Neste trabalho são apresentados dois novos descritores de forma para tarefas de recuperação de imagens por conteúdo (CBIR) e análise de formas, que são construídos sobre uma extensão do conceito de tensor scale baseada na Transformada de Distância Euclidiana (EDT). Primeiro, o algoritmo de tensor scale é utilizado para extrair informações da forma sobre suas estruturas locais (espessura, orientação e anisotropia) representadas pela maior elipse contida em uma região homogênea centrada em cada pixel da imagem. Nos novos descritores, o limite do intervalo das orientações das elipses do modelo de tensor scale é estendido de 180º para 360º, de forma a melhor discriminar a descrição das estruturas locais. Então, com base em diferentes abordagens de amostragem, visando resumir informações mais relevantes, os novos descritores são construídos. No primeiro descritor proposto, Tensor Scale Sector (TSS), a distribuição das orientações relativas das estruturas locais em setores circulares é utilizada para compor um vetor de características de tamanho fixo, para uma caracterização de formas baseada em região. No segundo descritor, o Tensor Scale Band (TSB), foram considerados histogramas das orientações relativas extraídos de bandas concêntricas, formando também um vetor de características de tamanho fixo, com uma função de distância de tempo linear. Resultados experimentais com diferentes bases de formas (MPEG-7 e MNIST) são apresentados para ilustrar e validar os métodos. TSS demonstra resultados comparáveis aos métodos estado da arte, que geralmente dependem de algoritmos custosos de otimização de correspondências. Já o TSB, com sua função de distância em tempo linear, se demonstra como uma solução adequada para grandes coleções de formas. / In this work, two new shape descriptors are proposed for tasks in Content-Based Image Retrieval (CBIR) and Shape Analysis tasks, which are built upon an extended tensor scale based on the Euclidean Distance Transform (EDT). First, the tensor scale algorithm is applied to extract shape attributes from its local structures (thickness, orientation, and anisotropy) as represented by the largest ellipse within a homogeneous region centered at each image pixel. In the new descriptors, the upper limit of the interval of local orientation of tensor scale ellipses is extended from 180º to 360º, to better discriminate the description of local structures. Then, the new descriptors are built based on different sampling approaches, aiming to summarize the most relevant features. In the first proposed descriptor, Tensor Scale Sector descriptor (TSS), the local distributions of relative orientations within circular sectors are used to compose a fixed-length feature vector, for a region-based shape characterization. For the second method, the Tensor Scale Band (TSB) descriptor, histograms of relative orientations are considered for each circular concentric band, to also compose a fixed-length feature vector, with linear time distance function for matching. Experimental results for different shape datasets (MPEG-7 and MNIST) are presented to illustrate and validate the methods. TSS can achieve high retrieval values comparable to state-of-the-art methods, which usually rely on time-consuming correspondence optimization algorithms, but uses a simpler and faster distance function, while the even faster linear complexity of TSB leads to a suitable solution for very large shape collections.

Esta dissertação apresenta um estudo comparativo de diferentes métodos computacionais de segmentação estrutural musical, onde o principal objetivo é delimitar fronteiras de seções musicais em um sinal de áudio, e rotulá-las, i.e. agrupar as seções encontradas que correspondem a uma mesma parte musical. São apresentadas novas propostas para segmentação estrutural nãosupervisionada, incluindo métodos para processamento em tempo real, alcançando resultados com taxas de erro inferiores a 12%. O método utilizado compreende um estudo dos descritores sonoros e meios de modelá-los temporalmente, uma exposição das técnicas computacionais de segmentação estrutural e novos métodos de avaliação dos resultados que penalizam tanto a incorreta detecção das fronteiras quanto o número incorreto de rótulos encontrados. O desempenho de cada técnica computacional é calculado utilizando diferentes conjuntos de descritores sonoros e os resultados são apresentados e analisados tanto quantitativa quanto qualitativamente. / A comparative study of different music structural segmentation methods is presented, where the goal is to delimit the borders of musical sections and label them, i.e. group the sections that correspond to the same musical part. Novel proposals for unsupervised segmentation are presented, including methods for real-time segmentation, achieving expressive results, with error ratio less then 12%. Our method consists of a study of sound descriptors, an exposition of the computational techniques for structural segmentation and the description of the evaluation methods utilized, which penalize both incorrect boundary detection and incorrect number of labels. The performance of each technique is calculated using different sound descriptor sets and the results are presented and analysed both from quantitative and qualitative points-of-view.

