Skip to main content
Log in

Predicting octanol/water partition coefficients and pKa for the SAMPL7 challenge using the SM12, SM8 and SMD solvation models

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Blind predictions of octanol/water partition coefficients and pKa at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. Octanol/water partition coefficients were predicted from solvation free energies computed using electronic structure calculations with the SM12, SM8 and SMD solvation models. Within these calculations we compared the use of gas- and solution-phase optimized geometries of the solute. Based on these calculations we found that in general the use of solution phase-optimized geometries increases the affinity of the solutes for water as compared to octanol, with the use of gas-phase optimized geometries resulting in the better agreement with experiment. The pKa is computed using the direct approach, scaled solvent-accessible surface model, and the inclusion of an explicit water molecule, where the latter two methods have previously been shown to offer improved predictions as compared to the direct approach. We find that the use of an explicit water molecule provides superior predictions, and that the predicted macroscopic pKa is sensitive to the employed microstates.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Notes

  1. All of our quantitative \(\log_{10} P_1^{{{\rm o}}/{{\rm w}}}\) comparisons to other submissions are based on the most recent data posted on the SAMPL7 website [10]. In the overview article, Ref. [4], our entry “TFE-SM8-vacuum-opt” was the top performing physical QM-based method based on RMSE with “COSMO-RS” ranked second. However, the “COSMO-RS” submission was updated on 10 December 2020 with the note “correct the standard state for one submission and update analysis.” We are comparing to this updated data set

References

  1. Sangster J (1989) Octanol–water partition coefficients of simple organic compounds. J Phys Chem Ref Data 18:1111–1227

    Article  CAS  Google Scholar 

  2. Ulrich N, Goss KU, Ebert A (2021) Exploring the octanol–water partition coefficient dataset using deep learning techniques and data augmentation. Commun Chem 90:4

    Google Scholar 

  3. Işık M, Bergazin TD, Fox T, Rizzi A, Chodera JD, Mobley DL (2020) Assessing the accuracy of octanol–water partition coefficient predictions in the SAMPL6 Part II log P challenge. J Comput Aided Mol Des 34:335–370

  4. Bergazin TD, Tielker N, Zhang Y, Mao J, Gunner MR, Francisco K, Ballatore C, Kast SM, Mobley DL (2021) Evaluation of log P, pKa, and log D predictions for the SAMPL7 blind challenge. J. Comput.-Aided Mol. Des. 35, 771–802

  5. Bannan CC, Burley KH, Chiu M, Shirts MR, Gilson MK, Mobley DL (2016) Blind predictions of cyclohexane–water distribution coefficients from the SAMPL5 challenge. J Comput Aided Mol Des 30:927–944

  6. Işık M, Rustenburg AS, Rizzi A, Gunner MR, Mobley DL, Chodera JD (2021) Overview of the SAMPL6 p \({K}_{{\rm a}}\) challenge: evaluating small molecule microscopic and macroscopic p\({K}_{{\rm a}}\) predictions. J Comput Aided Mol Des 35:131–166

  7. Marenich AV, Cramer CJ, Truhlar DG (2013) Generalized Born Solvation Model SM12. J Chem Theory Comput 9:609–620

    Article  CAS  Google Scholar 

  8. Marenich AV, Olson RM, Kelly CP, Cramer CJ, Truhlar DG (2007) Self-consistent reaction field model for aqueous and nonaqueous solutions based on accurate polarized partial charges. J Chem Theory Comput 3:2011–2033

    Article  CAS  Google Scholar 

  9. Marenich AV, Cramer CJ, Truhlar DG (2009) Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J Phys Chem B 113:6378–6396

    Article  CAS  Google Scholar 

  10. SAMPL7 logP Prediction Challenge. https://github.com/samplchallenges/SAMPL7/tree/master/physical_property. Accessed 11 Mar 2021

  11. OECD (1995) Test No. 107: partition coefficient (n-octanol/water): Shake Flask Method. https://doi.org/10.1787/9789264069626-en. https://www.oecd-ilibrary.org/content/publication/9789264069626-en

  12. Ouimet JA, Paluch AS (2020) Predicting octanol/water partition coefficients for the SAMPL6 challenge using the SM12, SM8, and SMD solvation models. J Comput Aided Mol Des 34:575–588

  13. Sørensen JM, Arlt W (eds) (1979) Liquid–liquid equilibrium data collection, part 1: binary systems. DECHEMA, Frankfurt am Main

