Дисертації з теми "Molécules – Informatique"
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Verlan, Serghei. "Systèmes de Head et applications à la bio-informatique." Metz, 2004. http://docnum.univ-lorraine.fr/public/UPV-M/Theses/2004/Verlan.Serghei.SMZ0404.pdf.
This work is situated in the heart of a recent domain: (bio)molecular computing, which is a domain where biology and computer science meet. This domain investigates models of computing having biological inspiration. Head splicing systems, based on the splicing operation, as well as their extensions are one of the most important models of computing in this domain. We concentrated on the study of different extensions of Head systems by showing often optimal universality results with respect to main parameters of these systems what permitted us to establish several frontiers between decidability and undecidability for these extensions. Moreover, we found several common features of these systems and we designed a generic method that permits to prove easily equivalences with classical models of computing. We also considered membrane systems that are inspired by the structure and the functioning of a living cell. We were particularly interested in the combination of these models and Head systems: splicing membrane systems and we solved a number of open problems for these systems. This work manipulates fundamental notions of the theory of computing and of the molecular computing. It gives solutions to certain important open problems of the last domain and it poses at the same time several interesting questions
Sperandio, Olivier. "Applications et développements informatiques de protocoles de drug design et criblage virtuel." Paris 5, 2007. http://www.theses.fr/2007PA05P612.
This thesis in structural bioinformatics and chemoinformatics concentrates on the optimization of the therapeutics compounds identification process. It relies on the three main components of the chemical compounds virtual screening: preparation of a computational version of the chemical library to be screened; identification of novel active compounds using chemical similarity with respect to known active molecules (LBVS); and identification of novel active compounds using the 3D structure of the target binding site (SBVS). This work implied: to develop a computer program (MED-3DMC) that generates conformation ensembles of small molecules ; then to create a LBVS program (MED-SuMoLig) that can screen thousands of chemical compounds using their pharmaco-topological profile; and finally to use a hierarchical SBVS procedure to identify novel inhibitors for protein-membrane interaction using the coagulation factor Va as a proof of concept
Qin, Zhengran. "Nanoréseaux auto-organisés de molécules électroactives : propriétés des nanodomaines moléculaires." Paris 7, 2012. http://www.theses.fr/2012PA077119.
We have developed molecular functionalized nanodomains and studied their properties which depend on their sizes and chemical environment. Two ways based on the self-assembly of monolayers SAMs have been followed to build these nanodomains: by self-exchange at grain boundaries of the alkylthiol SAM and by replication of a nanostructured inorganic template growing by self organization on Au(lll). The electroactive molecules are functionalized alkyl thiols by the "semiconductor" group tertiophene (3T) or by the electroactive juglone (Jug) function. The electronic properties of 3TCnSH domains were studied by STM. The electrochemical properties and infrared spectroscopic of the juglonethiol domain (JugS(CH₂)₄SH) were analyzed through modeling, and correlated with the size of domains. The later System nano2D showed an enhanced biodetection for ODN hybridation and could be replicated in 3D network
Fathallah, Mohamed. "Calcul et localisation de l'énergie d'une molécule : programmation informatique et applications en mécanique moléculaire, et essai de décomposition atomique en mécanique quantique." Aix-Marseille 3, 1991. http://www.theses.fr/1991AIX30025.
Gaüzère, Benoit. "Application des méthodes à noyaux sur graphes pour la prédiction des propriétés des molécules." Phd thesis, Université de Caen, 2013. http://tel.archives-ouvertes.fr/tel-00933187.
Gaüzère, Benoît. "Application des méthodes à noyaux sur graphes pour la prédiction des propriétés des molécules." Caen, 2013. http://www.theses.fr/2013CAEN2043.
