La résistance aux antibiotiques est une menace sérieuse pour la santé publique. En effet, si on ne change pas rapidement notre consommation excessive d'antibiotiques, la situation actuelle va se dégrader jusqu'à basculer dans une ère dite "post-antibiotique", dans laquelle plus aucun antibiotique ne sera efficace contre les infections microbiennes. Bien que ce phénomène de résistance apparaît naturellement, l'utilisation abusive d'antibiotiques accélère le processus. De plus, la présence de pathogènes multi-résistants neutralise l'effet des traitements existants et dans le cas de chirurgies courantes (césariennes, transplantations d'organe...), la situation peut rapidement s'aggraver voire devenir mortelle. C'est pourquoi des directives, émanant des autorités sanitaires, doivent être mises en place afin de contrôler l'utilisation des médicaments, et ce, à tous les niveaux de la société, des individus au secteur agricole en passant par les professionnels de santé et les industries pharmaceutiques. Le monde de la recherche scientifique, quant à elle, doit trouver des nouvelles stratégies pour enrayer la propagation de la résistance. Dans ce contexte, cette thèse a pour objectif le développement d'une méthode de prédiction, par calculs d'énergie libre, des mutations de β-lactamases favorables à l'hydrolyse des β-lactames. Ces travaux méthodologiques ont donc conduit au développement : (1) de nouveaux paramètres pour les enzymes à zinc, implémentés dans le champ de force OPLS-AA et validés par des simulations de dynamique moléculaire sur un panel de métalloenzymes représentatives, (2) d'un protocole de paramétrisation de ligands covalents pour étudier le comportement de certains β-lactames dans CMY-136, une nouvelle β-lactamase caractérisée au laboratoire, et (3) d'un protocole de calcul d'énergie libre évalué au moyen de compétitions internationales de prédiction. Ce dernier a ensuite été utilisé pour tenter d'expliquer pourquoi la carbamylation de la sérine catalytique n'a pas lieu dans certaines oxacillinases. Au travers de ces travaux, nous avons pu améliorer significativement notre approche computationnelle et désormais tout est en place pour une exploration exhaustive des mutations possibles dans les β-lactamases. / Antibiotic resistance is a global concern threatening worldwide health. Indeed, if we don't change our overconsumption of antibiotics, the current situation could worsen until a "post-antibiotic" era in which existing treatment would be ineffective against microbial infections. Despite the natural occurrence of antibiotic resistance, the misuse of antibiotics is speeding up the process. Furthermore, presence of multi-resistant pathogens negates the effect of modern treatments and usual surgeries (caesarean sections, organ transplantations...) might be riskier in the future, or even lethal. That's why, common guidelines have to be edicted by health authorities in order to control antibiotic use at every level of society, from individuals to healthcare industry including health professionals and agriculture sector. As for scientific research, new strategies have to be considered in order to limit the spread of antibiotic resistance. In that context, the presented thesis aimed at developing a protocol to predict, by free energy calculations, β-lactamase mutations which could promote the hydolysis of β-lactams antibiotics. In order to achieve that, we developed several methodological approaches including: (1) new parameters for zinc enzymes implemented in OPLS-AA force field and thereafter validated using molecular dynamics simulations of representative zinc-containing metalloenzymes, (2) a protocol to parameterize covalent ligands in order to analyze the dynamical behavior of some β-lactams in CMY-136, a novel β-lactamase recently characterized in our laboratory, and (3) a pmx-based free energy protocol. The latter was also assessed through several international blinded prediction challenges, and finally used to find out why carbamylation of the catalytic serine is not observed in certain OXA enzymes. Throughout this work, we made significant improvements in our protocol, and now everything is in place for an exhaustive prediction of possible mutations in β-lactamases.

