La RMN à l’état solide est une méthode de choix pour l’étude des protéines insolubles et des complexes protéiques de haut poids moléculaire. L’insolubilité intrinsèque des protéines fibrillaires, ainsi que leur architecture complexe, rendent difficile leur caractérisation structurale par la cristallographie et par la RMN en solution. La RMN à l‘état solide n’est pas limitée par le poids moléculaire et constitue donc un outil puissant pour l’étude des protéines fibrillaires. L’attribution des résonances RMN est le prérequis pour obtenir des informations structurales à résolution atomique. La première partie de ce travail de thèse décrit le développement de méthodes en RMN à l’état solide pour l’attribution des résonances. Nous avons appliqué ces méthodes afin d’attribuer le domaine C-terminal du prion Ure2 (33 kDa), qui est à ce jour la plus grande protéine attribuée par RMN à l’état solide. Nos résultats fournissent les bases pour l’étude de protéines à haut poids moléculaire à l’échelle atomique. Ceci est démontré dans la seconde partie de ce travail de thèse avec les premières études RMN à l’état solide des fibrilles des prions Ure2 et Sup35. Nous avons caractérisé la structure de ces prions pour les fibrilles entières ainsi que pour les domaines isolés. La troisième fibrille étudiée est l’α- synuclein, fibrille associée à la maladie de Parkinson, pour laquelle nous présentons l’attribution des résonances RMN ainsi que la structure secondaire d’un nouveau polymorphe. Les études présentées ici fournissent de nouvelles clés pour comprendre la diversité des architectures de fibrilles, en considérant les fibrilles comme entités individuelles d’un point de vue structural / Solid-state NMR is the method of choice for studies on insoluble proteins and other high molecular weight protein complexes. The inherent insolubility of fibrillar proteins, as well as their complex architecture, makes the application of x-ray crystallography and solution state NMR difficult. Solid-state NMR is not limited by the molecular weight or by the absence of long-range structural order, and is thus a powerful tool for the 3D structural investigation of fibrillar proteins. The assignment of the NMR resonances is a prerequisite to obtain structural information at atomic level. The first part of this thesis describes the development of solid-state NMR methods to assign the resonances in large proteins. We apply these methods to assign the 33 kDa C-terminal domain of the Ure2p prion which is up to now the largest protein assigned by solid-state NMR. Our results provide the basis to study high molecular weight proteins at atomic level. This is demonstrated in the second part with the first high-resolution solid-state NMR study of Ure2 and Sup35 prion fibrils. We describe the conformation of the functional domains and prion domains in the full-length fibrils and in isolation. The third fibrillar protein addressed in this work is the Parkinson’s disease related α-synuclein whereof we demonstrate the NMR resonance assignment and the secondary structure determination of a new polymorph. Thus, the studies described here provide new insights in the structural diversity of fibril architectures, and plead to view fibrils as individuals from a structural point of view, rather than a homogenous protein family

As proteínas são moléculas que desempenham funções essenciais para a vida. Para entender a função de uma proteína é preciso conhecer sua estrutura tridimensional. No entanto, encontrar a estrutura da proteína pode ser um processo caro e demorado, exigindo profissionais altamente qualificados. Neste sentido, métodos computacionais têm sido investigados buscando predizer a estrutura de uma proteína a partir de uma sequência de aminoácidos. Em geral, tais métodos computacionais utilizam conhecimentos de estruturas de proteínas já determinadas por métodos experimentais, para tentar predizer proteínas com estrutura desconhecida. Embora métodos computacionais como, por exemplo, o Rosetta, I-Tasser e Quark tenham apresentado sucesso em suas predições, são apenas capazes de produzir estruturas significativamente semelhantes às já determinadas experimentalmente. Com isso, por utilizarem conhecimento a priori de outras estruturas pode haver certa tendência em suas predições. Buscando elaborar um algoritmo eficiente para Predição de Estruturas de Proteínas livre de tendência foi desenvolvido um Algoritmo de Estimação de Distribuição (EDA) específico para esse problema, com modelagens full-atom e algoritmos ab initio. O fato do algoritmo proposto ser ab initio é mais interessante para aplicação envolvendo proteínas com baixa similaridade, com relação às estruturas já conhecidas. Três tipos de modelos probabilísticos foram desenvolvidos: univariado, bivariado e hierárquico. O univariado trata o aspecto de multi-modalidade de uma variável, o bivariado trata os ângulos diedrais (Φ Ψ) de um mesmo aminoácido como variáveis correlacionadas. O hierárquico