Binding of α-hydroxy-β-amino acid inhibitors to methionine aminopeptidase. The performance of two types of scoring functions

  • Anne Techau Jørgensen
  • Morten Dahl Sørensen
  • Fredrik Björkling
  • Tommy Liljefors


The binding mode of a recently described set of α-hydroxy-β-amino acid inhibitors of methionine aminopeptidase type 2 is suggested in the present work. The binding mode is supported by analysis of published structures of transition state analogues co-crystallised with E. coli methionine aminopeptidase and by a comparison of molecular interaction fields calculated using GRID for E. coli and human methionine aminopeptidase. Based on the suggested binding mode two types of scoring functions have been evaluated and compared. These are the commercially available consensus score, CScore, and scoring of the ligands employing energies calculated using the Merck Molecular Force Field (MMFF). Enriched subsets of ligands were obtained when using CScore, but these scores could not be used to assess the relative affinities of individual compounds. Although still not sufficiently accurate for reliable predictive purposes, an improved correlation was obtained between structure and affinity using a combined force field energy including contributions from solvation and conformational energy penalty for binding.

scoring functions CScore Merck Molecular Force Field (MMFF) methionine aminopeptidase angiogenesis α-hydroxy-β-amino acid inhibitors GRID conformational energies solvation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Folkman, J., Nat. Med., 1 (1995) 27.Google Scholar
  2. 2.
    Folkman, J., N. Eng. J. Med., 333 (1995) 1757.Google Scholar
  3. 3.
    Griffith, E.C., Su, Z., Turk, B.E., Chen, S., Chang, Y.-H., Wu, Z., Biemann, K. and Liu, J.O., Chem. Biol., 4 (1997) 461.Google Scholar
  4. 4.
    Turk, B.E., Griffith, E.C., Wolf, S., Biemann, K., Chang, Y.H. and Liu, J.O., Chem. Biol., 6 (1999) 823.Google Scholar
  5. 5.
    Wang, J.Y., Lou, P.P. and Henkin, J., J. Cell. Biochem., 77 (2000) 465.Google Scholar
  6. 6.
    Kusaka, M., Sudo, K., Matsutani, E., Kozai, Y., Marui, S., Fujita, T., Ingber, D. and Folkman, J., Br. J. Cancer, 69 (1994) 212.Google Scholar
  7. 7.
    Ingber, D., Fujita, T., Kishimoto, S., Sudo, K., Kanamaru, T., Brem, H. and Folkman, J., Nature, 348 (1990) 555.Google Scholar
  8. 8.
    Griffith, E.C., Su, Z., Niwayama, S., Ramsay, C.A., Chang, Y.-H. and Liu, J.O., Proc. Natl. Acad. Sci. USA, 95 (1998) 15183.Google Scholar
  9. 9.
    Bradshaw, R.A., Brickey, W.W. and Walker, K.W., Trends Biochem. Sci., 23 (1998) 263.Google Scholar
  10. 10.
    Liu, S., Widom, J., Kemp, C.W., Crews, C.M. and Clardy, J., Science, 282 (1998) 1324.Google Scholar
  11. 11.
    Lowther, W.T., Orville, A.M., Madden, D.T., Lim, S., Rich, D.H. and Matthews, B.W., Biochemistry, 38 (1999) 7678.Google Scholar
  12. 12.
    Tahirov, T.H., Oki, H., Tsukihara, T., Ogasahara, K., Yutani, K., Ogata, K., Izu, Y., Tsunasawa, S. and Kato, I., J. Mol. Biol., 284 (1998) 101.Google Scholar
  13. 13.
    Abbott Laboratories. Substituted beta-amino acid inhibitors of methionine aminopeptidase-2. Int. Pat. Appl. WO 99/57098, 1999.Google Scholar
  14. 14.
    Goodford, P.J., J. Med. Chem., 28 (1985) 849.Google Scholar
  15. 15.
    GRID v. 20, Molecular Discovery Ltd., 4 Chandos Street, London, England, 2001-2002.Google Scholar
  16. 16.
    Böhm, H.-J. and Stahl, M. In K. B. Lipkowitz and D. B. Boyd (ed.), Reviews in Computational Chemistry, Volume 18. John Wiley and Sons, Inc., Hoboken, New Jersey, 2002, pp. 41.Google Scholar
  17. 17.
    Gohlke, H. and Klebe, G., Cur. Opin. Struct. Biol., 11 (2001) 231.Google Scholar
  18. 18.
