Characterizing hydrophobicity at the nanoscale: A molecular dynamics simulation study

Molecular Dynamics Investigation of Nanoscale Hydrophobicity of Polymer Surfaces: What Makes Water Wet?

The wettability of a polymer surface─related to its hydrophobicity or tendency to repel water─can be crucial for determining its utility, such as for a coating or a purification membrane. While wettability is commonly associated with the macroscopic measurement of a contact angle between surface, water, and air, the molecular physics that underlie these macroscopic observations are not fully known, and anticipating the relative behavior of different polymers is challenging. To address this gap in molecular-level understanding, we use molecular dynamics simulations to investigate and contrast interactions of water with six chemically distinct polymers: polytetrafluoroethylene, polyethylene, polyvinyl chloride, poly(methyl methacrylate), Nylon-66, and poly(vinyl alcohol). We show that several prospective quantitative metrics for hydrophobicity agree well with experimental contact angles. Moreover, the behavior of water in proximity to these polymer surfaces can be distinguished with analysis of interfacial water dynamics, extent of hydrogen bonding, and molecular orientation─even when macroscopic measures of hydrophobicity are similar. The predominant factor dictating wettability is found to be the extent of hydrogen bonding between polymer and water, but the precise manifestation of hydrogen bonding and its impact on surface water structure varies. In the absence of hydrogen bonding, other molecular interactions and polymer mechanics control hydrophobic ordering. These results provide new insights into how polymer chemistry specifically impacts water-polymer interactions and translates to surface hydrophobicity. Such factors may facilitate the design or processing of polymer surfaces to achieve targeted wetting behavior, and presented analyses can be useful in studying the interfacial physics of other systems.

Hydrophobic association and solvation of neopentane in urea, TMAO and urea-TMAO solutions

A detailed knowledge of hydrophobic association and solvation is crucial for understanding the con-formational stability of proteins and polymers in osmolyte solutions. Using molecular dynamics simulations, it is found that the hydrophobic association of neopentane molecules is greater in a mixed urea-TMAO-water solution in comparison to that in 8 M urea solution, 4 M TMAO solution and neat water. The neopentane association in urea solution is greater than that in TMAO solution or neat water. We find the association is even less in TMAO solution than pure water. From free energy calculations, it is revealed that the neopentane sized cavity creation in mixed urea-TMAO-water is most unfavorable and that causes the highest hydrophobic association. The cavity formation in urea solution is either more unfavorable or comparable to that in TMAO solution. Importantly, it is found that the population of neopentane-neopentane contact pair and the free energy contribution for the cavity formation step in TMAO solution are very sensitive towards the choice of TMAO force-fields. A careful construction of TMAO force-fields is important for studying the hydrophobic association. Interestingly it is observed that the total solute-solvent dispersion interaction energy contribution is always the most favorable in mixed urea-TMAO-water. The magnitude of this interaction energy is greater in urea solution relative to TMAO solution for two different force-fields of TMAO, whereas the lowest value is obtained in pure water. It is revealed that the extent of the overall hydrophobic association in osmolyte solutions is mainly governed by the cavity creation step and it nullifies the contribution coming from the solute-solvent interaction contribution.

Exploring the role of hydrophilic amino acids in unfolding of protein in aqueous ethanol solution

Hydrophobic association is the key contributor behind the formation of well packed core of a protein which is often believed to be an important step for folding from an unfolded chain to its compact functional form. While most of the protein folding/unfolding studies have evaluated the changes in the hydrophobic interactions during chemical denaturation, the role of hydrophilic amino acids in such processes are not discussed in detail. Here we report the role of the hydrophilic amino acids behind ethanol induced unfolding of protein. Using free energy simulations, we show that chicken villin head piece (HP-36) protein unfolds gradually in presence of water-ethanol binary mixture with increasing composition of ethanol. However, upon mutation of hydrophilic amino acids by glycine while keeping the hydrophobic amino acids intact, the compact state of the protein is found to be stable at all compositions with gradual flattening of the free energy landscape upon increasing compositions. The local environment around the protein in terms of ethanol/water number significantly differs in wild type protein compared to the mutated protein. The calculated Wyman-Tanford preferential binding coefficient of ethanol for wild type protein reveals that a greater number of cosolutes (here ethanol) bind to the unfolded state compared to its folded state. However, no significant increase in binding coefficient of ethanol at the unfolded state is found for mutated protein. Local-bulk partition coefficient calculation also suggests similar scenarios. Our results reveal that the weakening of hydrophobic interactions in aqueous ethanol solution along with larger preferential binding of ethanol to the unfolded state mediated by hydrophilic amino acids combinedly helps unfolding of protein in aqueous ethanol solution.