divide o problema em subproblemas e tenta tratá-los separadamente. Os resultados desta pesquisa mostraram que é possível obter melhores resultados quando considerado a relação bivariada (Φ Ψ). O hierárquico também mostrou melhorias nos resultados obtidos, principalmente para proteínas com mais de 50 resíduos. Além disso, foi realiza uma comparação com algumas heurísticas da literatura, como: Busca Aleatória, Monte Carlo, Algoritmo Genético e Evolução Diferencial. Os resultados mostraram que mesmo uma metaheurística pouco eficiente, como a Busca Aleatória, pode encontrar a solução correta, porém utilizando muito conhecimento a priori (predição que pode ser tendenciosa). Por outro lado, o algoritmo proposto neste trabalho foi capaz de obter a estrutura da proteína esperada sem utilizar conhecimento a priori, caracterizando uma predição puramente ab initio (livre de tendência). / Proteins are molecules that perform critical roles in the living organism and they are essential for their lifes. To understand the function of a protein, its 3D structure should be known. However, to find the protein structure is an expensive and a time-consuming task, requiring highly skilled professionals. Aiming to overcome such a limitation, computational methods for Protein Structure Prediction (PSP) have been investigated, in order to predict the protein structure from its amino acid sequence. Most of computational methods require knowledge from already determined structures from experimental methods in order to predict an unknown protein. Although computational methods such as Rosetta, I-Tasser and Quark have showed success in their predictions, they are only capable to predict quite similar structures to already known proteins obtained experimentally. The use of such a prior knowledge in the predictions of Rosetta, I-Tasser and Quark may lead to biased predictions. In order to develop a computational algorithm for PSP free of bias, we developed an Estimation of Distribution Algorithm applied to PSP with full-atom and ab initio model. A computational algorithm with ab initio model is mainly interesting when dealing with proteins with low similarity with the known proteins. In this work, we developed an Estimation of Distribution Algorithm with three probabilistic models: univariate, bivariate and hierarchical. The univariate deals with multi-modality of the distribution of the data of a single variable. The bivariate treats the dihedral angles (Proteins are molecules that perform critical roles in the living organism and they are essential for their lifes. To understand the function of a protein, its 3D structure should be known. However, to find the protein structure is an expensive and a time-consuming task, requiring highly skilled professionals. Aiming to overcome such a limitation, computational methods for Protein Structure Prediction (PSP) have been investigated, in order to predict the protein structure from its amino acid sequence. Most of computational methods require knowledge from already determined structures from experimental methods in order to predict an unknown protein. Although computational methods such as Rosetta, I-Tasser and Quark have showed success in their predictions, they are only capable to predict quite similar structures to already known proteins obtained experimentally. The use of such a prior knowledge in the predictions of Rosetta, I-Tasser and Quark may lead to biased predictions. In order to develop a computational algorithm for PSP free of bias, we developed an Estimation of Distribution Algorithm applied to PSP with full-atom and ab initio model. A computational algorithm with ab initio model is mainly interesting when dealing with proteins with low similarity with the known proteins. In this work, we developed an Estimation of Distribution Algorithm with three probabilistic models: univariate, bivariate and hierarchical. The univariate deals with multi-modality of the distribution of the data of a single variable. The bivariate treats the dihedral angles (Φ Ψ) within an amino acid as correlated variables. The hierarchical approach splits the original problem into subproblems and attempts to treat these problems in a separated manner. The experiments show that, indeed, it is possible to achieve better results when modeling the correlation (Φ Ψ). The hierarchical model also showed that is possible to improve the quality of results, mainly for proteins above 50 residues. Besides, we compared our proposed techniques among other metaheuristics from literatures such as: Random Walk, Monte Carlo, Genetic Algorithm and Differential Evolution. The results show that even a less efficient metaheuristic such as Random Walk managed to find the correct structure, however using many prior knowledge (prediction that may be biased). On the other hand, our proposed EDA for PSP was able to find the correct structure with no prior knowledge at all, so we can call this prediction as pure ab initio (biased-free).

