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SAMPL6 Octanol–water partition coefficients from alchemical free energy calculations with MBIS atomic charges

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Abstract

In molecular modeling the description of the interactions between molecules forms the basis for a correct prediction of macroscopic observables. Here, we derive atomic charges from the implicitly polarized electron density of 11 molecules in the SAMPL6 challenge using the Hirshfeld-I and Minimal Basis Set Iterative Stockholder (MBIS) partitioning method. These atomic charges combined with other parameters in the GAFF force field and different water/octanol models were then used in alchemical free energy calculations to obtain hydration and solvation free energies, which after correction for the polarization cost, result in the blind prediction of the partition coefficient. From the tested partitioning methods and water models the S-MBIS atomic charges with the TIP3P water model presented the smallest deviation from the experiment. Conformational dependence of the free energies and the energetic cost associated with the polarization of the electron density are discussed.

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References

  1. Mobley DL, Wymer KL, Lim NM, Guthrie JP (2014) J Comput Aided Mol Des 28(3):135

    Article  CAS  Google Scholar 

  2. Muddana HS, Gilson MK (2012) J Comput Aided Mol Des 26(5):517

    Article  CAS  Google Scholar 

  3. Muddana HS, Fenley AT, Mobley DL, Gilson MK (2014) J Comput Aided Mol Des 28(4):305

    Article  CAS  Google Scholar 

  4. Bannan CC, Burley KH, Chiu M, Shirts MR, Gilson MK, Mobley DL (2016) J Comput Aided Mol Des 30(11):927

    Article  CAS  Google Scholar 

  5. Rustenburg AS, Dancer J, Lin B, Feng JA, Ortwine DF, Mobley DL, Chodera JD (2016) J Comput Aided Mol Des 30(11):945

    Article  CAS  Google Scholar 

  6. Bannan CC, Mobley DL, Skillman AG (2018) J Comput Aided Mol Des 32(10):1165

    Article  CAS  Google Scholar 

  7. Klimovich PV, Mobley DL (2015) J Comput Aided Mol Des 29(11):1007

    Article  CAS  Google Scholar 

  8. Işık M, Levorse D, Mobley DL, Rhodes T, Chodera JD (2019) J Comput Aided Mol Des. https://doi.org/10.1007/s10822-019-00271-3

    Article  PubMed  Google Scholar 

  9. Bannan CC, Calabró G, Kyu DY, Mobley DL (2016) J Chem Theory Comput 12(8):4015

    Article  CAS  Google Scholar 

  10. Daina A, Michielin O, Zoete V (2014) J Chem Inf Model 54(12):3284

    Article  CAS  Google Scholar 

  11. Kundi V, Ho J (2019) J Phys Chem B 123(31):6810

    Article  CAS  Google Scholar 

  12. Klopman G, Li JY, Wang S, Dimayuga M (1994) J Chem Inf Comput Sci 34(4):752

    Article  CAS  Google Scholar 

  13. Ghose AK, Crippen GM (1986) J Comput Chem 7(4):565

    Article  CAS  Google Scholar 

  14. Wang R, Fu Y, Lai L (1997) J Chem Inf Comput Sci 37(3):615

    Article  CAS  Google Scholar 

  15. Cheng T, Zhao Y, Li X, Lin F, Xu Y, Zhang X, Li Y, Wang R, Lai L (2007) J Chem Inf Model 47(6):2140

    Article  CAS  Google Scholar 

  16. Marenich AV, Cramer CJ, Truhlar DG (2013) J Chem Theory Comput 9(1):609

    Article  CAS  Google Scholar 

  17. Marenich AV, Cramer CJ, Truhlar DG (2009) J Chem Theory Comput 5(9):2447

    Article  CAS  Google Scholar 

  18. Muddana HS, Sapra NV, Fenley AT, Gilson MK (2014) J Comput Aided Mol Des 28(3):277

    Article  CAS  Google Scholar 

  19. Lara A, Riquelme M, Vöhringer-Martinez E (2018) J Comput Chem 39(22):1728

    Article  CAS  Google Scholar 

  20. Riquelme M, Lara A, Mobley DL, Verstraelen T, Matamala AR, Vöhringer-Martinez E (2018) J Chem Inf Model 58(9):1779

    Article  CAS  Google Scholar 

  21. Heidar-Zadeh F, Ayers PW, Verstraelen T, Vinogradov I, Vöhringer-Martinez E, Bultinck P (2018) J Phys Chem A 122(17):4219

