Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Fragmentation drives tropical forest fragments to early successional states: A modelling study for Brazilian Atlantic forests

Land use leads to massive habitat destruction and fragmentation in tropical forests. Despite its global dimensions the effects of fragmentation on ecosystem dynamics are not well understood due to the complexity of the problem. We present a simulation analysis performed by the individual-based model FORMIND. The model was applied to the Brazilian Atlantic Forest, one of the world`s biodiversity hot spots, at the Plateau of Sao Paulo. This study investigates the long-term effects of fragmentation processes on structure and dynamics of different sized remnant tropical forest fragments (1-100 ha) at community and plant functional type (PFT) level. We disentangle the interplay of single effects of different key fragmentation processes (edge mortality, increased mortality of large trees, local seed loss and external seed rain) using simulation experiments in a full factorial design. Our analysis reveals that particularly small forest fragments below 25 ha suffer substantial structural changes, biomass and biodiversity loss in the long term. At community level biomass is reduced up to 60%. Two thirds of the mid- and late-successional species groups, especially shade-tolerant (late successional climax) species groups are prone of extinction in small fragments. The shade-tolerant species groups were most strongly affected; its tree number was reduced more than 60% mainly by increased edge mortality. This process proved to be the most powerful of those investigated, explaining alone more than 80% of the changes observed for this group. External seed rain was able to compensate approximately 30% of the observed fragmentation effects for shade-tolerant species. Our results suggest that tropical forest fragments will suffer strong structural changes in the long term, leading to tree species impoverishment. They may reach a new equilibrium with a substantially reduced subset of the initial species pool, and are driven towards an earlier successional state. The natural regeneration potential of a landscape scattered with forest fragments appears to be limited, as external seed rain is not able to fully compensate for the observed fragmentation-induced changes. Our findings suggest basic recommendations for the management of fragmented tropical forest landscapes. (C) 2011 Elsevier B.V. All rights reserved.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Hierarchical Assembly of CaMoO(4) Nano-Octahedrons and Their Photoluminescence Properties

Hierarchical assemblies of CaMoO4 (CM) nano-octahedrons were obtained by microwave-assisted hydrothemial synthesis at 120 degrees C for different times. These structures were structurally, morphologically and optically characterized by X-ray diffraction, micro-Raman spectroscopy, field-emission gun scanning electron microscopy, ultraviolet-visible absorption spectroscopy and photoluminescence measurements. First-principle calculations have been carried out to understand the structural and electronic order-disorder effects as a function of the particle/region size. Supercells of different dimensions were constructed to simulate the geometric distortions along both they and z planes of the scheelite structure. Based on these experimental results and with the help of detailed structural simulations, we were able to model the nature of the order-disorder in this important class of materials and discuss the consequent implications on its physical properties, in particular, the photoluminescence properties of CM nanocrystals.

MPO Inhibitors Selected by Virtual Screening

The hemeprotein myeloperoxidase (MPO) participates in innate immune defense through its ability to generate potent microbicidal oxidants. However, these oxidants are also key mediators of the tissue damage associated with many inflammatory diseases. Thus, there is considerable interest in developing therapeutically useful MPO inhibitors. Here, we used structure-based drug design (SBDD) and ligand-based drug design (LBDD) to select for potentially new and selective MPO inhibitors. A pharmacophore model was developed based on the crystal structure of human MPO in complex with salicylhydroxamic acid (SHA), a known inhibitor of the enzyme. The pharmacophore model was used to screen the ZINC database for potential ligands, which were further filtered on the basis of their physical-chemical properties and docking score. The filtered compounds were visually inspected, and nine were purchased for experimental studies. Surprisingly, almost all of the selected compounds belonged to the aromatic hydrazide class, which had been previously described as MPO inhibitors. The compounds selected by virtual screening were shown to inhibit the chlorinating activity of MPO; the top four compounds displayed IC(50) values ranging from 1.0 to 2.8 mM. MPO inactivation by the most effective compound was shown to be irreversible. Overall, our results show that SBDD and LBDD may be useful for the rational development of new MPO inhibitors.

Evaluation of intramolecular energy transfer process in the lanthanide(III) bis- and tris-(TTA) complexes: Photoluminescent and triboluminescent behavior