Dada a importância da ciência no desenvolvimento humano, a adoção da alfabetização científica como meta educacional mundial e o papel fundamental da educação formal nesse sentido, muito se tem feito para promover a educação continuada dos professores de ciências. Se se discute quais habilidades e competências são importantes para a atividade didática, o bom conhecimento do conteúdo é consenso. A análise dos registros do curso a distância Bioquímica das Drogas, planejado, ministrado, avaliado e aprimorado neste trabalho e oferecido a professores de Biologia, Química e Ciências da rede pública de ensino do Estado de São Paulo, revelou que: (1) o modelo de ensino em ambientes virtuais e de aprendizagem colaborativa pode ser adequadamente aplicado na formação continuada de professores, embora com restrições relacionadas ao letramento digital; (2) a participação de pós-graduandos na equipe didática trouxe valiosa contribuição para o projeto e para sua formação didática em EaD; (3) os professores têm diversas concepções alternativas em bioquímica, sobretudo com relação à complexidade da estrutura de proteínas e às inter-relações dos metabolismos de carboidratos, lipídeos e proteínas e (4) as intervenções didáticas realizadas foram eficientes para promover a aprendizagem de concepções científicas sobre o tema, incluindo as relacionadas às concepções alternativas detectadas. / Given the importance of Science to human development, the adoption of scientific literacy as a global educational goal, and the major role of formal education, many efforts have been made to promote continuing education of science teachers. While the discussion on which didactic skills are essential to teacher education still endures, mastering the subject matter remains a consensus. This work focuses on designing, implementing, and improving the distant education course Biochemistry of Drugs, offered to science teachers of public schools in São Paulo, Brazil. The analysis of the course records revealed that: (1) the collaborative learning model in virtual environments is adequate to teachers\' continuing education, although with some restrictions concerning digital literacy issues; (2) joining graduate students to the teaching staff contributed positively to the project itself as well as to the didactic training of the latter in distance education; (3) school teachers displayed several alternative conceptions in biochemistry, remarkably on the topics of protein structure and the correlation of the metabolism of carbohydrates, lipids and proteins; (4) the instruction efficiently facilitated learning of biochemical concepts, including those related to the misconceptions detected.

Les antibiotiques sont les médicaments les plus utilisés dans la médecine moderne. Depuis leurs découvertes, ils ont drastiquement changé la façon dont les infections sont traitées. Toutefois, à travers le processus d’adaptation, les bactéries deviennent éventuellement résistantes aux antibiotiques. Malgré leur omniprésence dans la biosphère, l’émergence de souches résistantes est favorisée par le mauvais usage des antibiotiques, ce qui crée une menace importante pour la santé publique. Les antibiotiques actuelles perdent graduellement leur efficacité, et vue le faible nombre de nouvelles molécules développées, la priorité est donnée pour la découverte de nouvelles stratégies capables de combattre les pathogènes. Les nouvelles cibles thérapeutiques idéales doivent exercer une faible pression évolutive, diminuer la virulence et être unique aux microorganismes. Une façon d’atteindre cet objectif est d’interférer dans la régulation et l’homéostasie du Fer chez les bactéries. La biodisponibilité du Fer a fortement influencé l’émergence de la vie sur terre et les stratégies évolutives qu’elle a adoptée. Ce qui a mené à l’apparition d’un mécanisme central de détection du Fer assurant la régulation de cet élément de haute importance. Ce senseur est un point faible que nous pourrons exploiter dans notre combat contre les infections bactériennes. La protéine Fur, pour « Ferric Uptake Regulator », est un régulateur de transcription métal dépendant qui est impliqué dans vaste réseau de régulation contrôlant principalement l’homéostasie du Fer et l’expression de facteurs de virulence. Le travail présenté dans ce manuscrit complète les études précédentes sur des inhibiteurs de la protéine