    Google Scholar 

  14. Marenich AV, Cramer CJ, Truhlar DG (2009) Performance of SM6, SM8, and SMD on the SAMPL1 test set for the prediction of small-molecule solvation free energies. J Phys Chem B 113:4538–4543

    Article  CAS  Google Scholar 

  15. Ribeiro RF, Marenich AV, Cramer CJ, Truhlar DG (2010) Prediction of SAMPL2 aqueous solvation free energies and tautomeric ratios using the SM8, SM8AD, and SMD solvation models. J Comput Aid Mol Des 24:317–333

  16. Jindal A, Vasudevan S (2017) Conformation of ethylene glycol in the liquid state: intra- versus intermolecular Interactions. J Phys Chem B 121:5595–5600

    Article  CAS  Google Scholar 

  17. Cramer CJ, Truhlar DG (1994) Quantum chemical conformational analysis of 1,2-ethanediol: correlation and solvation effects on the tendency to form internal hydrogen bonds in the gase phase and in aqueous solution. J Am Chem Soc 116:3892–3900

    Article  CAS  Google Scholar 

  18. Klimovich PV, Mobley DL (2010) Predicting hydration free energies using all-atom molecular dynamics simulations and multiple starting conformations. J Comput Aid Mol Des 24:307–316

  19. Nicholls A, Mobley DL, Guthrie JP, Chodera JD, Bayly CI, Cooper MD, Pande VS (2008) Predicting Small-molecule solvation free energies: an informal blind test for computational chemistry. J Med Chem 51:769–779

    Article  CAS  Google Scholar 

  20. Chamberlin AC, Cramer CJ, Truhlar DG (2008) Performance of SM8 on a test to predict small-molecule solvation free energies. J. Phys Chem B 112:8651–8655

    Article  CAS  Google Scholar 

  21. Jones MR, Brooks BR (2020) Quantum chemical predictions of water-octanol partition coefficients applied to the SAMPL6 logP blind challenge. J Comput Aid Mol Des 34:485–493

  22. Guan D, Lui R, Matthews S (2020) LogP prediction performance with the SMD solvation model and the M06 density functional family for SAMPL6 blind prediction challenge molecules. J Comput Aid Mol Des 34:511–522

  23. Gunner MR, Murakami T, Rustenburg AS, Işık M, Chodera JD (2020) Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states. J Comput Aid Mol Des 34:561–573

  24. Ho J (2015) Are thermodynamic cycles necessary for continuum solvent calculation of pK\(_{{\rm a}}\)s and reduction potentials? Phys Chem Chem Phys 17:2895–2868

    Article  Google Scholar 

  25. Thapa B, Schlegel HB (2017) Improved pK\(_{{\rm a}}\) Prediction of substituted alcohols, phenols, and hydroperoxides in aqueous medium using density functional theory and a cluster-continuum solvation model. J Phys Chem A 121:4698–4706

    Article  CAS  Google Scholar 

  26. Mirzaei S, Ivanov MV, Timerghazin QK (2019) Improving performance of the SMD solvation model: bondi radii improve predicted aqueous solvation free energies of ions and pK\(_{{\rm a}}\) values of thiols. J Phys Chem A 123:9498–9504

    Article  CAS  Google Scholar 

  27. Lian P, Johnston RC, Parks JM, Smith JC (2018) Quantum chemical calculation of pK\(_{{\rm a}}\)s of environmentally relevant functional groups: carboxylic acids, amines, and thiols in aqueous solution. J Phys Chem A 122:4366–4374

    Article  CAS  Google Scholar 

  28. Rodriguez SA, Baumgartner MT (2020) Betanidin pK\(_{{\rm a}}\) prediction using DFT methods. ACS Omega 5:13751–13759

    Article  CAS  Google Scholar 

  29. Cramer CJ (2002) Essentials of computational chemistry. Wiley, Chichester

    Google Scholar 

  30. Pliego JR Jr, Riveros JM (2002) Theoretical calculation of pK\(_{{\rm a}}\) using the cluster-continuum model. J Phys Chem A 106:7434–7439

    Article  CAS  Google Scholar 

  31. Kelly CP, Cramer CJ, Truhlar DG (2006) Adding explicit solvent molecules to continuum solvent calculations for the calculation of aqueous acid dissociation constants. J Phys Chem A 110:2493–9499

