Structures and redox characteristics of electron-deficient vanadyl phthalocyanines

The first single-crystal X-ray structures of substituted vanadyl phthalocyanine materials reveal the high-valence vanadium ions (denoted as V(IV)), whose coordination by a highly electron-deficient ligand is facilitated by an axial oxo group. The metal center of the hydrophilic V═O core, encapsulated in F-rich hydrophobic pockets, reaches a coordination number of 6 by binding an additional H(2)O that, in turn, hydrogen-bonds with ketones, resulting in solvent-induced variable solid-state architectures. Fluoroalkyl (R(f)) ligand substituents hinder π-π stacking interactions and favor ordered long-range packing, as well as the facile formation of film materials that exhibit high thermal stability and oxidation resistance. Reversible redox chemistry and spectroscopic studies in both solution and the solid-state indicate single-site isolation in both phases and an R(f)-induced propensity for electron uptake and inhibition of electron loss. Repeated redox cycles reorganize the thin films to accommodate Li(+) ions and facilitate their migration. The facile reduction, combined with high stability and ease of sublimation imparted by the R(f) scaffold that suppresses oxidations, recommends the new materials for sensors, color displays, electronic materials, and redox catalysts, as well as other applications.     

Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?

Due to the large number of different docking programs and scoring functions available, researchers are faced with the problem of selecting the most suitable one when starting a structure-based drug discovery project. To guide the decision process, several studies comparing different docking and scoring approaches have been published. In the context of comparing scoring function performance, it is common practice to use a predefined, computer-generated set of ligand poses (decoys) and to reevaluate their score using the set of scoring functions to be compared. But are predefined decoy sets able to unambiguously evaluate and rank different scoring functions with respect to pose prediction performance? This question arose when the pose prediction performance of our piecewise linear potential derived scoring functions (Korb et al. in J Chem Inf Model 49:84–96, 2009) was assessed on a standard decoy set (Cheng et al. in J Chem Inf Model 49:1079–1093, 2009). While they showed excellent pose identification performance when they were used for rescoring of the predefined decoy conformations, a pronounced degradation in performance could be observed when they were directly applied in docking calculations using the same test set. This implies that on a discrete set of ligand poses only the rescoring performance can be evaluated. For comparing the pose prediction performance in a more rigorous manner, the search space of each scoring function has to be sampled extensively as done in the docking calculations performed here. We were able to identify relative strengths and weaknesses of three scoring functions (ChemPLP, GoldScore, and Astex Statistical Potential) by analyzing the performance for subsets of the complexes grouped by different properties of the active site. However, reasons for the overall poor performance of all three functions on this test set compared to other test sets of similar size could not be identified.     

A novel algorithm to model the influence of host lattice flexibility in molecular dynamics simulations: loading dependence of self-diffusion in carbon nanotubes

We describe a novel algorithm that includes the effect of host lattice flexibility into molecular dynamics simulations that use rigid lattices. It uses a Lowe-Andersen thermostat for interface-fluid collisions to take the most important aspects of flexibility into account. The same diffusivities and other properties of the flexible framework system are reproduced at a small fraction of the computational cost of an explicit simulation. We study the influence of flexibility on the self-diffusion of simple gases inside single walled carbon nanotubes. Results are shown for different guest molecules (methane, helium, and sulfur hexafluoride), temperatures, and types of carbon nanotubes. We show, surprisingly, that at low loadings flexibility is always relevant. Notably, it has a crucial influence on the diffusive dynamics of the guest molecules.     

T-shaped Ni0 Systems Featuring Cationic Tetrylenes: Direct Observation of L/Z-type Ligand Duality,and Alkene Hydrogenation Catalysis

We report a facile synthetic method for accessing rare T-shaped Ni⁰ species, stabilised by low-coordinate cationic germylene and stannylene ligands which behave as Z-type ligands toward Ni⁰. An in-depth computational analysis indicates significant Ni^d→E^p donation (E=Ge, Sn), with essentially no E→Ni donation. The tetrylene ligand's Lewis acidity can be modulated in situ through the addition of a donor ligand, which selectively binds at the Lewis acidic tetrylene site. This switches this binding centre from a Z-type to a classical L-type ligand, with a concomitant geometry switch at Ni⁰ from T-shaped to trigonal planar. Exploring the effects of this geometry switch in catalysis, isolated T-shaped complexes 3 a – c and 4 a – c are capable of the hydrogenation of alkenes under mild conditions, whilst the closely related trigonal planar and tetrahedral Ni⁰ complexes 5 , D , and E , which feature L-type chloro- or cationic-tetrylene ligands, are inactive under these conditions. Further, addition of small amounts of N-bases to the catalytic systems involving T-shaped complexes significantly reduces turnover rates, giving evidence for the in situ modulation of ligand electronics for catalytic switching.     

Dielectric and Electrooptic Investigations in the Nematic Phase of 5-n-Pentyl-2-[4-n-nonyloxyphenyl]-1,3-dioxane

The dielectric constant and the dielectric loss of 5-n-pentyl-2-[4-n-nonyloxyphenyl]-1,3-dioxane were investigated in the region of 0.1 to 10 MHz. An isotropy temperature was detected, at which the static dielectric anisotropy Δε₀₁ = 0. Using both the Freedericksz and the DAP effect, we measured the frequency dependence of the threshold voltage U₀ and compared the results with those of the dielectric measurements. In the case of DAP effect we could find two different types of dispersions curves of U₀.