Fur en utilisant une approche combinée théorique et expérimentale grâce a des expériences de XAS, SAXS et MALLS associé a de la modélisation moléculaire. Nous décrivons pour la première fois la structure de Fur d’E. coli ainsi que la structure d’un tétramère de Fur d’un mutant de P. aeruginosa. Par ailleurs, les profils d’énergie libre des protéines Fur de différentes espèces ont été déterminé, pour des complexes tetramériques ou dans le cas de dimères liés à l’ADN, permettant une compréhension préliminaire de leur mécanistique. Les informations structurales obtenues grâce aux travaux présentés dans ce manuscrit permettront de mieux comprendre les mécanismes d’inhibition des protéines Fur ainsi que fournir de nouvelles opportunités pour le développement de molécules a visée thérapeutique. / The most commonly prescribed drugs in human medicine are antibiotics. Since their discovery, they have drastically impacted the way we treat infections. However, a bacterium eventually becomes resistant to antimicrobial treatment through the natural process of adaptative evolution. Even if resistant bacteria are omnipresent in the biosphere, their emergence rate is accelerated by the misuse of antimicrobial agents leading to the public health threat we are facing now. As currently available antimicrobial agents lose their effectiveness and very few new drugs are being developed, a breakthrough in new strategies to fight pathogens should be a priority. Ideal new therapeutic targets should exert weak evolutionary pressure, disarm or weaken the pathogen and be unique to microorganisms. One way to do so is by interfering with the iron regulation and its homeostasis within Bacteria. The bioavailability of iron strongly influenced early life and the metabolic strategies that sustained it. A central iron sensing mechanism evolved to ensure the regulation of such an important element. Sadly for bacteria this sensor became an exploitable weakness in our battle against infection. The “Ferric Uptake Regulator” is a metal dependent transcription regulator with a large regulatory network controlling iron homeostasis and bacterial virulence. This work continues previous investigations on Fur inhibitors using a combined experimental and theoretical approach by performing XAS, SAXS and MALLS experiments together with computer simulations. We describe for the first time the structures of Fur from E. coli in addition to a tetrameric Fur structure of a mutant from P. aeruginosa. Moreover, free energy profiles of Fur proteins, as tetramers or dimers bound to DNA, from different species were generated and key residues involved in the interactions determined, providing mechanistic insights into Fur complexes. The structural information gathered from this work will be used to better understand inhibition mechanisms of Fur proteins providing new opportunities to overcome drug development challenges.

Les nanoémulsions (NEs) huile/eau peuvent être utilisées en tant que systèmes de délivrance des médicaments pour l’encapsulation des substances actives hydrophobes afin d’améliorer leur stabilité et leur biodisponibilité. Néanmoins, leur stabilisation nécessite l’utilisation de concentrations plus importantes de tensioactifs par rapport aux émulsions conventionnelles en raison de l’augmentation de la surface spécifique. La plupart des tensioactifs synthétiques couramment utilisés dans la formulation des émulsions sont potentiellement irritants, voire toxiques. Cela entrave l'application thérapeutique des NEs en particulier pour les traitements à long terme. L'objectif de cette thèse est alors de formuler des NEs pharmaceutiques huile/eau stabilisées par un biopolymère, la beta-lactoglobuline (beta-lg), à la place des tensioactifs synthétiques.Les NEs ont été préparées par homogénéisation à haute pression (HHP). La composition de la formulation et les conditions du procédé ont été optimisées afin d’obtenir des gouttelettes nanométriques dans des NEs stables. Les résultats ont montré que les NEs les plus stables, avec une taille de gouttelettes < 200 nm, ont été obtenues quand 5 m/m% de l’huile ayant la viscosité la plus faible ont été utilisés en tant que phase huileuse, 95 m/m% de la solution de beta-lg à une concentration de 1 m/m% ont été utilisés en tant que phase aqueuse et 4 cycles d’HPH de 100 MPa ont été appliqués. Cette formulation a été stable contre