La cystoscopie est l’examen de référence pour le diagnostic et le traitement du cancer de la vessie. Le champ de vue (CdV) réduit des endoscopes complique le diagnostic et le suivi des lésions. Les mosaïques d’images sont une solution à ce problème car elles visualisent des CdV étendus. Toutefois, pour la vessie, le mosaïque d’images est un véritable défi à cause du faible contraste dans les images, des textures peu prononcées, de la variabilité intra- et inter-patient et des changements d’illumination dans les séquences. Ce défi est également à relever dans d’autres modalités endoscopiques ou dans des scènes non médicales comme les vidéos sous-marines. Dans cette thèse, une énergie variationnelle totale a d’abord été minimisée à l’aide d’un algorithme primal-dual du premier ordre pour obtenir un flot optique fournissant une correspondance dense et précise entre les points homologues des paires d’images. Les correspondances sont ensuite utilisées pour déterminer les paramètres des transformations requises pour le placement des images dans le repère global de la mosaïque. Les méthodes proposées pour l’estimation du flot optique dense incluent un terme d’attache aux données qui minimise le nombre des vecteurs aberrants et un terme de régularisation conçu pour préserver les discontinuités du champ devecteurs. Un algorithme de flot optique qui est robuste vis-à-vis de changements d’illumination importants (et utilisable pour différentes modalités) a également été développé dans ce contexte. La précision et la robustesse des méthodes de recalage proposées ont été testées sur des jeux de données (de flot optique) publiquement accessibles et sur des fantômes de vessies et de la peau. Des résultats sur des données patients acquises avec des cystoscopes rigides et flexibles, en lumière blanche ou en fluorescence, montrent la robustesse des algorithmes proposés. Ces résultats sont complétés par ceux obtenus pour d’autres séquences endoscopiques réelles de dermatoscopie, de scène sous-marine et de données d’exploration spatiale. / Cystoscopy is the reference procedure for the diagnosis and treatment of bladder cancer. The small field of view (FOV) of endoscopes makes both the diagnosis and follow-up of lesions difficult. Image mosaics are a solution to this problem since they visualize large FOVs of the bladder scene. However, due to low contrast, weak texture, inter- and intra-patient texture variability and illumination changes in these image sequences, the task of image mosaicing becomes challenging. This is also a major concern in other endoscopic data and non-medical scenes like underwater videos. In this thesis, a total variational energy has been first minimized using a first-order primal-dual algorithm in convex optimization to obtain optical flow vector fields giving a dense and accurate correspondence between homologous points of the image pairs. The correspondences are then used to obtain transformation parameters for registering the images to one global mosaic coordinate system. The proposed methods for dense optical flow estimation include a data-term which is modeled to minimize at most the outliers and a regularizer which is designed to preserve at their best the flow field discontinuities. An optical flow algorithm, which is robust to strong illumination changes (and which suits to different modalities), has also been developed in this framework. The registration accuracy and robustness of the proposed methods are tested on both publicly available datasets for optical flow estimation and on simulated bladder and skin phantoms. Results on patient data acquired with rigid and flexible cystoscopes under the white light and the fluorescence modality show the robustness of the proposed approaches. These results are also complemented with those of other real endoscopic data, dermoscopic sequences, underwater scenes and space exploration data.

