By incorporating the ion-induced dipole interaction through the -C ij 4 /r 4 ij term, we successfully capture cation-π interactions within a classical fixed-charge force field. To further optimize force fields, one of the modern solutions could involve creating a hybrid machine learning (ML) potential by coupling a traditional molecular mechanics (MM) force field with a ML potential -similar to the ML/MM method analogous to the QM/MM approach. In this scenario, the ML potential would numerically model the cation-π interaction for both short and the long ranges, rather than a predefined functional form, while the remaining interaction would be calculated using the traditional MM force field, such as OPLS-AA.