Multivariate and multiblock data analysis involves useful methodologies for analyzing large data sets in chemistry, biology, psychology, economics, sensory science, and industrial processes; among these methodologies, partial least squares (PLS) and orthogonal projections to latent structures (OPLS®) have become popular. Due to the increasingly computerized instrumentation, a data set can consist of thousands of input variables which contain latent information valuable for research and industrial purposes. When analyzing a large number of data sets (blocks) simultaneously, the number of variables and underlying connections between them grow very much indeed; at this point, reducing the number of variables keeping high interpretability becomes a much needed strategy. The main direction of research in this thesis is the development of a variable selection method, based on variable influence on projection (VIP), in order to improve the model interpretability of OnPLS models in multiblock data analysis. This new method is called multiblock variable influence on orthogonal projections (MB-VIOP), and its novelty lies in the fact that it is the first multiblock variable selection method for OnPLS models. Several milestones needed to be reached in order to successfully create MB-VIOP. The first milestone was the development of a single-block variable selection method able to handle orthogonal latent variables in OPLS models, i.e. VIP for OPLS (denoted as VIPOPLS or OPLS-VIP in Paper I), which proved to increase the interpretability of PLS and OPLS models, and afterwards, was successfully extended to multivariate time series analysis (MTSA) aiming at process control (Paper II). The second milestone was to develop the first multiblock VIP approach for enhancement of O2PLS® models, i.e. VIPO2PLS for two-block multivariate data analysis (Paper III). And finally, the third milestone and main goal of this thesis, the development of the MB-VIOP algorithm for the improvement of OnPLS model interpretability when analyzing a large number of data sets simultaneously (Paper IV). The results of this thesis, and their enclosed papers, showed that VIPOPLS, VIPO2PLS, and MB-VIOP methods successfully assess the most relevant variables for model interpretation in PLS, OPLS, O2PLS, and OnPLS models. In addition, predictability, robustness, dimensionality reduction, and other variable selection purposes, can be potentially improved/achieved by using these methods.

Project I Celogentin C, isolated by Kobayashi from the seeds of Celosia argentea in 2001 exhibits strong inhibitory behavior towards polymerization of tubulin – globular protein, which plays crucial role during the cell division cycle. We have attempted synthesis of the left-hand ring of celogentin C via the intramolecular alkylation and the Knoevenagel condensation strategies. Utilizing synthetic methodologies in the field of nitroacetyl chemistry, developed by Kornblum and Rajappa we have successfully prepared the intermolecular Knoevenagel condensation product – the late-stage precursor to the left-hand ring of celogentin C. Synthesis of this key intermediate subsequently led to the preparation of the left-hand ring and the total synthesis of celogentin C by other members of Castle's group. Project II Thioviridamide is the potent apoptosis inducer isolated by Hayakawa from the bacterial broth of Streptomyces olivoviridis. Unusual structural features of the thioviridamide macrocycle contain two novel amino acids, never before encountered in a natural product - S-(2-aminovinyl)cysteine (avCys) and β-hydroxy-N1,N3-dimethylhistidinium (hdmHis). No stereochemical information except for the Z-configuration of the β-thioenamide linkage was reported in the literature. We have performed a computational study to predict the thioviridamide stereochemistry. Initial populations of conformers for the likely candidate structures were produced using OPLS-AA force field. Prediction of the NMR properties was accomplished at the mPW1PW91/6-311+G(2d,p) level of theory with the polarizable continuum model of salvation. Utilizing Boltzmann averaging and statistical analysis we have determined that the only possible cases of stereochemical inversion occur at the sites of the two novel amino acids. Project III Model studies towards the synthesis of the β-thioenamide subunit of thioviridamide were performed. The radical addition reaction of thiyl radicals to ynamides produces Z- (kinetic products) or E- β-thioenamides (thermodynamic products) depending on the reaction conditions. Two distinct sets of reaction conditions allowing kinetic or thermodynamic control of β-thioenamide formation were developed. Synthesis of the model β-thioenamide subunit of thioviridamide was attempted.