Dans l’état de l’art actuel, la reconnaissance de symboles signifie généralement la reconnaissance des symboles isolés. Cependant, ces méthodes de reconnaissance de symboles isolés ne sont pas toujours adaptés pour résoudre les problèmes du monde réel. Dans le cas des documents composites qui contiennent des éléments textuels et graphiques, on doit être capable d’extraire et de formaliser les liens qui existent entre les images et le texte environnant, afin d’exploiter les informations incorporées dans ces documents.Liés à ce contexte, nous avons d’abord introduit une méthode de reconnaissance graphique basée sur la programmation dynamique et la mise en correspondance de caractéristiques issues de la transformée de Radon. Cette méthode permet d’exploiter la propriété de cette transformée pour inclure à la fois le contour et la structure interne des formes sans utiliser de techniques de compression de la représentation du motif dans un seul vecteur et qui pourrait passer à côté d’informations importantes. La méthode surpasse en performances les descripteurs de forme de l’état de l’art, mais reste principalement adapté pour la reconnaissance de symboles isolés seulement. Nous l’avons donc intégrée dans une approche complètement nouvelle pour la reconnaissance de symboles basé sur la description spatio-structurelle d’un «vocabulaire» de primitives visuelles extraites. La méthode est basée sur les relations spatiales entre des paires de types étiquetés de ce vocabulaire (dont certains peuvent être caractérisés avec le descripteur mentionné précédemment), qui sont ensuite utilisées comme base pour construire un graphe relationnel attribué (ARG) qui décrit des symboles. Grâce à notre étiquetage des types d’attribut, nous évitons le problème classique NP-difficile d’appariement de graphes. Nous effectuons une comparaison exhaustive avec d’autres modèles de relations spatiales ainsi qu’avec l’état de l’art des approches pour la reconnaissance des graphismes afin de prouver que notre approche combine efficacement les descripteurs statistiques structurels et globaux et les surpasse de manière significative.Dans la dernière partie de cette thèse, nous présentons une approche de type sac de caractéristiques utilisant les relations spatiales, où chaque paire possible primitives visuelles est indexée par sa configuration topologique et les types visuels de ses composants. Ceci fournit un moyen de récupérer les symboles isolés ainsi que d’importantes parties connues de symboles en appliquant soit un symbole isolée comme une requête soit une collection de relations entre les primitives visuelles. Finalement, ceci ouvre des perspectives vers des processus de reconnaissance de symboles fondés sur le langage naturel / In the current state-of-the-art, symbol recognition usually means recognising isolated symbols. However, isolated symbol recognition methods are not always suitable for solving real-world problems. In case of composite documents that contain textual and graphical elements, one needs to be able to extract and formalise the links that exist between the images and the surrounding text, in order to exploit the information embedded in those documents.Related to this context, we first introduce a method for graphics recognition based on dynamic programming matching of the Radon features. This method allows to exploit the Radon Transform property to include both boundary and internal structure of shapes without compressing the pattern representation into a single vector that may miss information. The method outperforms all major set of state-of-the-art of shape descriptors but remains mainly suited for isolated symbol recognition only. We therefore integrate it in a completely new approach for symbol recognition based on the spatio-structural description of a ‘vocabulary’ of extracted visual primitives. The method is based on spatial relations between pairs of labelled vocabulary types (some of which can be characterised with the previously mentioned descriptor), which are further used as a basis for building an attributed relational graph (ARG) to describe symbols. Thanks to our labelling of attribute types, we avoid the general NP-hard graph matching problem. We provide a comprehensive comparison with other spatial relation models as well as state-of-the-art approaches for graphics recognition and prove that our approach effectively combines structural and statistical descriptors together and outperforms them significantly.In the final part of this thesis, we present a Bag-Of-Features (BOFs) approach using spatial relations where every possible pair of individual visual primitives is indexed by its topological configuration and the visual type of its components. This provides a way to retrieve isolated symbols as well as significant known parts of symbols by applying either an isolated symbol as a query or a collection of relations between the important visual primitives. Eventually, it opens perspectives towards natural language based symbol recognition process

