Investigation of the relationship between the structure and function of Ts2, a neurotoxin from Tityus serrulatus venom

Scorpion toxins targeting voltage-gated sodium (NaV) channels are peptides that comprise 6076 amino acid residues cross-linked by four disulfide bridges. These toxins can be divided in two groups (a and beta toxins), according to their binding properties and mode of action. The scorpion a-toxin Ts2, previously described as a beta-toxin, was purified from the venom of Tityus serrulatus, the most dangerous Brazilian scorpion. In this study, seven mammalian NaV channel isoforms (rNaV1.2, rNaV1.3, rNaV1.4, hNaV1.5, mNaV1.6, rNaV1.7 and rNaV1.8) and one insect NaV channel isoform (DmNaV1) were used to investigate the subtype specificity and selectivity of Ts2. The electrophysiology assays showed that Ts2 inhibits rapid inactivation of NaV1.2, NaV1.3, NaV1.5, NaV1.6 and NaV1.7, but does not affect NaV1.4, NaV1.8 or DmNaV1. Interestingly, Ts2 significantly shifts the voltage dependence of activation of NaV1.3 channels. The 3D structure of this toxin was modeled based on the high sequence identity (72%) shared with Ts1, another T. serrulatus toxin. The overall fold of the Ts2 model consists of three beta-strands and one a-helix, and is arranged in a triangular shape forming a cysteine-stabilized a-helix/beta-sheet (CSa beta) motif.

Chromatin Structure of Ribosomal RNA Genes in Dipterans and Its Relationship to the Location of Nucleolar Organizers

Nucleoli, nuclear organelles in which ribosomal RNA is synthesized and processed, emerge from nucleolar organizers (NORs) located in distinct chromosomal regions. In polytene nuclei of dipterans, nucleoli of some species can be observed under light microscopy exhibiting distinctive morphology: Drosophila and chironomid species display well-formed nucleoli in contrast to the fragmented and dispersed nucleoli seen in sciarid flies. The available data show no apparent relationship between nucleolar morphology and location of NORs in Diptera. The regulation of rRNA transcription involves controlling both the transcription rate per gene as well as the proportion of rRNA genes adopting a proper chromatin structure for transcription, since active and inactive rRNA gene copies coexist in NORs. Transcription units organized in nucleosomes and those lacking canonical nucleosomes can be analyzed by the method termed psoralen gel retarding assay (PGRA), allowing inferences on the ratio of active to inactive rRNA gene copies. In this work, possible connections between chromosomal location of NORs and proportion of active rRNA genes were studied in Drosophila melanogaster, and in chironomid and sciarid species. The data suggested a link between location of NORs and proportion of active rRNA genes since the copy number showing nucleosomal organization predominates when NORs are located in the pericentric heterochromatin. The results presented in this work are in agreement with previous data on the chromatin structure of rRNA genes from distantly related eukaryotes, as assessed by the PGRA.

Relationship between Crystal Shape, Photoluminescence, and Local Structure in SrTiO3 Synthesized by Microwave-Assisted Hydrothermal Method

This paper describes the effect of using different titanium precursors on the synthesis and physical properties of SrTiO3 powders obtained by microwave-assisted hydrothermal method. X-ray diffraction measurements, X-ray absorption near-edge structure (XANES) spectroscopy, field emission scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscopy (HRTEM) were carried out to investigate the structural and optical properties of the SrTiO3 spherical and cubelike-shaped particles. The appropriate choice of the titanium precursor allowed the control of morphological and photoluminescence (PL) properties of SrTiO3 compound. The PL emission was more intense in SrTiO3 samples composed of spherelike particles. This behavior was attributed to the existence of a lower amount of defects due to the uniformity of the spherical particles.

N-4-Phenyl-substituted 2-acetylpyridine thiosemicarbazones: Cytotoxicity against human tumor cells, structure-activity relationship studies and investigation on the mechanism of action