    Muegge, I. and Rarey, M. In K. B. Lipkowitz and D. B. Boyd (ed.), Reviews in Computational Chemistry, Volume 17. Wiley-VCH, John Wiley and Sons, Inc., New York, 2001, pp. 1.Google Scholar
  19. 19.
    Bissantz, C., Folkers, G. and Rognan, D., J. Med. Chem., 43 (2000) 4759.Google Scholar
  20. 20.
    Charifson, P.S., Corkery, J.J., Murcko, M.A. and Walters, W.P., J. Med. Chem., 42 (1999) 5100.Google Scholar
  21. 21.
    Hoffmann, D., Kramer, B., Washio, T., Steinmetzer, T., Rarey, M. and Lengauer, T., J. Med. Chem., 42 (1999) 4422.Google Scholar
  22. 22.
    Sybyl v. 6.8, Tripos Inc., 1699 South Hanley Rd, St. Louis, Missouri, USAGoogle Scholar
  23. 23.
    Halgren, T.A., J. Comput. Chem., 17 (1996) 490.Google Scholar
  24. 24.
    Halgren, T.A., J. Comput. Chem., 17 (1996) 520.Google Scholar
  25. 25.
    Halgren, T.A., J. Comput. Chem., 17 (1996) 553.Google Scholar
  26. 26.
    Halgren, T.A. and Nachbar, R.B., J. Comput. Chem., 17 (1996) 587.Google Scholar
  27. 27.
    Halgren, T.A., J. Comput. Chem., 17 (1996) 616.Google Scholar
  28. 28.
    Mohamadi, F., Richards, N.G.J., Guida, W.C., Liskamp, R., Lipton, M., Caufield, C., Chang, G., Hendrickson, T. and Still, W.C., J. Comput. Chem., 11 (1990) 440.Google Scholar
  29. 29.
    GRID v. 16, Molecular Discovery Ltd., West Way House, Elms Parade, Oxford, England, 1996-1999.Google Scholar
  30. 30.
    GRID v. 18, Molecular Discovery Ltd., West Way House, Elms Parade, Oxford, England, 1999-2000.Google Scholar
  31. 31.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N. and Bourne, P.E., Nucl. Acids. Res., 28 (2000) 235.Google Scholar
  32. 32.
    Gundertofte, K., Liljefors, T., Norrby, P.-O. and Pettersson, I., J. Comput. Chem., 17 (1996) 429.Google Scholar
  33. 33.
    Jørgensen, A.T., Norrby, P.-O. and Liljefors, T., J. Comput-Aided Mol. Des., 16 (2002) 167.Google Scholar
  34. 34.
    Insight II v. 98.0 Molecular Modeling System, Molecular Simulations, Cambridge, U.K., 1998.Google Scholar
  35. 35.
    Goodman, J.M. and Still, W.C., J. Comput. Chem., 12 (1991) 1110.Google Scholar
  36. 36.
    Chang, G., Wayne, C.G. and Still, W.C., J. Am. Chem. Soc., 111 (1989) 4379.Google Scholar
  37. 37.
    Still, W.C., Tempczyk, A., Hawley, R.C. and Hendrickson, T., J. Am. Chem. Soc., 112 (1990) 6127.Google Scholar
  38. 38.
    Clark, R.D., Strizhev, A., Leonard, J.M., Blake, J.F. and Matthew, J.B., J. Mol. Graphics. Mod., 20 (2002) 281.Google Scholar
  39. 39.
    Rarey, M., Kramer, B., Lengauer, T. and Klebe, G., J. Mol. Biol., 261 (1996) 470.Google Scholar
  40. 40.
    Jones, G., Willett, P., Glen, R.C., Leach, A.R. and Taylor, R., J. Mol. Biol., 267 (1997) 727.Google Scholar
  41. 41.
    Meng, E.C., Shoichet, B.K. and Kuntz, I.D., J. Comput. Chem., 13 (1992) 505.Google Scholar
  42. 42.
    Muegge, I. and Martin, Y.C., J. Med. Chem., 42 (1999) 791.Google Scholar
  43. 43.
    Eldridge, M.D., Murray, C.W., Auton, T.R., Paolini, G.V. and Mee, R.P., J. Comput.-Aided Mol. Des., 11 (1997) 425.Google Scholar
  44. 44.
    Boström, J., Norrby, P.-O. and Liljefors, T., J. Comput.-Aided Mol. Des., 12 (1998) 383.Google Scholar
  45. 45.
    Lowther, W.T., Zhang, Y., Sampson, P.B., Honek, J.F. and Matthews, B.W., Biochemistry, 38 (1999) 14810.Google Scholar
  46. 46.
    Goodford, P. J., Molecular Discovery Ltd., England, personal communication, 2001.Google Scholar

Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Anne Techau Jørgensen
    • 1
  • Morten Dahl Sørensen
    • 2
  • Fredrik Björkling
    • 2
  • Tommy Liljefors
    • 1
  1. 1.Department of Medicinal ChemistryThe Danish University of Pharmaceutical SciencesCopenhagenDenmark
  2. 2.Medicinal Chemistry Research, LEO PharmaBallerupDenmark

Personalised recommendations