Este trabalho teve como objetivo a realização de estudos de Relações Quantitativas Tridimensionais Estrutura-Atividade, QSAR 3D, com identificação de alvos potenciais para compostos 5-nitro-heterocíclicos com estruturas azometínica ou oxadiazolínica com bioatividade dual, antifúngica e anti-T. cruzi, visando à identificação de novos compostos que possam ser aproveitados como possíveis candidatos a fármaco ou como compostos-líderes para novos estudos de modificação molecular. Os compostos estudados pertencem a quatro séries intimamente relacionadas, a saber: Série AzoO: 5-nitro-2-furfurilideno benzidrazidas 4-substituídas; Série AzoS: 5-nitro-2-tiofilideno benzidrazidas 4-substituídas; Série OxaO: 3-acetil-oxadiazolina 2,5-furfurilideno benzidrazidas 4-substituídas e Série OxaS: 3-acetil-oxadiazolina 2,5-tiofilideno benzidrazidas 4-substituídas. A utilização de forma integrada de ferramentas pertencentes às áreas de química farmacêutica, quimioinformática e bioinformática permite a caracterização de cavidades catalíticas de proteínas e a identificação das propriedades físico-químicas consideradas essenciais para a interação adequada entre ligante e biomacromolécula-alvo. Por outro lado, permitem também a identificação de alvos a partir da comparação de estruturas químicas, com as propriedades físico-químicas associadas, entre ligantes conhecidos e possíveis alvos; este procedimento de comparação de perfis moleculares, conhecido como virtual profiling, parte do princípio de que moléculas semelhantes a ligantes conhecidos de proteínas têm o potencial de interagir com essa mesma proteína, onde o grau de semelhança é determinado não somente pela estrutura química, mas também pela distribuição de características físico-químicas. As ferramentas utilizadas em estudos in silico incluem também análise de descritores topológicos que permitem a caracterização de propriedades físico-químicas considerando sua distribuição espacial em relação à estrutura química de uma dada molécula. O uso destes descritores permite a determinação do grau de semelhança entre moléculas ou partes de moléculas (fragmentos moleculares), e encontra-se na base das metodologias de triagem e de caracterização de sítios catalíticos de proteínas. Dentro da proposta de trabalho foram realizados estudos envolvendo virtual profiling, análise de fragmentos moleculares com base em descritores físico-químicos capazes de caracterizar superfícies de proteínas e ligantes, caracterização de cavidade catalítica de possível alvo e docking dos compostos a alvos putativos. Foi também realizada a determinação de atividade antifúngica e análise de resultados de QSAR 3D, levando finalmente à construção de uma hipótese quanto ao possível alvo biológico para os compostos azometínicos e oxadiazolínicos. O procedimento de virtual profiling apontou como possíveis alvos as enzimas CYP19A (aromatase), CYP3A4, CYP3A5 e CYP3A7. Embora estas enzimas não estejam diretamente envolvidas com as atividades biológicas testadas para os compostos até o momento, existem estudos que demonstram a interação de compostos azólicos de ação antifúngica, cujo alvo é CYP51 (14α-desmetilase), também com CYP19A e CYP3A4. Em conjunto com a análise da caracterização das propriedades físico-químicas com uso de descritores topológicos e a própria dualidade da atividade biológica, concluiu-se que seria possível a interação dos compostos das séries estudadas com CYP51, sendo esta enzima alvo não somente de antifúngicos azólicos, como também de compostos com ação anti-T. cruzi. A caracterização da cavidade catalítica de CYP51, tanto em termos de descritores de propriedades físico-químicas como de características estereoquímicas, associada ao estudos de QSAR 3D, confirmaram a possibilidade de interação da série oxadiazolínica com a CYP51, em orientação semelhante à dos antifúngicos azólicos. A série azometínica, que apresenta a mesma