Influence of Electronic Polarization on the Binding of Anions to a Chloride-Pumping Rhodopsin
The functional properties of some biological ion channels and membrane transport proteins are proposed to exploit anion-hydrophobic interactions. Here, we investigate a chloride-pumping rhodopsin (ClR) as an example of a membrane protein known to contain a defined anion binding site composed predominantly of hydrophobic residues. Using molecular dynamics simulations, we explore Cl- binding to this hydrophobic site and compare the dynamics arising when electronic polarization is neglected (CHARMM36 (c36) fixed-charge force field), included implicitly (via the prosECCo force field), or included explicitly (through the polarizable force field, AMOEBA). Free energy landscapes of Cl- moving out of the binding site and into bulk solution demonstrate that the inclusion of polarization results in stronger ion binding and a second metastable binding site in ClR. Simulations focused on this hydrophobic binding site also indicate longer binding durations and closer ion proximity when polarization is included. Furthermore, simulations reveal that Cl- within this binding site interacts with an adjacent loop to facilitate rebinding events that are not observed when polarization is neglected. These results demonstrate how the inclusion of polarization can influence the behavior of anions within protein binding sites and thereby reveal novel mechanisms. Statement of SignificanceMolecular simulations based on classical (Newtonian) mechanics represent the most common method of visualizing the behavior of water and ions within channels and nanopores. Although computationally efficient, many of the approximations required mean that these simulations often do not fully capture the complex and dynamic interactions involved. Here, we use the prosECCo force field that offers an improved electronic description whilst maintaining computational efficiency. We show that using this method to include the effects of polarization greatly influences the binding dynamics of anions to a protein binding site and yields results similar to more accurate but computationally demanding methods.