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The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
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Water and other polar molecules are attracted to ions. The electrostatic attraction between an ion and a molecule with a dipole is called an ion-dipole attraction. These attractions play an important role in the dissolution of ionic compounds in water.
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Atoms and molecules interact through bonds (or forces): intramolecular and intermolecular. The forces are electrostatic as they arise from interactions (attractive or repulsive) between charged species (permanent, partial, or temporary charges) and exist with varying strengths between ions, polar, nonpolar, and neutral molecules. The different types of intermolecular forces are ion–dipole, dipole–dipole, hydrogen bonds, and dispersion; among these, dipole–dipole, hydrogen...
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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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Per|Mut: Spatially Resolved Hydration Entropies from Atomistic Simulations.

Leonard P Heinz1, Helmut Grubmüller1

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Calculating hydration entropy is difficult. The new Per|Mut method uses permutation reduction and mutual information expansion to provide spatially resolved hydration entropies, overcoming sampling challenges in biophysical studies.

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Area of Science:

  • Biophysics
  • Computational Chemistry
  • Thermodynamics

Background:

  • The hydrophobic effect is crucial for biophysical processes, driven by hydration shell enthalpy and entropy.
  • Calculating solvation entropies is computationally challenging due to vast configuration spaces.
  • Local hydration entropy descriptions are needed to understand effects of molecular features.

Purpose of the Study:

  • Introduce and evaluate the novel Per|Mut method for calculating spatially resolved hydration entropies.
  • Address the sampling problem in solvation entropy calculations.
  • Enable local analysis of hydration entropy contributions.

Main Methods:

  • Developed the Per|Mut method utilizing permutation reduction (N! alleviation).
  • Employed a third-order mutual information expansion for entropy calculation.
  • Applied the method to argon, n-alkanes, and octanol systems.

Main Results:

  • Per|Mut effectively alleviates sampling challenges in entropy calculations.
  • The method provides spatially resolved hydration entropy data.
  • Successful application demonstrated on model systems.

Conclusions:

  • Per|Mut offers a viable approach for detailed hydration entropy analysis.
  • The method facilitates understanding local contributions to the hydrophobic effect.
  • Spatially resolved entropy calculations are now more accessible.