atividade dual da série oxadiazolínica, embora com potências diferentes, não possui conformação adequada para a interação da forma proposta. Existem, no entanto, dados que indicam a possibilidade de interação de compostos no sítio catalítico da enzima de forma diferente em relação a compostos oxadiazolínicos e antifúngicos azólicos. / This study had as objective the study of Tridimensional Quantitative Structure-Activity Relationships, 3D QSAR, and the identification of potential targets for 5-nitro-heterocyclic compounds with azomethynic or oxadiazolynic structures presenting dual antifungal and anti-T. cruzi bioactivity, aiming the discovery of new compounds to be used as possible drug candidates or lead compounds. The studied compounds belong to four closely related series: AzoO series: 4-substituted 5-nitro-2-furfurylidene benzhydrazides; AzoS Series: 4-substituted 5-nitro-2-thiophylidene benzhydrazides; OxaO Series: 4-substituted 3-acetyl-oxadiazolyne 2,5-furfurylidene benzhydrazides; and OxaS Series: 4-substituted 3-acetyl-oxadiazolyne 2,5-thiophilydene benzhydrazides. The integrated use of tools belonging to the areas of medicinal chemistry, chemoinformatics, and bioinformatics allow for the characterization of catalytic cavities of proteins and the identification of physicochemical properties considered essential for the adequate interaction between ligand and target biomacromolecule. In addition to this, they also make possible the identification of targets through the comparison of chemical structures, with their associated physicochemical properties, of known ligands and their possible targets; this approach, known as virtual profiling, is based on the principle that molecules similar to known ligands of proteins can potentially interact with this same protein, with the similarity degree being determined not only by chemical structure but also through the distribution of physicochemical characteristics. The tools used in studies in silico also include the analysis of topological descriptors that can be used to analyse physicochemical characteristics considering their spacial distribution in relation to the chemical structure of a given molecule. The use of these descriptors makes possible the determination of the similarity degree between molecules or part of molecules (molecular fragments), and is the basis for methodologies of screening and characterization of the catalytic sites or proteins. Considering the proposed objective, studies were carried involving virtual profiling, analysis of molecular fragments based on physicochemical descriptors able to characterize the surface of ligands and proteins, characterization of the catalytic site of a possible target, and docking of the compounds to putative targets. The antifungal activity of compounds was determined and 3D QSAR results analysed, leading to the formulation of a hypothesis for the possible biological target for the azomethynic and oxadiazolynic compounds. Virtual profiling results pointed as possible targets the P450 enzymes CYP19A (aromatase), CYP3A4, CYP3A5, and CYP3A7. Although these enzymes are not directly involved with the currently tested biological activities for these compounds, there are studies reporting the interaction of azole antifungal compounds, whose target is CYP51 (14α-demethylase), with CYP19A and CYP3A4. Taken together with the analysis of physicochemical characteristics based on topological descriptors, and considering the duality of determined biological activities, it was concluded that the interaction of the studied compounds with CYP51 was possible since this enzyme is the target nor only for azole antifungals, but also for anti-T. cruzi compounds. Characterization studies of CYP51 catalytic cavity considering not only physicochemical properties descriptors but also stereochemical characteristics, associated to the results of 3D QSAR, confirmed the possibility of interaction of compounds from the oxadiazolynic series with CYP51, in an orientation similar to azole antifungals. The azomethynic series, that also presents the same dual biological activity though with different potency, does not present an adequate conformation for the ineraction proposed for the oxadiazolynic series; however, there are reports indicating the possibility of interaction of compounds in the catalytic site of the enzyme in a different way from that of antifungal azoles and the proposed interaction of oxadiazolynic compounds.

