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Entropy and Solvation

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 ≥ 15); an...
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Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
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Cosolvent preferential molecular interactions in aqueous solutions.

M Hamsa Priya1, H S Ashbaugh, M E Paulaitis

  • 1William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, Ohio 43210, USA.

The Journal of Physical Chemistry. B
|October 14, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a new method combining Kirkwood-Buff (KB) theory and the Potential Distribution Theorem (PDT) to accurately calculate cosolvent preferential interaction parameters from molecular simulations. This approach provides reliable estimates for various solutes and solvents, even for complex molecules like proteins.

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Area of Science:

  • Physical Chemistry
  • Computational Chemistry
  • Solution Theory

Background:

  • Calculating preferential interaction parameters (PIPs) in cosolvent systems is crucial for understanding solution behavior.
  • Traditional methods face convergence issues when approaching the bulk solution limit.
  • Molecular simulations offer a powerful tool for probing molecular interactions in solutions.

Purpose of the Study:

  • To extend Kirkwood-Buff (KB) solution theory integrals for calculating cosolvent PIPs from molecular simulations.
  • To derive solute excess chemical potential and solute-solvent molecular distribution functions from a single simulation trajectory.
  • To address the convergence problem of PIPs in the bulk solution limit.

Main Methods:

  • Integration of Kirkwood-Buff (KB) solution theory with the Potential Distribution Theorem (PDT).
  • Derivation of solute excess chemical potential from the PDT.
  • Calculation of solute-solvent molecular distribution functions from simulation trajectories.
  • Application of group additivity for site-specific PIP estimation.

Main Results:

  • A novel KB/PDT approach reliably estimates PIPs for methanol, ethanol, glycerol, and urea in aqueous cosolvent solutions.
  • The method resolves convergence issues associated with PIP calculations in the bulk solution limit.
  • Site-specific PIPs calculated using group additivity show good agreement with whole-molecule calculations.
  • The approach is applicable to complex macromolecular solutes like proteins.

Conclusions:

  • The combined KB/PDT method provides accurate and reliable preferential interaction parameters from molecular simulations.
  • This approach overcomes limitations of previous methods, enabling robust PIP calculations.
  • The study demonstrates the potential for site-specific PIP analysis on complex solutes, advancing our understanding of molecular interactions in biological systems.