In our society in the 21st century one of the greatest challenges is to provide raw materials to the industry in a sustainable way. This requires increased use of renewable raw materials such as wood. Wood is widely used in pulp, paper and textile industries and ongoing research efforts aim to extend the use of wood in e.g. liquid biofuels and green chemicals. At Umeå Plant Science Center (UPSC) poplar trees are used as model systems to study wood formation. The objective is to understand the function of the genes underlying the wood forming process. This knowledge could result in improved chemical and physical wood properties suitable for different industrial processes. This will in turn meet the demands for a sustainable development. This thesis presents tools and strategies to unravel information regarding genetic perturbations in poplar trees by the use of nuclear magnetic resonance (NMR) spectroscopy and multivariate analysis (MVA). Furthermore, gas chromatography/mass spectrometry (GC/MS) is briefly discussed in this context. Multivariate methods to find patterns and trends in NMR data have been used for more than 30 years. In the beginning MVA was applied in pattern recognition studies in order to characterize chemical structures with different ligands and in different solvents. Today, the multivariate methods have developed and the research have changed focus towards the study of biofluids from plant extracts, urine, blood plasma, saliva etc. NMR spectra of biofluids can contain thousands of resonances, originating from hundreds of different compounds. This type of complex data can be hard to summarize and interpret without appropriate tools and require sophisticated strategies for data evaluation. Related fields of research are rapidly growing and are here referred to as metabolomics. Five different research projects are presented which includes analysis of poplar samples where macromolecules such as pectin and also small molecules such as metabolites were analysed by high resolution magic angle spinning (HR/MAS) NMR spectroscopy, 1H-13C HSQC NMR and GC/MS. The discussion topics include modelling of metabolomic time dependencies in combination with genetic variation, validation of orthogonal projections to latent structures (OPLS) models, selection of putative biomarkers related to genetic modification from OPLS-discriminant analysis (DA) models, measuring one of the main components found in the primary cell-walls of poplar i.e. pectin, the use of Fourier transformed two-dimensional (2D) NMR data in OPLS modelling and model complexity in a PLS model.

Biological processes in living organisms consist of a vast number of different molecular networks and interactions, which are complex and often hidden from our understanding. This work is focused on recovery of such details for two quite distant examples: acclimation to extreme freezing tolerance in Siberian spruce (Picea obovata) and detection of proteins associated with prostate cancer. The first biological system in the study, upon P. obovata, is interesting by this species ability to adapt and sustain extremely low temperatures, such as -60⁰C or below. Despite decades of investigations, the essential features and mechanisms of the amazing ability of this species still remains unclear. To enhance knowledge about extreme freezing tolerance, the metabolome and proteome of P. obovata’s needles were collected during the tree’s acclimation period, ranging from mid August to January, and have been analyzed. The second system within this study is the plasma proteome analysis of high risk prostate cancer (PCa) patients, with and without bone metastases. PCa is one of the most common cancers among Swedish men, which can abruptly develop into an aggressive, lethal disease. The diagnostic tools, including PSA-tests, are insufficient in predicting the disease’s aggressiveness and novel prognostic markers are urgently required. Both biological systems have been analyzed following similar steps: by two-dimensional difference gel electrophoresis (2D-DIGE) techniques, followed by protein identification using mass spectrometry (MS) analysis and multivariate methods. Data processing has been utilized for searching for proteins that serve as unique indicators for characterizing the status of the systems. In addition, the gas chromatography-mass spectrometry (GC-MS) study of the metabolic content of P.obovata’s needles, from the extended observation period, has been performed. The studies of both systems, combined with thorough statistical analysis of experimental outcomes, have resulted in novel insights and features for both P. obovata and prostate cancer. In particular, it has been shown that dehydrins, Hsp70s, AAA+ ATPases, lipocalin and several proteins involved in cellular metabolism etc., can be uniquely associated with acclimation to extreme freezing in conifers. Metabolomic analysis of P. obovata needles has revealed systematic metabolic changes in carbohydrate and lipid metabolism. Substantial increase of raffinose, accumulation of desaturated fatty acids, sugar acids, sugar alcohols, amino acids and polyamines that may act as compatible solutes or cryoprotectants have all been observed during the acclimation process. Relevant proteins for prostate cancer progression and aggressiveness have been identified in the plasma proteome study, for patients with and without bone metastasis. Proteins associated with lipid transport, coagulation, inflammation and immune response have been found among them.

