A proteomic approach toward the selection of proteins with enhanced intrinsic conformational stability

Journal of Proteome Research (2006)5: 2720-2726

Crystallographic studies of proteins involved in the mRNA localization mechanisms in Drosophila melanogaster and amidation of the peptidoglycan residues in Staphylococcus aureus

Part of the work described in this chapter, was the subject of the following publication: D. Vieira, T. a. Figueiredo, A. Verma, R. G. Sobral, A. M. Ludovice, H. de Lencastre, and J. Trincao, “Purification, crystallization and preliminary X-ray diffraction analysis of GatD, a glutamine amidotransferase-like protein from Staphylococcus aureus peptidoglycan,” Acta Crystallogr. Sect. F Struct. Biol. Commun., vol. 70, no. 5, pp. 1–4, Apr. 2014.

Molecular targeting of proteins by homocysteine: implications in familial and clinical hypercholesterolemia

Cardiovascular diseases (CVDs) are one of the leading causes of death and disability worldwide and one of its underlying causes is hypercholesterolemia. Hypercholesterolemia can have genetic (familial hypercholesterolemia, FH) and non-genetic causes (clinical hypercholesterolemia, CH), the first much more severe, with occurrence of premature atherosclerosis. While the pathophysiological role of homocysteine (Hcy) on CVD is still controversial, molecular targeting of protein by S and N-homocysteinylation offers a new paradigm to be considered in the vascular pathogenesis of hypercholesterolemia. On this regard, the present study aims to give new insights on protein targeting by Hcy in both CH and FH conditions. A total of 187 subjects were included: 65 normolipidemic and 122 hypercholesterolemic. Total (tHcy) and free (fHcy) fractions were quantified in serum samples after validation of an HPLCFD method, to assess S-homocysteinylation. Also, the lactonase (LACase) activity of paraoxonase-1 (PON1) was quantified by a colorimetric assay, as a surrogate of N-homocysteinylation. tHcy does not differ among groups. Nevertheless, fHcy declines in the hypercholesterolemic groups, with more evidence to the FH population. Consequently, there seems to be an increase of Shomocysteinylation, regardless of lipid lowering therapy (LLT). Also, despite of LLT use, LACase activity is lower in FH, thus the risk for protein N-homocysteinylation seems to be higher. Moreover, the decrease in LACase/ApoA1 and LACase/HDL ratios in FH, shows that HDL is dysfunctional in this population, despite its normal concentration values. Data supports that the pathophysiological role of Hcy on hypercholesterolemia may reside in its ability to post-translationally modify proteins. This role is particularly evident in FH condition. In the future, it will be interesting to identify which target proteins are modified and thus involved in vascular pathology progression.

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.

Molybdenum-containing proteins from Sulphate Reducing Bacteria: studying proteins with novel cofactors and revealing new features of old enzymes

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

Development of thermoresponsive (polysulfone/polyacrylonitrile) - based membranes for bioseparation processes

