Observation of Optical Second Harmonic Generation in Wet-Spun Films of Na-DNA

The observation of optical second harmonic generation (SHG) from wetspun films of Na-DNA is reported. The SHG signal is stronger at a relative humidity of 92% (corresponding to the B conformation of Na-DNA) than at low humidity of -33% (corresponding to a disordered conformation of Na-DNA). The strength of the SHG signal is also dependent on the orientation of the incident laser beam polarization with respect to the DNA helical axes.     

The EPR spectrum of O on magnesium oxide

The EPR spectrum of O⁻ on MgO has been observed following the reaction of N₂O with electrons trapped at the surface. The spectrum of the ion in axial symmetry is characterized by g_⊥ = 2.041 and g_∥ = 2.0016. Upon exposure to H₂, CO, CO₂ or additional N₂O the spectrum is replaced by another having g₁ = 2.0172, g₂ = 2.0100 and g₃ = 2.0014. This spectrum is tentatively assigned to the O₃⁻ ion.     

Template-directed intramolecular C-glycosidation. cation-mediated synthesis of ketooxetanes from thioglycosides

Bicyclic ketooxetanes may be assembled using cation-mediated cyclisation reactions of thioglycosides possessing silyl enol ether-containing side-chains.     

Ferrous Iron Binding Key to Mms6 Magnetite Biomineralisation: A Mechanistic Study to Understand Magnetite Formation Using pH Titration and NMR Spectroscopy

Formation of magnetite nanocrystals by magnetotactic bacteria is controlled by specific proteins which regulate the particles’ nucleation and growth. One such protein is Mms6. This small, amphiphilic protein can self‐assemble and bind ferric ions to aid in magnetite formation. To understand the role of Mms6 during in vitro iron oxide precipitation we have performed in situ pH titrations. We find Mms6 has little effect during ferric salt precipitation, but exerts greatest influence during the incorporation of ferrous ions and conversion of this salt to mixed‐valence iron minerals, suggesting Mms6 has a hitherto unrecorded ferrous iron interacting property which promotes the formation of magnetite in ferrous‐rich solutions. We show ferrous binding to the DEEVE motif within the C‐terminal region of Mms6 by NMR spectroscopy, and model these binding events using molecular simulations. We conclude that Mms6 functions as a magnetite nucleating protein under conditions where ferrous ions predominate.     

Investigation of Lewis Acid versus Lewis Base Catalysis in Asymmetric Cyanohydrin Synthesis

The asymmetric addition of trimethylsilyl cyanide to aldehydes can be catalysed by Lewis acids and/or Lewis bases, which activate the aldehyde and trimethylsilyl cyanide, respectively. It is not always apparent from the structure of the catalyst whether Lewis acid or Lewis base catalysis predominates. To investigate this in the context of using salen complexes of titanium, vanadium and aluminium as catalysts, a Hammett analysis of asymmetric cyanohydrin synthesis was undertaken. When Lewis acid catalysis is dominant, a significantly positive reaction constant is observed, whereas reactions dominated by Lewis base catalysis give much smaller reaction constants. [{Ti(salen)O}₂] was found to show the highest degree of Lewis acid catalysis, whereas two [VO(salen)X] (X=EtOSO₃ or NCS) complexes both displayed lower degrees of Lewis acid catalysis. In the case of reactions catalysed by [{Al(salen)}₂O] and triphenylphosphine oxide, a non‐linear Hammett plot was observed, which is indicative of a change in mechanism with increasing Lewis base catalysis as the carbonyl compound becomes more electron‐deficient. These results suggested that the aluminium complex/triphenylphosphine oxide catalyst system should also catalyse the asymmetric addition of trimethylsilyl cyanide to ketones and this was found to be the case.     

An X-ray scattering study of hydrogenated nanocrystalline silicon with varying crystalline fraction

Using X-ray diffraction (XRD) and small angle X-ray scattering (SAXS), we probed the nanostructural features of several PECVD grown nc-Si:H thin films with varying crystalline volume fraction. XRD results of a mixed phase film, 70% a-Si:H and 30% c-Si:H, show these crystallites have a preferred [220] orientation in the growth direction. Another film with approximately 90% c-Si also shows elongated grains, but with a preferred [111] orientation. The SAXS results also show an increase in scattering intensity when compared to the mixed phase material. In the mixed phase material, models show that the electron density fluctuations between the amorphous and crystalline phases are not enough to explain the measured SAXS scattering. Hydrogen clustered at the crystallite boundaries and in void regions of the a-Si phase must be included as well.     

Stereoselective Synthesis and X-Ray Structure Determination of Labeled [1, 2, 3-<Superscript>13</Superscript>C<Subscript>3</Subscript>]-1-(Phenylsulfinyl)-3-Benzyloxyacetone

[1,2,3-¹³C₃]-1-(Phenylsulfinyl)-3-benzyloxyacetone, C₁₆H₁₆O₃S, (3) has been synthesized and its crystal structure has been determined by a single-crystal X-ray diffraction analysis. The X-ray diffraction study revealed that compound 3 crystallizes in the monoclinic crystal system in the acentric space group Pc, with cell constants at T = 100 K: a = 16.073(5), b = 5.5079(16), c = 7.949(2) Å, β = 100.221(4)^°, V = 692.6(3) ų, Z = 2, d _calc = 1.383 g/cm³. Compound 3 contains the chiral tetravalent three-coordinated sulfur atom, which has a distorted tetrahedral configuration with a lone electron pair occupying one of the tetrahedron vertices. In the crystal, the molecules are packed in stacks along the b axis; the stacks consist of the molecules of the same chirality. Furthermore, the stacks of the molecules of the opposite chirality alternate along the c axis. The molecules in neighboring stacks are arranged by head-to-tail orientations. There are no short intermolecular contacts in the crystal of 3.     

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure-activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein-ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.