The empirical approaches used during SAMPL6 can be divided into three categories, Database Lookup (DL), Linear Free Energy Relationship (LFER), and Quantitative Structure-Property/Machine Learning (QSPR/ML) approaches . The physical approaches can be divided into pure quantum-mechanical (QM) methods, QM with a linear empirical correction (QM+LEC) to account for the free energy of the proton in solution or potential systematic errors caused by the chosen method, and QM in combination with molecular mechanics (QM+MM). Generally speaking, the empirical methods require significantly less computational effort than their physics-based counterparts once they are parameterized.