Perspectives in Drug Discovery and Design

, Volume 19, Issue 1, pp 99–116 | Cite as

ACD/Log P method description

  • Alanas A. PetrauskasEmail author
  • Eduard A. Kolovanov


This study describes the development of the ACD/Log P calculation method. Analysis of 14 calculation methods revealed that the most accurate calculations are obtained when correction factors are used. We evaluated the correction factors used by Hansch and Leo in CLOGP in order to simplify their method. Most of the CLOGP structural factors are included in our fragmental increments. Aliphatic and aromatic factors are replaced with additive interfragmental increments. Missing increments are estimated by two empirical equations with simple physical interpretation. The final method uses three simple equations with several types of parameters. The training set included 3601 compounds and the correlation between experimental and calculated Log P values gave R = 0.992, S = 0.21. The method was validated by comparing it with 17 other methods on various data sets of independently selected drugs and other compounds. In all cases, our method produced the best results. The weakness of this method is that it uses a large number of individual increments for aromatic interactions. Each increment represents a combination of several effects which presently cannot be separated.

ACD/Log P CLOGP correction factors fragmental methods Hansch–Leo approach hydrophobicity lipophilicity octanol–water partition coefficients 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mannhold, R. and Dross, K., Quant. Struct.-Act. Relat., 15 (1996) 403.Google Scholar
  2. 2.
    Meylan, W. and Howard, P., J. Pharm. Sci., 84 (1995) 83.PubMedGoogle Scholar
  3. 3.
    Klopman, G., Li, J.-Y., Wang, S. and Dimayuga, M., J. Chem. Inf. Comput. Sci., 34 (1994) 752.CrossRefGoogle Scholar
  4. 4.
    Rekker, R.F. and Mannhold, R., Calculation of Drug Lipophilicity, VCH, Weinheim, 1992.Google Scholar
  5. 5.
    Chou, J. and Jurs, P.C., J. Chem. Inf. Comput. Sci., 19 (1979) 172.CrossRefGoogle Scholar
  6. 6.
    Leo, A., Jow, P.Y.C., Silipo, C. and Hansch, C., J. Med. Chem., 18 (1975) 865.PubMedCrossRefGoogle Scholar
  7. 7.
    Hansch, C. and Leo, A., Substituent Constants for Correlation Analysis in Chemistry and Biology, Wiley, New York, NY, 1979.Google Scholar
  8. 8.
    Leo, A.J., Chem. Rev., 93 (1993) 1281.CrossRefGoogle Scholar
  9. 9.
    Hansch, C., Leo, A. and Hoekman, D., Exploring QSAR. Hydrophobic, Electronic, and Steric Constants, American Chemical Society, Washington, DC, 1995.Google Scholar
  10. 10.
    Nys, G.G. and Rekker, R.F., Chim. Ther., 8 (1973) 521.Google Scholar
  11. 11.
    Nys, G.G. and Rekker, R.F., Eur. J. Med. Chem., 9 (1974) 361.Google Scholar
  12. 12.
    Rekker, R.F., The Hydrophobic Fragmental Constant, Pharmacochemistry Library, Vol. 1, Elsevier, Amsterdam, 1977.Google Scholar
  13. 13.
    Rekker, R.F. and de Kort, H.M., Eur. J. Med. Chem., 14 (1979) 479.Google Scholar
  14. 14.
    Viswanadhan, V.N., Ghose, A.K., Revankar, G.R. and Robins, R.K., J. Chem. Inf. Comput. Sci., 29 (1989) 163.CrossRefGoogle Scholar
  15. 15.
    Convard, T., Dubost, J.-P., Le Solleu, H. and Kummer, E., Quant. Struct.-Act. Relat., 13 (1994) 34.Google Scholar
  16. 16.
    Ghose, A.K. and Crippen, G.M., J. Comput. Chem., 7 (1986) 565.CrossRefGoogle Scholar
  17. 17.
    Ghose, A.K. and Crippen, G.M., J. Chem. Inf. Comput. Sci., 27 (1987) 21.PubMedCrossRefGoogle Scholar
  18. 18.
    Ghose, A.K., Pritchett, A. and Crippen, G.M., J. Comput. Chem., 9 (1988) 80.CrossRefGoogle Scholar
  19. 19.
    Suzuki, T. and Kudo, Y., J. Comput.-Aided Mol. Design, 4 (1990) 155.CrossRefGoogle Scholar
  20. 20.
    Brickmann, J. and Waldherr-Teschner, M., Informationstechnik, 33 (1991) 83.Google Scholar
  21. 21.
    Kellogg, G.E. and Abraham, D., J. Comput.-Aided Mol. Design, 5 (1991) 545.CrossRefGoogle Scholar
  22. 22.
    Ulmschneider, M., Ph.D. Thesis, University of Haute-Alsace, Mulhouse, France, 1993.Google Scholar
  23. 23.
    Palm, V.A., Quantitative Theory of Organic Reactions (Rus), Khimiya, Leningrad, 1977.Google Scholar
  24. 24.
    Rekker, R.F., ter Laak, A.M. and Mannhold, R., Quant. Struct.-Act. Relat., 12 (1993) 152.Google Scholar
  25. 25.
    Moriguchi, I., Hirono, S., Liu, Q., Nakagome, I. and Matsushita, Y., Chem. Pharm. Bull., 40 (1992) 127.Google Scholar
  26. 26.
    Moriguchi, I., Hirono, S., Nakagome, I. and Hirano, H., Chem. Pharm. Bull., 42 (1994) 976.Google Scholar
  27. 27.
    Viswanadhan, V.N., Reddy, M.R., Baccquet, R.J. and Erion, M.D., J. Comput. Chem., 14 (1993) 1019.CrossRefGoogle Scholar
  28. 28.
    Bodor, N., Gabanyi, Z. and Wong, C.-K., J. Am. Chem. Soc., 111 (1989) 3783.CrossRefGoogle Scholar
  29. 29.
    Bodor, N. and Huang, M.-J., J. Pharm. Sci., 81 (1992) 272.PubMedGoogle Scholar
  30. 30.
    Data from SciLogP Demo version, SciVision, Lexington, MA.Google Scholar
  31. 31.
    Martin, Y.C., Duban, M.E. and Bures, M.G., Calculating LogP: A Work-In-Progress, report on Scholar
  32. 32.
    Leo, A.J., Chem. Pharm. Bull., 43 (1995) 512.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  1. 1.ACD, Inc.TorontoCanada
  2. 2.ACD, Inc.TorontoCanada

Personalised recommendations