N-4-Phenyl 2-acetylpyridine thiosemicarbazone (H2Ac4Ph; N-(phenyl)-2-(1-(pyridin-2-yl)ethylidene) hydrazinecarbothioamide) and its N-4-ortho-, -meta- and -para-fluorophenyl (H2Ac4oFPh, H2Ac4mFPh, H2Ac4pFPh), N-4-ortho-, -meta- and -para-chlorophenyl (H2Ac4oClPh, H2Ac4mClPh, H2Ac4pClPh), N-4-ortho-, -meta- and -para-iodophenyl (H2Ac4oIPh, H2Ac4mIPh, H2Ac4pIPh) and N-4-ortho-, -meta- and -para-nitrophenyl (H2Ac4oNO(2)Ph, H2Ac4mNO(2)Ph, H2Ac4pNO(2)Ph) derivatives were assayed for their cytotoxicity against human malignant breast (MCF-7) and glioma (T98G and U87) cells. The compounds were highly cytotoxic against the three cell lineages (IC50: MCF-7, 52-0.16 nM; T98G, 140-1.0 nM; U87, 160-1.4 nM). All tested thiosemicarbazones were more cytotoxic than etoposide and did not present any haemolytic activity at up to 10(-5) M. The compounds were able to induce programmed cell death. H2Ac4pClPh partially inhibited tubulin assembly at high concentrations and induced cellular microtubule disorganization. (C) 2012 Elsevier Ltd. All rights reserved.

Variations in Structure Explain the Viscometric Behavior of AOT Microemulsions at Low Water/AOT Molar Ratios

The viscosity of AOT/water/decane water-in-oil microemulsions exhibits a well-known maximum as a function of water/AOT molar ratio, which is usually attributed to increased attractions among nearly spherical droplets. The maximum can be removed by adding salt or by changing the oil to CCl4. Systematic small-angle X-ray scattering (SAXS) measurements have been used to monitor the structure of the microemulsion droplets in the composition regime where the maximum appears. On increasing the droplet concentration, the scattering intensity is found to scale with the inverse of the wavevector, a behavior which is consistent with cylindrical structures. The inverse wavevector scaling is not observed when the molar ratio is changed, moving the system away from the value corresponding to the viscosity maximum. It is also not present in the scattering from systems containing enough added salt to essentially eliminate the viscosity maximum. An asymptotic analysis of the SAXS data, complemented by some quantitative modeling, is consistent with cylindrical growth of droplets as their concentration is increased. Such elongated structures are familiar from related AOT systems in which the sodium counterion has been exchanged for a divalent one. However, the results of this study suggest that the formation of non-spherical aggregates at low molar ratios is an intrinsic property of AOT.

Lamivudine salts with improved solubilities

To optimize solubility of drugs, current strategies mainly focus on engineering and screening of smart crystal phases. Two salts of the anti-human immunodeficiency virus (HIV) drug lamivudinenamely, lamivudine hydrochloride and lamivudine hydrochloride monohydrate, were prepared in the course of screening the crystallization conditions of lamivudine duplex, an uncommon DNA-mimic, double-stranded helical structure made up of partially protonated drug pairs. Here, water solubilities of lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex are reported. The aqueous solubility of this anti-HIV drug was significantly increased in both salts and also in lamivudine duplex in relation to the water solubility of lamivudine form II. In comparison with the lamivudine form II incorporated into therapeutic formulations, the drug solubility was increased at a temperature of 299 +/- 2 K by factors of 1.2, 3.3, and 4.5 in lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex, respectively, demonstrating that this solid-state property of lamivudine can be improved by crystal engineering strategies. Solubility profiles were understood on the basis of structural and solventsolute interaction approaches. At last, correlations between solubility and crystal structures allowed for a rational approach to understand how this physicochemical feature could be enhanced by engineering new salts of the drug. (C) 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:21432154, 2012

Relationship between B-Cell-specific moloney murine leukemia virus integration site 1 (BMI-1) and homologous recombination regulatory genes in invasive ductal breast carcinomas

