Quantitative prediction of physical properties of liquids is important for many applications. Computational methods based on either explicit or implicit solvent models can be used to approximate thermodynamics properties of… Click to show full abstract
Quantitative prediction of physical properties of liquids is important for many applications. Computational methods based on either explicit or implicit solvent models can be used to approximate thermodynamics properties of liquids. Here, we evaluate the predictive power of implicit solvent models for solvation free energy of organic molecules in organic solvents. We compared the results calculated with four generalized Born (GB) models (GBStill, GBHCT, GBOBCI, and GBOBCII), the Poisson-Boltzmann (PB) model, and the density-based solvent model SMD with previous solvation free energy calculations (Zhang et al. J. Chem. Inf. MODEL 2015, 55, 1192-1201) and experimental data. The comparison indicates that both PB and GB give poor agreement with explicit solvent calculations and even worse agreement with experiments (root-mean-square deviation ≈ 15 kJ/mol). The main problem seems to be the prediction of the apolar contribution, which should include the solvent entropy. The quantum mechanical-based SMD model gives significantly better agreement with experimental data than do PB or GB, but it is not as good as explicit solvent calculation results. The dielectric constant ε of the solvent is found to be a powerful predictor for the polar contribution to the free energy in implicit models; however, the Onsager relation may not hold for realistic solvent, as suggested by explicit solvent and SMD calculations. From the comparison, we also find that with an optimization of the apolar contribution, the PB model gives slightly better agreement with experiments than the SMD model, whereas the correlation between the optimized GB models and experiments remains poor. Further optimization of the apolar contribution is needed for GB models to be able to treat solvents other than water.
               
Click one of the above tabs to view related content.