Crystal structure and statistical coupling analysis of highly glycosylated peroxidase from royal palm tree (Roystonea regia)

Royal palm tree peroxidase (RPTP) is a very stable enzyme in regards to acidity, temperature, H(2)O(2), and organic solvents. Thus, RPTP is a promising candidate for developing H(2)O(2)-sensitive biosensors for diverse applications in industry and analytical chemistry. RPTP belongs to the family of class III secretory plant peroxidases, which include horseradish peroxidase isozyme C, soybean and peanut peroxidases. Here we report the X-ray structure of native RPTP isolated from royal palm tree (Roystonea regia) refined to a resolution of 1.85 angstrom. RPTP has the same overall folding pattern of the plant peroxidase superfamily, and it contains one heme group and two calcium-binding sites in similar locations. The three-dimensional structure of RPTP was solved for a hydroperoxide complex state, and it revealed a bound 2-(N-morpholino) ethanesulfonic acid molecule (MES) positioned at a putative substrate-binding secondary site. Nine N-glycosylation sites are clearly defined in the RPTP electron-density maps, revealing for the first time conformations of the glycan chains of this highly glycosylated enzyme. Furthermore, statistical coupling analysis (SCA) of the plant peroxidase superfamily was performed. This sequence-based method identified a set of evolutionarily conserved sites that mapped to regions surrounding the heme prosthetic group. The SCA matrix also predicted a set of energetically coupled residues that are involved in the maintenance of the structural folding of plant peroxidases. The combination of crystallographic data and SCA analysis provides information about the key structural elements that could contribute to explaining the unique stability of RPTP. (C) 2009 Elsevier Inc. All rights reserved.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009

Lie algebra methods for the applications to the statistical theory of turbulence

Approximate Lie symmetries of the Navier-Stokes equations are used for the applications to scaling phenomenon arising in turbulence. In particular, we show that the Lie symmetries of the Euler equations are inherited by the Navier-Stokes equations in the form of approximate symmetries that allows to involve the Reynolds number dependence into scaling laws. Moreover, the optimal systems of all finite-dimensional Lie subalgebras of the approximate symmetry transformations of the Navier-Stokes are constructed. We show how the scaling groups obtained can be used to introduce the Reynolds number dependence into scaling laws explicitly for stationary parallel turbulent shear flows. This is demonstrated in the framework of a new approach to derive scaling laws based on symmetry analysis [11]-[13].

A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets

We propose a likelihood ratio test ( LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrapbased approach. LRT is shown to be significantly faster and statistically powerful even within non- Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.

cis-4-decenoic acid provokes mitochondrial bioenergetic dysfunction in rat brain

Aims: In the present work we investigated the in vitro effect of cis-4-decenoic acid, the pathognomonic metabolite of medium-chain acyl-CoA dehydrogenase deficiency, on various parameters of bioenergetic homeostasis in rat brain mitochondria. Main methods: Respiratory parameters determined by oxygen consumption were evaluated, as well as membrane potential, NAD(P)H content, swelling and cytochrome c release in mitochondrial preparations from rat brain, using glutamate plus malate or succinate as substrates. The activities of citric acid cycle enzymes were also assessed. Key findings: cis-4-decenoic acid markedly increased state 4 respiration, whereas state 3 respiration and the respiratory control ratio were decreased. The ADP/O ratio, the mitochondrial membrane potential, the matrix NAD(P)H levels and aconitase activity were also diminished by cis-4-decenoic acid. These data indicate that this fatty acid acts as an uncoupler of oxidative phosphorylation and as a metabolic inhibitor. cis-4-decenoic acid also provoked a marked mitochondrial swelling when either KCl or sucrose was used in the incubation medium and also induced cytochrome c release from mitochondria, suggesting a non-selective permeabilization of the inner mitochondria! membrane. Significance: It is therefore presumed that impairment of mitochondrial homeostasis provoked by cis-4-decenoic acid may be involved in the brain dysfunction observed in medium-chain acyl-CoA dehydrogenase deficient patients. (C) 2010 Elsevier Inc. All rights reserved.