916 resultados para ACS
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We report an optical sensor based on localized surface plasmon resonance (LSPR) to study small-molecule protein interaction combining high sensitivity refractive index sensing for quantitative binding information and subsequent conformation-sensitive plasmon-activated circular dichroism spectroscopy. The interaction of α-amylase and a small-size molecule (PGG, pentagalloyl glucose) was log concentration-dependent from 0.5 to 154 μM. In situ tests were additionally successfully applied to the analysis of real wine samples. These studies demonstrate that LSPR sensors to monitor small molecule–protein interactions in real time and in situ, which is a great advance within technological platforms for drug discovery.
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This work measures and tries to compare the Antioxidant Capacity (AC) of 50 commercial beverages of different kinds: 6 wines, 12 beers, 18 soft drinks and 14 flavoured waters. Because there is no reference procedure established for this purpose, three different optical methods were used to analyse these samples: Total Radical trapping Antioxidant Parameter (TRAP), Trolox Equivalent Antioxidant Capacity (TEAC) and Ferric ion Reducing Antioxidant Parameter (FRAP). These methods differ on the chemical background and nature of redox system. The TRAP method involves the transfer of hydrogen atoms while TEAC and FRAP involves electron transfer reactions. The AC was also assessed against three antioxidants of reference, Ascorbic acid (AA), Gallic acid (GA) and 6-hydroxy-2,5,7,8-tetramethyl- 2-carboxylic acid (Trolox). The results obtained were analyzed statistically. Anova one-way tests were applied to all results and suggested that methods and standards exhibited significant statistical differences. The possible effect of sample features in the AC, such as gas, flavours, food colouring, sweeteners, acidity regulators, preservatives, stabilizers, vitamins, juice percentage, alcohol percentage, antioxidants and the colour was also investigated. The AC levels seemed to change with brand, kind of antioxidants added, and kind of flavour, depending on the sample. In general, higher ACs were obtained for FRAP as method, and beer for kind of sample, and the standard expressing the smaller AC values was GA.
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Eight new peptides were isolated from the skin secretion of the frog Leptodactylus pustulatus and their amino acid sequences determined by de novo sequencing and by cDNA cloning. Structural similarities between them and other antimicrobial peptides from the skin secretion of Leptodactylus genus frogs were found. Ocellatins-PT1 to -PT5 (25 amino acid residues) are amidated at the C-terminus, while ocellatins-PT6 to -PT8 (32 amino acid residues) have free carboxylates. Antimicrobial activity, hemolytic tests, and cytotoxicity against a murine fibroblast cell line were investigated. All peptides, except for ocellatin-PT2, have antimicrobial activity against at least one Gram negative strain. Ocellatin-PT8 inhibited the growth of Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Salmonella choleraesuis strains with MICs in the 60−240 μM range. No significant effect was observed in human erythrocytes and in a murine fibroblast cell line after exposure to the peptides at MICs. A comparison between sequences obtained by both direct HPLC-MS de novo sequencing and cDNA cloning demonstrates the secretion of mature peptides derived from a pre-pro-peptide structure.
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Methanol decomposition is one of the key reactions in direct methanol fuel cell (DMFC) state-of-the-art technology, research, and development. However, its mechanism still presents many uncertainties, which, if answered, would permit us to refine the manufacture of DMFCs. The mechanism of methanol decomposition on ruthenium surfaces was investigated using density functional theory and a periodic supercell approach. The possible pathways, involving either initial C−H, C−O or O−H scission, were defined from experimental evidence regarding the methanol decomposition on ruthenium and other metallic surfaces. The study yielded the O−H scission pathway as having both the most favorable energetics and kinetics. The computational data, which present a remarkable closeness with the experimental results, also indicate methanol adsorption, the starting point in all possible pathways, to be of weak nature, implying a considerable rate of methanol desorption from the ruthenium, compromising the reaction.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Ligand K-edge XAS of an [Fe3S4]0 model complex is reported. The pre-edge can be resolved into contributions from the í2Ssulfide, í3Ssulfide, and Sthiolate ligands. The average ligand-metal bond covalencies obtained from these pre-edges are further distributed between Fe3+ and Fe2.5+ components using DFT calculations. The bridging ligand covalency in the [Fe2S2]+ subsite of the [Fe3S4]0 cluster is found to be significantly lower than its value in a reduced [Fe2S2] cluster (38% vs 61%, respectively). This lowered bridging ligand covalency reduces the superexchange coupling parameter J relative to its value in a reduced [Fe2S2]+ site (-146 cm-1 vs -360 cm-1, respectively). This decrease in J, along with estimates of the double exchange parameter B and vibronic coupling parameter ì2/k-, leads to an S ) 2 delocalized ground state in the [Fe3S4]0 cluster. The S K-edge XAS of the protein ferredoxin II (Fd II) from the D. gigas active site shows a decrease in covalency compared to the model complex, in the same oxidation state, which correlates with the number of H-bonding interactions to specific sulfur ligands present in the active site. The changes in ligand-metal bond covalencies upon redox compared with DFT calculations indicate that the redox reaction involves a two-electron change (one-electron ionization plus a spin change of a second electron) with significant electronic relaxation. The presence of the redox inactive Fe3+ center is found to decrease the barrier of the redox process in the [Fe3S4] cluster due to its strong antiferromagnetic coupling with the redox active Fe2S2 subsite.
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Inorganic Chemistry 50(21):10600-7
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Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605p
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J. Am. Chem. Soc., 2009, 131 (23), pp 7990–7998 DOI: 10.1021/ja809448r
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Biochemistry. 2009 Feb 10;48(5):873-82. doi: 10.1021/bi801773t.
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Biochemistry. 2008 Oct 14;47(41):10852-62. doi: 10.1021/bi801375q
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Inorg Chem. 2008 Jul 7;47(13):5677-84. doi: 10.1021/ic702405d
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Acc. Chem. Res., 2006, 39 (10), pp 788–796 DOI: 10.1021/ar050104k
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Biochemistry, 2004, 43 (46), pp 14566–14576 DOI: 10.1021/bi0485833
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Inorg. Chem., 2003, 42 (4), pp 938–940 DOI: 10.1021/ic0262886