This work deals with the application of graph kernel methods to the prediction of molecular properties. In this document, we first present a state of the art of graph kernels used in chemoinformatics and particurlarly those which are based on bags of patterns. Within this framework, we introduce the treelet kernel based on a set of trees which allows to encode most of the structural information encoded in molecular graphs. We also propose a combination of this kernel with multiple kernel learning methods in order to extract a subset of relevant patterns. This kernel is then extended by including cyclic information using two molecular representations defined by the relevant cycle graph and the relevant cycle hypergraph. Relevant cycle graph allows to encode the cyclic system of a molecule
Hiblot, Nicolas. "Informatique instrumentale (logiciels et matériels) d’un spectromètre de Résonance Quadrupolaire Nucléaire : Nouvelle méthode de détection des molécules azotées." Thesis, Nancy 1, 2008. http://www.theses.fr/2008NAN10010/document.
In spite of a renewed interest in NQR (NQR), especially of nitrogen-14 (for instance, for the detection and characterization of explosives), a full NQR instrument, ready to use in the laboratory, is not commercially available. This thesis is devoted to the design of an entirely homemade spectrometer, reasonably transportable, including the transmit-receive system, frequency generation, data acquisition, probes and a specialized software for driving the instrument and for data processing. The essential contribution of this thesis is the software for managing the whole instrument and controlling various experiences. Moreover, a new method is proposed for improving NQR sensitivity. It is based on a particular processing of the NQR signal
Wieczorek, Samuel. "Une mesure d'inclusion entre objets structurés : application à la classification de molécules." Phd thesis, Grenoble 1, 2009. http://www.theses.fr/2009GRE10121.
The identification of bioactive molecules is a major problem in biology and medicinal chemistry. The discovery of such molecules is mainly based on the screening of large chemical libraries, that are small regarding the size of the chemical space. In this context, scientists need automatic tools to analyze and design rational chemical libraries. The subject of this thesis is to provide a tool that is able to compare molecules or, more generally, structured objects. We propose a generic algorithm which identifies several common substructures between two structured objects (such as graphs or logical formulae), and evaluates an inclusion index between theses objects. This inclusion index corresponds to a real value subsumption test, and should complete the theta subsumption test which is classically used in relational learning algorithms. In the field of chemistry, a molecular similarity measure, defined with two inclusion indexes, allows to classify compounds with respect to their structures. The algorithm is more efficient than the molecular similarity measures or the kernel functions it was compared to. The algorithm may be used to predict the bioactivity of chemical compounds
Wieczorek, Samuel. "Une mesure d'inclusion entre objets structurés : application à la classification de molécules." Phd thesis, Université Joseph Fourier (Grenoble), 2009. http://tel.archives-ouvertes.fr/tel-00406361.
L'objectif de cette thèse est de fournir un outil de comparaison des molécules et plus généralement d'objets structurés. Nous proposons dans ce travail un algorithme générique qui identifie plusieurs sous-structures communes à entre deux objets, représentés par des graphes ou des formules logiques et évalue un degré d'inclusion entre ces objets.
Ce degré d'inclusion correspond à un test de subsomption à valeur réelle entre formules logiques qui pourrait compléter le test de theta-subsomption classique dans les algorithmes d'apprentissage relationnel. Dans le domaine de la chimie, une mesure de similarité moléculaire a été définie à partir de deux degrés d'inclusion pour classer des molécules. L'algorithme se révèle être plus performant que les mesures de similarité et fonctions noyau auxquelles il a été comparé. Il pourra être envisagé de l'utiliser dans des problèmes de prédiction de bio-activité.
Douguet, Dominique. "Etude des interactions protéine-protéine et protéine-ligand par bio- et chimie-informatique structurale : Identification de petites molécules bio-actives." Habilitation à diriger des recherches, Université de Nice Sophia-Antipolis, 2007. http://tel.archives-ouvertes.fr/tel-00320089.