les phénomènes de croissance de gouttelettes pendant au moins 30 jours grâce à un film interfacial quasiment purement élastique. La gomme xanthane, un polysaccaride naturel, a été ajoutée à la formulation optimale à une concentration de 0,5 m/m% en tant qu’agent épaississant. Cela a permis d’obtenir une texture crémeuse avec un comportement rhéofluidifiant. Dans cette dernière formulation, la vitesse de migration des gouttelettes a été considérablement réduite et la stabilité des NEs a été améliorée.Les effets du procédé d’HPH sur les différents niveaux de structure de la protéine ont été évalués à l’aide de méthodes spectroscopiques, chromatographiques et électrophorétiques. L’influence de ce traitement sur ses propriétés interfaciales et émulsionnantes a également été étudiée. L’efficacité émulsionnante optimale a été obtenue quand les conditions d’HPH n’ont pas altéré la structure de la beta-lg, ni ses propriétés interfaciales. Néanmoins, un traitement d’HHP excessif (300 MPa/5 cycles) a induit des modifications structurelles, principalement une transformation des feuillets beta en structures désordonnées, une large perte dans le cœur hydrophobe, et une agrégation importante par des liaisons disulfure intermoléculaires. La beta-lg modifiée par l’HHP a montré une hydrophobie de surface plus importante conduisant à une vitesse d’adsorption à l’interface huile/eau plus élevée et une formation plus précoce d’un film interfacial. La dénaturation de la protéine par ce traitement à haute pression, qui a été effectuée avant le processus d’émulsification, n'a pas modifié de façon significative l'efficacité émulsionnante. La réduction de l’efficacité a été probablement plutôt induite par la dénaturation simultanée avec l’émulsification sous conditions d’écoulement très turbulent.L’intérêt de la formulation développée en tant que véhicule pour un modèle de substance active hydrophobe a été étudié avec l’isotrétinoïne (IT), usuellement utilisé pour le traitement de l’acné sévère. La formulation développée a permis d’encapsuler 0,033 m/m% d’IT sans aucune modification de la stabilité du système. Environ 10 % de l’IT ajoutée ont été solubilisés dans la phase aqueuse en association avec la protéine libre en excès. L’IT encapsulée dans les gouttelettes huileuses a été plus stable contre la photo-isomérisation que celle associée à la protéine libre. La formulation développée apparait prometteuse en tant que système de délivrance de l’IT pour une application cutanée. / Oil-in-water nanoemulsions can be used as drug delivery systems for the encapsulation of hydrophobic active substances in order to increase their solubility and their bioavailability. However, due to their higher specific area, their stabilization requires higher surfactant concentrations compared to conventional emulsions. Most of the synthetic surfactants commonly used in emulsion formulation are potentially irritant and even toxic, which hinders the therapeutic application of nanoemulsions especially during long-term treatment. The objective of this thesis is thus to formulate pharmaceutical oil/water nanoemulsions stabilized by a biopolymer, beta-lactoglobulin (beta-lg), instead of synthetic surfactants. Nanoemulsions were prepared by high pressure homogenization (HPH). The formulation composition and the process conditions were optimized in order to obtain nanometric droplets within stable nanoemulsions. The results showed that the most stable nanoemulsions, with droplet size inférieure à 200 nm, were obtained when 5 w/w% of the oil with the lowest viscosity value was used as the oily phase, 95 w/w% of beta-lg solution at a concentration of 1 w/w% was used as the aqueous phase, and 100 MPa of homogenization pressure was applied for 4 cycles. This formulation was stable against droplet growth phenomena during 30 days at least, thanks to a quasi purely elastic interfacial film. Xanthan gum, a natural polysaccharide, was added to the optimal formulation as a texturizing agent at a concentration of 0.5 w/w%. This allowed obtaining a cream texture with a shear thinning behavior. In this formulation, the migration rate of droplets was considerably reduced and the nanoemulsions stability was enhanced.The effects of the homogenization process on the different levels of the protein structure were assessed by spectroscopic, chromatographic and electrophoretic methods. The