    Article  CAS  Google Scholar 

  32. Alongi KS, Shields GC (2010) Theoretical calculations of acid dissociation constants: a review article. Annu Rep Comput Chem 6:113–138

    Article  CAS  Google Scholar 

  33. Thapa B, Schlegel HB (2015) Calculations of pKa’s and redox potentials of nucleobases with explicit waters and polarizable continuum solvation. J Phys Chem A 119:5134–5144

    Article  CAS  Google Scholar 

  34. Thapa B, Schlegel HB (2016) Theoretical calculation of pK\(_{{\rm a}}\)’s of selenols in aqueous solution using an implicit solvation model and explicit water molecules. J Phys Chem A 120:8916–8922

    Article  CAS  Google Scholar 

  35. Thapa B, Schlegel HB (2016) Density functional theory calculation of pK\(_{{\rm a}}\)’s of thiols in aqueous solution using explicit water molecules and the polarizable continuum model. J Phys Chem A 120:5726–5735

    Article  CAS  Google Scholar 

  36. Weininger D (1988) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 28:31–36

  37. Daylight Chemical Information Systems, Inc. https://www.daylight.com/. Accessed 11 Mar 2021

  38. O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchinson GR (2011) Open Babel: an open chemical toolbox. J Cheminf 3:33

    Article  Google Scholar 

  39. Open Babel: The Open Source Chemistry Toolbox. http://openbabel.org/wiki/Main_Page. Accessed 11 Mar 2021

  40. Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174

    Article  CAS  Google Scholar 

  41. Gasteiger J, Marsili M (1978) A new model for calculating atomic charges in molecules. Tetrahedron Lett 34:3181–3184

    Article  Google Scholar 

  42. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Petersson GA, Nakatsuji H, Li X, Caricato M, Marenich AV, Bloino J, Janesko BG, Gomperts R, Mennucci B, Hratchian HP, Ortiz JV, Izmaylov AF, Sonnenberg JL, Williams-Young D, Ding F, Lipparini F, Egidi F, Goings J, Peng B, Petrone A, Henderson T, Ranasinghe D, Zakrzewski VG, Gao J, Rega N, Zheng G, Liang W, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Throssell K, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark MJ, Heyd JJ, Brothers EN, Kudin KN, Staroverov VN, Keith TA, Kobayashi R, Normand J, Raghavachari K, Rendell AP, Burant JC, Iyengar SS, Tomasi J, Cossi M, Millam JM, Klene M, Adamo C, Cammi R, Ochterski JW, Martin RL, Morokuma K, Farkas O, Foresman JB, Fox DJ (2019) Gaussian 16. Revision C.01. Gaussian, Inc., Wallingford

  43. Zhao Y, Truhlar DG (2008) The M06 theory of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four M06-class functionals and 12 other functionals. Theor Chem Acc 120:215–241

    Article  CAS  Google Scholar 

  44. Shao Y, Gan Z, Epifanovsky E, Gilbert ATB, Wormit M, Kussmann J, Lange AW, Behn A, Deng J, Feng X, Ghosh D, Goldey M, Horn PR, Jacobson LD, Kaliman I, Khaliullin RZ, Kús T, Landau A, Liu J, Proynov EI, Rhee YM, Richard RM, Rohrdanz MA, Steele RP, Sundstrom EJ, Woodcock HL III, Zimmerman PM, Zuev D, Albrecht B, Alguire E, Austin B, Beran GJO, Bernard YA, Berquist E, Brandhorst K, Bravaya KB, Brown ST, Casanova D, Chang CM, Chen Y, Chien SH, Closser KD, Crittenden DL, Diedenhofen M, DiStasio RA Jr, Dop H, Dutoi AD, Edgar RG, Fatehi S, Fusti-Molnar L, Ghysels A, Golubeva-Zadorozhnaya A, Gomes J, Hanson-Heine MWD, Harbach PHP, Hauser AW, Hohenstein EG, Holden ZC, Jagau TC, Ji H, Kaduk B, Khistyaev K, Kim J, Kim J, King RA, Klunzinger P, Kosenkov D, Kowalczyk T, Krauter CM, Lao KU, Laurent A, Lawler KV, Levchenko SV, Lin CY, Liu F, Livshits E, Lochan RC, Luenser A, Manohar P, Manzer SF, Mao SP, Mardirossian N, Marenich AV, Maurer SA, Mayhall NJ, Oana CM, Olivares-Amaya R, O’Neill DP, Parkhill JA, Perrine TM, Peverati R, Pieniazek PA, Prociuk A, Rehn DR, Rosta E, Russ NJ, Sergueev N, Sharada SM, Sharmaa S, Small DW, Sodt A, Stein T, Stück D, Su YC, Thom AJW, Tsuchimochi T, Vogt L, Vydrov O, Wang T, Watson MA, Wenzel J, White A, Williams CF, Vanovschi V, Yeganeh S, Yost SR, You ZQ, Zhang IY, Zhang X, Zhou Y, Brooks BR, Chan GKL, Chipman DM, Cramer CJ, Goddard WA III, Gordon MS, Hehre WJ, Klamt A, Schaefer HF III, Schmidt MW, Sherrill CD, Truhlar DG, Warshel A, Xua X, Aspuru-Guzik A, Baer R, Bell AT, Besley NA, Chai JD, Dreuw A, Dunietz BD, Furlani TR, Gwaltney SR, Hsu CP, Jung Y, Kong J, Lambrecht DS, Liang W, Ochsenfeld C, Rassolov VA, Slipchenko LV, Subotnik JE, Van Voorhis T, Herbert JM, Krylov AI, Gill PMW, Head-Gordon M (2015) Advances in molecular quantum chemistry contained in the Q-Chem 4 program package. Mol Phys 113:184–215

