Computing spatially resolved rotational hydration entropies from atomistic simulations
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For a first principles understanding of macromolecular processes, a quantitative understanding of the underlying free energy landscape and in particular its entropy contribution is crucial. The stability of biomolecules, such as proteins, is governed by the hydrophobic effect, which arises from competing enthalpic and entropic contributions to the free energy of the solvent shell. While molecular dynamics simulations have revealed much insight, solvation shell entropies are notoriously difficult to calculate, especially when spatial resolution is required. Here, we present a method that allows for the computation of spatially resolved rotational solvent entropies via a non-parametric k-nearest-neighbor density estimator. We validated our method using analytic test distributions and applied it to an atomistic simulation of a water box. With an accuracy of better than 9.6 resolution should shed new light on the hydrophobic effect and the thermodynamics of solvation in general.
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