Mestrado integrado em Engenharia Química e Bioquímica

The role of Di-iron proteins in pathogen resistance

Dissertation presented to obtain the Ph.D. degree in Biochemistry

Design of bio-inspired ionic liquids for protein stabilisation

Ionic Liquids (ILs) consist in organic salts that are liquid at/or near room temperature. Since ILs are entirely composed of ions, the formation of ion pairs is expected to be one essential feature for describing solvation in ILs. In recent years, protein - ionic liquid (P-IL) interactions have been the subject of intensive studies mainly because of their capability to promote folding/unfolding of proteins. However, the ion pairs and their lifetimes in ILs in P-IL thematic is dismissed, since the action of ILs is therefore the result of a subtle equilibrium between anion-cation interaction, ion-solvent and ion-protein interaction. The work developed in this thesis innovates in this thematic, once the design of ILs for protein stabilisation was bio-inspired in the high concentration of organic charged metabolites found in cell milieu. Although this perception is overlooked, those combined concentrations have been estimated to be ~300 mM among the macromolecules at concentrations exceeding 300 g/L (macromolecular crowding) and transient ion-pair can naturally occur with a potential specific biological role. Hence the main objective of this work is to develop new bio-ILs with a detectable ion-pair and understand its effects on protein structure and stability, under crowding environment, using advanced NMR techniques and calorimetric techniques. The choline-glutamate ([Ch][Glu]) IL was synthesized and characterized. The ion-pair was detected in water solutions using mainly the selective NOE NMR technique. Through the same technique, it was possible to detect a similar ion-pair promotion under synthetic and natural crowding environments. Using NMR spectroscopy (protein diffusion, HSQC experiments, and hydrogen-deuterium exchange) and differential scanning calorimetry (DSC), the model protein GB1 (production and purification in isotopic enrichment media) it was studied in the presence of [Ch][Glu] under macromolecular crowding conditions (PEG, BSA, lysozyme). Under dilute condition, it is possible to assert that the [Ch][Glu] induces a preferential hydration by weak and non-specific interactions, which leads to a significant stabilisation. On the other hand, under crowding environment, the [Ch][Glu] ion pair is promoted, destabilising the protein by favourable weak hydrophobic interactions , which disrupt the hydration layer of the protein. However, this capability can mitigates the effect of protein crowders. Overall, this work explored the ion-pair existence and its consequences on proteins in conditions similar to cell milieu. In this way, the charged metabolites found in cell can be understood as key for protein stabilisation.

Localization studies of the FemXAB protein family in Staphylococcus aureus

Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Production optimization of rotavirus-like particles: a system biology approach

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

New analytical methodologies for doping control – detection of anabolic androgenic steroids in human urine

Dissertation submitted to Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa in fulfilment of the requirements for the degree of Doctor of Philosophy (Biochemistry - Biotechnology)

Development of new methodologies in sample treatment for proteomics workflow based on enzymatic probe sonication technology and mass spectrometry

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia, for the degree of Doctor of Philosophy in Biochemistry

The role of ribonuclease R in bacterial adaptation to cold shock

RESUMO:Os microrganismos reagem à súbita descida de temperatura através de uma resposta adaptativa específica que assegura a sua sobrevivência em condições desfavoráveis. Esta adaptação inclui alterações na composição da membrana, na maquinaria de tradução e transcrição. A resposta ao choque térmico pelo frio induz uma repressão da transcrição. No entanto, a descida de temperatura induz a produção de um grupo de proteínas específicas que ajudam a ajustar/re-ajustar o metabolismo celular às novas condições ambientais. Em E. coli o processo de adaptação demora apenas quatro horas, no qual um grupo de proteínas específicas são induzidas. Depois desde período recomeça lentamente a produção de proteínas.A ribonuclease R, uma das proteínas induzidas durante o choque térmico pelo frio, é uma das principais ribonucleases em E. coli envolvidas na degradação do RNA. É uma exoribonuclease que degrada RNA de cadeia dupla, possui funções importantes na maturação e “turnover” do RNA, libertação de ribossomas e controlo de qualidade de proteínas e RNAs. O nível celular desta enzima aumenta até dez vezes após exposição ao frio e estabiliza em células na fase estacionária. A capacidade de degradar RNA de dupla cadeia é importante a baixas temperaturas quando as estruturas de RNA estão mais estáveis. No entanto, este mecanismo é desconhecido. Embora a resposta específica ao “cold shock” tenha sido descoberta há mais de duas décadas e o número de proteínas envolvidas sugerirem que esta adaptação é rápida e simples, continuamos longe de compreender este processo. No nosso trabalho pretendemos descobrir proteínas que interactuem com a RNase R em condições ambientais diferentes através do método “TAP-tag” e espectrometria de massa. A informação obtida pode ser utilizada para deduzir algumas das novas funções da RNase R durante a adaptação bacteriana ao frio e durante a fase estacionária. Mais importante ainda, RNase R poderá ser recrutada para um complexo de proteínas de elevado peso molecular durante o “cold-shock”.------------ABSTRACT:Microorganisms react to the rapid temperature downshift with a specific adaptative response that ensures their survival in unfavorable conditions. Adaptation includes changes in membrane composition, in translation and transcription machinery. Cold shock response leads to overall repression of translation. However, temperature downshift induces production of a set of specific proteins that help to tune cell metabolism and readjust it to the new environmental conditions. For Escherichia coli the adaptation process takes only about four hours with a relatively small set of specifically induced proteins involved. After this time, protein production resumes, although at a slower rate. One of the cold inducible proteins is RNase R, one of the main E. coli ribonucleases involved in RNA degradation. RNase R is an exoribonuclease that digest double stranded RNA, serves important functions in RNA maturation and turnover, release of stalled ribosomes by trans-translation, and RNA and protein quality control. The level of this enzyme increases about ten-fold after cold induction, and it is also stabilised in cells growing in stationary phase. The RNase R ability to digest structured RNA is important at low temperatures where RNA structures are stabilized but the exact role of this mechanism remains unclear. Although specific bacterial cold shock response was discovered over two decades ago and the number of proteins involved suggests that this adaptation is fast and simple, we are still far from understanding this process. In our work we aimed to discover the proteins interacting with RNase R in different environmental conditions using TAP tag method and mass spectrometry analysis. The information obtained can be used to deduce some of the new functions of RNase R during adaptation of bacteria to cold and in stationary growth phase. Most importantly RNase R can be recruited into a high molecular mass complex of protein in cold shock.