From the Helichrysum genus 600 species occur in Africa of which 244 species are found in South Africa. The most commonly used Helichrysum species for medicinal purposes are H. cymosum, H. odoratissimum, H. petiolare and H. nudifolium. The medicinal uses include the treatment of coughs, colds, fever, infection, headaches, menstrual pain and are very popular for wound dressing. Previous published research has shown that H. aureonitens has antiviral properties against Herpes simplex virus type 1 (HSV-1). In this study, further investigation into the Helichrysum species was undertaken, to establish the active constituents responsible for anti-HSV activity using a metabolomics approach. The cytotoxicity of 12 Helichrysum species was investigated and ranged from <3.125 μg/ml to 277.8 μg/ml on the vero cell line. The 12 Helichrysum species also showed various levels of antiviral activity against HSV, with both the water-methanol and chloroform extracts of H. adenocarpum subsp. adenocarpum being the most active extract at 25 μg/ml. In this study the activity of Helichrysum species against HIV-1 RT was also investigated. Helichrysum populifolium was the most active extract, inhibiting the HIV-1 RT enzyme by 63.78 % at 200 μg/ml. The bioactivity data and the spectral nuclear magnetic resonance (NMR) data of al the Helichrysum species from this study was analysed using the SIMCA-P software to discriminate between the different species on the basis of their bioactivity and chemical composition. The samples did not group well on Principal Component Analysis (PCA) but did separate well using the Orthogonal Projection to Latent Structure – Discriminate Analysis (OPLS-DA) on the basis of their activity and NMR spectra data. From the OPLS scoring plots analysis, contribution plots were created which indicated regions responsible for the difference between the species, with these regions being investigated to identify the bioactive constituents. It was thus possible to use metabolomics to discriminate between samples on the basis of their activity and show that it could probably be used in future as a tool to identify active ingredients in medicinal plants and accelerate drug discovery. Copyright / Dissertation (MSc)--University of Pretoria, 2009. / Plant Science / unrestricted

<p>Transport into and across the cells of the human body is a prerequisite for the pharmacological action of drugs. Passive membrane permeability and active transport mechanisms are major determinants of the intestinal absorption of drugs, as well as of the distribution to target tissues and the subsequent metabolism and excretion from the body. In this thesis, the role of ATP-binding cassette (ABC) transporters and passive permeability on drug absorption and disposition was investigated. Particular emphasis was placed on defining the molecular properties important for these transport mechanisms. </p><p>The influence of different transport pathways on predictions of intestinal drug absorption was investigated using experimental models of different complexity. Experimental models that include the paracellular pathway gave improved predictions of intestinal drug absorption, especially for incompletely absorbed drugs. Further, the inhibition of the ABC transporters breast cancer resistance protein (BCRP/ABCG2) and multidrug-resistance associated protein 2 (MRP2/ABCC2) was experimentally investigated using structurally diverse datasets that were representative of orally administered drugs. A large number of previously unknown inhibitors were identified among registered drugs, but their clinical relevance for drug-drug interactions and drug-induced toxicity remains to be determined. The majority of the inhibitors affected all three major ABC transporters BCRP, MRP2 and P-glycoprotein (P gp/ABCB1), and these multi-specific inhibitors were found to be enriched in highly lipophilic weak bases. </p><p>To summarize, the present work has led to an increased knowledge of the molecular features of importance for ABC transporter inhibition and passive membrane permeability. Previously unknown ABC transporter inhibitors were identified and predictive computational models were developed for the different drug transport mechanisms. These could be valuable tools to assist in the prioritization of experimental efforts in early drug discovery.</p>

Transport into and across the cells of the human body is a prerequisite for the pharmacological action of drugs. Passive membrane permeability and active transport mechanisms are major determinants of the intestinal absorption of drugs, as well as of the distribution to target tissues and the subsequent metabolism and excretion from the body. In this thesis, the role of ATP-binding cassette (ABC) transporters and passive permeability on drug absorption and disposition was investigated. Particular emphasis was placed on defining the molecular properties important for these transport mechanisms. The influence of different transport pathways on predictions of intestinal drug absorption was investigated using experimental models of different complexity. Experimental models that include the paracellular pathway gave improved predictions of intestinal drug absorption, especially for incompletely absorbed drugs. Further, the inhibition of the ABC transporters breast cancer resistance protein (BCRP/ABCG2) and multidrug-resistance associated protein 2 (MRP2/ABCC2) was experimentally investigated using structurally diverse datasets that were representative of orally administered drugs. A large number of previously unknown inhibitors were identified among registered drugs, but their clinical relevance for drug-drug interactions and drug-induced toxicity remains to be determined. The majority of the inhibitors affected all three major ABC transporters BCRP, MRP2 and P-glycoprotein (P gp/ABCB1), and these multi-specific inhibitors were found to be enriched in highly lipophilic weak bases. To summarize, the present work has led to an increased knowledge of the molecular features of importance for ABC transporter inhibition and passive membrane permeability. Previously unknown ABC transporter inhibitors were identified and predictive computational models were developed for the different drug transport mechanisms. These could be valuable tools to assist in the prioritization of experimental efforts in early drug discovery.

