  The impact of targeted replacement of individual terms in empirical force
fields is quantitatively assessed for pure water, dichloromethane (DCM), and
solvated K$^+$ and Cl$^-$ ions. For the electrostatics, point charges (PCs) and
machine learning (ML)based minimally distributed charges (MDCM) fitted to the
molecular electrostatic potential are evaluated together with electrostatics
based on the Coulomb integral. The impact of explicitly including second-order
terms is investigated by adding a fragment molecular orbital (FMO)-derived
polarization energy to an existing force field, in this case CHARMM. It is
demonstrated that anisotropic electrostatics reduce the RMSE for water (by 1.6
kcal/mol), DCM (by 0.8 kcal/mol) and for solvated Cl$^-$ clusters (by 0.4
kcal/mol). An additional polarization term can be neglected for DCM but notably
improves errors in pure water (by 1.1 kcal/mol) and in Cl$^-$ clusters (by 0.4
kcal/mol) and is key to describing solvated K$^+$, reducing the RMSE by 2.3
kcal/mol. A 12-6 Lennard-Jones functional form is found to perform
satisfactorily with PC and MDCM electrostatics, but is not appropriate for
descriptions that account for the electrostatic penetration energy. The
importance of many-body contributions is assessed by comparing a strictly
2-body approach with self-consistent reference data. DCM can be approximated
well with a 2-body potential while water and solvated K$^+$ and Cl$^-$ ions
require explicit many-body corrections. The present work systematically
quantifies which terms improve the performance of an existing force field and
what reference data to use for parametrizing these terms in a tractable fashion
for ML fitting of pure and heterogeneous systems.