Evaluation of different natural ingredients as satiety inductors

Dissertation to obtain a Master’s Degree in Chemical and Biochemical Engineering

Anti-apolipoprotein A-I antibodies in the pathogenesis of Alzheimer disease : project plan

RESUMO: A doença de Alzheimer (AD) é a forma mais comum de demência em todo o mundo e sua prevalência deverá duplicar até 2050. Os mecanismos precisos responsáveis pela AD são desconhecidas mas as características histopatológicas estão bem caracterizadas. A hipótese mais importante para a perda neuronal e declínio cognitivo na AD é a cascata amilóide que indica que AD é o resultado da sobreprodução de beta amilóide (Aβ) e / ou remoção ineficaz; a acumulação do BA no cérebro seria o passo crítico na patogénese da AD. Actualmente, a identificação de proteínas que se ligam ao Aβ e modulam a sua agregação e neurotoxicidade pode proporcionar a base para novas abordagens terapêuticas. A apolipoproteína AI (ApoA-I), o principal componente das HDL humanas, interage com o domínio extracelular da proteína precursora de amilóide (APP), bem como com o Aβ. Estudos epidemiológicos têm mostrado uma diminuição acentuada da ApoA-I plasmática em doentes com AD, com uma correlação inversa entre o nível de ApoA-I e o risco de AD. Este trabalho pretende apresentar um projecto que tem como objectivo investigar se os anticorpos anti-apo AI podem impedir a formação de complexos Aβ / ApoA-I, bloqueando o efeito protector da ApoA-I. A hipótese baseia-se na possibilidade dos doentes com AD terem anticorpos anti-ApoA-I plasmáticos e de estes poderem interferir com a formação do complexo no LCR.------- ABSTRACT:Alzheimer’s disease (AD) is the most common form of dementia world-wide and its prevalence is expected to double by the year 2050. The precise mechanisms responsible for AD are unknown but the histopathologic features are well-characterised. The most compelling hypothesis for neuronal loss and cognitive decline in AD is the amyloid cascade hypothesis which states that AD is the result of amyloid beta (Aβ) overproduction and/or ineffective clearance and its accumulation in the brain would be the critical step in AD pathogenesis. Currently, identification of proteins that bind Aβ and modulate its aggregation and neurotoxicity could provide the basis for novel treatment approaches. Apolipoprotein A-I (ApoA-I), the main constituent of human HDL, ApoA-I interacts with the extracellular domain of amyloid precursor protein (APP), as well as with Aβ itself. Epidemiological studies have shown a marked decrease of plasma ApoA-I levels in AD patients, with an inverse correlation between the ApoA-I level and the risk of AD. This work intends to present a project that aims to investigate if anti-ApoA-I antibodies may prevent the formation of the Aβ /ApoA-I complex and by doing so blocking the protective effect of ApoA-I in AD. We base the hypothesis on the possibility that patients with AD might have anti-ApoA-I antibodies in plasma and that these can interfere with the complex formation in the cerebrospinal fluid (CSF).