Preferential Solvation: Dividing Surface vs Excess Numbers

Shimizu, Seishi; Matubayasi, Nobuyuki

doi:10.1021/jp410567c

Cited by 97 publications

(335 citation statements)

References 46 publications

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“…Now, let us divide the solution into two parts; the first part (called the "solute's vicinity") contains a solute molecule, the other part (called the "bulk") is far away from the solute. 6,7,23,27,40,41 To explore the thermodynamic consequence of this soluteinduced concentration change of the solvent species, let us first write down the Gibbs−Duhem equation for each part, vicinity (represented by *) and bulk: 6,7,23,27,40,41 …”

Section: Statistical Thermodynamic Theory Of Solute−hydrotrope Interamentioning

confidence: 99%

“…Thus, the Gibbs−Duhem eqs 1 and 2 have now been rewritten explicitly in terms of the concentration change (n i * − n i ) in the solute's vicinity. 6,7,23,27,40,41 Now we introduce the excess solvation number of the species i around the solute defined as follows:…”

Section: Statistical Thermodynamic Theory Of Solute−hydrotrope Interamentioning

confidence: 99%

“…6,7,23,27,40,41 By equating the species u in eq 7 with the species 2 and 3 at dT = 0, respectively, we obtain the following:…”

Section: ■ Appendix Amentioning

confidence: 99%

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Hydrotropy: Monomer–Micelle Equilibrium and Minimum Hydrotrope Concentration

2014

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Drug molecules with low aqueous solubility can be solubilized by a class of cosolvents, known as hydrotropes. Their action has often been explained by an analogy with micelle formation, which exhibits critical micelle concentration (CMC). Indeed, hydrotropes also exhibit "minimum hydrotrope concentration" (MHC), a threshold concentration for solubilization. However, MHC is observed even for nonaggregating monomeric hydrotropes (such as urea); this raises questions over the validity of this analogy. Here we clarify the effect of micellization on hydrotropy, as well as the origin of MHC when micellization is not accompanied. On the basis of the rigorous Kirkwood-Buff (KB) theory of solutions, we show that (i) micellar hydrotropy is explained also from preferential drug-hydrotrope interaction; (ii) yet micelle formation reduces solubilization effeciency per hydrotrope molecule; (iii) MHC is caused by hydrotrope-hydrotrope self-association induced by the solute (drug) molecule; and (iv) MHC is prevented by hydrotrope self-aggregation in the bulk solution. We thus need a departure from the traditional view; the structure of hydrotrope-water mixture around the drug molecule, not the structure of the aqueous hydrotrope solutions in the bulk phase, is the true key toward understanding the origin of MHC.

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Section: Statistical Thermodynamic Theory Of Solute−hydrotrope Interamentioning

confidence: 99%

Section: Statistical Thermodynamic Theory Of Solute−hydrotrope Interamentioning

confidence: 99%

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Hydrotropy: Monomer–Micelle Equilibrium and Minimum Hydrotrope Concentration

2014

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“…1) one obtains a number which would be 0 if the distribution were entirely average (no special interactions), positive for typical small molecules if the molecules have fairly strong interactions and negative for systems with unfavourable interactions. [14][15][16][17][28][29][30][31][32][33][34][35][36] The values for systems of interest are readily found from the hydrotrope app discussed below. These numbers are called the Kirkwood-Buff Integrals (KBI) and the free energy of the system can be calculated on a rigorous, assumption-free basis from the KBI.…”

Section: Seishi Shimizumentioning

confidence: 99%

Practical molecular thermodynamics for greener solution chemistry

2017

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We all know that to enhance solubility using greener chemistry we should harness sound principles of molecular-based thermodynamics. The problem is that even for simple systems it can be hard to know how to use fundamental tools for formulation benefit, and for the more complex systems that we must often use, calculations required for molecular thermodynamics can often be quite involved. In this paper we show that a fundamental, assumption-free statistical thermodynamics approach, the Kirkwood-Buff theory, can be used in practical, complex aqueous systems to provide the insights we need to optimise formulations. The theory itself is not that difficult, but its implementation, which requires many steps of thermodynamic calculations, has up to now not been straightforward. Taking full advantage of an interactive approach, here we review what the Kirkwood-Buff theory can provide for formulators; we use the power of modern web browsers to provide open-source, user-friendly, responsive-design apps to do the hard work of data analysis, leaving formulators to focus on the interpretation of the results for their specific optimisation task. Indeed the apps are intended to be used by researchers and formulators for specific systems of interest to them.

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“…As discussed in the Introduction, the magnitude of stabilization or destabilization is quantified by the change in preferential hydration, W ∆Γ , 10,25,64,65 which in the following we designate ∆Γ for short. Since the lattice model is incompressible, so that ( ) 0 PV ∆ = (where P and V are the system pressure and volume, respectively), the enthalpic and energetic changes of any process 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 15 are necessarily identical.…”

Section: Changes In Thermodynamic Quantities Upon Macromolecular Surfmentioning

confidence: 99%

Macromolecular Stabilization by Excluded Cosolutes: Mean Field Theory of Crowded Solutions

Sapir

Harries

2015

J. Chem. Theory Comput.

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We propose a mean field theory to account for the experimentally determined temperature dependence of protein stabilization that emerges in solutions crowded by preferentially excluded cosolutes. Based on regular solution theory and employing the Flory-Huggins approximation, our model describes cosolutes in terms of their size, and two temperature-dependent microscopic parameters that correspond to macromolecule-cosolute and bulk solution interactions. The theory not only predicts a "depletion force" that can account for the experimentally observed stabilization of protein folding or association in the presence of excluded cosolutes but also predicts the full range of associated entropic and enthalpic components. Remarkably, depending on cosolute identity and in accordance with experiments, the theory describes entropically as well as enthalpically dominated depletion forces, even those disfavored by entropy. This emerging depletion attraction cannot be simply linked to molecular volumes. Instead, the relevant parameter is an effective volume that represents an interplay between solvent, cosolute, and macromolecular interactions. We demonstrate that the apparent depletion free energy is often accompanied by significant yet compensating entropy and enthalpy terms that, although having a net zero contribution to stabilization, can obscure the underlying molecular mechanism. This study underscores the importance of including often-neglected free energy terms that correspond to solvent-cosolute and cosolute-macromolecule interactions, which for most typical cosolutes are expected to be temperature dependent. We propose that experiments specifically aimed at resolving the temperature-dependence of cosolute exclusion from macromolecular surfaces should help reveal the full range of the underlying molecular mechanisms of the depletion force.

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Preferential Solvation: Dividing Surface vs Excess Numbers

Cited by 97 publications

References 46 publications

Hydrotropy: Monomer–Micelle Equilibrium and Minimum Hydrotrope Concentration

Hydrotropy: Monomer–Micelle Equilibrium and Minimum Hydrotrope Concentration

Practical molecular thermodynamics for greener solution chemistry

Macromolecular Stabilization by Excluded Cosolutes: Mean Field Theory of Crowded Solutions

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