Advertisement

Perspectives in Drug Discovery and Design

, Volume 19, Issue 1, pp 47–66 | Cite as

Calculating partition coefficient by atom-additive method

  • Renxiao Wang
  • Ying Gao
  • Luhua LaiEmail author
Article

Abstract

A new atom-additive method is presented for calculating octanol/water partition coefficient (log P) of organic compounds. The method, XLOGP v2.0, gives log P values by summing the contributions of component atoms and correction factors. Altogether 90 atom types are used to classify carbon, nitrogen, oxygen, sulfur, phosphorus and halogen atoms, and 10 correction factors are used for some special substructures. The contributions of each atom type and correction factor are derived by multivariate regression analysis of 1853 organic compounds with known experimental log P values. The correlation coefficient (r) for fitting the whole set is 0.973 and the standard deviation (s) is 0.349 log units. Comparison of various log P calculation procedures demonstrates that our method gives much better results than other atom-additive approaches and is at least comparable to fragmental approaches. Because of the simple methodology, the `missing fragment' problem does not occur in our method.

atom-additive atom type correction factor partition coefficient 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hansch, C. and Fujita, T., J. Am. Chem. Soc., 86 (1964) 1616.CrossRefGoogle Scholar
  2. 2.
    Hansch, C., Bjorkroth, J.P. and Leo, A., J. Pharm. Sci., 76 (1987) 663.PubMedGoogle Scholar
  3. 3.
    Hansch, C. and Muir, R.M., Nature, 194 (1964) 178.CrossRefGoogle Scholar
  4. 4.
    Leo, A., Chem. Rev., 93 (1993) 1281.CrossRefGoogle Scholar
  5. 5.
    Rekker, R.F., The Hydrophobic Fragment Constant, Elsevier, New York, NY, 1977.Google Scholar
  6. 6.
    Rekker, R.F. and Mannhold, R., Calculation of Drug Lipophilicity, VCH, Weinheim, 1992.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., Comprehensive Medicinal Chemistry, Vol. 4, Pergamon, Oxford, 1990.Google Scholar
  9. 9.
    Klopman, G., Li, J.-Y., Wang, S. and Dimayuga, M., J. Chem. Inf. Comput. Sci., 34 (1994) 752.CrossRefGoogle Scholar
  10. 10.
    Meylan, W.M. and Howard, P.H., J. Pharm. Sci., 84 (1995) 83.PubMedGoogle Scholar
  11. 11.
    Suzuki, T. and Kudo, Y., J. Comput.-Aided Mol. Design, 4 (1990) 155.CrossRefGoogle Scholar
  12. 12.
    Broto, P., Moreau, G. and Vandycke, C., Eur. J. Med. Chem., 19 (1984) 71.Google Scholar
  13. 13.
    Ghose, A.K., Pritchett, A. and Crippen, G.M., J. Comput. Chem., 9 (1988) 80.CrossRefGoogle Scholar
  14. 14.
    Convard, T., Dubost, J.-P. and Le Solleu, H., Quant. Struct.-Act. Relat., 13 (1994) 34.Google Scholar
  15. 15.
    Kellogg, G.E., Semus, S.F. and Abraham, D.J., J. Comput.-Aided Mol. Design, 5 (1991) 545.CrossRefGoogle Scholar
  16. 16.
    Abraham, D.J. and Kellogg, G.E., J. Comput.-Aided Mol. Design, 8 (1994) 41.CrossRefGoogle Scholar
  17. 17.
    Wang, R., Fu, Y. and Lai, L., J. Chem. Inf. Comput. Sci., 37 (1997) 615.CrossRefGoogle Scholar
  18. 18.
    Hansch, C., Leo, A. and Hoekman, D. Exploring QSAR: Hydrophobic, Electronic, and Steric Constants, Vol. 2, American Chemical Society, Washington, DC, 1995.Google Scholar
  19. 19.
    SYBYL v6.4, Tripos Associates, St. Louis, MO, 1998. http://www.tripos.com/Google Scholar
  20. 20.
    Mannhold, R. and Dross, K., Quant. Struct.—Act. Relat., 15 (1996) 403.Google Scholar
  21. 21.
    Furet, P., Sele, A. and Cohen, N.C., J. Mol. Graph., 6 (1998) 182.CrossRefGoogle Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  1. 1.Institute of Physical ChemistryPeking UniversityBeijingPeople's Republic of China
  2. 2.Institute of Physical ChemistryPeking UniversityBeijingPeople's Republic of China

Personalised recommendations