A first-principles study of surface and subsurface H on and in Ni(1 1 1): diffusional properties and coverage-dependent behavior

Periodic, self-consistent, density functional theory (GGA-PW91) calculations are performed for both surface and subsurface atomic hydrogen on and in Ni(1 1 1). At a low coverage (θ=0.25 ML), the binding energies (BEs) of a hydrogen atom in surface fcc, subsurface octahedral (first layer), and subsurface octahedral (second layer) sites are −2.89, −2.18, and −2.11 eV, respectively. The activation energy barriers for hydrogen diffusion from the surface to the first subsurface layer and from the first to the second subsurface layer are estimated to be 0.88 and 0.52 eV, respectively. In the entire coverage range studied, hydrogen occupies surface fcc and hcp sites and subsurface octahedral sites. In addition, the magnitude of the BE per hydrogen atom and the magnetization of the nickel slabs both decrease as hydrogen coverage increases. Vibrational frequencies of hydrogen at various surface and subsurface sites are calculated and are in reasonable agreement with experimental data. A phase stability calculation with a 2 × 2 surface unit cell shows that a p(2 × 2)-2H overlayer structure (θ=0.5 ML) and a p(1 × 1)-1H structure (θ=1.0 ML) are stable at low hydrogen pressures, in agreement with numerous experimental results. A very large increase in pressure is required to populate subsurface sites. After such an increase occurs, the first subsurface layer is filled completely.     

Nonparametric estimation of distributions with categorical and continuous data

In this paper we consider the problem of estimating an unknown joint distribution which is defined over mixed discrete and continuous variables. A nonparametric kernel approach is proposed with smoothing parameters obtained from the cross-validated minimization of the estimator's integrated squared error. We derive the rate of convergence of the cross-validated smoothing parameters to their ‘benchmark’ optimal values, and we also establish the asymptotic normality of the resulting nonparametric kernel density estimator. Monte Carlo simulations illustrate that the proposed estimator performs substantially better than the conventional nonparametric frequency estimator in a range of settings. The simulations also demonstrate that the proposed approach does not suffer from known limitations of the likelihood cross-validation method which breaks down with commonly used kernels when the continuous variables are drawn from fat-tailed distributions. An empirical application demonstrates that the proposed method can yield superior predictions relative to commonly used parametric models.     

Spherical coordinate representations of solvent composition for liquid chromatography method development using experimental design

One of the major techniques used for the method development of ternary and quaternary high performance liquid chromatography (HPLC) systems has been to use mixture designs, often referred to as "Glajch's Triangle". This technique does not allow for the systematic and simultaneous optimization of other factors such as gradient time, pH and temperature that affect the quality of separations. An alternative approach is to use experimental designs. The condition, however, that the composition of all components of the mobile phase must total 100% presents a problem when trying to mathematically represent ranges of each mobile phase constituent of a ternary or quaternary system. A method is described here, based on spherical coordinate representations, that adheres to the constraints of the mobile phase composition and allows experimental designs, such as central composite and factorial designs, to be applied to the simultaneous optimization of the mobile phase composition. Other factors, in particular temperature and gradient time, can then be included in the design. As a result of applying these designs to the HPLC separation of phenols and corticosteroids, it was found necessary to include three-way interactions between experimental factors in the model. The significance of these interactions shows that they need to be considered in HPLC method development.     

Effect of subsurface oxygen on the reactivity of the Ag(111) surface

Periodic, self-consistent, density functional theory calculations have been performed to demonstrate that subsurface oxygen (O(sb)) dramatically increases the reactivity of the Ag(111) surface. O(sb) greatly facilitates the dissociation of H2, O2, and NO and enhances the binding of H, C, N, O, O2, CO, NO, C2H2, and C2H4 on the Ag(111) surface. This effect originates from an O(sb)-induced upshift of the d-band center of the Ag surface and becomes more pronounced at higher O(sb) coverage. Our findings point to the important role that near-surface impurities, such as O(sb), can play in determining the thermochemistry and kinetics of elementary steps catalyzed by transition metal surfaces.     

<Emphasis Type="Italic">L</Emphasis>-Carnitine Supplementation: A New Paradigm for its Role in Exercise

Summary. Early research investigating the effects of L-carnitine supplementation has examined its role in substrate metabolism and in acute exercise performance. These studies have yielded equivocal findings, partially due to difficulties in increasing muscle carnitine concentrations. However, recent studies have proposed that L-carnitine may play a different role in exercise physiology, and preliminary results have been encouraging. Current investigations have theorized that L-carnitine supplementation facilitates exercise recovery. Proposed mechanism is as follows: 1) increased serum carnitine concentration enhances capillary endothelial function; 2) increased blood flow and reduced hypoxia mitigate the cascade of ensuing, destructive chemical events following exercise; 3) thus allowing reduced structural damage of skeletal muscle mediated by more intact receptors in muscle needed for improved protein signaling. This paradigm explains decreased markers of purine catabolism, free radical formation, and muscle tissue disruption after resistance exercise and the increased repair of muscle proteins following long-term L-carnitine supplementation.     