Este trabalho teve como objetivo a realização de estudos de Relações Quantitativas Tridimensionais Estrutura-Atividade, QSAR 3D, com identificação de alvos potenciais para compostos 5-nitro-heterocíclicos com estruturas azometínica ou oxadiazolínica com bioatividade dual, antifúngica e anti-T. cruzi, visando à identificação de novos compostos que possam ser aproveitados como possíveis candidatos a fármaco ou como compostos-líderes para novos estudos de modificação molecular. Os compostos estudados pertencem a quatro séries intimamente relacionadas, a saber: Série AzoO: 5-nitro-2-furfurilideno benzidrazidas 4-substituídas; Série AzoS: 5-nitro-2-tiofilideno benzidrazidas 4-substituídas; Série OxaO: 3-acetil-oxadiazolina 2,5-furfurilideno benzidrazidas 4-substituídas e Série OxaS: 3-acetil-oxadiazolina 2,5-tiofilideno benzidrazidas 4-substituídas. A utilização de forma integrada de ferramentas pertencentes às áreas de química farmacêutica, quimioinformática e bioinformática permite a caracterização de cavidades catalíticas de proteínas e a identificação das propriedades físico-químicas consideradas essenciais para a interação adequada entre ligante e biomacromolécula-alvo. Por outro lado, permitem também a identificação de alvos a partir da comparação de estruturas químicas, com as propriedades físico-químicas associadas, entre ligantes conhecidos e possíveis alvos; este procedimento de comparação de perfis moleculares, conhecido como virtual profiling, parte do princípio de que moléculas semelhantes a ligantes conhecidos de proteínas têm o potencial de interagir com essa mesma proteína, onde o grau de semelhança é determinado não somente pela estrutura química, mas também pela distribuição de características físico-químicas. As ferramentas utilizadas em estudos in silico incluem também análise de descritores topológicos que permitem a caracterização de propriedades físico-químicas considerando sua distribuição espacial em relação à estrutura química de uma dada molécula. O uso destes descritores permite a determinação do grau de semelhança entre moléculas ou partes de moléculas (fragmentos moleculares), e encontra-se na base das metodologias de triagem e de caracterização de sítios catalíticos de proteínas. Dentro da proposta de trabalho foram realizados estudos envolvendo virtual profiling, análise de fragmentos moleculares com base em descritores físico-químicos capazes de caracterizar superfícies de proteínas e ligantes, caracterização de cavidade catalítica de possível alvo e docking dos compostos a alvos putativos. Foi também realizada a determinação de atividade antifúngica e análise de resultados de QSAR 3D, levando finalmente à construção de uma hipótese quanto ao possível alvo biológico para os compostos azometínicos e oxadiazolínicos. O procedimento de virtual profiling apontou como possíveis alvos as enzimas CYP19A (aromatase), CYP3A4, CYP3A5 e CYP3A7. Embora estas enzimas não estejam diretamente envolvidas com as atividades biológicas testadas para os compostos até o momento, existem estudos que demonstram a interação de compostos azólicos de ação antifúngica, cujo alvo é CYP51 (14α-desmetilase), também com CYP19A e CYP3A4. Em conjunto com a análise da caracterização das propriedades físico-químicas com uso de descritores topológicos e a própria dualidade da atividade biológica, concluiu-se que seria possível a interação dos compostos das séries estudadas com CYP51, sendo esta enzima alvo não somente de antifúngicos azólicos, como também de compostos com ação anti-T. cruzi. A caracterização da cavidade catalítica de CYP51, tanto em termos de descritores de propriedades físico-químicas como de características estereoquímicas, associada ao estudos de QSAR 3D, confirmaram a possibilidade de interação da série oxadiazolínica com a CYP51, em orientação semelhante à dos antifúngicos azólicos. A série azometínica, que apresenta a mesma atividade dual da série oxadiazolínica, embora com potências diferentes, não possui conformação adequada para a interação da forma proposta. Existem, no entanto, dados que indicam a possibilidade de interação de compostos no sítio catalítico da enzima de forma diferente em relação a compostos oxadiazolínicos e antifúngicos azólicos. / This study had as objective the study of Tridimensional Quantitative Structure-Activity Relationships, 3D QSAR, and the identification of potential targets for 5-nitro-heterocyclic compounds with azomethynic or oxadiazolynic structures presenting dual antifungal and anti-T. cruzi bioactivity, aiming the discovery of new compounds to be used as possible drug candidates or lead compounds. The studied compounds belong to four closely related series: AzoO series: 4-substituted 5-nitro-2-furfurylidene benzhydrazides; AzoS Series: 4-substituted 5-nitro-2-thiophylidene benzhydrazides; OxaO Series: 4-substituted 3-acetyl-oxadiazolyne 2,5-furfurylidene benzhydrazides; and OxaS Series: 4-substituted 3-acetyl-oxadiazolyne 2,5-thiophilydene benzhydrazides. The integrated use of tools belonging to the areas of medicinal chemistry, chemoinformatics, and bioinformatics allow for the characterization of catalytic cavities of proteins