Journal of Computer-Aided Molecular Design

, Volume 17, Issue 12, pp 797–810 | Cite as

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

  • Anu J. Tervo
  • Tommi H. Nyrönen
  • Toni Rönkkö
  • Antti Poso

Abstract

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.

3D QSAR COMT inhibitors CoMFA GRID/GOLPE docking 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Männistö, P.T. and Kaakkola, S., Pharmacol. Rev., 51 (1999) 593.PubMedGoogle Scholar
  2. 2.
    Axelrod, J. and Tomchick, R., J. Biol. Chem., 233 (1958) 702.PubMedGoogle Scholar
  3. 3.
    Guldberg, H.C. and Marsden, C.A., Pharmacol. Rev., 27 (1975) 135.PubMedGoogle Scholar
  4. 4.
    Bonifati, V. and Meco, G., Pharmacol. Ther., 81 (1999) 1.CrossRefPubMedGoogle Scholar
  5. 5.
    Gordin, A., Kaakkola, S. and Teräväinen, H., Adv. Neurol., 91 (2003) 237.PubMedGoogle Scholar
  6. 6.
    Guttman, M., Leger, G., Reches, A., Evans, A., Kuwabara, H., Cedarbaum, J.M. and Gjedde, A., Mov. Disord., 8 (1993) 298.CrossRefPubMedGoogle Scholar
  7. 7.
    Najib, J., Clin. Ther., 23 (2001) 802.CrossRefPubMedGoogle Scholar
  8. 8.
    De Santi, C., Giulianotti, P.C., Pietrabissa, A., Mosca, F. and Pacifici, G.M., Eur. J. Clin. Pharmacol., 54 (1998) 215.CrossRefPubMedGoogle Scholar
  9. 9.
    Zurcher, G., Colzi, A. and Da Prada, M.J., Neural. Transm. Suppl., 32 (1990) 375.Google Scholar
  10. 10.
    Micek, S.T. and Ernst, M.E., Am. J. Health Syst. Pharm., 56 (1999) 2195.PubMedGoogle Scholar
  11. 11.
    Olanow, C.W., Arch. Neurol., 57 (2000) 263.CrossRefPubMedGoogle Scholar
  12. 12.
    Taskinen, J., Vidgren, J., Ovaska, M., Bäckström, R., Pippuri, A. and Nissinen, E., Quant. Struct.-Act. Relat., 8 (1989) 210.Google Scholar
  13. 13.
    Lotta, T., Taskinen, J., Bäckström, R. and Nissinen, E., J. Comput.-Aided Mol. Des., 6 (1992) 253.CrossRefGoogle Scholar
  14. 14.
    Cramer III, R.D., Patterson, D.E. and Bunce, J.D., J. Am. Chem. Soc., 110 (1988) 5959.CrossRefGoogle Scholar
  15. 15.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, I.N., Shindyalov, P.E. and Bourne, P.E., Nucleic Acids Res., 28 (2000) 235.CrossRefPubMedGoogle Scholar
  16. 16.
    Vidgren, J., Svensson, L.A. and Liljas, A., Nature, 368 (1994) 354.CrossRefPubMedGoogle Scholar
  17. 17.
    Buolamwini, J.K. and Assefa, H., J. Med. Chem., 45 (2002) 841.CrossRefPubMedGoogle Scholar
  18. 18.
    Sippl, W., J. Comput.-Aided Mol. Des., 14 (2000) 559.CrossRefPubMedGoogle Scholar
  19. 19.
    Liu, H., Huang, X., Shen, J., Luo, X., Li, M., Xiong, B., Chen, G., Yang, Y., Jiang, H. and Chen, K., J. Med. Chem., 45 (2002) 4816.CrossRefPubMedGoogle Scholar
  20. 20.
    Böhm, H.J., J. Comput.-Aided Mol. Des., 8 (1994) 243.CrossRefPubMedGoogle Scholar
  21. 21.
    Goodford, P.J., J. Med. Chem., 28 (1985) 849.CrossRefPubMedGoogle Scholar
  22. 22.
    Baroni, M., Costantino, G., Cruciani, G., Riganelli, D., Valigi, R. and Clementi, S., Quant. Struct.-Act. Relat., 12 (1993) 9.Google Scholar
  23. 23.
    Sybyl 6.8, Tripos Inc., St. Louis, MO.Google Scholar
  24. 24.
    Sadowski, J. and Gasteiger, J., Chem. Rev., 93 (1993) 2567.CrossRefGoogle Scholar
  25. 25.
    Sadowski, J., Gasteiger, J. and Klebe, G., J. Chem. Inf. Comput. Sci., 34 (1994) 1000.CrossRefGoogle Scholar
  26. 26.
    Clark, M., Cramer III, R.D. and Van Opdenbosch, N., J. Comput. Chem., 10 (1989) 982.CrossRefGoogle Scholar
  27. 27.
    Rarey, M., Kramer, B., Lengauer, T. and Klebe, G., J. Mol. Biol., 261 (1996) 470.CrossRefPubMedGoogle Scholar
  28. 28.
    Gasteiger, J. and Marsili, M., Tetrahedron, 36 (1980) 3219.CrossRefGoogle Scholar
  29. 29.
    Purcell, W.P. and Singer, J.A., J. Chem. Eng. Data 12 (1967) 235.CrossRefGoogle Scholar
  30. 30.
    Stewart, J.J., J. Comput.-Aided Mol. Des., 4 (1990) 1.CrossRefPubMedGoogle Scholar
  31. 31.
    Besler, B.H., Merz, K.M. and Kollman, P.A., J. Comput. Chem., 11 (1990) 431.CrossRefGoogle Scholar
  32. 32.
    Cramer III, R.D., Bunce, J.D. and Patterson, D.E., Quant. Struct.-Act. Relat., 7 (1988) 18.Google Scholar
  33. 33.
    Oprea, T.I. and Garcia, A.E., J. Comput.-Aided Mol. Des., 10 (1996) 186.CrossRefPubMedGoogle Scholar
  34. 34.
    Pastor, M., Cruciani, G. and Clementi, S., J. Med. Chem., 40 (1997) 1455.CrossRefPubMedGoogle Scholar
  35. 35.
    Clark, R.D., Strizhev, A., Leonard, J.M., Blake, J.F. and Matthew, J.B., J. Mol. Graph. Model., 20 (2002) 281.CrossRefPubMedGoogle Scholar
  36. 36.
    Wallace, A.C., Laskowski, R.A. and Thornton, J.M., Protein Eng., 8 (1995) 127.PubMedGoogle Scholar
  37. 37.
    Lehtonen, J. V., Rantanen, V.-V., Still, D.-J., Ekholm, J., Björklund, D., Iftikhar, Z., Huhtala, M., Jussila, A., Jaakkola, J., Pentikäinen, O.T., Nyrönen, T.A., S.T., Gyllenberg, M. and Johnson, M.S., BODIL: a molecular modeling environment for structure-function analysis and drug discovery, unpublished, http://www.abo.fi/fak/mnf/bkf/ research/johnson/bodil.html.Google Scholar

Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Anu J. Tervo
    • 1
    • 2
  • Tommi H. Nyrönen
    • 2
  • Toni Rönkkö
    • 1
  • Antti Poso
    • 1
  1. 1.Department of Pharmaceutical ChemistryUniversity of KuopioKuopioFinland
  2. 2.CSC – Scientific Computing Ltd.EspooFinland

Personalised recommendations