    Article  CAS  Google Scholar 

  45. Q-CHEM. http://www.q-chem.com/. Accessed 11 Mar 2021

  46. SAMPL7 Physical Property pKa Microstates. https://github.com/samplchallenges/SAMPL7/commits/master/physical_property/pKa/microstates. (accessed March 11, 2021)

  47. Fındık BK, Haslak ZP, Arslan E, Aviyente V (2021) SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules. J Comput Aid Mol Des 35:841–851

  48. Warnau J, Wichmann K, Reinisch J (2021) COSMO-RS predictions of logP in the SAMPL7 blind challenge. J Comput Aided Mol Des 35:813–818

  49. Klamt A, Eckert F, Arlt W (2010) COSMO-RS: an alternative to simulation for calculating thermodynamic properties of liquid mixtures. Annu Rev Chem Biomol Eng 1:101–122

    Article  CAS  Google Scholar 

  50. Ohio Supercomputer Center: Ohio Supercomputer Center (1987). http://osc.edu/ark:/19495/f5s1ph73

Download references

Acknowledgements

Computing support was provided by the Ohio Supercomputer Center [50]. We appreciate the National Institutes of Health for its support of the SAMPL project via R01GM124270 to David L. Mobley (UC Irvine).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew S. Paluch.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human and animal rights

This article does not contain any studies with human or animal subjects.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (ZIP 38 kb)

Appendix 1: Relating the distribution coefficient to relative free energies

Appendix 1: Relating the distribution coefficient to relative free energies

Let’s assume we have our neutral reference molecule plus five additional states:

  1. 0.

    H\(_2\)A, our neutral reference molecule

  2. 1.

    HA, deprotonated species with a formal charge of −1, corresponding to a loss of one hydrogen as compared to our neutral reference molecule

  3. 2.

    H3A+, protonated species with a formal charge of +1, corresponding to the gain of one hydrogen as compared to our neutral reference molecule

  4. 3.

    AH2, tautomer of our neutral reference molecule with a formal charge of 0

  5. 4.

    A2, deprotonated species with a formal charge of −2, corresponding to a loss of two hydrogens as compared to our neutral reference molecule

  6. 5.

    H4A+2, protonated species with a formal charge of +2, corresponding to the gain of two hydrogens as compared to our neutral reference molecule

This leads to:

$$\begin{aligned}&\log_{10} D_1^{\rm o/w}\left( T,P\right) \\&\quad = \log_{10}\left( \frac{c_{1-0,\mathrm {o}}}{c_{1-0,\mathrm {w}}+c_{1-1,\mathrm {w}}+c_{1-2,\mathrm {w}}+c_{1-3,\mathrm {w}} +c_{1-4,\mathrm {w}}+c_{1-5,\mathrm {w}}}\right) \end{aligned}$$
(15)