La modélisation par homologie permet d'obtenir un modèle tridimensionnel d'une protéine lorsque sa structure n'a pas été déterminée expérimentalement. Ma contribution dans ce domaine fut la réalisation du serveur @TOME avec le soutien de la GENOPOLE Languedoc-Roussillon (accessible à l'adresse http://bioserver.cbs.cnrs.fr). Ce serveur était le premier de ce type à avoir été développé en France. Le serveur @TOME rassemble et traite d'une manière automatique toutes les étapes nécessaires à la construction d'un modèle 3D d'une protéine. Cela inclut la reconnaissance du repliement, la construction des modèles protéiques et leur évaluation. Les résultats du CASP5 en 2005 (session internationale d'évaluation des méthodes de prédiction de la structure des protéines ; http://predictioncenter.llnl.gov/) ont montré que notre serveur utilisé en mode automatique propose des modèles très proches de la structure expérimentale lorsque l'identité de séquence avec la structure support est supérieure à 30%. Le serveur a été classé 26ième sur 187 groupes inscrits.
Dans un second temps, mes recherches m'ont permis de réaliser une base de données de complexes protéiques co-cristallisés, base fondatrice du projet DOCKGROUND. Ce projet de grande envergure, soutenu par le NIH depuis 2005, vise à établir un système intégré et dynamique de bases de données dédié à l'étude et à la prédiction des interactions entre protéines et permettre ainsi d'améliorer nos connaissances des interactions et de développer des outils de prédiction plus fiables. Ce travail a été effectué au sein de l'équipe du Pr. Ilya Vakser à l'Université de Stony Brook, NY, USA. Dans la réalisation de cette première base de données, un ensemble de programmes collectent, classent et annotent les complexes protéiques qui ont été co-cristallisés (données sur la séquence, la fonction, le repliement 3D, les particularités telles qu'une fixation à de l'ADN, ...). Ensuite, j'ai mis en œuvre une sélection dynamique des représentants des complexes contenus dans cette base. Les représentants sont essentiels pour éviter une surreprésentation de certaines familles de protéines. Cette base de donnée est accessible par Internet et est régulièrement mise à jour (http://dockground.bioinformatics.ku.edu). Le projet DOCKGROUND va être poursuivi par la réalisation de 3 autres bases de données qui s'ancreront sur la présente appelée ‘Bound-Bound'.
L'objectif principal de mes travaux est d'identifier de nouveaux composés bio-actifs afin de comprendre le fonctionnement de leur cible dans un contexte biologique. Les méthodes que j'utilise se basent sur la chémoinformatique, le criblage virtuel et le de novo ‘drug design'. Dans le cadre de ce dernier, j'ai mis au point un programme propriétaire LEA3D (‘Ligand by Evolutionary Algorithm' 3D). Le programme génère des petites molécules à partir de la combinaison de fragments moléculaires issus de drogues et de molécules ‘bio' (substrats ou produits de réactions enzymatiques). Le criblage virtuel basé sur la structure protéique et le de novo ‘drug design' par LEA3D, ont été appliqués avec succès à la thymidine monophosphate kinase (TMPK) de Mycobacterium tuberculosis dans le cadre d'une collaboration avec une équipe de chimistes et de biologistes de l'Institut Pasteur. De nouvelles familles d'inhibiteurs ont été identifiées dont un inhibiteur synthétique trois fois plus affin que le substrat naturel. Plusieurs publications et une demande de brevet couvrent les résultats de ces recherches. Dans la continuité de ces travaux, je m'intéresse maintenant, plus particulièrement, à développer des stratégies de criblages de fragments (molécules de petit poids moléculaire). Il a été montré que de petites chimiothèques contenant des petites molécules polaires sont plus efficaces pour identifier des touches. Ce travail doit être réalisé conjointement avec des criblages structuraux expérimentaux comme la RMN ou la diffraction des rayons X. Ces derniers se posent comme une alternative aux tests in vitro avec pour avantage de donner une information détaillée, au niveau atomique, des interactions entre le ligand et sa cible. S'ensuit une étape d'optimisation/maturation des touches en ligands plus élaborés et plus affins par l'utilisation d'outils de chémoinformatique.
Krier, Mireille. "Conception rationnelle de chimiothèques focalisées." Strasbourg 1, 2005. https://publication-theses.unistra.fr/public/theses_doctorat/2005/KRIER_Mireille_2005.pdf.
