ACD/Log P method description


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.

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  1. 1.

    Mannhold, R. and Dross, K., Quant. Struct.-Act. Relat., 15 (1996) 403.

    CAS  Google Scholar 

  2. 2.

    Meylan, W. and Howard, P., J. Pharm. Sci., 84 (1995) 83.

    PubMed  CAS  Google Scholar 

  3. 3.

    Klopman, G., Li, J.-Y., Wang, S. and Dimayuga, M., J. Chem. Inf. Comput. Sci., 34 (1994) 752.

    CAS  Article  Google 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.

    CAS  Article  Google Scholar 

  6. 6.

    Leo, A., Jow, P.Y.C., Silipo, C. and Hansch, C., J. Med. Chem., 18 (1975) 865.

    PubMed  CAS  Article  Google 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.

    CAS  Article  Google 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.

    CAS  Google Scholar 

  11. 11.

    Nys, G.G. and Rekker, R.F., Eur. J. Med. Chem., 9 (1974) 361.

    CAS  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.

    CAS  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.

    CAS  Article  Google Scholar 

  15. 15.

    Convard, T., Dubost, J.-P., Le Solleu, H. and Kummer, E., Quant. Struct.-Act. Relat., 13 (1994) 34.

    CAS  Google Scholar 

  16. 16.

    Ghose, A.K. and Crippen, G.M., J. Comput. Chem., 7 (1986) 565.

    CAS  Article  Google Scholar 

  17. 17.

    Ghose, A.K. and Crippen, G.M., J. Chem. Inf. Comput. Sci., 27 (1987) 21.

    PubMed  CAS  Article  Google Scholar 

  18. 18.

    Ghose, A.K., Pritchett, A. and Crippen, G.M., J. Comput. Chem., 9 (1988) 80.

    CAS  Article  Google Scholar 

  19. 19.

    Suzuki, T. and Kudo, Y., J. Comput.-Aided Mol. Design, 4 (1990) 155.

    CAS  Article  Google 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.

    CAS  Article  Google Scholar 

  22. 22.

    Ulmschneider, M., Ph.D. Thesis, University of Haute-Alsace, Mulhouse, France, 1993.

  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.

    CAS  Google Scholar 

  25. 25.

    Moriguchi, I., Hirono, S., Liu, Q., Nakagome, I. and Matsushita, Y., Chem. Pharm. Bull., 40 (1992) 127.

    CAS  Google Scholar 

  26. 26.

    Moriguchi, I., Hirono, S., Nakagome, I. and Hirano, H., Chem. Pharm. Bull., 42 (1994) 976.

    CAS  Google Scholar 

  27. 27.

    Viswanadhan, V.N., Reddy, M.R., Baccquet, R.J. and Erion, M.D., J. Comput. Chem., 14 (1993) 1019.

    CAS  Article  Google Scholar 

  28. 28.

    Bodor, N., Gabanyi, Z. and Wong, C.-K., J. Am. Chem. Soc., 111 (1989) 3783.

    CAS  Article  Google Scholar 

  29. 29.

    Bodor, N. and Huang, M.-J., J. Pharm. Sci., 81 (1992) 272.

    PubMed  CAS  Google Scholar 

  30. 30.

    Data from SciLogP Demo version, SciVision, Lexington, MA.

  31. 31.

    Martin, Y.C., Duban, M.E. and Bures, M.G., Calculating LogP: A Work-In-Progress, report on

  32. 32.

    Leo, A.J., Chem. Pharm. Bull., 43 (1995) 512.

    CAS  Google Scholar 

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Correspondence to Alanas A. Petrauskas.

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Petrauskas, A.A., Kolovanov, E.A. ACD/Log P method description. Perspectives in Drug Discovery and Design 19, 99–116 (2000).

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