Can a Coarse-grained Water Model Capture the Key Physical Features of the Hydrophobic Effect?

Coarse-grained (CG) Molecular Dynamics can be a powerful method for probing complex processes. However, most CG force fields use pairwise non-bonded interaction potentials sets, which can limit their ability to capture complex multi-body phenomena such as the hydrophobic effect. As the hydrophobic effect primarily manifests itself due to the non-polar solute affecting the nearby hydrogen bonding network in water, capturing such effects using a simple one CG site or “bead” water model is a challenge. In this work, we systematically test the ability of CG one site water models for capturing critical features of the solvent environment around a hydrophobe as well as the Potential of Mean Force (PMF) of neopentane association. We study two bottom-up water models: a Simple Pairwise (SP) Force-Matched water model constructed using the Multiscale Coarse-Graining method and the Bottom-Up Many-Body Projected Water (BUMPer) model, which has three-body correlations implicitly embedded into it. We also test the top-down monatomic (mW) and the Machine Learned mW (ML-mW) water models. We find that the top-down models perform well in capturing the structural correlation in the water functions near the hydrophobe, but not the energetics of the PMF. BUMPer outperforms the SP water model in capturing structural correlations, but also gives an accurate PMF in contrast to the two mW models. Our study highlights the importance of including three-body interactions in CG water models, either explicitly or implicitly, while in general highlighting the applicability of bottom-up CG water models for studying hydrophobic association effects in a quantitative fashion.