Synthesis of hydroperoxide and perketal derivatives of polyunsaturated fatty acids as potential antimalarial agents

Hydroperoxide derivatives of beta-oxa-substituted polyunsaturated fatty acids were prepared by 15-lipoxygenase catalysed oxidation and perketal derivatives of fatty acid hydroperoxides were synthesized. The perketals are more stable than their parent fatty acid hydroperoxides, but less active as antimalarial agents in the in vitro growth inhibition of Plasmodium falciparum. (C) 1998 Elsevier Science Ltd. All rights reserved.

Enzyme reactions as index of freshness of Fish and Shellfish

An attempt has been made in this study to screen some fish muscle enzymes to assess their potential worth in testing the degree of freshness of fish. A problem with routine enzyme activity determinations is the complexity of the method of enzyme assay. Hence, in the present study as far as possible simple assay techniques were adopted. Several species were screened to assess the possibility of employing this procedure on a large scale. It is hoped that findings of this study will lead to the development of meaningful criteria in testing the freshness of fish. This thesis has been divided into five chapters

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

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.

Modeling Calcium Concentration and Biochemical Reactions

Almost all regions of the brain receive one or more neuromodulatory inputs, and disrupting these inputs produces deficits in neuronal function. Neuromodulators act through intracellular second messenger pathways to influence the electrical properties of neurons, integration of synaptic inputs, spatio-temporal firing dynamics of neuronal networks, and, ultimately, systems behavior. Second messengers pathways consist of series of bimolecular reactions, enzymatic reactions, and diffusion. Calcium is the second messenger molecule with the most effectors, and thus is highly regulated by buffers, pumps and intracellular stores. Computational modeling provides an innovative, yet practical method to evaluate the spatial extent, time course and interaction among second messenger pathways, and the interaction of second messengers with neuron electrical properties. These processes occur both in compartments where the number of molecules are large enough to describe reactions deterministically (e.g. cell body), and in compartments where the number of molecules is small enough that reactions occur stochastically (e.g. spines). – In this tutorial, I explain how to develop models of second messenger pathways and calcium dynamics. The first part of the tutorial explains the equations used to model bimolecular reactions, enzyme reactions, calcium release channels, calcium pumps and diffusion. The second part explains some of the GENESIS, Kinetikit and Chemesis objects that implement the appropriate equations. In depth explanation of calcium and second messenger models is provided by reviewing code, both in XPP, Chemesis and Kinetikit, that implements simple models of calcium dynamics and second messenger cascades.

Lysine biosynthesis and nitrogen metabolism in quinoa (Chenopodium quinoa): Study of enzymes and nitrogen-containing compounds

Aspartate kinase (AK, EC 2.7.2.4), homoserine dehydrogenase (HSDH, EC 1.1.1.3) and dihydrodipicolinate synthase (DHDPS, EC 4.2.1.52) were isolated and partially purified from immature Chenopodium quinoa Willd seeds. Enzyme activities were studied in the presence of the aspartate-derived amino acids lysine, threonine and methionine and also the lysine analogue S-2-aminoethyl-L-cysteine (AEC), at 1 mM and 5 mM. The results confirmed the existence of, at least, two AK isoenzymes, one inhibited by lysine and the other inhibited by threonine, the latter being predominant in quinoa seeds. HSDH activity was also shown to be partially inhibited by threonine, whereas some of the activity was resistant to the inhibitory effect, indicating the presence of two isoenzymes, one resistant and another sensitive to threonine inhibition. Only one DHDPS isoenzyme highly sensitive to lysine inhibition was detected. The results suggest that the high concentration of lysine observed in quinoa seeds is possibly due to a combined effect of increased lysine, synthesis and accumulation in the soluble form and/or as protein lysine. Nitrogen assimilation was also investigated and based on nitrate content, nitrate reductase activity, amino acid distribution and ureide content, the leaves were identified as the predominant site of nitrate reduction in this plant species. The amino acid profile analysis in leaves and roots also indicated an important role of soluble glutamine as a nitrogen transporting compound. (c) 2007 Elsevier Masson SAS. All rights reserved.

Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus

Much progress has been made on inferring population history from molecular data. However, complex demographic scenarios have been considered rarely or have proved intractable. The serial introduction of the South-Central American cane Load Bufo marinas in various Caribbean and Pacific islands involves four major phases: a possible genetic admixture during the first introduction, a bottleneck associated with founding, a transitory, population boom, and finally, a demographic stabilization. A large amount of historical and demographic information is available for those introductions and can be combined profitably with molecular data. We used a Bayesian approach to combine this information With microsatellite (10 loci) and enzyme (22 loci) data and used a rejection algorithm to simultaneously estimate the demographic parameters describing the four major phases of the introduction history,. The general historical trends supported by microsatellites and enzymes were similar. However, there was a stronger support for a larger bottleneck at introductions for microsatellites than enzymes and for a more balanced genetic admixture for enzymes than for microsatellites. Verb, little information was obtained from either marker about the transitory population boom observed after each introduction. Possible explanations for differences in resolution of demographic events and discrepancies between results obtained with microsatellites and enzymes were explored. Limits Of Our model and method for the analysis of nonequilibrium populations were discussed.

Combined bioremediation and enzyme production by Aspergillus sp. in olive mill and winery wastewaters

Olive mill wastewaters (OMW) and vinasses (VS) are effluents produced respectively by olive mills and wineries, both sectors are of great economic importance in Mediterranean countries. These effluents cause a large environmental impact, when not properly processed, due to their high concentration of phenolic compounds, COD and colour. OMW may be treated by biological processes but, in this case, a dilution is necessary, increasing water consumption. The approach here in proposed consists on the bioremediation of OMW and VS by filamentous fungi. In a screening stage, three fungi (Aspergillus ibericus, Aspergillus uvarum, Aspergillus niger) were selected to bioremediate undiluted OMW, two-fold diluted OMW supplemented with nutrients, and a mixture of OMW and VS in the proportion 1:1 (v/v). Higher reductions of phenolic compounds, colour and COD were achieved mixing both residues; with A. uvarum providing the best results. In addition, the production of enzymes was also evaluated during this bioremediation process, detecting in all cases lipolytic, proteolytic and tannase activities. A. ibericus, A. uvarum and A. niger achieved the highest value of lipase (1253.7 ± 161.2 U/L), protease (3700 ± 124.3 U/L) and tannase (284.4 ± 12.1 U/L) activities, respectively. Consequently, this process is an interesting alternative to traditional processes to manage these residues, providing simultaneously high economic products, which can be employed in the same industries.

Single molecule simulation of diffusion and enzyme kinetics

This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place. Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.

Changes in activity of the regulatory glycolytic enzymes and of the pyruvate-dehydrogenase complex during the development of Xenopus laevis.

In this study we investigated the variations of the maximal activities of the rate-controlling glycolytic enzymes (i.e., hexokinase, HK; phosphofructokinase, PFK; pyruvate kinase, PK) and of the pyruvate-dehydrogenase complex (PDHc) during the early embryogenesis of Xenopus laevis (from cleavage through hatching). All the enzymatic assays, using different coupled reactions, were performed spectrophotometrically on cytosolic and mitochondrial fractions. The maximal HK activity increases markedly from neurulation onwards, PFK activity presents a peak around gastrulation, PK activity remains relatively constant throughout the period studied and the highest PDHc activity is observed during cleavage. The specific activities display the same temporal pattern. Furthermore, in the sequence of reactions by which glucose is degraded to form acetyl-CoA, the maximal activities of PFK and PK are not limiting while those of HK and PDHc could be rate-limiting at relatively late developmental stages (hatching).

Response of hexokinase enzymes and the insulin system to dietary carbohydrates in the common carp, Cyprinus carpio.

The response of the common carp to diets with varying amounts of digestible starch, provided either as pea meal (LP, HP, 30 and 46% peas, respectively) or as cereal (LW, HW, 30 and 46% wheat, respectively), was studied and compared with the response to a carbohydrate-free protein-rich diet (CF). Here we focused on the utilisation of dietary carbohydrates by examining the relationship between dietary starch intake, hepatic hexokinase activities, circulating insulin and muscle insulin receptor system. Plasma glucose concentration and hepatic high Km hexokinase (glucokinase, GK) activity were not affected by the content of digestible starch, but 6 h after feeding enzyme activity was higher in the fish fed carbohydrate diets. Similarly, low Km hexokinase (HK) activity was also higher in the fish 24 h after feeding. Fat gain and protein retention were significantly improved by increased digestible starch intake, especially in the HP group, which in turn, presented the highest plasma insulin levels. Glycogen stores were moderately increased by the ingestion of digestible starch. The number of insulin receptors was greater in the CF group than in fish on carbohydrates, except the HP group. Our results confirmed that the common carp uses dietary carbohydrates efficiently, especially when there are provided by peas. This efficiency might be related to the enhanced response of postprandial insulin observed in the HP group.

