title: Comparison of Implicit and Explicit Solvent Models for the Calculation of Solvation Free Energy in Organic Solvents.
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.
  
  
  METHODS
  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.
authors.affiliation: Department of Chemistry and Soft Matter Research Center, Zhejiang University , Hangzhou 310027, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing , 100083 Beijing, China.
authors.forename: Haiyang
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Department of Chemistry and Soft Matter Research Center, Zhejiang University , Hangzhou 310027, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Wu
authors.affiliation: Department of Chemistry and Soft Matter Research Center, Zhejiang University , Hangzhou 310027, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University , Husargatan 3, Box 596, SE-75124 Uppsala, Sweden.
authors.forename: David
authors.identifier: http://orcid.org/0000-0002-7659-8526
authors.initials: D
authors.lastname: van der Spoel