Temperature effects on the spatial distribution of electrolyte mixtures at the aqueous liquid-vapor interface.

The microscopic picture of ions at the aqueous liquid-vapor interface continues to be an important and active area of research. Both experiments and simulations have shown that certain ions, such as Br- and I-, prefer to adsorb at the interface, but there is not yet a consensus as to the relative importance of various ion-specific properties that influence surface solvation. In a previous study, we systematically explored the effect of ion size on determining whether or not a monovalent ion would adsorb at the surface, and found that, for electrolyte mixtures represented by non-polarizable models, the larger/smaller anions are enriched/depleted at the interface. Here, we extend that study to include temperature effects enabling a van't Hoff analysis of the enthalpic and entropic contributions. We perform configurational-bias Monte Carlo simulations in the Gibbs ensemble to investigate the partitioning of mixtures of differently sized ions at the aqueous liquid-vapor interface from 284.09 K to 347.22 K at a pressure of 1 atm. Ions are represented using our own previously developed models that vary only in size (i.e., the Lennard-Jones σ parameter changes, while all other parameters are held constant across ion types). System properties studied include surface tension, interfacial width, ion surface excess, number density profiles, z-dependent transfer free energy, enthalpy, entropy, and anion-cation coordination numbers.

Column selection for comprehensive two-dimensional liquid chromatography using the hydrophobic subtraction model.

Two-dimensional (2D) liquid chromatography (2DLC) methods have grown in popularity due to their enhanced peak capacity that allows for resolving complex samples. Given the large number of commercially available column types, one of the major challenges in implementing 2DLC methods is the selection of suitable column pairs. Column selection is typically informed by chemical intuition with subsequent experimental optimization. In this work a computational screening method for 2DLC is proposed whereby virtual 2D chromatograms are calculated utilizing the Snyder-Dolan hydrophobic subtraction model (HSM) for reversed-phase column selectivity. Towards this end, 319 225 column pairs resulting from the combination of 565 columns and 100 sets of 1000 diverse analytes are examined. Compared to other screening approaches, the present method is highly predictive for column pairs that are able to resolve the largest number of analytes. This approach shows a strong sensitivity to the choice of the second dimension column (having a shorter operating time) and a preference for those with embedded polar moieties, whereas a relatively weak preference for C18 and phenyl columns is found for the first dimension.

Molecular simulation studies of reversed-phase liquid chromatography.

Over the past 20 years, molecular simulation methods have been applied to the modeling of reversed-phase liquid chromatography (RPLC). The purpose of these simulations was to provide a molecular-level understanding of: (i) the structure and dynamics of the bonded phase and its interface with the mobile phase, (ii) the interactions of analytes with the bonded phase, and (iii) the retention mechanism for different analytes. However, the investigation of chromatographic systems poses significant challenges for simulations with respect to the accuracy of the molecular mechanics force fields and the efficiency of the sampling algorithms. This review discusses a number of aspects concerning molecular simulation studies of RPLC systems including the historical development of the subject, the background needed to understand the two prevalent techniques, molecular dynamics (MD) and Monte Carlo (MC) methods, and the wealth of insight provided by these simulations. Examples from the literature employing MD approaches and from the authors' laboratory using MC methods are discussed. The former can provide information on chain dynamics and transport properties, whereas the latter techniques are uniquely suited for the investigation of phase and sorption equilibria that underly RPLC retention, and both can be used to elucidate the bonded-chain conformations and solvent distributions.

Modeling helical proteins using residual dipolar couplings, sparse long-range distance constraints and a simple residue-based force field.

We present a fast and simple protocol to obtain moderate-resolution backbone structures of helical proteins. This approach utilizes a combination of sparse backbone NMR data (residual dipolar couplings and paramagnetic relaxation enhancements) or EPR data with a residue-based force field and Monte Carlo/simulated annealing protocol to explore the folding energy landscape of helical proteins. By using only backbone NMR data, which are relatively easy to collect and analyze, and strategically placed spin relaxation probes, we show that it is possible to obtain protein structures with correct helical topology and backbone RMS deviations well below 4 Å. This approach offers promising alternatives for the structural determination of proteins in which nuclear Overha-user effect data are difficult or impossible to assign and produces initial models that will speed up the high-resolution structure determination by NMR spectroscopy.

Structure and dynamics of the aqueous liquid-vapor interface: a comprehensive particle-based simulation study.

This research addresses a comprehensive particle-based simulation study of the structural, dynamic, and electronic properties of the liquid-vapor interface of water utilizing both ab initio (based on density functional theory) and empirical (fixed charge and polarizable) models. Numerous properties such as interfacial width, hydrogen bond populations, dipole moments, and correlation times will be characterized with identical schemes to draw useful conclusions on the strengths and weakness of the proposed models for interfacial water. Our findings indicate that all models considered in this study yield similar results for the radial distribution functions, hydrogen bond populations, and orientational relaxation times. Significant differences in the models appear when examining both the dipole moments and surface relaxation near the aqueous liquid-vapor interface. Here, the ab initio interaction potential predicts a significant decrease in the molecular dipole moment and expansion in the oxygen-oxygen distance as one approaches the interface in accordance with recent experiments. All classical polarizable interaction potentials show a less dramatic drop in the molecular dipole moment, and all empirical interaction potentials studied yield an oxygen-oxygen contraction as the interface is approached.

Determination of helical membrane protein topology using residual dipolar couplings and exhaustive search algorithm: application to phospholamban.

Dipolar waves are distinct hallmarks of both the secondary and tertiary structures of alpha-helical proteins that are immobilized in membrane bilayers or embedded in anisotropic media. We present a simple, semi-empirical approach that exploits the modulation of the amplitude and average of dipolar waves to determine the topology of alpha-helical proteins. Moreover, we describe the application of this method for the structural determination of a detergent solubilized membrane protein, phospholamban (PLB) that is involved in calcium regulation of cardiac muscle. When combined with high-resolution solid-state NMR data, this method can serve as a fast route for determining the topology of helical membrane proteins solubilized in detergent micelles.