Dynamical properties of the soft sticky dipole model of water: molecular dynamics simulations

Dynamical properties of the soft sticky dipole (SSD) model of water are calculated by means of molecular dynamics simulations. Since this is not a simple point model, the forces and torques arising from the SSD potential are derived here. Simulations are carried out in the microcanonical ensemble employing the Ewald method for the electrostatic interactions. Various time correlation functions and dynamical quantities associated with the translational and rotational motion of water molecules are evaluated and compared with those of two other commonly used models of liquid water, namely the transferable intermolecular potential-three points (TIP3P) and simple point charge/extended (SPC/E) models, and also with experiments. The dynamical properties of the SSD water model are found to be in good agreement with the experimental results and appear to be better than the TIP3P and SPC/E models in most cases, as has been previously shown for its thermodynamic, structural, and dielectric properties. Also, molecular dynamics simulations of the SSD model are found to run much faster than TIP3P, SPC/E, and other multisite models

The Surface Potential of the Water–Vapor Interface from Classical Simulations

The electrochemical surface potential across the water–vapor interface provides a measure of the orientation of water molecules at the interface. However, the large discrepancies between surface potentials calculated from <i>ab initio</i> (AI) and classical molecular dynamics (MD) simulations indicate that what is being calculated may be relevant to different test probes. Although a method for extracting the electrochemical surface potential from AIMD simulations has been given, methods for MD simulations have not been clarified. Here, two methods for extracting the surface potential relevant to electrochemical measurements from MD simulations are presented. This potential is shown to be almost entirely due to the dipole contribution. In addition, the molecular origin of the dipole contribution is explored by using different potential energy functions for water. The results here show that the dipole contribution arises mainly from distortions in the hydration shell of the full hydrogen bonded waters on the liquid side of the interface, which is determined by the charge distribution of the water model. Disturbingly, the potential varies by 0.4 eV depending on the model. Although there is still no consensus on what that charge distribution should be, recent results indicate that it contains both a large quadrupole and negative charge out of the molecular plane, i.e., three-dimensional (3D) charge. Water models with 3D charge give the least distortion of the hydration shell and the best agreement with experimental surface potentials, although there is still uncertainty in the experimental values

Identifying Residues That Cause pH-Dependent Reduction Potentials

The pH dependence of the reduction potential <i>E</i>° for a metalloprotein indicates that the protonation state of at least one residue near the redox site changes and may be important for its activity. The responsible residue is usually identified by site-specific mutagenesis, which may be time-consuming. Here, the titration of <i>E</i>° for <i>Chromatium vinosum</i> high-potential iron–sulfur protein is predicted to be in good agreement with experiment using density functional theory and Poisson–Boltzmann calculations if only the sole histidine undergoes changes in protonation. The implementation of this approach into CHARMMing, a user-friendly web-based portal, allows users to identify residues in other proteins causing similar pH dependence