We can readily compute \(\log_{10} P_1^{\rm o/w}\) from the transfer free energy of the neutral solute between the two phases. Let us therefore take the difference between \(\log_{10} D_1^{\rm o/w}\) and \(\log_{10} P_1^{\rm o/w}\) to obtain an expression that may be used to “correct” our predicted value of \(\log_{10} P_1^{\rm o/w}.\) Taking the difference and simplifying we have:

$$\begin{aligned} \begin{aligned}&\log_{10} D_1^{\rm o/w}\left( T,P\right) - \log_{10} P_1^{\rm o/w}\left( T,P\right) \\&\quad = \log_{10} \left( \frac{c_{1-0,\mathrm {o}}}{c_{1-0,\mathrm {w}}+c_{1-1,\mathrm {w}}+c_{1-2,\mathrm {w}}+c_{1-3,\mathrm {w}} +c_{1-4,\mathrm {w}}+c_{1-5,\mathrm {w}}}\right) - \log_{10} \left( \frac{c_{1-0,\mathrm {o}}}{c_{1-0,\mathrm {w}}}\right) \\&\quad = \log_{10} \left( \frac{c_{1-0,\mathrm {o}}}{c_{1-0,\mathrm {w}}+c_{1-1,\mathrm {w}}+c_{1-2,\mathrm {w}}+c_{1-3,\mathrm {w}} +c_{1-4,\mathrm {w}}+c_{1-5,\mathrm {w}}} \cdot \frac{c_{1-0,\mathrm {w}}}{c_{1-0,\mathrm {o}}}\right) \\&\quad = \log_{10} \left( \frac{c_{1-0,\mathrm {w}}}{c_{1-0,\mathrm {w}}+c_{1-1,\mathrm {w}}+c_{1-2,\mathrm {w}}+c_{1-3,\mathrm {w}} +c_{1-4,\mathrm {w}}+c_{1-5,\mathrm {w}}}\right) \\&\quad = \log_{10} \left( \frac{1}{1+\frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} +\frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}}}\right) \\&\quad =-\log_{10} \left( 1+\frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} +\frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}}\right) \end{aligned} \end{aligned}$$
(16)

Next, we will work out expressions for the relative concentrations in terms of the free energies of reaction computed in the present study. Starting with state 1, we have:

$$\begin{aligned} \mathrm {H}_2\text{A} \rightleftharpoons \mathrm {H}^+ + \mathrm {HA}^- \end{aligned}$$
(17)
$$\begin{aligned} K\mathrm {a}_1 = \frac{\left[ \mathrm {H}^+\right] \left[ \mathrm {HA}^-\right] }{\left[ \mathrm {H}_2\text{A}\right] } = \frac{c_{\mathrm {H}^+,\mathrm {w}}c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned}$$
(18)

where:

$$\begin{aligned} \begin{aligned} \mathrm {pH}&= -\log_{10} c_{\mathrm {H}^+,\mathrm {w}} \\ \ln c_{\mathrm {H}^+,\mathrm {w}}&= -\mathrm {pH} / \log_{10} e \end{aligned} \end{aligned}$$
(19)

and then:

$$\begin{aligned} & -\frac{\varDelta G_{1-0}^{\rm rxn}\left( T,P\right) }{RT}= \ln K\mathrm {a}_1 = \ln c_{\mathrm {H}^+,\mathrm {w}} + \ln \frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ &-\frac{\varDelta G_{1-0}^{\rm rxn}\left( T,P\right) }{RT}= -\frac{\mathrm {pH}}{\log_{10} e} + \ln \frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ &-\frac{\varDelta G_{1-0}^{\rm rxn}\left( T,P\right) }{RT}+ \frac{\mathrm {pH}}{\log_{10} e} = \ln \frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned}$$
(20)

where \(\varDelta G_{1-0}^{\rm rxn}\) is the corresponding free energy of reaction computed in the present study. This leads to the desired result:

$$\begin{aligned} \frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = \exp \left[ -\frac{\varDelta G_{1-0}^{\rm rxn}\left( T,P\right) }{RT} + \frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned}$$
(21)

