A View of the Hydrophobic Effect

Southall, Noel; Dill, Ken A.; Haymet, A. D. J.

doi:10.1021/jp015514e

Cited by 836 publications

(809 citation statements)

References 164 publications

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“…Although it is the most important liquid on our planet, it is also the most complicated chemically. There still is no comprehensive theory of pure water, although that of Dill (the 'Mercedes Benz model') (Southall et al 2002;Dill & Bromberg, 2003) provides a very important start, and alternatives by others (Lazaridis, 2001;Chandler, 2002Chandler, , 2005 are also important contributions. These theories, however, are still at levels that are too abstract to give useful predictions at the level of molecular detail required for the design of ligands.…”

Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

“…Water is also the home of the hydrophobic effect (Lazaridis, 2001;Chandler, 2002Chandler, , 2005Southall et al 2002;Dill & Bromberg, 2003). The nature of the insolubility of hydrocarbons in water -the hydrophobic effect -is central to biology: as a guess, 80% of the free energy of an average molecular recognition event -whether protein folding or protein-ligand association -is due to the hydrophobic effect.…”

Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

“…The solubility of hydrophobic hydrocarbons in water as a function of temperature is one example. This solubility -for example, of cyclohexane, a representative hydrocarbon -is remarkably indifferent to temperature, although between 0 °C and 100 °C the free energy of solution changes from being almost entirely entropic to almost entirely enthalpic (Southall et al 2002). This type of compensation -an example of a so-called enthalpy/entropy compensation (EEC) -remains poorly understood.…”

Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

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Designing ligands to bind proteins

Whitesides

Krishnamurthy

2005

Quart. Rev. Biophys.

125

108

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The ability to design drugs (so-called 'rational drug design') has been one of the long-term objectives of chemistry for 50 years. It is an exceptionally difficult problem, and many of its parts lie outside the expertise of chemistry. The much more limited problem -how to design tight-binding ligands (rational ligand design) -would seem to be one that chemistry could solve, but has also proved remarkably recalcitrant. The question is 'Why is it so difficult?' and the answer is 'We still don't entirely know'. This perspective discusses some of the technical issues -potential functions, protein plasticity, enthalpy/entropy compensation, and others -that contribute, and suggests areas where fundamental understanding of protein-ligand interactions falls short of what is needed. It surveys recent technological developments (in particular, isothermal titration calorimetry) that will, hopefully, make now the time for serious progress in this area. It concludes with the calorimetric examination of the association of a series of systematically varied ligands with a model protein. The counterintuitive thermodynamic results observed serve to illustrate that, even in relatively simple systems, understanding protein-ligand association is challenging. Rational ligand designMolecular recognition is, in a sense, the most important process in molecular biology. Most of the reactions and interactions that dominate the operation of living systems -recognition of sequences in nucleic acids by complementary nucleic acids and by proteins; folding of proteins; recognition of ligands by proteins; interaction of drugs and target proteins; differential stabilization of the transition state and ground state of biochemical reactions by enzymes; many others -involve molecular recognition. Understanding molecular recognition is centrally important to understanding -and controlling -the set of molecular processes that make up the cell, and life.The problem of understanding molecular recognition translates, in utilitarian terms, into being able to design ligands that bind to specific sites on biomacromolecules (most often, proteins). This problem is intellectually enormously interesting, since solving it would provide ways of modulating the activities of proteins in vivo. More practically, it is central to the idea of socalled 'rational drug design'. Generating drugs has been, and remains, a difficult, expensive, failure-prone, and highly empirical activity. The difficulty and cost of developing new drugs has become prohibitive for the pharmaceutical industry, and without improved efficiency and productivity from the R&D groups of this industry, there is a widespread concern that the rate at which new drugs will be developed in the future will be substantially less than it has been in the past. The process of generating a drug is, of course, much more complicated than simply designing a ligand that targets a protein: 'hits' and 'leads' are an important part of the process, but ADME/Tox/PK/PD (adsorption, distribution, metabolism, excre...

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Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

Section: Interactions: Water and The Hydrophobic Effectmentioning

confidence: 99%

See 1 more Smart Citation

Designing ligands to bind proteins

Whitesides

Krishnamurthy

2005

Quart. Rev. Biophys.

