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Toward a more efficient handling of conformational flexibility in computer-assisted modelling of drug molecules

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Perspectives in Drug Discovery and Design

Summary

Several computational search techniques are described to map the conformation space of flexible organic molecules. A vast multiplicity of geometries is produced that has to be minimized according to a particular energy function. Comparative studies on a nine-membered cyclic lactam are taken as an example. They show that thoroughly tailored search conditions can obtain roughly comparable search efficiencies. Out of the vast multiplicity of geometrically possible and computationally accessible conformers, only a limited number will be of relevance for the problem under consideration. In ligand design for drug discovery, a relative energy ranking determined on isolated conformers is only of limited use for the selection of biologically relevant conformers. This is due to an unsatisfactory transferability of energy scales between different energy functions and the strong modulation of conformational energies of isolated molecules once exposed to a structured molecular environment. A knowledge-based approach, using torsionangle libraries as retrieved for common fragments in small-molecule crystal structures, allows one to map more efficiently the biologically relevant part of conformation space. The relevance of these libraries for the conditions at the binding pocket of a protein is evidenced by experimental data. Sets of well-distributed conformers can be used to compare different drug molecules binding to common targets. Such comparisons reveal new modes of structural superposition of the molecules and consideration of their physicochemical properties leads to interesting pharmacophore hypotheses. They indicate possible binding geometries at the recognition site of a protein and highlight the structural similarities and differences that correlate with changes in the biological properties. Comparisons of GP IIb/IIIa receptor antagonists and of thrombin inhibitors are discussed.

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References

  1. Goto, H., Osawa, E. and Yamato, M., Tetrahedron, 49 (1993) 387.

    Google Scholar 

  2. Saunders, M., J. Comput. Chem., 12 (1991) 645.

    Google Scholar 

  3. Saunders, M., Houk, K.N., Wu, Y.D., Still, W.C., Lipton, M., Chang, G. and Guida, W.C., J. Am. Chem. Soc., 112 (1990) 1419.

    Google Scholar 

  4. Osawa, E. and Orville-Thomas, W.J. (Eds.), J. Mol. Struct. (THEOCHEM), 114 (1994).

  5. Pearlman, R.S., In Kubinyi, H. (Ed.) 3D QSAR in Drug Design: Theory, Methods and Applications, ESCOM, Leiden, 1993, p. 41.

    Google Scholar 

  6. Müller, K., Ammann, H.J., Doran, D.M., Gerber, P.R., Gubernator, K. and Schrepfer, G., Bull. Soc. Chim. Belg., 97 (1988) 655