and the identification of physicochemical properties considered essential for the adequate interaction between ligand and target biomacromolecule. In addition to this, they also make possible the identification of targets through the comparison of chemical structures, with their associated physicochemical properties, of known ligands and their possible targets; this approach, known as virtual profiling, is based on the principle that molecules similar to known ligands of proteins can potentially interact with this same protein, with the similarity degree being determined not only by chemical structure but also through the distribution of physicochemical characteristics. The tools used in studies in silico also include the analysis of topological descriptors that can be used to analyse physicochemical characteristics considering their spacial distribution in relation to the chemical structure of a given molecule. The use of these descriptors makes possible the determination of the similarity degree between molecules or part of molecules (molecular fragments), and is the basis for methodologies of screening and characterization of the catalytic sites or proteins. Considering the proposed objective, studies were carried involving virtual profiling, analysis of molecular fragments based on physicochemical descriptors able to characterize the surface of ligands and proteins, characterization of the catalytic site of a possible target, and docking of the compounds to putative targets. The antifungal activity of compounds was determined and 3D QSAR results analysed, leading to the formulation of a hypothesis for the possible biological target for the azomethynic and oxadiazolynic compounds. Virtual profiling results pointed as possible targets the P450 enzymes CYP19A (aromatase), CYP3A4, CYP3A5, and CYP3A7. Although these enzymes are not directly involved with the currently tested biological activities for these compounds, there are studies reporting the interaction of azole antifungal compounds, whose target is CYP51 (14α-demethylase), with CYP19A and CYP3A4. Taken together with the analysis of physicochemical characteristics based on topological descriptors, and considering the duality of determined biological activities, it was concluded that the interaction of the studied compounds with CYP51 was possible since this enzyme is the target nor only for azole antifungals, but also for anti-T. cruzi compounds. Characterization studies of CYP51 catalytic cavity considering not only physicochemical properties descriptors but also stereochemical characteristics, associated to the results of 3D QSAR, confirmed the possibility of interaction of compounds from the oxadiazolynic series with CYP51, in an orientation similar to azole antifungals. The azomethynic series, that also presents the same dual biological activity though with different potency, does not present an adequate conformation for the ineraction proposed for the oxadiazolynic series; however, there are reports indicating the possibility of interaction of compounds in the catalytic site of the enzyme in a different way from that of antifungal azoles and the proposed interaction of oxadiazolynic compounds.

Le trafic maritime est le principal contributeur des bruits sous-marins anthropique : depuis les années 1970, l’augmentation du trafic maritime hauturier a provoqué dans certaines zones une augmentation du bruit ambiant de plus de 10 dB. En réponse à cette préoccupation, la Directive Cadre pour la Stratégie pour le Milieu Marin (DCSMM) recommande un suivi acoustique. Peu d’études s’intéressent à l’activité côtière et aux bruits rayonnés par les petites embarcations ainsi qu’à leurs conséquences sur la faune marine alors que ces environnements côtiers sont les pourvoyeurs de 41.7 % des services écosystémiques produits par les océans.A mi-chemin entre le monde académique et le monde industriel, le travail présenté aux différents questions scientifiques et industrielles sur la thématique du trafic côtier, en termes de l’étude de son influence dans le paysage acoustique et de capacité à détecter et classifier les embarcations côtières.En l’absence d’information sur le trafic maritime côtier, un protocole d’identification visuelle par traitement d’images GoPro® produisant les mêmes données que l’AIS (position, vitesse, taille et type d’embarcation) est proposé et permet la création de carte du trafic maritime sur un disque de 1.6km de rayon. D’un point de vue acoustique, le trafic est caractérisé par deux descripteurs acoustiques, le SPL lié à la distance du bateau le plus proche et l’ANL caractérisant le nombre de bateaux dans un disque de 500 m de rayon. Le suivi spatio-temporel de ces descripteurs permet d’identifier l’impact du trafic maritime dans le paysage acoustique des environnements côtiers. La détection et la classification sont réalisées après caractérisation individuelle du bruit par un ensemble de paramètres acoustiques et par l’utilisation d’algorithmes d’apprentissage supervisé. Un protocole spécifique pour la création de l’arborescence de classification est proposé par comparaison des données acoustiques aux caractéristiques