The main goal of this present work was to develop a new approach making the compromise between a minimum size and maximal molecular diversity for a compound library. This key issue in medicinal chemistry was tackled with computer assisted library design enumerating systematically molecules which acquire their structural complexity through combinations of three types of building blocks: scaffolds (S), linkers (L) and functional groups (F). A scaffold library was created from commercially available screening collections. In order to analyze the chemical diversity of these libraries, a general workflow was developed aimed at (1) identifying drug-like compounds, (2) cluster them by common substructures (scaffolds) and (3) measure the scaffold diversity encoded by each screening collection independently of its size. The combinatorial scaffold-based library concept (SLF) was illustrated by the lead optimization of a known PDE4 inhibitor, zardaverine. A library of 320 molecules was evaluated by virtual screening techniques which selected 9 compounds for synthesis and biological assay. This led to a 900 fold increase of affinity in comparison to zardaverine in one screening cycle
Nguyen, Ngoc Thanh Dien. "Détermination de nouvelles constantes atomiques de lipophilie utilisables pour la prévision du log P d'une molécule." Bordeaux 2, 1996. http://www.theses.fr/1996BOR2B002.
Nouleho, ilemo Stefi. "Algorithmique de graphes pour la similarité structurelle de molécules et de réactions." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG028.
A synthesis pathway is, for a given molecule, a sequence of reactions making possible to obtain it from purchasable molecules or easily synthesizable. In chemoinformatics, predicting or assisting the conception of synthesis pathways for new molecules is a challenge. It consists in analyzing the very large databases of existing molecular reactions to build new synthesis pathways from existing plans of similar molecules. In this context, the similarity between molecules relies on their topology.We introduce a structural representation of molecules called the graph of cycles. This representation is based on the cycles in the molecular graph and their interconnections.This representation is canonical and allows us to define a similarity measure between structures of molecules and is computable in a reasonable amount of time. Our studies show that it is more adapted for works on synthesis pathways than the other existing similarity measures.Based on the graph of cycles, we proposed a classification of reactions according to the effects on the structure of molecules. This is the first step for the prediction of synthesis pathways
Poezevara, Guillaume. "Fouille de graphes pour la découverte de contrastes entre classes : application à l'estimation de la toxicité des molécules." Phd thesis, Université de Caen, 2011. http://tel.archives-ouvertes.fr/tel-01018425.
Del, Rio Alberto. "Mécanismes de reconnaissance chirale en chromatographie liquide haute performance : études théoriques et chimio-informatiques." Aix-Marseille 3, 2005. http://www.theses.fr/2005AIX30061.
Combined theoretical and chemoinformatics studies are presented in the field of enantioselective recognition. Several approaches are used such as molecular modeling, DFT calculations, molecular dynamics, QSAR techniques and other data mining procedures. The focus is the establishment of connections between available experimental data and these diverse algorithms based on the mathematical and topological description of chiral molecules. The outcomes of the aforementioned calculations account for a use of these techniques as a core strategy to achieve reliable prediction systems, infer the mechanisms of chiral recognition, generate new lead chiral receptors and assist experimental techniques such as chiral liquid chromatography. Moreover, computational methods promise to have a wide range of applications for both academia and industries, ranging from enantioselective reactions to analytical and semi-preparative separations or large-scale, production of enantiopure compounds
Bournez, Colin. "Conception d'un logiciel pour la recherche de nouvelles molécules bioactives." Thesis, Orléans, 2019. http://www.theses.fr/2019ORLE3043.
