The Binomial Cell Model of Hydrophobic Solvation

Alexandrovsky, V. V.; Basilevsky, M. V.; Leontyev, Igor; Мазо, М. А.; Сулимов, В. Б.

doi:10.1021/jp031189e

Cited by 18 publications

(41 citation statements)

References 31 publications

(129 reference statements)

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“…The procedure based on the IT approach 5-7 inserts the first two distribution moments 〈m〉 and σ 2 as input data and applies the binomial cell model 13 for the individual peaks constituting P m . The primary default distribution, originating from the cell theory of dense fluids, takes into account only entropic effects accompanying cavity formation.…”

Section: Resultsmentioning

confidence: 99%

“…Note that, according to (13) and (14), the number n of volume cells must be determined individually for every solute cavity, together with λ 0 and λ 1 , as a solution to eq 14. For the further application, it is convenient to define where ϑ is considered as a second variable satisfying (14).…”

Section: Information Theory Correctionmentioning

confidence: 99%

“…This approach appears different from that accepted earlier. 5,6,13 This could be circumvented by using the canonical formulation (12) where λ 2 is a regular Lagrangian multiplier. In essence, the two approaches prove to be equivalent (see the Appendix).…”

Section: Information Theory Correctionmentioning

confidence: 99%

“…For such a type of distribution, called "binomialexponential"(BE), these sums can be treated analytically. 13 As a result we obtain (18) in the closed form Finally the IT equations (14) are rewritten as follows:…”

Section: Computational Schemementioning

confidence: 99%

“…It also successfully treated nonspherical real solutes, 13 namely, C 1 -C 6 hydrocarbons, including linear, branched, and cyclic structures. 12 The prediction that ∆G cav is proportional to the cavity volume υ within the considered range of cavity sizes is in accord with recent conclusions of other authors.…”

Section: Introductionmentioning

confidence: 99%

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Excluded Volume Effect for Large and Small Solutes in Water

et al. 2005

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The cavitation effect, i.e., the process of the creation of a void of excluded volume in bulk solvent (a cavity), is considered. The cavitation free energy is treated in terms of the information theory (IT) approach [Hummer, G.; Garde, S.; Garcia, A. E.; Paulaitis, M. E.; Pratt, L. R. J. Phys. Chem. B 1998, 102, 10469]. The binomial cell model suggested earlier is applied as the IT default distribution p(m) for the number m of solute (water) particles occupying a cavity of given size and shape. In the present work, this model is extended to cover the entire range of cavity size between small ordinary molecular solutes and bulky biomolecular structures. The resulting distribution consists of two binomial peaks responsible for producing the free energy contributions, which are proportional respectively to the volume and to the surface area of a cavity. The surface peak dominates in the large cavity limit, when the two peaks are well separated. The volume effects become decisive in the opposite limit of small cavities, when the two peaks reduce to a single-peak distribution as considered in our earlier work. With a proper interpolation procedure connecting these two regimes, the MC simulation results for model spherical solutes with radii increasing up to R = 10 A [Huang, D. H.; Geissler, P. L.; Chandler, D. J. Phys. Chem. B 2001, 105, 6704] are well reproduced. The large cavity limit conforms to macroscopic properties of bulk water solvent, such as surface tension, isothermal compressibility and Tolman length. The computations are extended to include nonspherical solutes (hydrocarbons C1-C6).

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Section: Resultsmentioning

confidence: 99%

Section: Information Theory Correctionmentioning

confidence: 99%

Section: Information Theory Correctionmentioning

confidence: 99%

Section: Computational Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Excluded Volume Effect for Large and Small Solutes in Water

et al. 2005

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Computation of hydration free energies of organic solutes with an implicit water model

et al. 2006

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A new approach for computing hydration free energies DeltaG(solv) of organic solutes is formulated and parameterized. The method combines a conventional PCM (polarizable continuum model) computation for the electrostatic component DeltaG(el) of DeltaG(solv) and a specially detailed algorithm for treating the complementary nonelectrostatic contributions (DeltaG(nel)). The novel features include the following: (a) two different cavities are used for treating DeltaG(el) and DeltaG(nel). For the latter case the cavity is larger and based on thermal atomic radii (i.e., slightly reduced van der Waals radii). (b) The cavitation component of DeltaG(nel) is taken to be proportional to the volume of the large cavity. (c) In the treatment of van der Waals interactions, all solute atoms are counted explicitly. The corresponding interaction energies are computed as integrals over the surface of the larger cavity; they are based on Lennard Jones (LJ) type potentials for individual solute atoms. The weighting coefficients of these LJ terms are considered as fitting parameters. Testing this method on a collection of 278 uncharged organic solutes gave satisfactory results. The average error (RMSD) between calculated and experimental free energy values varies between 0.15 and 0.5 kcal/mol for different classes of solutes. The larger deviations found for the case of oxygen compounds are probably due to a poor approximation of H-bonding in terms of LJ potentials. For the seven compounds with poorest fit to experiment, the error exceeds 1.5 kcal/mol; these outlier points were not included in the parameterization procedure. Several possible origins of these errors are discussed.

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Fundamental measure theory of hydrated hydrocarbons

Соколов

Chuev

2006

J Mol Model

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To calculate the solvation of hydrophobic solutes, we have developed a method based on the fundamental measure treatment of density functional theory. This method allows us to carry out calculations of density profiles and the solvation energy for various hydrophobic molecules with high accuracy. We have applied the method to the hydration of various hydrocarbons (linear, branched and cyclic). The calculations of the entropic and enthalpic parts are also carried out. We have examined the question of the temperature dependence of the entropy convergence. Finally, we have calculated the mean force potential between two large hydrophobic nanoparticles immersed in water.

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The Binomial Cell Model of Hydrophobic Solvation

Cited by 18 publications

References 31 publications

Excluded Volume Effect for Large and Small Solutes in Water

Excluded Volume Effect for Large and Small Solutes in Water

Computation of hydration free energies of organic solutes with an implicit water model

Fundamental measure theory of hydrated hydrocarbons

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