influence of this treatment on its interfacial and emulsifying properties was also investigated. The optimal emulsifying efficiency was obtained when the homogenization conditions did alter neither the structure of beta-lg nor its interfacial properties. However, an excessive HPH treatment (300 MPa/5 cycles) introduced structural modifications, mainly from beta-sheets into random coils, wide loss in lipocalin core, and protein aggregation by intermolecular disulfide bridges. HPH modified beta-lg displayed higher surface hydrophobicity inducing a higher adsorption rate at the O/W interface and an earlier formation of an elastic interfacial film. Structural and interfacial properties modifications by HPH denaturation appeared qualitatively similar to that of the heat denaturation with, however, differences in extent. Protein denaturation by a high pressure treatment that was performed before the emulsification process did not alter significantly its emulsifying efficiency. The reduction in the efficiency was rather induced by the simultaneous denaturation with the emulsification under high turbulent flow.The efficiency of the developed formulation as a vehicle for a model hydrophobic active substance was studied using isotretinoin, usually used for the treatment of severe acne. The developed formulation was able to encapsulate 0.033 w/w of isotretinoin without any modification on the system stability. About 10 % of the added isotretinoin was solubilized in the aqueous phase associated with the free protein in excess. Isotretinoin encapsulated in the oily droplets was more stable against photo isomerization than the one associated to the excess protein in the aqueous phase. The developed formulation seems promising as a drug delivery system of isotretinoin for a dermal application.

Pentameric ligand-gated ion channels (pLGICs) are membrane-embedded receptors found extensively in pre- and post-synaptic membranes throughout the nervous system where they play an important role in neurotransmission. The function of the prototypic pLGIC, the nicotinic acetylcholine receptor (nAChR) is highly sensitive to changes in its lipid environment, while other pLGICs display varying lipid sensitivities. This thesis presents a multidisciplinary investigation into the features of the transmembrane domain (TMD) that determine the unique functional and physical traits of different pLGICs. Using two prokaryotic homologues of the nAChR, ELIC and GLIC, as models, I focus on the outermost, lipid-exposed α-helix, M4, which, despite being distant from the primary allosteric pathway coupling agonist binding to channel gating, exercises significant control over channel function. Here, I present evidence that M4 acts as a lipid sensor, detecting changes in the surrounding lipids and transmitting these changes to the channel pore via contacts with the adjacent TMD α-helices, M1 and M3, and/or with structures in the extracellular domain. Using ELIC and GLIC chimeras, I first show that the TMD is the main driver of pLGIC thermal stability. I then demonstrate that the M4 α-helices in each channel play different roles in channel maturation and function, which suggests a divergent evolutionary path. Following this, I show that the M4 C-terminus is essential to both maturation and function in GLIC, while in ELIC its role is less defined, again showcasing possible evolutionary differences. Building on these findings, I examined the role of aromatic residues at the M4 – M1/M3 interface, and found that they predictably determine the interactions between M4 and M1/M3. Notably, the addition of aromatic residues to enhance M4-M1/M3 interactions in ELIC promotes channel function, while the elimination of aromatic residues at the M4-M1/M3 interface in GLIC is detrimental to channel function. Furthermore, I show that these same aromatics alter the strength of pLGIC lipid sensing and the sensitivity to certain disease-causing mutations, both indicating that aromatic residues are key players in channel function, stability and modulation. Finally, I and my collaborators identified and characterized a novel desensitization-linked lipid binding site in ELIC. Extensive mutagenesis studies coupled with biophysical measurements allowed us to develop a model describing how lipid binding influences the rates of ELIC desensitization to shape the agonist-induced response.