    Google Scholar 

  7. Gerber, P.R. and Müller, K., J. Comput.-Aided Mol. Design, 9 (1995) 251.

    Google Scholar 

  8. Böhm, H.J., Klebe, G., Lorenz, T., Mietzner, T. and Siggel, L., J. Comput. Chem., 11 (1990) 1021.

    Google Scholar 

  9. Peishoff, C.E. and Dixon, J.S., J. Comput. Chem., 13 (1992) 565.

    Google Scholar 

  10. Yodo, M., Kataoka, T. and Marshall, G.R., manuscript in preparation.

  11. Saunders, M. and Jarret, R.M., J. Comput. Chem., 7 (1986) 578.

    Google Scholar 

  12. Koca, J., J. Mol. Struct. (THEOCHEM), 308 (1994) 13.

    Google Scholar 

  13. Koca, J. and Carlsen, P.H.J., J. Mol. Struct. (THEOCHEM), 257 (1992) 105, 131.

    Google Scholar 

  14. Kolossvary, I. and Guida, W.C., J. Comput. Chem., 14 (1993) 691.

    Google Scholar 

  15. Maranas, C.D. and Floudas, C.A., J. Chem. Phys., 100 (1994) 1247.

    Google Scholar 

  16. Michel, A.G. and Jeandenans, C., Comput. Chem., 17 (1993) 49.

    Google Scholar 

  17. Goto, H. and Osawa, E., J. Chem. Soc., Perkin Trans. II, (1993) 187.

    Google Scholar 

  18. Goto, H. and Osawa, E., Tetrahedron Lett., 33 (1992) 1343.

    Google Scholar 

  19. Goto, H. and Osawa, E., J. Mol. Struct. (THEOCHEM), 104 (1993) 157.

    Google Scholar 

  20. Perez, J.J., Villar, H.O. and Arteca, G.A., J. Phys. Chem., 98 (1994) 2318.

    Google Scholar 

  21. Meza, J.C. and Martinez, M.L., J. Comput. Chem., 15 (1994) 627.

    Google Scholar 

  22. Guarnieri, F. and Wilson, S.R., Tetrahedron, 48 (1992) 4271.

    Google Scholar 

  23. Noguta, T. and Go, N., Biopolymers, 24 (1985) 427.

    Google Scholar 

  24. Hagler, A.T., Peptides, 7 (1985) 213.

    Google Scholar 

  25. Howard, A.E. and Kollman, P.A., J. Med. Chem., 31 (1988) 1669.

    Google Scholar 

  26. Sun, Y.X. and Kollman, P.A., J. Comput. Chem., 13 (1992) 33.

    Google Scholar 

  27. Byrne, D., Li, J., Platt, E., Robson, B. and Weiner, P., J. Comput.-Aided Mol. Design, 8 (1994) 67.

    Google Scholar 

  28. Mayer, D., Naylor, C.B., Motoc, I. and Marshall, G.R., J. Comput.-Aided Mol. Design, 1 (1987) 3.

    Google Scholar 

  29. Iijima, H., Dunbar Jr., J.B. and Marshall, G.R., Proteins, 2 (1987) 330.

    Google Scholar 

  30. Zabrocki, J., Smith, G.D., Dunbar J.B., Jr., Ijima, H. and Marshall, G.M., J. Am. Chem. Soc., 110 (1988) 5875.

    Google Scholar 

  31. Goodman, J.M. and Still, W.C., J. Comput. Chem., 12 (1991) 1110.

    Google Scholar 

  32. Ghose, A.K., Jaeger, E.P., Kowalczyk, P.J., Peterson, M.L. and Treasurywala, A.M., J. Comput. Chem., 14 (1993) 1050.

    Google Scholar 

  33. SYBYL, Tripos Associates, Inc., St. Louis, MO.

  34. Crippen, G. and Havel, T.F., Distance Geometry and Molecular Conformation, Research Studies Press, Wiley, New York, NY, 1988.

    Google Scholar 

  35. Weiner, P.K., Profeta, S., Wipff, G., Havel, T., Kuntz, I.D., Langridge, R. and Kollman, P.A., Tetrahedron, 39 (1983) 1113.

    Google Scholar 

  36. Crippen, G.M., J. Comput. Chem., 13 (1992) 351.

    Google Scholar 

  37. Billeter, M., Howard, A.E., Kuntz, I.D. and Kollman, P.A., J. Am. Chem. Soc., 110 (1988) 8385.

    Google Scholar 

  38. Clark, D.E., Jones, G., Willet, P., Kenny, P.W. and Glen, R.C., J. Chem. Inf. Comput. Sci., 34 (1994) 197.

    Google Scholar 

  39. Saunders, M., J. Am. Chem. Soc., 109 (1987) 3150.

    Google Scholar 

  40. Saunders, M., J. Comput. Chem., 10 (1989) 203.

    Google Scholar 

  41. Ferguson, D.M. and Raber, D.J., J. Am. Chem. Soc., 111 (1989) 4371.

    Google Scholar 

  42. Saunders, M. and Jimenezvazquez, H.A., J. Comput. Chem., 14 (1993) 330.

    Google Scholar 

  43. Morley, S.D., Jackson, D.E., Saunders, M.R. and Vinter, J.G., J. Comput. Chem., 13 (1992) 693.

    Google Scholar 

  44. Freyberg, V.B. and Braun, W., J. Comput. Chem., 12 (1991) 1065.

    Google Scholar 

  45. Gerber, P.R., Gubernator, K. and Müller, K., Helv. Chim. Acta, 71 (1988) 1429.

    Google Scholar 

  46. Allen, F.H. and Kennard, O., Acc. Chem. Res., 16 (1983) 146.

    Google Scholar 

  47. Klebe, G., J. Mol. Struct. (THEOCHEM), 114 (1994) 53.

    Google Scholar 

  48. MOMO, Beck, H. and Egert, E., University of Göttingen, Göttingen, 1988.

  49. Smith, A. and Linder, J., J. Comput.-Aided Mol. Design, 5 (1991) 235.

    Google Scholar 

  50. Dauber-Osguthorpe, P., Roberts, V.A., Osguthorpe, D.J., Wolff, J., Genest, M. and Hagler, A.T., Proteins, 4 (1988) 31.