Kinases belong to a family of proteins greatly involved in several aspects of cell control including division or signaling. They are often associated with serious pathologies such as cancer. Therefore, they represent important therapeutic targets in medicinal chemistry. Currently, it has become difficult to design new innovative kinase inhibitors, particularly since the active site of these proteins share a great similarity causing selectivity issues. One of the main used experimental method is fragment-based drug design. Thus, we developed our own software, Frags2Drugs, which uses this approach to build bioactive molecules. Frags2Drugs relies on publicly available experimental data, especially co-crystallized ligands bound to protein kinase structure. We first developed a new fragmentation method to acquire our library composed of thousands of three-dimensional fragments. Our library is then stored as a graph object where each fragment corresponds to a node and each relation, representing a possible chemical bond between fragments, to a link between the two concerned nodes. We have afterwards developed an algorithm to calculate all possible combinations between each available fragment, directly in the binding site of the target. Our program Frags2Drugs can quickly create thousands of molecules from an initial user-defined fragment (the seed). In addition, many methods for filtering the results, in order to retain only the most promising compounds, were also implemented. The software were validated on three protein kinases involved in different cancers. The proposed molecules were then synthesized and show excellent in vitro activity
Kerkache, Asma. "Nouveaux chemins d'accès à des molécules-aimants multifonctionnelles par post-fonctionnalisation." Thesis, Lyon, 2021. http://www.theses.fr/2021LYSE1307.
Virtual storage spaces (Cloud) has become common today. However, these are not dematerialized and are hosted in data centers (Data Center), they are bulky and energy consuming. Research in the field of magnetic information storage has made considerable progress with, among others, the discovery of single-molecule magnets (SMMs). These compounds could significantly increase the storage capacities of future hard drives. Magnet molecules are complexes of coordination chemistry or organometallic chemistry, isolated from each other. They have intrinsic magnetic properties unlike conventional magnets where the magnetic information retention properties come from a cooperative effect of all molecules in the material. This therefore results in a noticeable difference in the capacity for storing information. The first magnet-molecule, the famous [Mn12], was discovered in 1980. Its magnetic properties were characterized a few years later, thus opening a new chapter in the field of molecular magnetism. The characteristics of a molecule-magnet are linked to the energy barrier that defines these complexes: ΔE = | D | S² (D for anisotropy and S for the spin of the complex). From 2003, the replacement of transition metals by lanthanide ions revolutionized research in this field. Previous laboratory work has shown that the nuclearity of molecular structures and the number of ligands have a major impact on the magnetic properties of the molecule-magnet. It turns out that the simplest complexes are generally those with the best performance. The main subject of the thesis is to develop mononuclear complexes. The idea is to be able to subsequently modify these compounds by post-functionalization of the organic ligand in order to exacerbate the magnetic performances and / or to add new properties (luminescence for example, multifunctionality) to the initial molecule-magnet. To do this, a library of original β-diketone ligands was produced. These ligands have functions which subsequently make it possible to carry out organic modification reactions on the magnet molecule. Two post-functionalization reactions were thus considered: a Palladium-coupling reaction (Sonogashira or Suzuki-Miyaura) and a click reaction (Huisgen cycloaddition). A second aim of this thesis is based on the results of a recent theoretical study which proposes the use of the sulfur atom in the coordination sphere of the metal center of the SMM. The latter would improve the axiality of the molecule and therefore the magnetic properties of the final molecular structure. The synthesis of sulfur analogues of β-diketone ligands was then undertaken to study the influence of the sulfur atom compared to its oxygenated counterparts in the final magnet molecule. β-monothioketone and keto-sulfoxide ligands have therefore been synthesized. The corresponding lanthanide ion-based complexes have been isolated, their molecular structures as well as their magnetic and luminescence properties have been characterized
Martiny, Virginie. "Vers la prédiction des propriétés ADME-Tox des molécules à visée thérapeutique par une approche basée sur la structure des enzymes du métabolisme." Paris 7, 2013. http://www.theses.fr/2013PA077175.
