Journal of Computer-Aided Molecular Design

, Volume 27, Issue 5, pp 389–402 | Cite as

ClogPalk: a method for predicting alkane/water partition coefficient

  • Peter W. Kenny
  • Carlos A. Montanari
  • Igor M. Prokopczyk
Article

Abstract

Alkane/water partition coefficients (Palk) are less familiar to the molecular design community than their 1-octanol/water equivalents and access to both data and prediction tools is much more limited. A method for predicting alkane/water partition coefficient from molecular structure is introduced. The basis for the ClogPalk model is the strong (R2 = 0.987) relationship between alkane/water partition coefficient and molecular surface area (MSA) that was observed for saturated hydrocarbons. The model treats a molecule as a perturbation of a saturated hydrocarbon molecule with the same MSA and uses increments defined for functional groups to quantify the extent to which logPalk is perturbed by the introduction each functional group. Interactions between functional groups, such as intramolecular hydrogen bonds are also parameterized within a perturbation framework. The functional groups and interactions between them are specified substructurally in a transparent and reproducible manner using SMARTS notation. The ClogPalk model was parameterized using data measured for structurally prototypical compounds that dominate the literature on alkane/water partition coefficients and then validated using an external test set of 100 alkane/water logP measurements, the majority of which were for drugs.

Keywords

Alkane/water ClogPalk Ligand efficiency Lipophilicity logP logPalk Molecular surface area Partition coefficient SMARTS Solvation 

Notes

Acknowledgments

We are grateful to the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and the Conselho Nacional de Pesquisa (CNPq) for financial support. We also thank OpenEye Scientific Software for providing access to software and the anonymous reviewers of the manuscript for their constructive comments.

Supplementary material

10822_2013_9655_MOESM1_ESM.zip (120 kb)
Supplementary material (ZIP 120 kb)