    Google Scholar 

  51. Allinger, N.L., J. Am. Chem. Soc., 99 (1977) 8127.

    Google Scholar 

  52. Clark, M., Cramer R.D. III, and Van Opdenbosch, N., J. Comput. Chem., 10 (1989) 982.

    Google Scholar 

  53. PCModel/MMX, Serena Software, Bloomington, IN.

  54. MM2P, Molecular Design Ltd., San Leandro, CA.

  55. BIOGRAF, Biodesign, Inc., Pasadena, CA.

  56. Dewar, M.J.S., Zoebisch, E.G., Healy, E.F. and Stewart, J.J.P., J. Am. Chem. Soc., 107 (1985) 3902.

    Google Scholar 

  57. Kroon-Batenburg, L.M.J., Kroon, J. and Northolt, M.G., Das Papier, 44 (1990) 639.

    Google Scholar 

  58. Kroon-Batenburg, L.M.J., Kroon, J. and Northolt, M.G., Polymer Commun., 27 (1986) 290.

    Google Scholar 

  59. Kroon-Batenburg, L.M.J. and Kroon, J., Biopolymers, 29 (1990) 1243.

    Google Scholar 

  60. Byrn, S.R., Annu. Rep. Med. Chem., 29 (1986) 346.

    Google Scholar 

  61. Stephenson, G., Ph.D. Thesis, Purdue University, West Lafayette, IN, 1994.

    Google Scholar 

  62. Maverick, E., Mirsky, K., Knobler, C.B. and Trueblood, K.N., Acta Crystallogr., B47 (1991) 272.

    Google Scholar 

  63. Klebe, G., In Jeffrey, G.A. and Piniella, J.F. (Eds.) The Application of Charge Density Research to Chemistry and Drug Design, Nato Advanced Study Institute, Plenum, New York, NY, 1991, pp. 287–318.

    Google Scholar 

  64. Weiner, S.J., Kollman, P.A., Nguyen, D.T. and Case, D.A., J. Comput. Chem., 7 (1986) 230.

    Google Scholar 

  65. Brooks, B.R., Bruccoleri, R.E., Olafson, B.D., States, D.J., Swaminathan, S. and Karplus, M., J. Comput. Chem., 4 (1983) 187.

    Google Scholar 

  66. Böhm, H.J. and Brode, S., J. Am. Chem. Soc., 113 (1991) 7131.

    Google Scholar 

  67. Klebe, G., In Bürgi, H.B. and Dunitz, J.D. (Eds.) Structure Correlation, VCH Weinheim, 1994, pp. 543–603.

  68. Ricketts, E.M., Bradshaw, J., Hann, M., Hayes, F., Tanna, N. and Ricketts, D.M., J. Chem. Inf. Comput. Sci., 33 (1993) 905.

    Google Scholar 

  69. Bernstein, F.C., Koetzle, T.F., Williams, G.J.B., Meyer, E.F., Brice, M.D., Rodgers, J.R., Kennard, O., Shimanouchi, T. and Tasumi, M., J. Mol. Biol., 112 (1977) 535.

    Google Scholar 

  70. Klebe, G. and Mietzner, T., J. Comput.-Aided Mol. Design, 8 (1994) 583.

    Google Scholar 

  71. DeClerq, P.J., Hoflack, J. and Cauwbergh, S., QCPE Program No. QCMP079, Quantum Chemistry Program Exchange, Bloomington, IN.

  72. Kato, Y., Itai, A. and Iitaka, Y., Tetrahedron, 43 (1987) 5229.

    Google Scholar 

  73. Kato, Y., Inoue, A., Yamada, M., Tomioka, N. and Itai, A., J. Comput.-Aided Mol. Design, 6 (1992) 475.

    Google Scholar 

  74. Herrmann, R.B. and Herron, D.K., J. Comput.-Aided Mol. Design, 5 (1991) 511.

    Google Scholar 

  75. Manaut, M., Sanz, F., Jose, J. and Milesi, M., J. Comput.-Aided Mol. Design, 5 (1991) 371.

    Google Scholar 

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

    Google Scholar 

  77. Dean, P.M. and Chau, P.L., J. Mol. Graphics, 5 (1987) 152.

    Google Scholar 

  78. Dean, P.M., Callow, P. and Chau, P.L., J. Mol. Graphics, 6 (1988) 28.

    Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  81. Viswanadhan, V.N., Ghose, A.K., Revankar, G.R. and Robins, R.K., J. Chem. Inf. Comput. Sci., 29 (1989) 163.

