953 resultados para MODEL COMPOUNDS


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We report on experimental studies of the Kondo physics and the development of non-Fermi-liquid scaling in UCu(4+x)Al(8-x) family. We studied 7 different compounds with compositions between x = 0 and 2. We measured electrical transport (down to 65 mK) and thermoelectric power (down to 1.8 K) as a function of temperature, hydrostatic pressure, and/or magnetic field. Compounds with Cu content below x = 1.25 exhibit long-range antiferromagnetic order at low temperatures. Magnetic order is suppressed with increasing Cu content and our data indicate a possible quantum critical point at x(cr) approximate to 1.15. For compounds with higher Cu content, non-Fermi-liquid behavior is observed. Non-Fermi-liquid scaling is inferred from electrical resistivity results for the x = 1.25 and 1.5 compounds. For compounds with even higher Cu content, a sharp kink occurs in the resistivity data at low temperatures, and this may be indicative of another quantum critical point that occurs at higher Cu compositions. For the magnetically ordered compounds, hydrostatic pressure is found to increase the Neel temperature, which can be understood in terms of the Kondo physics. For the non-magnetic compounds, application of a magnetic field promotes a tendency toward Fermi-liquid behavior. Thermoelectric power was analyzed using a two-band Lorentzian model, and the results indicate one fairly narrow band (10 meV and below) and a second broad band (around hundred meV). The results imply that there are two relevant energy scales that need to be considered for the physics in this family of compounds. (C) 2011 Elsevier B.V. All rights reserved.

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Two-photon absorption spectra of a triarylamine compounds dissolved in toluene were measured using the well-known Z-scan technique, employing 120-fs laser pulse-width. According to the results, an extra band located at around 900 nm was observed only for triarylamine with azoaromatic units. On the other hand, a shift in the two-photon absorption band for triarylamine, with and without azoaromatic units, is observed when different electron donor/acceptors groups are changed. The fitting of the spectra, using sum-over-states model, allowed us to obtain the spectroscopic parameters of each molecule, which appears to be in reasonable agreement with molecules presenting similar structural moieties. (C) 2010 Elsevier B.V. All rights reserved.

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Chagas disease, caused by the protozoan Trypanosoma cruzi, is one of the most serious amongst the so-called neglected diseases in Latin America, specially in Brazil. So far there has been no effective treatment for the chronic phase of this disease. Cruzain is a major cysteine protease of T cruzi and it is recognized as a valid target for Chagas disease chemotherapy. The mechanism of cruzain action is associated with the nucleophilic attack of an activated sulfur atom towards electrophilic groups. In this report, features of a putative pharmacophore model of the enzyme, developed as a virtual screening tool for the selection of potential cruzain inhibitors, are described. The final proposed model was applied to the ZINC v.7 database and afterwards experimentally validated by an enzymatic inhibition assay. One of the compounds selected by the model showed cruzain inhibition in the low micromolar range.

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The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.

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A spectroscopic study was performed showing that the [Fe(III)(L(2-))(2)](1-) (L(2-) = dopacatecholate) complex reacts with Ni(II), Co(II) and Zn(II) in an aqueous solution containing S(2)O(3)(2-) resulting in the soluble [M(L(1-))(3)](1-) (L(1-) = dopasemiquinone; M = Ni(II), Co(II) or Zn(II) complex species. The Raman and IR spectra of the [CTA][M(L(1-))(3)] complexes, CTA hexadecyltrimethylammonium cation, in the solid state were obtained. The kinetic constants for the metal substitution reactions were determined at four different temperatures, providing values for Delta W(not equal) Delta S(not equal) and Delta G(not equal). The reactions were slow (k = 10(-1)1 M s(-1)) and endothermic. The system investigated can be considered as a simplified model to explain some aspects of siderophore chemistry. (c) 2007 Elsevier Inc. All rights reserved.

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There is a need of scientific evidence of claimed nutraceutical effects, but also there is a social movement towards the use of natural products and among them algae are seen as rich resources. Within this scenario, the development of methodology for rapid and reliable assessment of markers of efficiency and security of these extracts is necessary. The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. Cystoseira is a brown alga containing fucoxanthin and other carothenes whose pressure-assisted extracts were assayed to discover a possible beneficial effect on complications related to diabetes evolution in an acute but short-term model. Urine was selected as the sample and CE-TOF-MS as the analytical technique to obtain the fingerprints in a non-target metabolomic approach. Multivariate data analysis revealed a good clustering of the groups and permitted the putative assignment of compounds statistically significant in the classification. Interestingly a group of compounds associated to lysine glycation and cleavage from proteins was found to be increased in diabetic animals receiving vehicle as compared to control animals receiving vehicle (N6, N6, N6-trimethyl-L-lysine, N-methylnicotinamide, galactosylhydroxylysine, L-carnitine, N6-acetyl-N6-hydroxylysine, fructose-lysine, pipecolic acid, urocanic acid, amino-isobutanoate, formylisoglutamine. Fructoselysine significantly decreased after the treatment changing from a 24% increase to a 19% decrease. CE-MS fingerprinting of urine has provided a group of compounds different to those detected with other techniques and therefore proves the necessity of a cross-platform analysis to obtain a broad view of biological samples.

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This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

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Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Ethnopharmacological Relevance: Mouriri pusa Gardn. (Melastomataceae) is a medicinal plant commonly used by people living in the Cerrado to treat gastrointestinal disturbances. This medicinal plant has shown intense gastroprotective action in rodent gastric lesion, but still there are no data about its healing effect on gastric mucosa.Aim of the Study: To evaluate the methanolic extract (MeOH) obtained from Mouriri pusa leaves for its effect on the cicatrisation process of gastric ulcer.Mterials and Methods: The healing effects on gastric ulcers inducted by subserosal injection of acetic acid were evaluated by macroscopic and microscopic measures, imunohistochemistry and cell counting in rats treated with MeOH extract of Mouriri pusa (250 mg/kg, p.o./daily) for 14 or 30 days. The toxicity of Mouriri pusa was also evaluated by body and organ weight measure and clinical biochemical parameters.Results: Mouriri pusa treatments lasting 14 and 30 days showed elevated mucus secretion (PAS) and thicker regenerative gastric mucosa, denoting increased cell proliferation, which was confirmed by PCNA immunohistochemical analysis. Moreover, there was important cell recruitment (neutrophils and mast cells) to the site of the ulcer, which is an important factor in ulcer healing. No toxic effect was observed in all parameters evaluated. Phenolic compounds present in the MeOH extract like tannins, flavonoids and epicatechin are the probable agents involved in the healing effects of this medicinal plant.Conclusions: These findings showed a potential effect of Mouriri pusa in increasing regeneration of damaged gastric mucosa with safety for human use. (C) 2007 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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A study using two classification methods (SDA and SIMCA) was carried out in this work with the aim of investigating the relationship between the structure of flavonoid compounds and their free-radical-scavenging ability. In this work, we report the use of chemometric methods (SDA and SIMCA) able to select the most relevant variables (steric, electronic, and topological) responsible for this ability. The results obtained with the SDA and SIMCA methods agree perfectly with our previous model, in which we used other chemometric methods (PCA, HCA and KNN) and are also corroborated with experimental results from the literature. This is a strong indication of how reliable the selection of variables is.