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Internally defined distances in 3D-quantitative structure-activity relationships

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Abstract

A new type of 3D-QSAR descriptors is introduced. For each molecule under consideration an internal coordinate system is defined relative to molecular points, such as positions of atoms in the molecule or centers of mass or certain substructures. From the origin of this system distances to the solvent accessible surface are calculated at defined spherical coordinate angles, θ and φ. The distances represent steric features, while the molecular electrostatic potentials at the intersection points with the surface represent the electrostatic contributions. The approach is called IDA (internal distances analysis). Matrices obtained by varying the spherical coordinate angles by fixed increments are correlated with the biological activity by partial least squares (PLS). The descriptors, tested with the benchmark steroids and an also well characterized benzodiazepine data set, turn out to be highly predictive. Additionally, they share the advantage of grid-based methods that the obtained models can be visualized, and thus be directly used in a rational drug design approach.

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References

  1. Hansch, C.A., Accounts Chem. Res., 2 (1996) 232.

    Google Scholar 

  2. Balaban, A.T., Chem. Phys. Lett., 89 (1982) 399.

    Google Scholar 

  3. Hall, L.H. and Kier, L.B., In Lipkowitz, K.B. and Boyd, D.B., (eds.) Reviews in Computational Chemistry Vol. 2., VCH Publishers, New York, NY, 1991, pp. 367–422.

    Google Scholar 

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

    Google Scholar 

  5. Dunn, W.J., Wold, S., Edlund, U. and Hellberg, S., Quant. Struct.-Act. Relat., 3 (1984) 131.

    Google Scholar 

  6. Robinson, D.D., Winn, P.J., Lyne, P.D. and Richards, W.G, J. Med. Chem., 42 (1999) 573.

    Google Scholar 

  7. Good, A.C., So, S.-S. and Richards, W.G, J. Med. Chem., 36 (1993) 433.

    Google Scholar 

  8. Good, A.C., Peterson, S.J. and Richards, W.G., J.Med. Chem., 36 (1993) 2929.

    Google Scholar 

  9. Klebe, G., Abraham, U. and Mietzner, T., J. Med. Chem., 37 (1994) 4130.

    Google Scholar 

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

    Google Scholar 

  11. Jain, A.N., Koile, K. and Chapman, D., J. Med. Chem., 37 (1994) 2315.

    Google Scholar 

  12. Hopfinger, A.J., J. Am. Chem. Soc., 102 (1980) 7196.

    Google Scholar 

  13. Green, J., Kahn, S., Savoj, H., Sprague, P, and Teig, S., J. Chem. Inf. Comput. Sci., 34 (1994) 1297.

    Google Scholar 

  14. Barnum, D., Greene, J., Smellie, A., and Sprague, P., J. Chem. Inf. Comput. Sci., 36, (1996) 563.

    Google Scholar 

  15. Hahn, M. and Rogers, D., J. Med. Chem., 38 (1995) 2080.

    Google Scholar 

  16. Silverman, B.D. and Platt,_D.E., J. Med. Chem., 39 (1996) 2129.

    Google Scholar 

  17. Bravi, G., Gancia, E., Mascagni, P., Pegna, M., Todeschini, R. and Zaliani, A.J, J. Comput. Aid. Mol. Des., 11 (1997) 79.

    Google Scholar 

  18. Wagener, M., Sadowski, J. and Gasteiger, J., J. Am. Chem. Soc., 117 (1995) 7769.

    Google Scholar 

  19. Pastor, M., Cruciani, G., McLay, I., Pickett, S. and Clementi, S., J. Med. Chem., 43 (2000) 3233.

    Google Scholar 

  20. Lee, B. and Richards, F.M., J. Mol. Biol., 55 (1971) 379.

    Google Scholar 

  21. Flowers, D.R., J. Mol. Graphics Mod., 15 (1997) 238.

    Google Scholar 

  22. TSAR 3.3, Oxford Molecular Ltd., The Medawar Centre, Oxford Science Park, Oxford, 2000.

  23. Ståhle, L. and Wold, S., In Ellis, G.P. and West, G.B. (eds.), Progress in Medicinal Chemistry, Vol. 25, Elvesier Scientific Publishers, Amsterdam, 1988, pp. 292–338.

    Google Scholar 

  24. CORINA Molecular Networks, GmbH Computerchemie, Langenmarckplatz 1, Erlangen, 1997.

    Google Scholar 

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

    Google Scholar 

  26. Maddalena, D. and Johnston, G.A.R., J. Med. Chem., 38 (1995) 715.

    Google Scholar 

  27. So, S.-S and Karplus, M., J. Med. Chem., 39 (1996) 5246.

    Google Scholar 

  28. Winkler, D.A. and Burden, F.R., Quant. Struct.-Act. Relat., 17 (1998) 224.

    Google Scholar 

  29. Drapper, N.R. and Smith, H., Applied Regression Analysis, J. Wiley & Sons, New York, NY, 1981, p. 93.

    Google Scholar 

  30. Hahn, M. and Rogers, D., J. Med. Chem., 38 (1995) 2091.

    Google Scholar 

  31. Baroni, M., Constantino, G., Cruciani, G., Riganelli, D., Valigi, R. and Clementi, S., Quant. Struct.-Act. Relat., 12 (1993) 9.

    Google Scholar 

  32. Motoc I. and Marshall, G.R., Chem. Phys. Lett., 116 (1985) 415.

    Google Scholar 

  33. Kubinyi, H, Hamprecht, F.A. and Mietzner, T., J.Med. Chem., 41 (1998) 2553.

    Google Scholar 

  34. Coats, E.A., In Kubinyi, H., Folkers, G. and Martin, Y.C. (eds), 3D QSAR in Drug Design., Vol 3, Recent Advances, Kluwer/ESCOM, Dordrecht, 1998, pp. 199–213.

    Google Scholar 

  35. Klein, C. T., Viernstein, H. and Wolschann, P., Sci. Pharm., 68 (2000) 15.

    Google Scholar 

  36. Golbraikh, A. and Tropsha, A., J. Mol. Graph. Mod., 20 (2002) 269.

    Google Scholar 

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Correspondence to Christian Th. Klein.

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Klein, C.T., Kaiblinger, N. & Wolschann, P. Internally defined distances in 3D-quantitative structure-activity relationships. J Comput Aided Mol Des 16, 79–93 (2002). https://doi.org/10.1023/A:1016308417830

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