    Google Scholar 

  82. Martin, Y.C., Bures, M.G., Danaher, E.A., DeLazzer, J., Lico, I. and Pavlik, P., J. Comput.-Aided Mol. Design, 7 (1993) 83.

    Google Scholar 

  83. Klebe, G., J. Mol. Biol., 237 (1994) 212.

    Google Scholar 

  84. Kopple, K.D., Baures, P.W., Bean, J.W., D'Ambrosio, C.A., Hughes, J.L., Peishoff, C.E. and Eggleston, D.S., J. Am. Chem. Soc., 114 (1992) 9615.

    Google Scholar 

  85. McDowell, R.S., Blackburn, B.K., Gadek, T.R., McGee, L.R., Rawson, T., Reynolds, M.E., Robarge, K.D., Somers, T.C., Thorsett, E.D., Tischler, M., Webb R.R. II, and Venuti, M.C., J. Am. Chem. Soc., 116 (1994) 5077.

    Google Scholar 

  86. Ku, T.W., Ali, F.E., Barton, L.S., Bean, J.W., Bondinell, W.E., Burgess, J.L., Callahan, J.F., Calvo, R.R., Chen, L., Eggleston, D.S., Gleason, J.G., Huffman, W.F., Hwang, S.M., Jakas, D.R., Karash, C.B., Keenan, R.M., Kopple, K.D., Miller, W.H., Newlander, K.A., Nichols, A., Parker, M.F., Peishoff, C.E., Samanen, J.M., Uzinskas, I. and Venslavsky, J.W., J. Am. Chem. Soc., 115 (1993) 8861.

    Google Scholar 

  87. Alig, L., Edenhofer, A., Müller, M. and Weller, T., U.S. Patent 5,039,850, 1991.

  88. Himmelsbach, F., European Patent EP 0 483 667.

  89. Hirschmann, R., Sprengeler, P.A., Kawasaki, T., Leahy, J.W., Shakespeare, W.C. and Smith A.B., III, J. Am. Chem.-Soc., 114 (1992) 9699.

    Google Scholar 

  90. Stubbs, M.T. and Bode, W., Perspect. Drug Discov. Design, 1 (1993) 431.

    Google Scholar 

  91. Liu, L.W., Vu, T.K.H., Esmon, C.T. and Coughlin, S.R., J. Biol. Chem., 266 (1991) 16977.

    Google Scholar 

  92. Banner, D.W. and Hadvary, P., J. Biol. Chem., 266 (1991) 20085.

    Google Scholar 

  93. Lyle, T.A., Perspect. Drug Discov. Design, 1 (1993) 453.

    Google Scholar 

  94. Gasteiger, J., Rudolph, C. and Sadowski, J., Tetrahedron Comput. Methodol., 3 (1990) 537.

    Google Scholar 

  95. Brandstetter, H., Turk, D., Hoeffken, H.W., Grosse, D., Stürzebecher, J., Martin, P.D., Edwards, B.F.P. and Bode, W., J. Mol. Biol., 226 (1992) 1085.

    Google Scholar 

  96. Hilpert, K., Ackermann, J., Banner, D., Gast, A., Gubernator, K., Hadvary, P., Labler, L., Müller, K., Schmid, G., Tschopp, T. and Van den Waterbeemd, H., J. Med. Chem., 37 (1994) 3889.

    Google Scholar 

  97. Hahn, M. and Wipke, W.T., Tetrahedron Comput. Methodol., 1 (1988) 81.

    Google Scholar 

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This paper is dedicated to Prof. Dr. Richard Neidlein (University of Heidelberg, Heidelberg, Germany) on the occasion of his 65th birthday.

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Klebe, G. Toward a more efficient handling of conformational flexibility in computer-assisted modelling of drug molecules. Perspectives in Drug Discovery and Design 3, 85–105 (1995). https://doi.org/10.1007/BF02174468

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