This work reports the energy transfer mechanism process of [Eu(TTA)(2)(NO(3))(TPPO)(2)] (bis-TTA complex) and [Eu(TTA)(3)(TPPO)(2)] (tris-TTA complex) based on experimental and theoretical spectroscopic properties, where TTA = 2-thienoyltrifluoroacetone and TPPO = triphenylphosphine oxide. These complexes were synthesized and characterized by elemental analyses, infrared spectroscopy and thermogavimetric analysis. The theoretical complexes geometry data by using Sparkle model for the calculation of lanthanide complexes (SMLC) is in agreement with the crystalline structure determined by single-crystal X-ray diffraction analysis. The emission spectra for [Gd(TTA)(3)(TPPO)(2)] and [Gd(TTA)(2) (NO(3))(TPPO)(2)] complexes are associated to T -> S(0) transitions centered on coordinated TTA ligands. Experimental luminescent properties of the bis-TTA complex have been quantified through emission intensity parameters Omega(lambda)(lambda = 2 and 4), spontaneous emission rates (A(rad)), luminescence lifetime (tau), emission quantum efficiency (eta) and emission quantum yield (q), which were compared with those for tris-TTA complex. The experimental data showed that the intensity parameter value for bis-TTA complex is twice smaller than the one for tris-TTA complex, indicating the less polarizable chemical environment in the system containing nitrate ion. A good agreement between the theoretical and experimental quantum yields for both Eu(Ill) complexes was obtained. The triboluminescence (TL) of the [Eu(TTA)(2)(NO(3))(TPPO)(2)] complexes are discussed in terms of ligand-to-metal energy transfer. (c) 2007 Elsevier B.V. All fights reserved.

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Tuberculosis (TB) is one of the most common infectious diseases known to man and responsible for millions of human deaths in the world. The increasing incidence of TB in developing countries, the proliferation of multidrug resistant strains, and the absence of resources for treatment have highlighted the need of developing new drugs against TB. The shikimate pathway leads to the biosynthesis of chorismate, a precursor of aromatic amino acids. This pathway is absent from mammals and shown to be essential for the survival of Mycobacterium tuberculosis, the causative agent of TB. Accordingly, enzymes of aromatic amino acid biosynthesis pathway represent promising targets for structure-based drug design. The first reaction in phenylalanine biosynthesis involves the conversion of chorismate to prephenate, catalyzed by chorismate mutase. The second reaction is catalyzed by prephenate dehydratase (PDT) and involves decarboxylation and dehydratation of prephenate to form phenylpyruvate, the precursor of phenylalanine. Here, we describe utilization of different techniques to infer the structure of M. tuberculosis PDT (MtbPDT) in solution. Small angle X-ray scattering and ultracentrifugation analysis showed that the protein oligomeric state is a tetramer and MtbPDT is a flat disk protein. Bioinformatics tools were used to infer the structure of MtbPDT A molecular model for MtbPDT is presented and molecular dynamics simulations indicate that MtbPDT i.s stable. Experimental and molecular modeling results were in agreement and provide evidence for a tetrameric state of MtbPDT in solution.

In silico screening of HIV-1 non-nucleoside reverse transcriptase and protease inhibitors

Two targets, reverse transcriptase (RT) and protease from HIV-1, were used during the past two decades to the discovery of non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) that belong to the arsenal of the antiretroviral therapy. Herein these enzymes were chosen as templates for conducting a computer-aided ligand design. Ligand and structure-based drug designs were the starting points to select compounds from a database bearing more than five million compounds by means of cheminformatic tools. New promising lead structures are retrieved from the database, which are open to acquisition and test. Classes of molecules already described as NNRTI or PI in the literature also came out and were useful to prove the reliability of the workflow, and thus validating the work carried out so far. (c) 2007 Elsevier Masson SAS. All rights reserved.

Classical and hologram QSAR studies on a series of inhibitors of trypanosomatid Glyceraldehyde-3-Phosphate Dehydrogenase

Leishmaniasis and trypanosomiasis are major causes of morbidity and mortality in both tropical and subtropical regions of the world. The current available drugs are limited, ineffective, and require long treatment regimens. Due to the high dependence of trypanosomatids on glycolysis as a source of energy, some glycolytic enzymes have been identified as attractive targets for drug design. In the present work, classical Two-Dimensional Quantitative Structure -Activity Relationships (2D QSAR) and Hologram QSAR (HQSAR) studies were performed on a series of adenosine derivatives as inhibitors of Leishmania mexicana Glyceraldehyde-3-Phosphate Dehydrogenase (LmGAPDH). Significant correlation coefficients (classical QSAR, r(2)=0.83 and q(2) =0.81; HQSAR, r(2)=0.91 and q(2) =0.86) were obtained for the 56 training set compounds, indicating the potential of the models for untested compounds. The models were then externally validated using a test set of 14 structurally related compounds and the predicted values were in good agreement with the experimental results (classical QSAR, r(pred)(2) = 0.94; HQSAR, r(pred)(2) = 0.92).

Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

Structural basis for selective inhibition of purine nucleoside phosphorylase from Schistosoma mansoni: Kinetic and structural studies

Selectivity plays a crucial role in the design of enzyme inhibitors as novel antiparasitic agents, particularly in cases where the target enzyme is also present in the human host. Purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive target for the discovery of potential antischistosomal agents. In the present work, kinetic studies were carried out in order to determine the inhibitory potency, mode of action and enzyme selectivity of a series of inhibitors of SmPNP. In addition, crystallographic studies provided important structural insights for rational inhibitor design, revealing consistent structural differences in the binding mode of the inhibitors in the active sites of the SmPNP and human PNP (HsPNP) structures. The molecular information gathered in this work should be useful for future medicinal chemistry efforts in the design of new inhibitors of SmPNP having increased affinity and selectivity. (C) 2010 Elsevier Ltd. All rights reserved.