40 resultados para photochemical reaction mechanisms


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The study of the effect of radiation on living tissues is a rather complex task to address mainly because they are made of a set of complex functional biological structures and interfaces. Particularly if one is looking for where damage is taking place in a first stage and what are the underlying reaction mechanisms. In this work a new approach is addressed to study the effect of radiation by making use of well identified molecular hetero-structures samples which mimic the biological environment. These were obtained by assembling onto a solid support deoxyribonucleic acid (DNA) and phospholipids together with a soft water-containing polyelectrolyte precursor in layered structures and by producing lipid layers at liquid/air interface with DNA as subphase. The effects of both ultraviolet (UV) radiation and carbon ions beams were systematically investigated in these heterostructures, namely damage on DNA by means vacuum ultraviolet (VUV), infrared (IR), X-Ray Photoelectron (XPS) and impedance spectroscopy. Experimental results revealed that UV affects furanose, PO2-, thymines, cytosines and adenines groups. The XPS spectrometry carried out on the samples allowed validate the VUV and IR results and to conclude that ionized phosphate groups, surrounded by the sodium counterions, congregate hydration water molecules which play a role of UV protection. The ac electrical conductivity measurements revealed that the DNA electrical conduction is arising from DNA chain electron hopping between base-pairs and phosphate groups, with the hopping distance equal to the distance between DNA base-pairs and is strongly dependent on UV radiation exposure, due loss of phosphate groups. Characterization of DNA samples exposed to a 4 keV C3+ ions beam revealed also carbon-oxygen bonds break, phosphate groups damage and formation of new species. Results from radiation induced damage carried out on biomimetic heterostructures having different compositions revealed that damage is dependent on sample composition, with respect to functional targeted groups and extent of damage. Conversely, LbL films of 1,2-dipalmitoyl-sn-Glycero-3-[Phospho-rac-(1-glycerol)] (Sodium Salt) (DPPG) liposomes, alternated with poly(allylamine hydrochloride) (PAH) revealed to be unaffected, even by prolonged UV irradiation exposure, in the absence of water molecules. However, DPPG molecules were damaged by the UV radiation in presence of water with cleavage of C-O, C=O and –PO2- bonds. Finally, the study of DNA interaction with the ionic lipids at liquid/air interfaces revealed that electrical charge of the lipid influences the interaction of phospholipid with DNA. In the presence of DNA in the subphase, the effects from UV irrladiation were seen to be smaller, which means that ionic products from biomolecules degradation stabilize the intact DPPG molecules. This mechanism may explain why UV irradiation does not cause immediate cell collapse, thus providing time for the cellular machinery to repair elements damaged by UV.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

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New emerging contaminants could represent a danger to the environment and Humanity with repercussions not yet known. One of the major worldwide pharmaceutical and personal care productions are antimicrobials products, triclosan, is an antimicrobial agent present in most products. Despite the high removal rate of triclosan present in wastewater treatments, triclosan levels are on the rise in the environment through disposal of wastewater effluent and use of sewage sludge in land application. Regulated in the EC/1272/2008 (annex VI, table 3.1), this compound is considered very toxic to aquatic life and it has been reported that photochemical transformation of triclosan produces dioxins. In the current work it was defined three objectives; determination of the most efficient process in triclosan degradation, recurring to photochemical degradation methods comparing different sources of light; identification of the main by-products formed during the degradation and the study of the influence of the Fenton and photo-Fenton reaction. Photochemical degradation methods such as: photocatalysis under florescent light (UV), photocatalysis under visible light (sunlight), photocatalysis under LEDs, photo-Fenton and Fenton reaction have been compared in this work. The degradation of triclosan was visualized through gas chromatography/mass spectrometry (GC/MS). In this study photo-Fenton reaction has successfully oxidized triclosan to H2O and CO2 without any by-products within 2 hours. Photocatalysis by titanium dioxide (TiO2) under LEDs was possible, having a degradation rate of 53% in an 8 hours essay. The degradation rate of the Fenton reaction, UV light and sunlight showed degradation between 90% and 95%. The results are reported to the data observed without statistic support, since this was not possible during the work period. Hydroquinone specie and 2,4-dichlorophenol by-products were identified in the first hour of photocatalysis by UV. A common compound, possibly identified has C7O4H , was present at the degradation by UV, sunlight and LEDs and was concluded to be a contaminant. In the future more studies in the use of LEDs should be undertaken given the advantages of long durability and low consumption of energy of these lamps and that due to their negative impact on the environment fluorescent lamps are being progressively made unavailable by governments, requiring new solutions to be found. Fenton and photo-Fenton reactions can also be costly processes given the expensive reagents used.

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Aziridines, a class of organic compounds containing a three membered heterocycle with a nitrogen atom, are extremely valuable molecules in organic and medicinal chemistry. They are frequently used as versatile precursors in the synthesis of natural products, and many biologically active molecules possess the aziridine moiety. The reactivity of aziridines has been studied, for example, in ring-opening reactions with thiols. However, not much interest seems to be given to reactions of aziridines in aqueous media, despite the numberless advantages of using water as solvent in organic chemistry. The nucleophilic ring-opening reaction of aziridines in aqueous media was here explored. Following the Kaplan aziridine synthetic methodology, in which pyridinium salts undergo a photochemical transformation to give bicyclic vinyl aziridines, new aziridines were synthetized. Their nucleophilic ring-opening reaction in water under physiological conditions was investigated and a range of sulphur, nitrogen, carbon and oxygen nucleophiles tested. Thiols, anilines and azide proved to be good nucleophiles to react with the aziridines, giving the ring-opening product in moderate to good yields. The best results were obtained with thiols, more specifically with cysteine-derived nucleophiles. Preliminary results show that these bicyclic vinyl aziridines can modify calcitonin, a peptide containing two cysteine amino acids residues, grating them the potential to be used in bioconjugation as ligands to cysteine-containing proteins, or even as enzyme inhibitors of, for example, cysteine proteases. Additionally, exploratory investigations suggest that the separation of both enantiomers of the bicyclic vinyl aziridine can be performed by taking advantage of an enzymatic methodology for the resolution of racemic secondary alcohols. Both enantiomers would be highly valuable as precursors in the synthesis of enantiomerically pure molecules, as no other method is currently reported for their separation.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Dissertação apresentada para a obtenção do Grau de Doutor em Química, especialidade em Química-Física, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertação de Mestrado em Engenharia Informática