    Article  CAS  Google Scholar 

  22. Landrum G. Rdkit: Open-source cheminformatics. http://www.rdkit.org

  23. Neese F (2011) Wiley Interdiscip Rev Comput Mol Sci 2(1):73

    Article  Google Scholar 

  24. Bultinck P, Van Alsenoy C, Ayers PW, Carbó-Dorca R (2007) J Chem Phys 126(14):144111

    Article  Google Scholar 

  25. Verstraelen T, Vandenbrande S, Heidar-Zadeh F, Vanduyfhuys L, Van Speybroeck V, Waroquier M, Ayers PW (2016) J Chem Theory Comput 12(8):3894

    Article  CAS  Google Scholar 

  26. Verstraelen T, Tecmer P, Heidar-Zadeh F, Boguslawski K, Chan M, Zhao Y, Kim TD, Vandenbrande S, Yang D, González-Espinoza CE, Fias S, Limacher PA, Berrocal D, Malek A, Ayers PW (2015) Horton 2.0.0. Accessed 25 Jan 2018

  27. Ramos Matos G Duarte, Kyu DY, Loeffler HH, Chodera JD, Shirts MR, Mobley DL, Chem J (2017) Eng Data 62(5):1559

    Article  Google Scholar 

  28. Berendsen H, Grigera JR, Straatsma TP (1987) J Phys Chem 91(24):6269

    Article  CAS  Google Scholar 

  29. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein M (1983) J Chem Phys 79:926

    Article  CAS  Google Scholar 

  30. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, Lindahl E (2015) SoftwareX 1–2:19

    Article  Google Scholar 

  31. Van Gunsteren WF, Berendsen HJC (1988) Mol Simul 1(3):173

    Article  Google Scholar 

  32. Parrinello M, Rahman A (1981) J Appl Phys 52(12):7182

    Article  CAS  Google Scholar 

  33. Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) J Chem Phys 103(19):8577

    Article  CAS  Google Scholar 

  34. Hess B, Bekker H, Berendsen H, Fraaije J (1997) J Comput Chem 18(12):1463

    Article  CAS  Google Scholar 

  35. Shirts MR, Mobley DL, Chodera JD, Pande VS (2007) J Phys Chem B 111(45):13052

    Article  CAS  Google Scholar 

  36. Klimovich PV, Shirts MR, Mobley DL (2015) J Comput Aided Mol Des 29(5):397

    Article  CAS  Google Scholar 

  37. Shirts MR, Chodera JD (2008) J Chem Phys 129(12):124105

    Article  Google Scholar 

  38. McQuarrie DA, Simon JD (1997) Physical chemistry: a molecular approach. University Science Books, Sausalito

    Google Scholar 

  39. Procacci P, Guarnieri G (2019) J Comput-Aided Mol Des. https://doi.org/10.1007/s10822-019-00233-9

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank financial support by Fondecyt No. 11160193.

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Authors and Affiliations

  1. Instituto de Ciencias Químicas, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile

    Maximiliano Riquelme

  2. Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, Concepción, Chile

    Esteban Vöhringer-Martinez

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  1. Maximiliano Riquelme
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  2. Esteban Vöhringer-Martinez
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Correspondence to Esteban Vöhringer-Martinez.

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Riquelme, M., Vöhringer-Martinez, E. SAMPL6 Octanol–water partition coefficients from alchemical free energy calculations with MBIS atomic charges. J Comput Aided Mol Des 34, 327–334 (2020). https://doi.org/10.1007/s10822-020-00281-6

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