On the electronic nature of low-barrier hydrogen bonds in enzymatic reactions

The electronic nature of low-barrier hydrogen bonds (LBHBs) in enzymatic reactions is discussed based on combined low temperature neutron and x-ray diffraction experiments and on high level ab initio calculations by using the model substrate benzoylacetone. This molecule has a LBHB, as the intramolecular hydrogen bond is described by a double-well potential with a small barrier for hydrogen transfer. From an “atoms in molecules” analysis of the electron density, it is found that the hydrogen atom is stabilized by covalent bonds to both oxygens. Large atomic partial charges on the hydrogen-bonded atoms are found experimentally and theoretically. Therefore, the hydrogen bond gains stabilization from both covalency and from the normal electrostatic interactions found for long, weak hydrogen bonds. Based on comparisons with other systems having short-strong hydrogen bonds or LBHBs, it is proposed that all short-strong and LBHB systems possess similar electronic features of the hydrogen-bonded region, namely polar covalent bonds between the hydrogen atom and both heteroatoms in question.

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.

In vivo enzymatic activity of acetylCoA synthetase in skeletal muscle revealed by 13C turnover from hyperpolarized [1-13C]acetate to [1-13C]acetylcarnitine

BACKGROUND: Acetate metabolism in skeletal muscle is regulated by acetylCoA synthetase (ACS). The main function of ACS is to provide cells with acetylCoA, a key molecule for numerous metabolic pathways including fatty acid and cholesterol synthesis and the Krebs cycle. METHODS: Hyperpolarized [1-(13)C]acetate prepared via dissolution dynamic nuclear polarization was injected intravenously at different concentrations into rats. The (13)C magnetic resonance signals of [1-(13)C]acetate and [1-(13)C]acetylcarnitine were recorded in vivo for 1min. The kinetic rate constants related to the transformation of acetate into acetylcarnitine were deduced from the 3s time resolution measurements using two approaches, either mathematical modeling or relative metabolite ratios. RESULTS: Although separated by two biochemical transformations, a kinetic analysis of the (13)C label flow from [1-(13)C]acetate to [1-(13)C]acetylcarnitine led to a unique determination of the activity of ACS. The in vivo Michaelis constants for ACS were KM=0.35±0.13mM and Vmax=0.199±0.031μmol/g/min. CONCLUSIONS: The conversion rates from hyperpolarized acetate into acetylcarnitine were quantified in vivo and, although separated by two enzymatic reactions, these rates uniquely defined the activity of ACS. The conversion rates associated with ACS were obtained using two analytical approaches, both methods yielding similar results. GENERAL SIGNIFICANCE: This study demonstrates the feasibility of directly measuring ACS activity in vivo and, since the activity of ACS can be affected by various pathological states such as cancer or diabetes, the proposed method could be used to non-invasively probe metabolic signatures of ACS in diseased tissue.

Involvement of free radicals in peroxidatic reactions catalyzed by chloroperoxidase

The mechanism of chloroperoxidase (CPO)-catalyzed peroxidatic reactions of several substituted hydroquinones was studied at various hydrogen peroxide concentrations. The pathway was studied using cytochrome c as the radical trapping agent. As the hydroquinones became more hindered there was a difference in the amount of radicals trapped. For hydroquinone, 59.3% radical pathway, and methylhydroquinone, 81.4% radical, the difference in radicals trapped is due to a difference in pathway. For 2,3-dimethylhydroquinone (75.4%), trimethylhydroquinone (44.5%), and t-butylhydroquinone (0%) other non-peroxidatic reactions are noticed. Thus, for the more substituted hydroquinones the difference in radicals trapped can not be assigned to a difference in radical pathway. Also, there were problems drawing conclusions for this system due to the catalytic reaction of hydrogen peroxide. The radical trapping ability of 2,4,6-trimethylphenol was investigated for various other substrates. TMP reacted with the radicals generated in the enzymatic reactions of phenol, resorcinol, and m-methoxyphenol. Thus, this TMP system offers further potential as another radical trapping agent for use in these studies.

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.