References

  1. 1.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25CrossRefGoogle Scholar
  2. 2.
    Van de Waterbeemd H, Smith DA, Jones BC (2001) Lipophilicity in PK design: methyl, ethyl, futile. J Comput-Aided Mol Des 15:273–286CrossRefGoogle Scholar
  3. 3.
    Harless E, von Bibra E (1847) Die Ergebnisse der Versuche über die Wirkung des Schwefeläthers, ErlangenGoogle Scholar
  4. 4.
    Nernst W (1891) Verteilung eines Stoffes zwischen zwei Lösungsmitteln und zwischen Lösungsmittel und Dampfraum. Z Phys Chem 8:110–139Google Scholar
  5. 5.
    Meyer H (1899) Zur Theorie der Alkoholnarkose. Arch Exp Pathol Pharmacol 42:109–118CrossRefGoogle Scholar
  6. 6.
    Overton CE (1901) Studien über die Narkose zugleich ein Beitrag zur allgemeinen Pharmakologie. Gustav Fischer, JenaGoogle Scholar
  7. 7.
    Collander R (1951) Partition of organic compounds between higher alcohols and water. Acta Chem Scand 5:774–780CrossRefGoogle Scholar
  8. 8.
    Meyer KH (1937) The theory of narcosis. Trans Far Soc 33:1062–1068CrossRefGoogle Scholar
  9. 9.
    Hansch C, Muir RM, Fujita T, Maloney PP, Geiger F, Streich M (1963) The correlation of biological activity of plant growth regulators and chloromycetin derivatives with Hammett constants and partition coefficients. J Am Chem Soc 85:2817–2824CrossRefGoogle Scholar
  10. 10.
    Banks WA, Kastin A (1985) Peptides and the blood-brain barrier: lipophilicity as a predictor of permeability. Brain Res Bull 15:287–292CrossRefGoogle Scholar
  11. 11.
    Kellogg GE, Burnett JC, Abraham DJ (2001) Very empirical treatment of solvation and entropy: a force field derived from Log Po/w. J Comput-Aid Mol Des 15:381–393CrossRefGoogle Scholar
  12. 12.
    Schneider N, Lange G, Hindle S, Klein R, Rarey MA (2013) A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: methods behind the HYDE scoring function. J Comput-Aid Mol Des 27:15–29CrossRefGoogle Scholar
  13. 13.
    Delaney JS (2005) Predicting aqueous solubility from structure. Drug Discov Today 10:289–295CrossRefGoogle Scholar
  14. 14.
    Waring MJ, Johnstone C (2007) A quantitative assessment of hERG liability as a function of lipophilicity. Bioorg Med Chem Lett 17:1759–1764CrossRefGoogle Scholar
  15. 15.
    Rytting JH, Davis SS, Higuchi T (1972) Suggested thermodynamic standard state for comparing drug molecules in structure-activity studies. J Pharm Sci 61:816–818CrossRefGoogle Scholar
  16. 16.
    Finkelstein A (1976) Water and nonelectrolyte permeability of lipid bilayer membranes. J Gen Physiol 68:127–135CrossRefGoogle Scholar
  17. 17.
    Radzicka A, Wolfenden R (1988) Comparing the polarities of the amino acids: side-chain distribution coefficients between the vapor phase, cyclohexane, 1-octanol, and neutral aqueous solution. Biochem 27:1664–1670CrossRefGoogle Scholar
  18. 18.
    Lambert WJ, Wright LA (1989) Prediction of alkane-water partition coefficients using a C18 derivatized polystyrene-divinylbenzene stationary phase. J Chromat 464:400–404CrossRefGoogle Scholar
  19. 19.
    Xlang T-X, Anderson BD (1994) Substituent contributions to the transport of substituted p-toluic acids across lipid bilayer membranes. J Pharm Sci 83:1511–1518CrossRefGoogle Scholar
  20. 20.
    Mayer PT, Anderson BD (2002) Transport across 1, 9-decadiene precisely mimics the chemical selectivity of the barrier domain in egg lecithin bilayers. J Pharm Sci 91:640–646CrossRefGoogle Scholar
  21. 21.
    Toulmin A, Wood JM, Kenny PW (2008) Toward prediction of alkane/water partition coefficients. J Med Chem 51:3720–3730CrossRefGoogle Scholar
  22. 22.
    Abraham MH, Chadha HS, Whiting GS, Mitchell RC (1994) Hydrogen bonding. 32. An analysis of water-octanol and water-alkane partitioning and the ΔlogP parameter of Seiler. J Pharm Sci 83:1085–1100CrossRefGoogle Scholar
  23. 23.
    Dallas AJ, Carr PW (1992) A thermodynamic and solvatochromic investigation of the effect of water on the phase-transfer properties of octan-1-ol. J Chem Soc Perkin Trans 2:2155–2161Google Scholar
  24. 24.
    Abraham MH, Whiting GS, Fuchs R, Chambers EJ (1990) Thermodynamics of solute transfer from water to hexadecane. J Chem Soc Perk Trans 2:291–300Google Scholar
  25. 25.
    Wolfenden R, Radzicka A (1994) On the probability of finding a water molecule in a nonpolar cavity. Science 265:936–937CrossRefGoogle Scholar
  26. 26.
