Abstract
Charge scaling, also denoted as the electronic continuum correction, has proven to be an efficient method for effectively including electronic polarization in force field molecular dynamics simulations without additional computational costs. However, scaling charges in existing force fields, fitted at least in part to experimental data, lead to inconsistencies, such as overscaling. We have, therefore, recently developed a four-site water model consistent with charge scaling, i.e., possessing the correct low-frequency dielectric constant of 45. Here, we build on top of this water model to develop charge-scaled models of biologically relevant Li(+), Na(+), K(+), Ca(2+), and Mg(2+) cations as well as Cl(-), Br(-), and I(-) anions, employing machine learning to streamline and speed up the parametrization process. On the one hand, we show that the present model outperforms the best existing charge scaled model of aqueous ions. On the other hand, the present work points to a future need for consistently and simultaneously improving the water and ion models within the electronic continuum correction framework.