.D. and Martin, Y.C., J. Chem. Inf. Comput. Sci., 37 (1997) 1.

61. Flower, D.R., J. Chem. Inf. Comput. Sci., 38 (1998) 379.

62. Xue, J., Godden, J.W. and Bajorath, J., J. Chem. Inf. Comput. Sci., 39 (1999) 881.

63. Cramer, R.D., Redl, G. and Berkhoff, C.E., J. Med. Chem., 17 (1973) 533.

64. Hagadone, T.R., J. Chem. Inf. Comput. Sci., 32 (1992) 515.

65. Van Drie, J.H., J. Comput.-Aided Mol. Design, 11 (1997) 39.

66. Pickett, S.D., Luttmann, C., Guerin, V., Laoui, A. and James, E., J. Chem. Inf. Comput. Sci., 38 (1998) 144.

67. Chen, X., Rusinko III, A., Tropsha, A. and Young, S.S., J. Chem. Inf. Comput. Sci., 39 (1999) 887.

68. Kearsley, S.K. and Smith, G.M., Tetrahedron Comput. Methods, 3 (1990) 615.

69. Good, A.C., Hodgkin, E.E. and Richards, G.W., J. Chem. Inf. Comput. Sci., 32 (1992) 188.

70. Jain, A.N., Dietterich, T.G., Lathrop, R.H., Chapman, D., Critchlow Jr., R.E., Bauer, B.E., Webster, T.S. and Lozano-Perez, T., J. Comput.-Aided Mol. Design, 8 (1994) 635.

71. Klebe, G., Mietzner, T. and Weber, F, J. Comput.-Aided Mol. Design, 8 (1994) 751.

72. McMartin, C. and Bohacek, R.S., J. Comput.-Aided Mol. Design, 9 (1995) 237.

73. Perkins, T.D.J., Mills, J.E.J. and Dean, P.M., J. Comput.-Aided Mol. Design, 9 (1995) 479.

74. Jones, G., Willett, P. and Glen, R.C., J. Comput.-Aided Mol. Design, 9 (1995) 532.

75. Lemmen, C., Hiller, C. and Lengauer, T., J. Comput.-Aided Mol. Design, 12 (1998) 491.

76. Mestres, J., Rohrer, D.C. and Maggiora, G.M., J. Comput. Chem., 18 (1997) 934.

77. Lemmen, C., Lengauer, T. and Klebe, G., J. Med. Chem., 41 (1998) 4502.

78. Miller, M.D., Sheridan, R.P. and Kearsley, S.K., J. Med. Chem., 42 (1999) 1505.

79. Klebe, G., In Kubinyi, H. (Ed.) 3D QSAR in Drug Design: Theory, Methods and Applications, ESCOM, Leiden, 1993, p. 173.

80. Mattos, C. and Ringe, D., In Kubinyi, H. (Ed.) 3D QSAR in Drug Design: Theory, Methods and Applications, ESCOM, Leiden, 1993, p. 226.

81. Bohm, H.-J. and Klebe, G., Angew. Chem. Int. Ed. Engl., 35 (1996) 2588.

82. Grootenhuis, P.D.J. and van Helden, S.P., In Wipff, G. (Ed.) Computational Approaches in Supramolecular Chemistry, Kluwer Academic, Dordrecht, 1994, p. 137.

83. Babine, R.E. and Bender, S.L., Chem. Rev., 97 (1997) 1359.

85. Meng, E.C., Shoichet, B.K. and Kuntz, I.D., J. Comput. Chem., 13 (1992) 505.

86. Rohrer, D.C., In Carb6 R. (Ed.) Molecular Similarity and Reactivity: From Quantum Chemical to Phenomenological Approaches, Kluwer, Amsterdam, 1995, p. 141.

87. Mestres J., Rohrer, D.C. and Maggiora, G.M., J. Mol. Graph. Model, 15 (1997) 114.

88. Mestres, J., Rohrer, D.C. and Maggiora, G.M., J. Comput.-Aided Mol. Design, 13 (1999) 79.

89. Mestres, J., Rohrer, D.C. and Maggiora, G.M., J. Comput.-Aided Mol. Design, 14 (2000) 39.

90. Gasteiger, J. and Marsili, M., Tetrahedron 36 (1980) 3219.

91. Sadowski, J., Gasteiger, J. and Klebe, G., Inf. Comput. Sci., 34 (1994) 1000.

Perspectives in Drug Discovery and Design, 20: 209-230, 2000. KLUWER/ESCOM

© 2000 Kluwer Academic Publishers. Printed in the Netherlands.

Discovering high-affinity ligands from the computationally predicted structures and affinities of small molecules bound to a target: A virtual screening approach

TAMIJ. MARRONE*, BROCK A. LUTY andPETERW. ROSE*

Agouron Pharmaceuticals, Inc., A Warner Lambert Company, San Diego, CA 92121-1111, U.S.A.

Summary. We describe a 'virtual NMR screening' method to assist in the design of inhibitors that occupy different sites within a target. We dock small molecules into the active site of an enzyme and score them. Keeping the tightest-binding lead fixed in space, we dock and score other small molecules in its presence. Using this approach, linker groups are used to join the compounds together to form a high-affinity inhibitor. We present validation of our computational approach by reproducing experimental results for FKBP and stromelysin. Docking simulations are not subject to experimental problems such as proteolysis, protein or compound insolubility, or enzyme size. Because docking is fast and our scoring method can distinguish between high- and low-affinity inhibitors, this docking procedure shows promise as integral part of a drug-design strategy.

Key words: docking, drug design, SAR by NMR, virtual screening

0 0

Post a comment