Next, we move on to state 2:

$$\begin{aligned}&\mathrm {H}_2\text{A} + \mathrm {H}^+ \rightleftharpoons \mathrm {H}_3\text{A}^+ \end{aligned}$$
(22)
$$\begin{aligned}&\quad K\mathrm {a}_2 = \frac{\left[ \mathrm {H}_3\text{A}^+\right] }{\left[ \mathrm {H}_2\text{A}\right] \left[ \mathrm {H}^+\right] } = \frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}c_{\mathrm {H}^+,\mathrm {w}}} \end{aligned}$$
(23)

and then:

$$\begin{aligned} \begin{aligned} -\frac{\varDelta G_{2-0}^{\rm rxn}\left( T,P\right) }{RT}&= \ln K\mathrm {a}_2 = -\ln c_{\mathrm {H}^+,\mathrm {w}} + \ln \frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{2-0}^{\rm rxn}\left( T,P\right) }{RT}&= \frac{\mathrm {pH}}{\log_{10} e} + \ln \frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{2-0}^{\rm rxn}\left( T,P\right) }{RT}&- \frac{\mathrm {pH}}{\log_{10} e} = \ln \frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned} \end{aligned}$$
(24)

where \(\varDelta G_{2-0}^{\rm rxn}\) is the corresponding free energy of reaction computed in the present study. This leads to the desired result:

$$\begin{aligned} \frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = \exp \left[ -\frac{\varDelta G_{2-0}^{\rm rxn}\left( T,P\right) }{RT} - \frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned}$$
(25)

Next, we move on to state 3, a tautomer of the neutral reference molecule:

$$\begin{aligned} \mathrm {H}_2\text{A} \rightleftharpoons \mathrm {AH}_2 \end{aligned}$$
(26)
$$\begin{aligned} K\mathrm {a}_3 = \frac{\left[ \mathrm {AH}_2\right] }{\left[ \mathrm {H}_2\text{A}\right] } = \frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned}$$
(27)

and then:

$$\begin{aligned} -\frac{\varDelta G_{3-0}^{\rm rxn}\left( T,P\right) }{RT} = \ln K\mathrm {a}_3 = \ln \frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned}$$
(28)

where \(\varDelta G_{3-0}^{\rm rxn}\) is the corresponding free energy of reaction computed in the present study. This leads to the desired result:

$$\begin{aligned} \frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = \exp \left[ -\frac{\varDelta G_{3-0}^{\rm rxn}\left( T,P\right) }{RT}\right] \end{aligned}$$
(29)

Next, we move on to state 4:

$$\begin{aligned} \mathrm {H}_2\text{A} \rightleftharpoons 2\mathrm {H}^+ + \text{A}^{-2} \end{aligned}$$
(30)
$$\begin{aligned} K\mathrm {a}_4 = \frac{\left[ \mathrm {H}^+\right] ^{2}\left[ \text{A}^{-2}\right] }{\left[ \mathrm {H}_2\text{A}\right] } = \frac{c_{\mathrm {H}^+,\mathrm {w}}^{2}c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned}$$
(31)

and then:

$$\begin{aligned} \begin{aligned} -\frac{\varDelta G_{4-0}^{\rm rxn}\left( T,P\right) }{RT}&= \ln K\mathrm {a}_4 = 2 \ln c_{\mathrm {H}^+,\mathrm {w}} + \ln \frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{4-0}^{\rm rxn}\left( T,P\right) }{RT}&= -2\frac{\mathrm {pH}}{\log_{10} e} + \ln \frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{4-0}^{\rm rxn}\left( T,P\right) }{RT}&+ 2 \frac{\mathrm {pH}}{\log_{10} e} = \ln \frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned} \end{aligned}$$
(32)

where \(\varDelta G_{4-0}^{\rm rxn}\) is the corresponding free energy of reaction computed in the present study. This leads to the desired result:

$$\begin{aligned} \frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = \exp \left[ -\frac{\varDelta G_{4-0}^{\rm rxn}\left( T,P\right) }{RT} + 2\frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned}$$
(33)

And last, we move on to state 5:

$$\begin{aligned} \mathrm {H}_2\text{A} + 2\mathrm {H}^+ \rightleftharpoons \mathrm {H}_4\text{A}^{+2} \end{aligned}$$
(34)
$$\begin{aligned} K\mathrm {a}_5 = \frac{\left[ \mathrm {H}_4\text{A}^{+2}\right] }{\left[ \mathrm {H}_2\text{A}\right] \left[ \mathrm {H}^+\right] ^{2}} = \frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}c^{2}_{\mathrm {H}^+,\mathrm {w}}} \end{aligned}$$
(35)

and then:

$$\begin{aligned} \begin{aligned} -\frac{\varDelta G_{5-0}^{\rm rxn}\left( T,P\right) }{RT}&= \ln K\mathrm {a}_5 = -2 \ln c_{\mathrm {H}^+,\mathrm {w}} + \ln \frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{5-0}^{\rm rxn}\left( T,P\right) }{RT}&= 2\frac{\mathrm {pH}}{\log_{10} e} + \ln \frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ -\frac{\varDelta G_{5-0}^{\rm rxn}\left( T,P\right) }{RT}&- 2\frac{\mathrm {pH}}{\log_{10} e} = \ln \frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \end{aligned} \end{aligned}$$
(36)

where \(\varDelta G_{5-0}^{\rm rxn}\) is the corresponding free energy of reaction computed in the present study. This leads to the desired result:

$$\begin{aligned} \frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = \exp \left[ -\frac{\varDelta G_{5-0}^{\rm rxn}\left( T,P\right) }{RT} - 2\frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned}$$
(37)

Relating back to original expression (16) we have:

$$\begin{aligned} \begin{aligned}1+&\frac{c_{1-1,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-2,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-3,\mathrm {w}}}{c_{1-0,\mathrm {w}}} +\frac{c_{1-4,\mathrm {w}}}{c_{1-0,\mathrm {w}}}+\frac{c_{1-5,\mathrm {w}}}{c_{1-0,\mathrm {w}}} \\ =&1+ \exp \left[ -\frac{\varDelta G_{1-0}^{\rm rxn}}{RT} + \frac{\mathrm {pH}}{\log_{10} e}\right] + \exp \left[ -\frac{\varDelta G_{2-0}^{\rm rxn}}{RT} - \frac{\mathrm {pH}}{\log_{10} e}\right] \\&+ \exp \left[ -\frac{\varDelta G_{3-0}^{\rm rxn}}{RT}\right]+\exp \left[ -\frac{\varDelta G_{4-0}^{\rm rxn}}{RT} + 2\frac{\mathrm {pH}}{\log_{10} e}\right]\\ &+ \exp \left[ -\frac{\varDelta G_{5-0}^{\rm rxn}}{RT} - 2\frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned} \end{aligned}$$
(38)

We find that the expression may be equivalently expressed as:

$$\begin{aligned} 1+\sum_{i=1}^{5} \frac{c_{1-i,\mathrm {w}}}{c_{1-0,\mathrm {w}}} = 1 + \sum_{i=1}^{5} \exp \left[ -\frac{\varDelta G_{i-0}^{\rm rxn}}{RT} -q_{i} \frac{\mathrm {pH}}{\log_{10} e}\right] \end{aligned}$$
(39)

where \(q_i\) is the molecular formal charge of state i.

Using this result, we can write a general expression for N states:

$$\begin{aligned} \begin{aligned}&\log_{10} D_1^{\rm o/w}\left( T,P\right) - \log_{10} P_1^{\rm o/w}\left( T,P\right) \\&\quad = -\log_{10} \left( 1+\sum_{i=1}^{N} \frac{c_{1-i,\mathrm {w}}}{c_{1-0,\mathrm {w}}}\right) \\&\quad = -\log_{10} \left( 1 + \sum_{i=1}^{N} \exp \left[ -\frac{\varDelta G_{i-0}^{\rm rxn}}{RT} -q_{i} \frac{\mathrm {pH}}{\log_{10} e}\right] \right) \end{aligned} \end{aligned}$$
(40)

and then:

$$\begin{aligned}&\log_{10} D_1^{\rm o/w}\left( T,P\right) = -\frac{\log_{10} e}{RT}\left[ \varDelta G_{1-0,\mathrm {o}}^{\mathrm {solv}}\left( T,P\right) -\varDelta G_{1-0,\mathrm {w}}^{\mathrm {solv}}\left( T,P\right) \right] \\&\quad -\log_{10} \left( 1 + \sum_{i=1}^{N} \exp \left[ -\frac{\varDelta G_{i-0}^{\rm rxn}}{RT} -q_{i} \frac{\mathrm {pH}}{\log_{10} e}\right] \right) \end{aligned}$$
(41)

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rodriguez, S.A., Tran, J., Sabatino, S.J. et al. Predicting octanol/water partition coefficients and pKa for the SAMPL7 challenge using the SM12, SM8 and SMD solvation models. J Comput Aided Mol Des 36, 687–705 (2022). https://doi.org/10.1007/s10822-022-00474-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-022-00474-1

Keywords

Navigation