B-cell-specific Moloney murine leukemia virus integration site 1 (Bmi-1) is a Polycomb group protein that is able to induce telomerase activity, enabling the immortalization of epithelial cells. Immortalized cells are more susceptible to double-strand breaks (DSB), which are subsequently repaired by homologous recombination (HR). BRCA1 is among the HR regulatory genes involved in the response to DNA damage associated with the RAD51 protein, which accumulates in DNA damage foci after signaling H2AX, another important marker of DNA damage. Topoisomerase III beta (topoIII beta) removes HR intermediates before chromosomal segregation, preventing damage to cellular DNA structure. In breast carcinomas positive for BMI-1 the role of proteins involved in HR remains to be investigated. The aim of this study was to evaluate the association between BMI-1 and homologous recombination proteins. Using tissue microarrays containing 239 cases of primary breast tumors, the expression of Bmi-1, BRCA-1, H2AX, Rad51, p53, Ki-67, topoIII beta, estrogen receptors (ER), progesterone receptors (PR), and HER-2 was analyzed by immunohistochemistry. We observed high Bmi-1 expression in 66 cases (27.6%). Immunohistochemical overexpression of BMI-1 was related to ER (p=0.004), PR (p<0.001), Ki-67 (p<0.001), p53 (p=0.003), BRCA1 (p=0.003), H2AX (p=0.024) and topoIII beta (p<0,001). Our results show a relationship between the expression of BMI-1 and HR regulatory genes, suggesting that Bmi-1 overexpression might be an important event in HR regulation. However, further studies are necessary to understand the mechanisms in which Bmi-1 could regulate HR pathways in invasive ductal breast carcinomas.

Spatio-temporal patterns of tuberculosis incidence in Ribeirao Preto, State of Sao Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

Introduction: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirao Preto, State of Sao Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. Methods: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. Results: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirao Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. Conclusions: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

Unveiling the relationship between complex networks metrics and word senses

The automatic disambiguation of word senses (i.e., the identification of which of the meanings is used in a given context for a word that has multiple meanings) is essential for such applications as machine translation and information retrieval, and represents a key step for developing the so-called Semantic Web. Humans disambiguate words in a straightforward fashion, but this does not apply to computers. In this paper we address the problem of Word Sense Disambiguation (WSD) by treating texts as complex networks, and show that word senses can be distinguished upon characterizing the local structure around ambiguous words. Our goal was not to obtain the best possible disambiguation system, but we nevertheless found that in half of the cases our approach outperforms traditional shallow methods. We show that the hierarchical connectivity and clustering of words are usually the most relevant features for WSD. The results reported here shed light on the relationship between semantic and structural parameters of complex networks. They also indicate that when combined with traditional techniques the complex network approach may be useful to enhance the discrimination of senses in large texts. Copyright (C) EPLA, 2012

Quantum Mechanics Insight into the Microwave Nucleation of SrTiO3 Nanospheres

An extensive investigation of strontium titanate, SrTiO3 (STO), nanospheres synthesized via a microwave-assisted hydrothermal (MAH) method has been conducted to gain a better insight into thermodynamic, kinetic, and reaction phenomena involved in STO nucleation and crystal growth processes. To this end, quantum chemical modeling based on the density functional theory and periodic super cell models were done. Several experimental techniques were employed to get a deep characterization of structural and optical features of STO nanospheres. A possible formation mechanism was proposed, based on dehydration of titanium and strontium clusters followed by mesoscale transformation and a self-assembly process along an oriented attachment mechanism resulting in spherical like shape. Raman and XANES analysis renders a noncentrosymmetric environment for the octahedral titanium, while infrared and first order Raman modes reveal OH groups which are unsystematically incorporated into uncoordinated superficial sites. These results seem to indicate that the key component is the presence of distorted TiO6 clusters to engender a luminescence property. Analysis of band structure, density Of states, and charge map shows that there is a close relationship among local broken symmetry, polarization, and energy split of the 3d orbitals of titanium. The interplay among these electronic and structural features provides necessary conditions to evaluate its luminescent properties under two energy excitation.

STRUCTURE AND DYNAMICS: THE TRANSITION FROM NONEQUILIBRIUM TO EQUILIBRIUM IN INTEGRATE-AND-FIRE DYNAMICS

The transient and equilibrium properties of dynamics unfolding in complex systems can depend critically on specific topological features of the underlying interconnections. In this work, we investigate such a relationship with respect to the integrate-and-fire dynamics emanating from a source node and an extended network model that allows control of the small-world feature as well as the length of the long-range connections. A systematic approach to investigate the local and global correlations between structural and dynamical features of the networks was adopted that involved extensive simulations (one and a half million cases) so as to obtain two-dimensional correlation maps. Smooth, but diverse surfaces of correlation values were obtained in all cases. Regarding the global cases, it has been verified that the onset avalanche time (but not its intensity) can be accurately predicted from the structural features within specific regions of the map (i.e. networks with specific structural properties). The analysis at local level revealed that the dynamical features before the avalanches can also be accurately predicted from structural features. This is not possible for the dynamical features after the avalanches take place. This is so because the overall topology of the network predominates over the local topology around the source at the stationary state.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.