Drug transport across cells and cell membranes in the human body is crucial for the pharmacological effect of drugs. Active transport governed by transport proteins plays an important role in this process. A vast number of transport proteins with a wide tissue distribution have been identified during the last 15 years. Several important examples of their role in drug disposition and drug-drug interactions have been described to date. Investigation of drug-drug interactions at the transport protein level are therefore of increasing interest to the academic, industrial and regulatory research communities. The gene expression of transport proteins involved in drug transport was investigated in the jejunum, liver, kidney and colon to better understand their influence on the ADMET properties of drugs. In addition, the gene and protein expression of transport proteins in cell lines, widely used for predictions of drug transport and metabolism, was examined. The substrate and inhibitor heterogeneity of many transport proteins makes it difficult to foresee whether the transport proteins will cause drug-drug interactions. Therefore, in vitro assays for OCT1 and OATP1B1, among the highest expressed transport proteins in human liver, were developed to allow investigation of the inhibitory patterns of these proteins. These assays were used to investigate two data sets, consisting of 191 and 135 registered drugs and drug-like molecules for the inhibition of OCT1 and OATP1B1, respectively. Numerous new inhibitors of the transport proteins were identified in the data sets and the properties governing inhibition were determined. Further, antidepressant drugs and statins displayed strong inhibition of OCT1 and OATP1B1, respectively. The inhibition data was used to develop predictive in silico models for each of the two transport proteins. The highly polymorphic nature of some transport proteins has been shown to affect drug response and may lead to an increased risk of drug-drug interactions, and therefore, the OCT1 in vitro assay was used to study the effect of common genetic variants of OCT1 on drug inhibition and drug-drug interactions. The results indicated that OCT1 variants with reduced function were more susceptible to inhibition. Further, a drug-drug interaction of potential clinical significance in the genetic OCT1 variant M420del was proposed. In summary, gene expression of transport proteins was investigated in human tissues and cell lines. In vitro assays for two of the highest expressed liver transport proteins were used to identify previously unknown SLC transport protein inhibitors and to develop predictive in silico models, which may detect previously known drug-drug interactions and enable new ones to be identified at the transport protein level. In addition, the effect of genetic variation on inhibition of the OCT1 was investigated.

Adaptation to environmental changes is important for the survival of living organisms. Under extreme abiotic conditions, organic molecules (such as lipids, proteins and nucleic acids) are prone to damage. Under these conditions stress response mechanisms are activated, either to prevent the source of damage or to promote the rapid turnover of damaged molecules. Like all photoautotrophic organisms, cyanobacteria are sensitive to high light intensity and oxidative stress, which induces damage to the photosynthetic apparatus. My thesis is divided in two subjects related to particular stress responses in the cyanobacterium Synechocystis sp. PCC 6803: 1) the role of Deg/HtrA proteases and 2) investigations on the small CAB-like proteins. Deg/HtrA proteases are ATP-independent serine endopeptidases with a characteristic C-terminal PDZ domain. These proteases are largely dispersed among living organisms, with many different functions, mostly involved in protein quality control. The genome of Synechocystis sp. PCC 6803 contains three genes coding for Deg/HtrA proteases: HtrA, HhoA and HhoB. These proteases are essential for survival under high light and heat stress, and may overlap in their functions. During my Ph.D. studies I focused on the identification of the precise localization of the Deg/HtrA proteases in the cyanobacterial cell, analyzed the biochemical properties of recombinant Synechocystis Deg/HtrA proteases in vitro and adopted proteomic and metabolomic approaches to study the physiological importance of these proteases. My data show that Deg/HtrA proteases are not only important in stress response mechanisms under adverse conditions, but are also involved in the stabilization of important physiological processes, such as polysaccharides biosynthesis and peptidoglycan turnover. The small CAB-like proteins (SCPs) belong to the light harvesting-like family of stress induced proteins and are thought to be involved in the photoprotection of the photosynthetic apparatus. Five small CAB-like proteins where identified in Synechocystis sp. PCC 6803 (ScpA-E). In my studies I identified another relative to the SCPs, LilA, which I found to be co-transcribed with ScpD. I also focused on the subcellular localization and identification of potential interaction partners of the SCPs.