Solvates structure prediction

So-called solvation/structural forces, or (in water) hydration forces, arise in the gap between a pair of particles or surfaces when solvent (water) molecules become ordered by the proximity of the surfaces. When such ordering occurs, there is a breakdown in the classical continuum theories of the van der Waals and electrostatic double-layer forces, with the consequence that the monotonic forces they conventionally predict are replaced (or accompanied) by exponentially decaying oscillatory forces with a periodicity roughly equal to the size of the confined species (Min et al, 2008). In practice, these confined species may be of widely variable structural and chemical types — ranging in size from small solvent molecules (like water) up to macromolecules and nanoparticles. 

Structure of Br may not be the same as that of the bulk. Some of the molecular dynamics calculations predict that halide anions in water tend to float on the surface of clusters consisting of water molecules rather than within water. This effect may cause a dissimilar solvation structure to that of the bulk. In addition, if the anion is segregated at the surface by surfactants such as large alkylammonium cations, the anion density at the surface should be high and its environment differ from the bulk. This is a preliminary report of the first experimental study of the solution surface by the EXAFS technique. This technique provides us information on the gas/liquid interface, the structure of Langmuir films, and the effect of the interface on chemical reactions. 

Partial molar volume is predicted in reasonable agreement with experiment, and solute-solute aggregation is also predicted as suggested by recent excimer fluorescence results. We conclude that integral equation theories are useful in revealing solvation structures of supercritical solutions. 

Computational studies investigate reaction mechanisms and pathways by constructing potential energy profiles. This involves exploring reaction thermodynamics and kinetics, by examining reactants and products as well as the transition states geometries and activation energy barriers. Like those seen in structure prediction, most current studies implement effective core potentials and density functional theory to perform calculations.However, ECPs can be paired with MP2 to account for electron correlation thus far, this approach has only been used for smaller chemical systems. " Eurthermore, solvation methods such as the polarizable continuum model can be employed to examine... 

Finally, there are programs that add water molecules after potential ligand poses are found solely to improve the scoring [114—116]. Only in the first two approaches are the structural predictions influenced directly by the water molecules. Obviously, all three possibilities to include explicit water molecules in docking can modify the score of a ligand in comparison to a mere implicit treatment of solvation and desolvation. In doing so the challenge is to correctly quantify water contributions. 

The story of diffusion of small ions in water is, however, still not complete and the picture given above is over-simplified. For example, theory would predict a rather similar size dependence of conductivity for alkali cations and halide anions. In reality, however, the limiting conductivities of positive (alkali) and negative (halide) ions lie on different curves when plotted against the inverse radius (or radius). The peak appears at a larger radius for the anions. In order to explain this result one needs to consider an accurate interaction potential that differentiates between a cation and an anion of equal size. Such a study was carried out by Rasaiah and Lynden-Bell [18], who indeed found that solvation structures around cations and anions are markedly different for ions of the same size (such as and Cr ions). 

Secondly, the proton chemical shifts decrease with increasing temperature. These results clearly demonstrate the capability of the theory to predict experimental results. Analysis on the radial distribution function provides molecular level information on solvation structure and its relation to NMR chemical shifts. 

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