A blind SAMPL6 challenge: insight into the octanol-water partition coefficients of drug-like molecules via a DFT approach
- 21 Downloads
In this study quantum mechanical methods were used to predict the solvation energies of a series of drug-like molecules both in water and in octanol, in the context of the SAMPL6 n-octanol/water partition coefficient challenge. In pharmaceutical design, n-octanol/water partition coefficient, LogP, describes the drug’s hydrophobicity and membrane permeability, thus, a well-established theoretical method that rapidly determines the hydrophobicity of a drug, enables the progress of the drug design. In this study, the solvation free energies were obtained via six different methodologies (B3LYP, M06-2X and ωB97XD functionals with 6-311+G** and 6-31G* basis sets) by taking into account the environment implicitly; the methodology chosen (B3LYP/6-311+G**) was used later to evaluate ΔGsolv by using explicit water as solvent. We optimized each conformer in different solvents separately, our calculations have shown that the stability of the conformers is highly dependent on the solvent environment. We have compared implicitly and explicitly solvated systems, the interaction of one explicit water with drug-molecules at the proper location leads to the prediction of more accurate LogP values.
KeywordsSAMPL6 Octanol/water partition coefficient Computer-aided drug design DFT Solvation free energies
Calculations reported in this paper were partially performed using the computational resources at CCBG funded by Bogazici University and as well as the resources of the TUBITAK ULAKBIM High Performance and Grid Computing Center (TRUBA resources).
- 8.Port A, Bordas M, Enrech R et al (2018) Critical comparison of shake-flask, potentiometric and chromatographic methods for lipophilicity evaluation (log Po/w) of neutral, acidic, basic, amphoteric, and zwitterionic drugs. Eur J Pharm Sci 122:331–340. https://doi.org/10.1016/j.ejps.2018.07.010 CrossRefPubMedGoogle Scholar
- 23.Frisch MJ, Trucks GW, Schlegel HB et al (2009) Gaussian 09 Revision E.01. Gaussian 09, Revis. E.01. Gaussian, WallingfordGoogle Scholar
- 30.Perdew JP (2003) Jacob’s ladder of density functional approximations for the exchange-correlation energy. AIP Publishing, College Park, pp 1–20Google Scholar
- 33.Zhao Y, Truhlar DG (2008) The M06 suite 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. https://doi.org/10.1007/s00214-007-0310-x CrossRefGoogle Scholar
- 36.Bryantsev VS, Diallo MS, van Duin ACT, Goddard WA (2009) Evaluation of B3LYP, X3LYP, and M06-class density functionals for predicting the binding energies of neutral, protonated, and deprotonated water clusters. J Chem Theory Comput 5:1016–1026. https://doi.org/10.1021/ct800549f CrossRefPubMedGoogle Scholar
- 39.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. https://doi.org/10.1021/jp810292n CrossRefPubMedPubMedCentralGoogle Scholar
- 42.Hansch C, Leo A, Hoek-man D (1996) Book reviews. J Med Chem 39:1189–1190Google Scholar