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Abstract The emergence of multi and extensively drug resistant tuberculosis (MDRTB and XDRTB) has increased the concern of public health authorities around the world. The World Health Organization has defined MDRTB as tuberculosis (TB) caused by organisms resistant to at least isoniazid and rifampicin, the main first-line drugs used in TB therapy, whereas XDRTB refers to TB resistant not only to isoniazid and rifampicin, but also to a fluoroquinolone and to at least one of the three injectable second-line drugs, kanamycin, amikacin and capreomycin. Resistance in Mycobacterium tuberculosis is mainly due to the occurrence of spontaneous mutations and followed by selection of mutants by subsequent treatment. However, some resistant clinical isolates do not present mutations in any genes associated with resistance to a given antibiotic, which suggests that other mechanism(s) are involved in the development of drug resistance, namely the presence of efflux pump systems that extrude the drug to the exterior of the cell, preventing access to its target. Increased efflux activity can occur in response to prolonged exposure to subinhibitory concentrations of anti-TB drugs, a situation that may result from inadequate TB therapy. The inhibition of efflux activity with a non-antibiotic inhibitor may restore activity of an antibiotic subject to efflux and thus provide a way to enhance the activity of current anti-TB drugs. The work described in this thesis foccus on the study of efflux mechanisms in the development of multidrug resistance in M. tuberculosis and how phenotypic resistance, mediated by efflux pumps, correlates with genetic resistance. In order to accomplish this goal, several experimental protocols were developed using biological models such as Escherichia coli, the fast growing mycobacteria Mycobacterium smegmatis, and Mycobacterium avium, before their application to M. tuberculosis. This approach allowed the study of the mechanisms that result in the physiological adaptation of E. coli to subinhibitory concentrations of tetracycline (Chapter II), the development of a fluorometric method that allows the detection and quantification of efflux of ethidium bromide (Chapter III), the characterization of the ethidium bromide transport in M. smegmatis (Chapter IV) and the contribution of efflux activity to macrolide resistance in Mycobacterium avium complex (Chapter V). Finally, the methods developed allowed the study of the role of efflux pumps in M. tuberculosis strains induced to isoniazid resistance (Chapter VI). By this manner, in Chapter II it was possible to observe that the physiological adaptation of E. coli to tetracycline results from an interplay between events at the genetic level and protein folding that decrease permeability of the cell envelope and increase efflux pump activity. Furthermore, Chapter III describes the development of a semi-automated fluorometric method that allowed the correlation of this efflux activity with the transport kinetics of ethidium bromide (a known efflux pump substrate) in E. coli and the identification of efflux inhibitors. Concerning M. smegmatis, we have compared the wild-type M. smegmatis mc2155 with knockout mutants for LfrA and MspA for their ability to transport ethidium bromide. The results presented in Chapter IV showed that MspA, the major porin in M. smegmatis, plays an important role in the entrance of ethidium bromide and antibiotics into the cell and that efflux via the LfrA pump is involved in low-level resistance to these compounds in M. smegmatis. Chapter V describes the study of the contribution of efflux pumps to macrolide resistance in clinical M. avium complex isolates. It was demonstrated that resistance to clarithromycin was significantly reduced in the presence of efflux inhibitors such as thioridazine, chlorpromazine and verapamil. These same inhibitors decreased efflux of ethidium bromide and increased the retention of [14C]-erythromycin in these isolates. Finaly, the methods developed with the experimental models mentioned above allowed the study of the role of efflux pumps on M. tuberculosis strains induced to isoniazid resistance. This is described in Chapter VI of this Thesis, where it is demonstrated that induced resistance to isoniazid does not involve mutations in any of the genes known to be associated with isoniazid resistance, but an efflux system that is sensitive to efflux inhibitors. These inhibitors decreased the efflux of ethidium bromide and also reduced the minimum inhibitory concentration of isoniazid in these strains. Moreover, expression analysis showed overexpression of genes that code for efflux pumps in the induced strains relatively to the non-induced parental strains. In conclusion, the work described in this thesis demonstrates that efflux pumps play an important role in the development of drug resistance, namely in mycobacteria. A strategy to overcome efflux-mediated resistance may consist on the use of compounds that inhibit efflux activity, restoring the activity of antimicrobials that are efflux pump substrates, a useful approach particularly in TB where the most effective treatment regimens are becoming uneffective due to the increase of MDRTB/XDRTB.

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Dissertation presented to obtain a Ph.D degree in Engineering and Technology Sciences, Gene Therapy at the Instituto de Tecnologia Quimica e Biológica, Universidade Nova de Lisboa

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Dissertação apresentada para obtenção do grau de Doutor em Bioquímica - especialidade Biotecnologia, pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia

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Dissertation presented to obtain the Ph.D degree in Neuroscience Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

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Dissertation presented to obtain a Doctoral degree in Biology, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa.

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Dissertation submitted to obtain the phD degree in Biochemistry, specialty in Physical- Biochemistry, by the Faculdade de Ciências e Tecnologia from the Universidade Nova de Lisboa

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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

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Dissertação para obtenção do Grau de Doutor em Biologia