One-component plasma on a spherical annulus and a random matrix ensemble

The two-dimensional one-component plasma at the special coupling \beta = 2 is known to be exactly solvable, for its free energy and all of its correlations, on a variety of surfaces and with various boundary conditions. Here we study this system confined to a spherical annulus with soft wall boundary conditions, paying special attention to the resulting asymptotic forms from the viewpoint of expected general properties of the two-dimensional plasma. Our study is motivated by the realization of the Boltzmann factor for the plasma system with \beta = 2, after stereographic projection from the sphere to the complex plane, by a certain random matrix ensemble constructed out of complex Gaussian and Haar distributed unitary matrices.Comment: v2, typos and references corrected, 24 pages, 1 figur

Analyzing multitarget activity landscapes using protein-ligand interaction fingerprints: interaction cliffs.

This is the original submitted version, before peer review. The final peer-reviewed version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/ci500721x.Activity landscape modeling is mostly a descriptive technique that allows rationalizing continuous and discontinuous SARs. Nevertheless, the interpretation of some landscape features, especially of activity cliffs, is not straightforward. As the nature of activity cliffs depends on the ligand and the target, information regarding both should be included in the analysis. A specific way to include this information is using protein-ligand interaction fingerprints (IFPs). In this paper we report the activity landscape modeling of 507 ligand-kinase complexes (from the KLIFS database) including IFP, which facilitates the analysis and interpretation of activity cliffs. Here we introduce the structure-activity-interaction similarity (SAIS) maps that incorporate information on ligand-target contact similarity. We also introduce the concept of interaction cliffs defined as ligand-target complexes with high structural and interaction similarity but have a large potency difference of the ligands. Moreover, the information retrieved regarding the specific interaction allowed the identification of activity cliff hot spots, which help to rationalize activity cliffs from the target point of view. In general, the information provided by IFPs provides a structure-based understanding of some activity landscape features. This paper shows examples of analyses that can be carried out when IFPs are added to the activity landscape model.M-L is very grateful to CONACyT (No. 217442/312933) and the Cambridge Overseas Trust for funding. AB thanks Unilever for funding and the European Research Council for a Starting Grant (ERC-2013- StG-336159 MIXTURE). J.L.M-F. is grateful to the School of Chemistry, Department of Pharmacy of the National Autonomous University of Mexico (UNAM) for support. This work was supported by a scholarship from the Secretariat of Public Education and the Mexican government

A theoretical entropy score as a single value to express inhibitor selectivity

<p>Abstract</p> <p>Background</p> <p>Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.</p> <p>Results</p> <p>Here we propose a new theoretical entropy score that can be calculated from a set of IC₅₀data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC₅₀data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like.</p> <p>Conclusions</p> <p>For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.</p

Cobalamin in inflammation III — glutathionylcobalamin and methylcobalamin/adenosylcobalamin coenzymes: the sword in the stone? How cobalamin may directly regulate the nitric oxide synthases

Several mysteries surround the structure and function of the nitric oxide synthases (NOS). The NOS oxygenase domain structure is unusually open with a large area of solvent that could accommodate an unidentified ligand. The exact mechanism of the two-step five-electron monoxygenation of arginine to NG-hydroxy-L-arginine, thence to citrulline and nitric oxide (NO), is not clear, particularly as arginine/NG-hydroxy-L-arginine is bound at a great distance to the supposed catalytic heme Fe [III], as the anti-stereoisomer. The Return of the Scarlet Pimpernel Paper proposed that cobalamin is a primary indirect regulator of the NOS. An additional direct regulatory effect of the ‘base-off’ dimethylbenzimidazole of glutathionylcobalamin (GSCbl), which may act as a sixth ligand to the heme iron, promote Co-oriented, BH4/BH3 radical catalysed oxidation of L-arginine to NO, and possibly regulate the rate of inducible NOS/NO production by the NOS dimers, is further advanced. The absence of homology between the NOS and methionine synthase/methylmalonyl CoA mutase may enable GSCbl to regulate both sets of enzymes simultaneously by completely separate mechanisms. Thus, cobalamin may exert central control over both pro-and anti-inflammatory systems

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Trauma, dream, and psychic change in psychoanalyses : a dialog between psychoanalysis and the neurosciences

To many psychoanalysts dreams are a central source of knowledge of the unconscious-the specific research object of psychoanalysis. The dialog with the neurosciences, devoted to the testing of hypotheses on human behavior and neurophysiology with objective methods, has added to psychoanalytic conceptualizations on emotion, memory, sleep and dreams, conflict and trauma. To psychoanalysts as well as neuroscientists, the neurological basis of psychic functioning, particularly concerning trauma, is of special interest. In this article, an attempt is made to bridge the gap between psychoanalytic findings and neuroscientific findings on trauma. We then attempt to merge both approaches in one experimental study devoted to the investigation of the neurophysiological changes (fMRI) associated with psychoanalytic treatment in chronically depressed patients. We also report on an attempt to quantify psychoanalysis-induced transformation in the manifest content of dreams. To do so, we used two independent methods. First, dreams reported during the cure of chronic depressed analysands were assessed by the treating psychoanalyst. Second, dreams reported in an experimental context were analyzed by an independent evaluator using a standardized method to quantify changes in dream content (Moser method). Single cases are presented. Preliminary results suggest that psychoanalysis-induced transformation can be assessed in an objective way

Quantification of Fat Infiltration in Thigh and Calf Muscles in Oculopharyngeal Muscular Dystrophy: Comparison of Three MRI Methods

The development of non-invasive measures of the degree and progression of muscle involvement is essential for clinical trials in oculopharyngeal muscular dystrophy (OPMD) patients. In this study, three quantitative MRI measures of muscular fat infiltration are compared with regard to applicability for longitudinal studies. A very high linear correlation is observed between fat infiltration according to the 2-point Dixon method and quantitative T2 values (R2 = 0.95). Fat infiltration according to SSFP histogram analysis exhibit a lower linear correlation with T2 values (R2 = 0.88). Dixon or T2 mapping techniques may be promising quantitative tools to study the pattern and involvement of fat infiltration longitudinally