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Journal Article

Computing spatially resolved rotational hydration entropies from atomistic simulations.

MPS-Authors
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Heinz,  L. P.
Department of Theoretical and Computational Biophysics, MPI for Biophysical Chemistry, Max Planck Society;

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Grubmüller,  H.
Department of Theoretical and Computational Biophysics, MPI for Biophysical Chemistry, Max Planck Society;

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3182317.pdf
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Supplementary Material (public)

3182317_Suppl.pdf
(Supplementary material), 205KB

Citation

Heinz, L. P., & Grubmüller, H. (2020). Computing spatially resolved rotational hydration entropies from atomistic simulations. Journal of Chemical Theory and Computation, 16(1), 108-118. doi:10.1021/acs.jctc.9b00926.


Cite as: http://hdl.handle.net/21.11116/0000-0005-5C95-C
Abstract
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 the statistical mechanics of liquids, as well as molecular dynamics simulations have provided much insight, solvation shell entropies remain 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 atomistic simulations of a water box. With an accuracy of better than 9.6%, the obtained spatial resolution should shed new light on the hydrophobic effect and the thermodynamics of solvation in general.