Comparing to ensemble averaged properties such as density and RDF, fitting free energy difference is an important, yet even more challenging task. For example, the MD free energy calculation is one of the most common techniques used to predict protein-ligand binding affinities, which is the key goal in computer-aided drug design (CADD). Comparing to other methods that rely on empirical scoring functions (e.g., molecular docking), free-energy based techniques such as free energy perturbation (FEP) is physically rigorous and can potentially reach the chemical accuracy (i.e., within 1 kcal/mol of error). However, it posts a great challenge to develop a general, yet accurate force field for FEP that can cover the diversified chemical space of drug-like molecules. An accurate description to the electrostatic interactions is particularly difficult. Due to the heavy computational cost of FEP, such calculations are still primarily conducted using conventional fixed charge models, including OPLS, GAFF, CGenFF, 43 and OpenFF. In these models polarization effects are not explicitly included, so atomic charges need to be carefully tuned to give a balanced description to the electrostatics.