physiques et contextuelle de chaque bateau.Les travaux présentés sont illustrés sur la flottille d’embarcations côtières présente dans la baie de Calvi (Corse) durant la saison estivale. / Marine traffic is the main contributor to anthropogenic underwater noise: since the 1970s, the increase in deep-sea shipping has increased the ambient noise by more than 10 dB in some areas. In response to this concern, the Marine Strategy Framework Directive (MSFD) recommends acoustic monitoring. Few studies are concerned with coastal activity and the noises radiated by small craft while these coastal environments are the purveyors of 41.7% of the ecosystem services produced by the oceans.Between the academic and the industrial world, this PhD was to answer the different scientific and industrial questions on the topic of the coastal traffic in terms of the influence in the soundscape and the detection and classification of the coastal craft.Without information on the coastal maritime traffic, a visual identification protocol is proposed using GoPro® images processing and produced the same data as the AIS (position, speed, size and type of craft); It allows to create maritime traffic maps on a disk of 1.6km radius. The traffic is characterized by two acoustic descriptors: the SPL linked to the distance of the nearest boat and the ANL linked to the number of boats present in a 500 m radius disc. The spatiotemporal monitoring of these descriptors allows to identify the impact on the maritime traffic on the coastal acoustic landscape. The acoustic detection and the classification are performed after individual characterization of the noise by a set of acoustic parameters and using of supervised machine learning algorithm. A specific protocol for the creation of the classification tree is proposed by comparing the acoustic data with the physical and contextual characteristics of each boat.The methods are applied on the flotilla of coastal boats present in the Bay of Calvi (Corsica) during summer.

<p>New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds.</p><p>The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled.</p><p>The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The <i>in silico</i> solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process. </p>

New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds. The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled. The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The in silico solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process.

Con el fin de relacionar la estructura y la actividad de series de compuestos, es importante usar descriptores moleculares relevantes. Los descriptores GRIND y VolSurf pertenecen a una nueva familia de descriptores llamado libre de alineamiento. Es decir, que no necesitan alinear los compuestos con el fin de comparar sus campos de interacciones molecular. En este estudio se ha aplicado esos descriptores para la selección de reactivos químicos a partir de una amplia base de datos. La selección se ha echo mediante un protocolo que permite maximizar la diversidad de la muestra y así obtener unos compuestos muy informativos. También se ha desarrollado nuevos descriptores de forma que están basado en los cambios de curvatura de la superficie molecular. Los resultados obtenidos indican que los nuevos descriptores de forma se integran muy bien en los descriptores GRIND originales y que permiten identificar los efectos de forma tanto favorable como desfavorable. Además, se ha desarrollado nuevos descriptores libre de alineamiento llamado 'anchor-GRIND' que usan un átomo de cada molécula como punto de referencia para la comparación de los campos de interacciones molecular. Los descriptores 'anchor-GRIND' permiten una descripción mas precisa y mas sencilla que los descriptores GRIND lo que los hace mas relevante para el análisis de ciertas familias de compuestos. / In order to correlate the differences of structure with the differences of activity of series of compounds, it is important to use relevant molecular descriptors. The GRIND and VolSurf descriptors belong to the so-called alignment-free descriptors family. In other words, they do not require to align the compounds in order to compare its molecular interaction fields. In this study, we applied these descriptors to the selection of chemical reagent from a database of compounds. The selection has been done following a protocol which allows to maximize the diversity of the sample and so to obtain some compounds highly informative. In addition we developed new shape descriptors which are based on the changes of curvature of the molecular surface. The results obtained show that the new shape descriptors are well integrated in the original GRIND descriptors. Furthermore, we designed new alignment-free descriptors called 'anchor-GRIND' which use one atom of each molecule as a reference point for the comparison of the molecular interaction fields. The 'anchor-GRIND' descriptors allow a more precise and more simple description than the GRIND descriptors, which makes them more relevant for the analysis of some families of compounds.