    Tsai R-S, Fan W, El Tayar N, Carrupt P-A, Testa B, Kier LB (1993) Solute-water interactions in the organic phase of a biphasic system. 1. Structural influence of organic solutes on the “water-dragging” effect. J Am Chem Soc 115:9632–9639CrossRefGoogle Scholar
  27. 27.
    Prokopenko NA, Bethea IA, Clemens CJ, Klimek A, Wargo K, Spivey C, Waziri K, Grushow A (2002) The effect of structure on hydrogen bonding: hydrogen bonded lactam dimers in CCl4. Phys Chem Chem Phys 4:490–495CrossRefGoogle Scholar
  28. 28.
    Golumbic C, Orchin M, Weller S (1949) Partition studies on phenols. I. Relation between partition coefficient and ionization constant. J Am Chem Soc 71:2624–2627CrossRefGoogle Scholar
  29. 29.
    Dearden JC, Bresnen GM (2005) Thermodynamics of water-octanol and water-cyclohexane partitioning of some aromatic compounds. Int J Mol Sci 6:119–129CrossRefGoogle Scholar
  30. 30.
    Seiler P (1974) Interconversion of lipophilicites from hydrocarbon/water systems into the octanol/water system. Eur J Med Chem 9:473–479Google Scholar
  31. 31.
    Leahy DE, Morris JJ, Taylor PJ, Wait AR (1992) Model solvent systems for QSAR. Part 2. Fragment values (f-values) for the critical quartet. J Chem Soc Perkin Trans 2:723–731Google Scholar
  32. 32.
    Zissimos AM, Abraham MH, Barker MC, Box KJ, Tam KY (2002) Calculation of Abraham descriptors from solvent-water partition coefficients in four different systems; evaluation of different methods of calculation. J Chem Soc Perkin Trans 2:470–477Google Scholar
  33. 33.
    Saunders RA, Platts JA (2004) Scaled polar surface area descriptors: development and application to three sets of partition coefficients. New J Chem 28:166–172CrossRefGoogle Scholar
  34. 34.
    Zerara M, Brickmann J, Kretschmer R, Exner TE (2008) Parameterization of an empirical model for the prediction of n-octanol, alkane and cyclohexane/water as well as brain/blood partition coefficients. J Comput-Aided Mol Des 23:105–111CrossRefGoogle Scholar
  35. 35.
    Lamarche O, Platts JA, Hersey A (2004) Theoretical prediction of partition coefficients via molecular electrostatic and electronic properties. J Chem Inf Comp Sci 44:848–855CrossRefGoogle Scholar
  36. 36.
    Caron G, Ermondi G (2005) Calculating virtual log P in the alkane/water system \({\text{log P}}_{\text{alk}}^{\text{N}}\) and its derived parameters \(\Updelta \log {\text{ P}}_{\text{oct - alk}}^{\text{N}}\) and \({\text{log D}}_{\text{alk}}^{\text{pH}}\)J Med Chem 48:3269–3279Google Scholar
  37. 37.
    Wittekindt C, Klamt A (2009) COSMO-RS as a predictive tool for lipophilicity. QSAR Comb Sci 28:874–877CrossRefGoogle Scholar
  38. 38.
    OpenEye Scientific Software, 9 Bisbee Court, Suite D, Santa Fe, NM 87508. http://www.eyesopen.com. Accessed 28 Feb 2013
  39. 39.
    Weininger D (1988) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comp Sci 28:31–36CrossRefGoogle Scholar
  40. 40.
    Weininger D, Weininger A, Weininger JL (1989) SMILES. 2. Algorithm for generation of unique SMILES notation. J Chem Inf Comp Sci 29:97–101CrossRefGoogle Scholar
  41. 41.
    OMEGA. OpenEye Scientific Software. http://www.eyesopen.com/omega. Accessed 28 Feb 2013
  42. 42.
    Hawkins PCD, Skillman AG, Warren GL, Ellingson BA, Stahl MT Conformer generation with OMEGA: algorithm and validation using high quality structures from the protein databank and Cambridge structural database. J Chem Inf Model 50:572–584Google Scholar
  43. 43.
    Halgren TA (1999) MMFF VI. MMFF94S option for energy minimization studies. J Comp Chem 20:720–729CrossRefGoogle Scholar
  44. 44.
    SZYBKI. OpenEye Scientific Software. http://www.eyesopen.com/szybki. Accessed 28 Feb 2013
  45. 45.
    Ewing VC, Sutton LE (1963) Investigation by electron diffraction of the molecular structures of sulphur hexafluoride, sulphur tetrafluoride, selenium hexafluoride and selenium tetrafluoride. Trans Faraday Soc 59:1241–1247CrossRefGoogle Scholar
  46. 46.
    Bondi A (1964) van der Waals volumes and radii. J Phys Chem 68:441–451CrossRefGoogle Scholar
  47. 47.
    GraphSim Toolkit. OpenEye Scientific Software. http://www.eyesopen.com/docs/toolkits/current/html/GraphSim_TK-c++/index.html. Accessed 16 May 2013
  48. 48.
    JMP version 10.0, SAS Institute, Cary, NC 27513. http://www.jmp.com. Accessed 28 Feb 2013
  49. 49.
    OEChem Toolkit. OpenEye Scientific Software. http://www.eyesopen.com/docs/toolkits/current/html/OEChem_TK-c++/index.html. Accessed 28 Feb 2013
  50. 50.
    Blomberg N, Cosgrove DA, Kenny PW, Kolmodin K (2009) Design of compound libraries for fragment screening. J Comput-Aid Mol Des 23:513–525CrossRefGoogle Scholar