125

108

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“…6 The hydrophobic effect itself has been widely studied with respect to the interaction of water with biopolymers. A review by Southall et al 7 has however highlighted some of the difficulties in interpreting the role of entropy and enthalpy on the driving forces for the hydrophobic effect 4 with relatively simple systems e.g. oil and water.…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics of Cellulose Amphiphilicity at the Graphene–Water Interface

2015

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Molecular dynamics (MD) simulations have been applied to study the interactions between hydrophobic and hydrophilic faces of ordered cellulose chains and a single layer of graphene in explicit aqueous solvent. The hydrophobic cellulose face is predicted to form a stable complex with graphene. This interface remains solvent-excluded over the course of simulations; the cellulose chains contacting graphene in general preserve intra-and inter-chain hydrogen bonds and a tg orientation of hydroxymethyl groups. Greater flexibility is observed in the more solvent-exposed cellulose chains of the complex. By contrast, the hydrophilic face of cellulose exhibits progressive rearrangement over the course of MD simulations, as it seeks to present its hydrophobic face, with disrupted intra-and interchain hydrogen bonding; residue twisting to form CH- interactions with graphene; and partial permeation of water. This transition is also accompanied by a more favorable cellulose-graphene adhesion energy as predicted at the PM6-DH2 level of theory. The stability of the cellulose-graphene hydrophobic interface in water exemplifies the amphiphilicity of cellulose and provides insight into favored interactions within graphene-cellulose materials. Furthermore, partial permeation of water between exterior cellulose chains may indicate potential in addressing cellulose recalcitrance.3

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“…An understanding of density fluctuations in bulk water and at interfaces, has played a central role in the description of hydrophobic effects, 1,1-12,14-20 which drive biomolecular [21][22][23][24][25][26] and other aqueous assemblies. [27][28][29][30][31] For example, the fact that P v (N), the probability of observing N water molecules in a small observation volume (v 1 nm 3 ), obeys Gaussian statistics, 3,32 has provided molecular-level insights into the the pressure-induced denaturation of proteins, [33][34][35] as well as the convergence of protein unfolding entropies at a particular temperature.…”

Section: Introductionmentioning

confidence: 99%

Sparse Sampling of Water Density Fluctuations in Interfacial Environments

Remsing

Patel

2016

J. Chem. Theory Comput.

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The free energetics of water density fluctuations near a surface, and the rare low-density fluctuations in particular, serve as reliable indicators of surface hydrophobicity; the easier it is to displace the interfacial waters, the more hydrophobic the underlying surface. However, characterizing the free energetics of such rare fluctuations requires computationally expensive, non-Boltzmann sampling methods like umbrella sampling. This inherent computational expense associated with umbrella sampling makes it challenging to investigate the role of polarizability or electronic structure effects in influencing interfacial fluctuations. Importantly, it also limits the size of the volume, which can be used to probe interfacial fluctuations. The latter can be particularly important in characterizing the hydrophobicity of large surfaces with molecular-level heterogeneities, such as those presented by proteins. To overcome these challenges, here we present a method for the sparse sampling of water density fluctuations, which is roughly two orders of magnitude more efficient than umbrella sampling. We employ thermodynamic integration to estimate the free energy differences between biased ensembles, thereby circumventing the umbrella sampling requirement of overlap between adjacent biased distributions. Further, a judicious choice of the biasing potential allows such free energy differences * To whom correspondence should be addressed 1 arXiv:1511.01518v1 [cond-mat.stat-mech] 4 Nov 2015 to be estimated using short simulations, so that the free energetics of water density fluctuations are obtained using only a few, short simulations. Leveraging the efficiency of the method, we characterize water density fluctuations in the entire hydration shell of the protein, ubiquitin; a large volume containing an average of more than six hundred waters.

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A View of the Hydrophobic Effect

Cited by 836 publications

References 164 publications

Designing ligands to bind proteins

Designing ligands to bind proteins

Molecular Dynamics of Cellulose Amphiphilicity at the Graphene–Water Interface

Sparse Sampling of Water Density Fluctuations in Interfacial Environments

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