A first-principles study of methanol decomposition on Pt(111)

A periodic, self-consistent, Density Functional Theory study of methanol decomposition on Pt(111) is presented. The thermochemistry and activation energy barriers for all the elementary steps, starting with O[bond]H scission and proceeding via sequential hydrogen abstraction from the resulting methoxy intermediate, are presented here. The minimum energy path is represented by a one-dimensional potential energy surface connecting methanol with its final decomposition products, CO and hydrogen gas. It is found that the rate-limiting step for this decomposition pathway is the abstraction of hydroxyl hydrogen from methanol. CO is clearly identified as a strong thermodynamic sink in the reaction pathway while the methoxy, formaldehyde, and formyl intermediates are found to have low barriers to decomposition, leading to very short lifetimes for these intermediates. Stable intermediates and transition states are found to obey gas-phase coordination and bond order rules on the Pt(111) surface.     

MPW1K Performs Much Better than B3LYP in DFT Calculations on Reactions that Proceed by Proton-Coupled Electron Transfer (PCET)

DFT calculations have been performed with the B3LYP and MPW1K functional on the hydrogen atom abstraction reactions of ethenoxyl with ethenol and of phenoxyl with both phenol and alpha-naphthol. Comparison with the results of G3 calculations shows that B3LYP seriously underestimates the barrier heights for the reaction of ethenoxyl with ethenol by both proton-coupled electron transfer (PCET) and hydrogen atom transfer (HAT) mechanisms. The MPW1K functional also underestimates the barrier heights, but by much less than B3LYP. Similarly, comparison with the results of experiments on the reaction of phenoxyl radical with alpha-naphthol indicates that the barrier height for the preferred PCET mechanism is calculated more accurately by MPW1K than by B3LYP. These findings indicate that the MPW1K functional is much better suited than B3LYP for calculations on hydrogen abstraction reactions by both HAT and PCET mechanisms.     

Reversible binding of the HPLC6 isoform of type I antifreeze proteins to ice surfaces and the antifreeze mechanism studied by multiple quantum filtering-spin exchange NMR experiment

Antifreeze proteins (AFPs) protect organisms from freezing damage by inhibiting the growth of seed-ice crystals. It has long been hypothesized that irreversible binding of AFPs to ice surfaces is responsible for inhibiting the growth of seed-ice crystals as such a mechanism supports the popularly accepted Kelvin effect for the explanation of local freezing-point depression. However, whether the binding is reversible or irreversible is still under debate due to the lack of direct experimental evidence. Here, we report the first direct experimental result, by using the newly developed multiple quantum (MQ) filtering-spin exchange NMR experiment, that shows that the binding of HPLC6 peptides to ice surfaces is reversible. It was found that the reversible process can be explained by the model of monolayer adsorption. These results suggest that the Kelvin effect is not suitable for explaining the antifreeze mechanism, and direct interactions between the peptides and the ice-surface binding sites are the driving forces for the binding of AFPs to ice surfaces. We propose that there exists a concentration gradient of AFP from an ice-binding surface to the solution due to the affinity of ice surfaces to AFPs. This concentration gradient creates a dense layer of AFP in contact with the ice-binding surface, which depresses the local freezing point because of the colligative property, but not the Kelvin effect.     

High-throughput protein crystallography and drug discovery

Single crystal X-ray diffraction is the technique of choice for studying the interactions of small organic molecules with proteins by determining their three-dimensional structures; however the requirement for highly purified protein and lack of process automation have traditionally limited its use in this field. Despite these shortcomings, the use of crystal structures of therapeutically relevant drug targets in pharmaceutical research has increased significantly over the last decade. The application of structure-based drug design has resulted in several marketed drugs and is now an established discipline in most pharmaceutical companies. Furthermore, the recently published full genome sequences of Homo sapiens and a number of micro-organisms have provided a plethora of new potential drug targets that could be utilised in structure-based drug design programs. In order to take maximum advantage of this explosion of information, techniques have been developed to automate and speed up the various procedures required to obtain protein crystals of suitable quality, to collect and process the raw X-ray diffraction data into usable structural information, and to use three-dimensional protein structure as a basis for drug discovery and lead optimisation.This tutorial review covers the various technologies involved in the process pipeline for high-throughput protein crystallography as it is currently being applied to drug discovery. It is aimed at synthetic and computational chemists, as well as structural biologists, in both academia and industry, who are interested in structure-based drug design.