MONITORING ENZYME REACTIONS BY FAST ATOM BOMBARDMENT MASS SPECTROMETRY

The potential for the direct analysis of enzyme reactions by fast atom bombardment (FAB) mass spectrometry has been investigated. Conditions are presented for the maintenance of enzymatic activity under FAB conditions along with FAB mass spectrometric data showing that these conditions can be applied to solutions of enzyme and substrate to follow enzymatic reactions inside the mass spectrometer in real-time. In addition, enzyme kinetic behavior under FAB mass spectrometric conditions is characterized using trypsin and its assay substrate, TAME, as an enzyme-substrate reaction model. These results show that two monitoring methods can be utilized to follow reactions by FAB mass spectrometry. The advantages of each method are discussed and illustrated by obtaining kinetic parameters from the direct analysis of enzyme reactions with assay or peptide substrates. ^

The hard-soft acid-base principle in enzymatic catalysis: dual reactivity of phosphoenolpyruvate.

In this paper, the chemical reactivity of C3 of phosphoenolpyruvate (PEP) has been analyzed in terms of density functional theory quantified through quantum chemistry calculations. PEP is involved in a number of important enzymatic reactions, in which its C3 atom behaves like a base. In three different enzymatic reactions analyzed here, C3 sometimes behaves like a soft base and sometimes behaves like a hard base in terms of the hard-soft acid-base principle. This dual nature of C3 of PEP was found to be related to the conformational change of the molecule. This leads to a testable hypothesis: that PEP adopts particular conformations in the enzyme-substrate complexes of different PEP-using enzymes, and that the enzymes control the reactivity through controlling the dihedral angle between the carboxylate and the C==C double bond of PEP.

Biodegradação enzimática de aminas aromáticas tóxicas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Aptamers binding to Bradykinin

Bradykinin is a peptide of the kinin group, involved in a number of receptor-mediated physiological actions, including inflammation and vasodilation, as well as neuromodulation, neuroprotection and promotion of neurogenesis. Bradykinin is the main ligand of the B2 receptor- the main kinin receptor- which is involved in the cardiac and renal protective effects of kinins in diseases. Antibodies have been considered for a long time as promising therapeutic agents in various fields, especially cancer-related ones. Aptamers, on the other hand, have proven to be an excellent alterative, since they have similar properties to those of monoclonal antibodies, such a high-specificity of recognition and high-affinity binding. Plus, they are developed using in vitro selection procedures and can be reproduced by enzymatic reactions. SELEX is a powerful tool for the development of both DNA and RNA aptamers. The main goal of this project was to design a method to select aptamers against bradykinin using capillary electrophoresis alongside the SELEX technique. The selection was done by comparing the aptamers’ (ssDNA-target complex) electrophoretic mobility with that of the ssDNA and the target, which allowed us to define an appropriate collection window that took into consideration the analytes’ detection time, thus enabling the collection of the desired oligonucleotides. After two selection rounds, the collected pool was sequenced, the affinity was measured and the aptamers’ secondary structure was predicted. We concluded that with only two selection cycles, the original DNA library’s bulk affinity grew around 0.4%. The structural characterization of the aptamers, performed with the aid of the Mfold software, revealed that there are many repetitive motifs amongst them, indicating that the selection process was successful. We have obtained 16 sequences of candidate aptamers as bradykinin ligands of similar sequences and secondary structures whose biological activity should be analyzed after synthesis; mainly in regard to their role as bradykinin inhibitors.

An efficient Azorean thermophilic consortium for lignocellulosic biomass degradation

[Excerpt] Lignocellulosic plant biomass is being envisioned by biorefinery industry as an alternative to current petroleum platform because of the large scale availability, low cost and environmentally benign production. The industrial bioprocessing designed to transform lignocellulosic biomass into biofuels are harsh and the enzymatic reactions may be severely compromised reducing the production of fermentable sugars from lignocellulosic biomass. Thermophilic bacteria consortium are a potential source of cellulases and hemicellulases adapted to extreme environmental conditions, which can be exploited as a new source for the development of more robust enzymatic cocktails. (...)

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.

Peroxisomal beta-oxidation--a metabolic pathway with multiple functions.

