Development and Test of Highly Accurate End Point Free Energy Methods. 4. Expanding Solvents Capability and logBB...

We reported an expanded Poisson-Boltzmann surface area (PBSA) solvation model for the high-throughput calculation of solvation free energies (SFEs) and partition coefficients (logP) across diverse organic solvents. Furthermore, a predictive model for blood-brain barrier (BBB) permeability (logBB) was developed. Using 1246 experimental SFE measurements from the Minnesota Solvation (MNSol) database, we parametrized the solvent accessible surface area (SASA) nonpolar term for 27 organic solvents, enabling PBSA calculations in a broad set of solvent environments. Across the MNSol data set, PBSA achieves an overall root-mean-square error (RMSE) of 1.10 kcal/mol, compared with 0.98 kcal/mol from quantum mechanical SMD calculations at the B3LYP/6-31G* level. To assess parameter transferability, we computed water-organic solvent logP values for 248 compounds spanning five solvent systems; PBSA yields an overall RMSE of 2.02 log units, slightly higher than the SMD result of 1.5 log units. Finally, we developed a quantitative model for BBB permeability (logBB) using multivariable linear regression based on PBSA-derived hydration free energies and selected organic-solvent SFEs. The model shows stable predictive performance on both the training (N = 865) and test (N = 97) sets, with RMSE ≈ 0.65 log units and MAE ≈ 0.5 log units, and demonstrates improved rank ordering on the test set (Kendall's tau = 0.45). Overall, this work extends PBSA applicability to a wide range of solvents and establishes physically motivated and computationally efficient approaches for predicting some key ADMET descriptors.