Effects of Packing Density and Chain Length on the Surface Hydrophobicity of Thin Films Composed of Perfluoroalkyl Acrylate Chains: A Molecular Dynamics Study

A good understanding of the surface hydrophobicity of fluorinated materials is useful for their application as coating materials. The present study investigates the surface hydrophobicity of perfluoroalkyl acrylate (PFA) thin films using molecular dynamics simulations. Surface hydrophobicity is characterized by examining the contact angle of a water droplet on PFA surfaces and the cavity formation free energy in the vicinity of the surface. It is found that the calculated microscopic contact angles are in good agreement with the experimental results and partially capture the difference in the hydrophobicity of the surface arising from the variation of packing density and side chain length of PFA. The variations of cavity formation free energy in the vicinity of the surface elucidate that the surface hydrophobicity is mainly governed by the packing density rather than the chain length of PFA. The hydrophobicity generally increases with decreasing the packing density to some extent and then turns to decrease as further reducing the packing density. At higher packing density, the surface hydrophobicity slightly decreases with increasing the chain length, while at the lower packing density, the surface hydrophobicity is increased when chain length of PFA is longer than six carbons. Furthermore, we found that the influence of packing density on the surface hydrophobicity is directly related to the variation of the surface roughness and chain flexibility, that is, the surface hydrophobicity increases with increase in the surface roughness, while the chain flexibility plays a secondary role in the enhancement by affecting the stability of water staying near the interface. The study provides a significant insight into the local hydrophobicity and microscopic structure of the PFA surfaces, which would be useful for the application of surface modification.

Computational modeling of ionic currents through difform graphene nanopores with consistent cross-sectional areas

Unveiling the mystery of ion transport behavior in nanopores with consistent cross-sectional areas shows that this behavior is highly related to the geometry and hydrophobicity of the nanopores.

Implicit Solvation Using the Superposition Approximation (IS-SPA): An Implicit Treatment of the Nonpolar Component to Solvation for Simulating Molecular Aggregation

Nonpolar solute-solvent interactions are the driving force for aggregation in important chemical and biological phenomena including protein folding, peptide self-assembly, and oil-water emulsion formation. Currently, the most accurate and computationally efficient description of these processes requires an explicit treatment of all solvent and solute atoms. Previous computationally feasible implicit solvent models, such as solute surface area approaches, are unsuccessful at capturing aggregation features including both structural and energetic trends while more theoretically rigorous approaches, such as Reference Interaction Site Model (RISM), are accurate but extremely computationally demanding. Our approach, denoted Implicit Solvation using the Superposition Approximation (IS-SPA), builds on previous theory utilizing the Kirkwood superposition approximation to approximate the mean force of the solvent from solute parameters. We introduce and verify a parabolic first solvation shell truncation of atomic solvation, fitting water distributions around a molecule, and a Monte Carlo integration of the mean solvent force. These extensions allow this method to be implemented as an efficient nonpolar implicit solvent model for molecular simulation. The approximations in IS-SPA are first explored and justified for the homodimerization of an array of different sized Lennard-Jones spheres. The accuracy and transferability of the approach are demonstrated by its ability to capture the position and relative energies of the desolvation barrier and free energy minimum of alkane homodimers. The model is then shown to reproduce the phase separation and solubility of cyclohexane and water. These promising results, coupled with 2 orders of magnitude speed-up for dilute systems as compared to explicit solvent simulations, demonstrate that IS-SPA is an appealing approach to boost the time- and length-scale of molecular aggregation simulations.