Produção de lipases de Aspergillus niger e Aspergillus fumigatus através de fermentação em estado sólido, avaliação da especificidade do substrato e seu uso em reações de esterificação e alcoólise: evaluation of substrate specificity and use in esterification and alcoholysis reactions

Filamentous fungi were cultured under solid state fermentation of soybean residues to produce lipases. Enzymes produced by Aspergillus niger esterified oleic and butyric acids in the presence of ethanol, while enzymes produced by Aspergillus fumigatus demonstrated no esterification activity toward lauric acid. In case of A. niger, direct lyophilization of fermented bran led to higher esterification activity. The esterification of oleic acid by enzymes of A. fumigatus was neither influenced by pH adjustment nor by the extraction process. Conversions to ethyl esters were higher after pH adjustment with lyophilized liquid extract of A. niger.

Maternal protein restriction affects gene expression and enzyme activity of intestinal disaccharidases in adult rat offspring

This study investigated the consequences of intrauterine protein restriction on the gastrointestinal tract and particularly on the gene expression and activity of intestinal disaccharidases in the adult offspring. Wistar rat dams were fed isocaloric diets containing 6% protein (restricted, n = 8) or 17% protein (control, n = 8) throughout gestation. Male offspring (n = 5-8 in each group) were evaluated at 3 or 16 weeks of age. Maternal protein restriction during pregnancy produced offspring with growth restriction from birth (5.7 ± 0.1 vs 6.3 ± 0.1 g; mean ± SE) to weaning (42.4 ± 1.3 vs 49.1 ± 1.6 g), although at 16 weeks of age their body weight was similar to control (421.7 ± 8.9 and 428.5 ± 8.5 g). Maternal protein restriction also increased lactase activity in the proximal (0.23 ± 0.02vs 0.15 ± 0.02), medial (0.30 ± 0.06vs 0.14 ± 0.01) and distal (0.43 ± 0.07vs 0.07 ± 0.02 U·g-1·min-1) small intestine, and mRNA lactase abundance in the proximal intestine (7.96 ± 1.11vs 2.38 ± 0.47 relative units) of 3-week-old offspring rats. In addition, maternal protein restriction increased sucrase activity (1.20 ± 0.02 vs 0.91 ± 0.02 U·g-1·min-1) and sucrase mRNA abundance (4.48 ± 0.51 vs 1.95 ± 0.17 relative units) in the duodenum of 16-week-old rats. In conclusion, the present study shows for the first time that intrauterine protein restriction affects gene expression of intestinal enzymes in offspring.

Cell wall degrading enzymes and interaction between Trichoderma Aggressivum and Agaricus Bisporus

Agaricus bisporus is the most commonly cultivated mushroom in North America and has a great economic value. Green mould is a serious disease of A. bisporus and causes major reductions in mushroom crop production. The causative agent of green mould disease in North America was identified as Trichoderma aggressivum f. aggressivum. Variations in the disease resistance have been shown in the different commercial mushroom strains. The purpose of this study is to continue investigations of the interactions between T. aggressivum and A. bisporus during the development of green mould disease. The main focus of the research was to study the roles of cell wall degrading enzymes in green mould disease resistance and pathogenesis. First, we tried to isolate and sequence the N-acetylglucosaminidase from A. bisporus to understand the defensive mechanism of mushroom against the disease. However, the lack of genomic and proteomic information of A. bisporus limited our efforts. Next, T. aggressivum cell wall degrading enzymes that are thought to attack Agaricus and mediate the disease development were examined. The three cell wall degrading enzymes genes, encoding endochitinase (ech42), glucanase (fJ-1,3 glucanase) and protease (prb 1), were isolated and sequenced from T. aggressivum f. aggressivum. The sequence data showed significant homology with the corresponding genes from other fungi including Trichoderma species. The transcription levels of the three T. aggressivum cell wall degrading enzymes were studied during the in vitro co-cultivation with A. bisporus using R T -qPCR. The transcription levels of the three genes were significantly upregulated compared to the solitary culture levels but were upregulated to a lesser extent in co-cultivation with a resistant strain of A. bisporus than with a sensitive strain. An Agrobacterium tumefaciens transformation system was developed for T. aggressivum and was used to transform three silencing plasmids to construct three new T. aggressivum phenotypes, each with a silenced cell wall degrading enzyme. The silencing efficiency was determined by RT-qPCR during the individual in vitro cocultivation of each of the new phenotypes with A. bisporus. The results showed that the expression of the three enzymes was significantly decreased during the in vitro cocultivation when compared with the wild type. The phenotypes were co-cultivated with A. bisporus on compost with monitoring the green mould disease progression. The data indicated that prbi and ech42 genes is more important in disease progression than the p- 1,3 glucanase gene. Finally, the present study emphasises the role of the three cell wall degrading enzymes in green mould disease infection and may provide a promising tool for disease management.