Fatty acid degradation in most organisms occurs primarily via the beta-oxidation cycle. In mammals, beta-oxidation occurs in both mitochondria and peroxisomes, whereas plants and most fungi harbor the beta-oxidation cycle only in the peroxisomes. Although several of the enzymes participating in this pathway in both organelles are similar, some distinct physiological roles have been uncovered. Recent advances in the structural elucidation of numerous mammalian and yeast enzymes involved in beta-oxidation have shed light on the basis of the substrate specificity for several of them. Of particular interest is the structural organization and function of the type 1 and 2 multifunctional enzyme (MFE-1 and MFE-2), two enzymes evolutionarily distant yet catalyzing the same overall enzymatic reactions but via opposite stereochemistry. New data on the physiological roles of the various enzymes participating in beta-oxidation have been gathered through the analysis of knockout mutants in plants, yeast and animals, as well as by the use of polyhydroxyalkanoate synthesis from beta-oxidation intermediates as a tool to study carbon flux through the pathway. In plants, both forward and reverse genetics performed on the model plant Arabidopsis thaliana have revealed novel roles for beta-oxidation in the germination process that is independent of the generation of carbohydrates for growth, as well as in embryo and flower development, and the generation of the phytohormone indole-3-acetic acid and the signal molecule jasmonic acid.

Mechanisms of leukocyte lipid body formation and function in inflammation

An area of increasingly interest for the understanding of cell signaling are the spatio-temporal aspects of the different enzymes involved in lipid mediator generation (eicosanoid-forming enzymes, phospholipases and their regulatory kinases and phosphatases) and pools of lipid precursors. The compartmentalization of signaling components within discrete and dynamic sites in the cell is critical for specificity and efficiency of enzymatic reactions of phosphorilation, enzyme activation and function. We hypothesized that lipid bodies - inducible non-membrane bound cytoplasmic lipid domains - function as specialized intracellular sites of compartmentalization of signaling with major roles in lipid mediator formation within leukocytes engaged in inflammatory process. Over the past years substantial progresses have been made demonstrating that all enzymes involved in eicosanoid synthesis localize at lipid bodies and lipid bodies are distinct sites for eicosanoid generation. Here we will review our current knowledge on the mechanisms of formation and functions of lipid bodies pertinent to inflammation.

Modelització de la producció de melanina a partir de polifenol oxidasa d'Agaricus bisporus

Les melanines són un grup heterogeni de polímers producte de reaccions enzimàtiques en els teixits vegetals que contenen compostos fenòlics o polifenòlics. Estudis recents han descobert algunes propietats benèfiques de les melanines sobre la salut, tals com antioxidants, antiinflamatòries, immunològiques i propietats anti-tumorals. Així, no només la seva eliminació ha de ser examinada, sinó que també podria considerar-se la seva addició a aliments funcionals de nova creació. D’aquesta manera, es requereix conèixer el mecanisme cinètic de la lanogènesi abans de la seva possible utilització industrial. S’ha desenvolupat un model cinètic per explicar la formació de melanina a partir de L-tirosina utilitzant polifenol oxidasa d’Agaricus bisporus i monitoritzant l'absorbància de la solució. Aquesta expressió permet descriure la formació de melanina en funció del temps de reacció i obtenir alguns paràmetres importants que defineixen el producte, com el coeficient d'extinció. L’absorbància comença a créixer després d'un període de latència en què es produeixen productes intermedis incolors. El coeficient d'extinció dels productes resultants no és un valor constant, perquè depèn de les condicions de cada experiment. La tirosinasa tingué un menor efecte catalitzador sobre la L-tirosina (primera reacció que catalitza), que sobre L-DOPA (segona reacció).

Um experimento de análise em fluxo envolvendo reações enzimáticas e quimiluminescência

An experiment is proposed to introduce some fundamentals of flow analysis, chemiluminescence and kinetic monitoring of enzymatic reactions in undergraduate courses. Chemiluminescence detection is performed with a simple spectrophotometer equipped with a lab-made spiral flow cell constructed from a polyethylene tube. The hydrogen peroxide produced by the glucose oxidation in the presence of glucose oxidase is continuously monitored by the reaction with luminol in alkaline media in a flow injection system. The exercise allows also the discussion of important analytical features and the comparison with different optical methods of analysis.