Binding of topotecan to a nicked DNA oligomer in solution

Topotecan (TPT) is in clinical use as an antitumor agent. It acts by binding to the covalent complex formed between nicked DNA and topoisomerase I, and inserts itself into the single-strand nick, thereby inhibiting the religation of the nick and acting as a poison. A crystal structure analysis of the ternary complex has shown how the drug binds (B. L. Staker, K. Hjerrild, M. D. Feese, C. A. Behnke, A. B. Burgin, L. Stewart, Proc. Natl. Acad. Sci. U.S.A., 2002, 99, 15 387-15 392), but has left a number of unanswered questions. Herein, we use NMR spectroscopy and molecular modeling to show that the solution structure of a complex of TPT with nicked natural DNA is similar, but not identical to the crystal conformation, and that other geometries are of very low population. We also show that the lactone form of TPT binds approximately 40 times more strongly than the ring-opened carboxylate.     

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.     

A systematic study of carboxylic acids in negative ion mode electrospray ionisation mass spectrometry providing a structural model for ion suppression

We report a systematic investigation of the effects and structural requirements for ion suppression in negative ion mode electrospray ionisation mass spectrometry of a series of carboxylic acids and present a structural model rationalising ion suppression effects.     

Conducting polymer diffraction gratings on gold surfaces created by microcontact printing and electropolymerization at submicron length scales

Conducting polymer diffraction gratings on Au substrates have been created using microcontact printing of C18-alkanethiols, followed by electropolymerization of either poly(aniline) (PANI) or poly(3,4-ethylenedioxythiophene) (PEDOT). Soft-polymer replicas of simple diffraction grating masters (1200 lines/mm) were used to define the alkanethiol template for polymer growth. Growth of PANI and PEDOT diffraction gratings was followed in real time, through in situ tapping-mode atomic force microscopy, and by monitoring diffraction efficiency (DE) as a function of grating depth. DE increased as grating depth increased, up to a limiting efficiency (13-26%, with white light illumination), defined by the combined optical properties of the grating and the Au substrate, and ultimately limited by the loss of resolution due to coalescence of the polymer films. Grating efficiency is strongly dependent upon the grating depth and the refractive index contrast between the grating material and the surrounding solutions. Both PEDOT and PANI gratings show refractive index changes as a function of applied potential, consistent with changes in refractive index brought about by the doping/dedoping of the conducting polymer. The DE of PANI gratings are strongly dependent on the pH of the superstrate solution; the maximum sensitivity (DeltaDE/DeltapH) is achieved with PANI gratings held at +0.4 V versus Ag/AgCl, where the redox chemistry is dominated by the acid-base equilibrium between the protonated (emeraldine salt) and deprotonated (emeraldine base) forms of PANI. Simulations of DE were conducted for various combinations of conducting polymer refractive index and grating depth, to compute sensitivity parameters, which are maximized when the grating depth is ca. 50% of its maximum obtainable depth.     

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.     

New RNA labeling methods offer dramatic sensitivity enhancements in 2H NMR relaxation spectra

A new labeling strategy is presented that greatly facilitates the measurement of 2H spin relaxation rates in RNA molecules as a probe of pico- to nanosecond time scale dynamics. In this labeling scheme the sugar positions are uniformly 13C-labeled, with position 2' protonated and all other sites on the sugar deuterated. Pulse sequences are presented for measurement of 2H R1 and R2 relaxation rates at positions 1', 3', and 4' with sensitivity gains that are on the order of 5-fold relative to previous methods that employed random fractional deuteration. The improved sensitivity is transformative and facilitates the study of motion in moderately sized RNA molecules with good sensitivity. The utility of the approach is demonstrated with an application to HIV-2 TAR, where the site-specific measures of molecular dynamics at sugar positions obtained here complement previous studies of dynamics at aromatic sites in the molecule.     

Measurement of long-range 1H-19F scalar coupling constants and their glycosidic torsion dependence in 5-fluoropyrimidine-substituted RNA

Long-range scalar 5J(H1',F) couplings were observed in 5-fluoropyrimidine-substituted RNA. We developed a novel S3E-19F-alpha,beta-edited NOESY experiment for quantitation of these long-range scalar 5J(H1',F) couplings, where the J-couplings can be extracted from inspection of intraresidual (H1',H6) NOE cross-peaks. Quantum chemical calculations were exploited to investigate the relation between scalar couplings and conformations around the glycosidic bond in oligonucleotides. The theoretical dependence of the observed 5J(H1',F) couplings on the torsion angle chi can be described by a generalized Karplus relationship. The corresponding density functional theory (DFT) analysis is outlined. Additional NMR experiments facilitating the resonance assignments of 5-fluoropyrimidine-substituted RNAs are described, and chemical shift changes due to altered shielding in the presence of fluorine-19 (19F) are presented.     

Optimization of HNO production from N,O-bis-acylated hydroxylamine derivatives

A wide range of N,O-bis-acylated hydroxylamine derivatives with chloro or arenesulfonyl leaving groups, and a related set of N-hydroxy-N-acylsulfonamides, have been synthesized and evaluated for nitroxyl (HNO) production. Mechanistic studies have revealed that the observed aqueous chemistry is more complicated than originally anticipated, and have been used to develop a new series of efficient HNO precursors (4u-4x, 7c-7d) with tunable half-lives.     

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.