Le virus respiratoire syncytial humain (hRSV) est le principal agent pathogène responsable des bronchiolites. Le complexe ARN polymérase (RdRp), du hRSV, nécessaire à la réplication de son génome, est composé a minima de la sous-unité catalytique (L), de son principal cofacteur qu’est la phosphoprotéine (P) et de la nucléoprotéine (N) qui assure l’encapsidation du génome viral. Le cœur de mon projet doctoral a été l’étude dynamique et structurale de domaines des protéines N et P du hRSV ainsi que leurs interactions avec certaines protéines cellulaires principalement par résonance magnétique nucléaire.Dans un premier temps j’ai étudié une potentielle interaction entre 2 domaines appartenant à la protéine N et à la protéine cellulaire Tax1BP1 impliquée notamment dans la régulation de l’autophagie. Ensuite, j’ai entrepris une étude structurale et dynamique de hRSV-P isolée notamment dans le but de déterminer des contacts transitoires au sein de la protéine et d’obtenir la structure tridimensionnelle du domaine d’oligomérisation de P. Enfin, j'ai participé à la caractérisation de l’interaction entre la protéine hRSV-P et le cofacteur de transcription du hRSV hRSV-M2-1, puis entre hRSV P et la phosphatase cellulaire PP1α, afin d’en cartographier les régions de contacts. / Human respiratory syncytial virus (hRSV) is the main pathogen responsible for bronchiolitis. The RNA polymerase complex (RdRp) of hRSV, necessary for the replication of its genome, is composed at least of the catalytic subunit (L), its main cofactor phosphoprotein (P) and nucleoprotein (N), which encapsidates the viral genome. At the heart of my doctoral project was the dynamic and structural study of domains of the proteins N and P of the hRSV as well as of their interactions with several cellular proteins, mainly by nuclear magnetic resonance.Firstly, I studied a potential interaction between 2 domains belonging to the N protein and to the Tax1BP1 cellular protein involved notably in regulation of autophagy. Secondly, I undertook a structural and dynamic study of isolated hRSV-P in order to determine transient contacts within the protein and to obtain the three-dimensional structure of the P oligomerization domain. Last, I participated in the characterization of the interaction between the hRSV-P protein and the hRSV transcription cofactor hRSV-M2-1, and between hRSV P and the cellular phosphatase PP1α to map the contact regions.

Proteins are involved in almost all functions in a living cell, and functions of proteins are realized by their tertiary structures. Protein three-dimensional structures can be solved by multiple experimental methods, but computational approaches serve as an important complement to experimental methods for comparing and analyzing protein structures. Protein structure comparison allows the transfer of knowledge about known proteins to a novel protein and plays an important role in function prediction. Obtaining a global perspective of the variety and distribution of protein structures also lays a foundation for our understanding of the building principle of protein structures. This dissertation introduces our computational method to compare protein 3D structures and presents a novel mapping of protein shapes that represents the variety and the similarities of 3D shapes of proteins and their assemblies. The methods developed in this work can be applied to obtain new biological insights into protein atomic structures and electron density maps.

The work concerns to structural characterization of two important proteins of 2'-5' oligoadenylate pathway participating in an immune response of organism to a viral infection. Studied proteins were ankyrin domain of mouse RNase L, the C-terminal part of human phosphodiesterase 12 and the complete human phosphodiesterase 12. The proteins were characterized by Raman spectroscopy, infrared spectroscopy, electronic circular dichroism, dynamic light scattering and in addition by two non-spectroscopic methods- differential calorimetry and electrophoresis. For each protein the secondary structures, thermal stability, weight of oligomers and generally a basic characterization by above mentioned methods were provided.

To what extent conformational preference of short peptide sequences within proteins determine their three-dimensional structure? Large-scale quantum chemical calculations coupled with modern solvation methods represent unique set of tools to elucidate key determinants of the biomolecular structure ab initio. Full conformational sampling was performed on model systems representing short peptide fragments. The computed data reveal some of the underlying physico-chemical principles determining the spatial structure of proteins, and provide very important data for finding and tuning the optimal algorithm that may provide a full coverage of (ideally all) low-energy conformers. Keywords: Conformational space, peptide fragments, protein structure, solvation methods, Ramachandran plot, DFT-D3 methods