  51. 51.
    SMARTS Theory Manual. Daylight chemical information systems. http://www. daylight.com/dayhtml/doc/theory/theory.smarts.html. Accessed 18 Feb 2013
  52. 52.
    Spicoli Toolkit. OpenEye Scientific Software. http://www.eyesopen.com/docs/toolkits/current/html/Spicoli_TK-c++/index.html. Accessed 28 Feb 28 2013
  53. 53.
    Currie DJ, Lough CE, Silver RF, Holmes HL (1966) Partition coefficients of some conjugated heteroenoid compounds and 1, 4-naphthoquinones. Can J Chem 44:1035–1043CrossRefGoogle Scholar
  54. 54.
    Delaney AD, Currie DJ, Holmes HL (1969) Partition coefficients of some N-alkyl and N,N-dialkyl derivatives of some cinnamamides and benzalcyanoacetamides in the system cyclohexane-water. Can J Chem 47:3273–3277CrossRefGoogle Scholar
  55. 55.
    Vezin WR, Florence A (1979) The determination of dissociation constants and partition coefficients of phenothiazine derivatives. Int J Pharm 3:231–237CrossRefGoogle Scholar
  56. 56.
    Okada S, Nakahara H, Yomota C, Mochida K (1985) The role of solvent in the partition of procaine and p-aminobenzoic acid between organic solvent and water. Chem Pharm Bull 33:4916–4922CrossRefGoogle Scholar
  57. 57.
    Young RC, Mitchell RC, Brown TH, Ganellin CR, Griffiths R, Jones M, Rana KK, Saunders D, Smith IR, Sore NE, Wilks TJ (1988) Development of a new physicochemical model for brain penetration and its application to design of centrally acting H2 receptor histamine antagonists. J Med Chem 31:656–671CrossRefGoogle Scholar
  58. 58.
    Rich PR, Harper R (1990) Partition coefficients of quinones and hydroquinones and their relation to biochemical activity. FEBS 269:139–144CrossRefGoogle Scholar
  59. 59.
    Gibbs PR, Radzicka A, Wolfenden R (1991) J Am Chem Soc 113:4714–4715CrossRefGoogle Scholar
  60. 60.
    El Tayar N, Tsai R-S, Testa B, Carrupt P-A, Hansch C, Leo A (1991) Percutaneous penetration of drugs: a quantitative structure-permeability relationship study. J Pharm Sci 80:744–749CrossRefGoogle Scholar
  61. 61.
    Guardado P, Balon M, Carmona C, Muñoz MA, Domene C (1997) Partition coefficients of indoles and betacarbolines. J Pharm Sci 86:106–109CrossRefGoogle Scholar
  62. 62.
    Shih P, Pedersen LG, Gibbs PR, Wolfenden R (1998) Hydrophobicities of the nucleic acid bases: distribution coefficients from water to cyclohexane. J Mol Biol 280:421–430CrossRefGoogle Scholar
  63. 63.
    Habgood MD, Liu ZD, Dehkordi LS, Khodr HH, Abbott J, Hider RC (1999) Investigation into the correlation between structure of hydroxypyridones and blood-brain barrier permeability. Biochem Pharmacol 57:1305–1310CrossRefGoogle Scholar
  64. 64.
    Acree WE, Abraham MH (2001) Solubility predictions for crystalline nonelectrolyte solutes dissolved in organic solvents based on the Abraham general solvation model. Can J Chem 79:1466–1476Google Scholar
  65. 65.
    Acree WE, Abraham MH (2002) Solubility predictions for crystalline polycyclic aromatic hydrocarbons (PAHs) dissolved in organic solvents based upon the Abraham general solvation model. Fluid Phase Equil 201:245–258CrossRefGoogle Scholar
  66. 66.
    Cabani S, Gianni P, Mollica V, Lepori L (1981) Group contributions to the thermodynamic properties of nonionic organic solutes in dilute aqueous solution. J Solut Chem 10:563–595CrossRefGoogle Scholar
  67. 67.
    Albert JS, Blomberg N, Breeze AL, Brown AJH, Burrows JN, Edwards PD, HA FolmerR, Geschwindner S, Griffen EJ, Kenny PW, Nowak T, Olsson L, Sanganee H, Shapiro AB (2007) An integrated approach to fragment-based lead generation: philosophy, strategy and case studies from AstraZeneca’s drug discovery programmes. Curr Top Med Chem 7:1600–1629CrossRefGoogle Scholar
  68. 68.
    Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9:430–431CrossRefGoogle Scholar
  69. 69.
    Gilson MK, Given JA, Bush BL, McCammon JA (1997) The statistical-thermodynamic basis for computation of binding affinities: a critical review. Biophys J 72:1047–1069CrossRefGoogle Scholar
  70. 70.
    Reynolds CH, Tounge BA, Bembenek SD (2008) Ligand binding efficiency: trends, physical basis, and implications. J Med Chem 51:2432–2438CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Peter W. Kenny
    • 1
  • Carlos A. Montanari
    • 1
  • Igor M. Prokopczyk
    • 1
  1. 1.Grupo de Estudos em Química Medicinal, NEQUIMED, Instituto de Química de São CarlosUniversidade de São PauloSão CarlosBrazil

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