Predicting ADME-Tox (Absorption, Distribution, Metabolism, Excretion and Toxicity) properties of drug candidates early in drug discovery process is critical to detect compounds with undesirable drug-like profile. Drug metabolizing enzymes are capable to modify compounds by interacting with them or can be involved in drug¬drug interactions. Cytochromes P450 (CYPs) and sulfotransferases (SULTs) are key drug metabolizing enzymes catalyzing oxidation and sulfoconjugation, respectively, leading to a possible modification of ADME-Tox properties of compounds, and in some cases to toxicity. The goal of this PhD study was to predict interactions of drug candidates with CYPs and SULTs, using in silico structure-based methods. We thus developed an approach based on docking/scoring methodology that considered the important flexibility of their active site by using molecular dynamic simulations (MD). When applied on CYPs, our protocol identified three MD-derived structures successfully discriminating active and inactive compounds. Regarding SULTs, we also identified several MD-derived structures able to correctly discriminate active and inactive compounds. In addition, we incorporated docking/scoring results of SULTs to create QSAR models. We anticipate to make our approach freely accessible to the scientific community to be able to predict interactions of their compounds of interest with CYPs and SULTs
Bricage, Marie. "Modélisation et Algorithmique de graphes pour la construction de structures moléculaires." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLV031/document.
In this thesis, we present an algorithmic approach allowing the generation of construction guides of organic molecular cages. These semi-molecular architectures have a defined internal space capable of trapping a target molecule called substrate. Many works propose to generate molecular organic cages obtained from symmetrical structures, which have a good complexity, but they are not specific because they do not take into account precise targets. The proposed approach makes it possible to generate guides for the construction of organic molecular cages specific to a given substrate. In order to ensure the specificity of the molecular cage for the target substrate, an intermediate structure, which is an expansion of the envelope of the target substrate, is used. This structure defines the shape of the space in which the substrate is trapped. Small sets of atoms, called molecular binding patterns, are then integrated into this intermediate structure. These molecular patterns are the sets of atoms needed by molecular cages to allow them to interact with the substrate to capture it
Belghit, Hayet. "VASSIMODo - Analyse visuelle des structures secondaires en dynamique moléculaire." Electronic Thesis or Diss., Reims, 2024. http://www.theses.fr/2024REIMS003.
Numerical simulations are increasingly used in molecular modelling. With the evolution of high-performance computing thanks to new generations of processors, these simulations are produced for increasingly complex systems over ever longer durations. The emergence of advanced graphics rendering has underscored the pivotal role of images. These advancements have given rise to the scientific visualization field, which focuses on generating comprehensible and interactive graphical representations of scientific data. It enables the visual exploration, analysis, and interpretation of numerical results, as well as the communication of scientific results. Combining scientific simulation and interactive visualization has become essential for observing, analyzing, and understanding complex phenomena. In structural biology, there are a number of static visualization methods for molecules. While they have been adapted to the frame-by-frame visualization of a simulation, they do not consider changes over time to visualize them.In this thesis, we focus on the visualization of protein secondary structures in the context of molecular dynamics simulations. Proteins represent one of the four main categories of organic compounds essential to the cell. They are biological macromolecules composed of one or more polypeptide chains. Due to the varied chemical properties of the amino acids making up the protein, their position along the polypeptide chain influences their spatial arrangement, forming regular structural patterns such as α-helices, β-sheets and turns. This organization is referred to the secondary structure of proteins, stabilized by hydrogen bonds between neighboring amino acid residues.The aim of this work is to create a 4D (3D+time) method for visually analyzing molecular simulations of protein secondary structures. To do so, for each structural pattern (β-sheet, α-helix, turn), we developed a dedicated representation enabling us to visualize and quantify their amplitude of movement, as well as other properties that facilitate visual analysis. This method provides a better understanding of the usefulness of these structures and highlights their function throughout a simulation.VASSIMODo (Visual Analysis of Secondary Structures in MOlecular Dynamics) is a method for the visual analysis of protein secondary structures, enabling to study the fluctuation of structural patterns throughout a molecular dynamics simulation. It detects which structural elements move the most or are the most stable during a trajectory. It represents this fluctuation graphically and quantifies it. To analyze long trajectories, this method can be applied to a sliding window to evaluate partial behaviour. In addition, VASSIMODo provides a static image that shows the fluctuation of secondary structures during a simulation, facilitating the dissemination of scientific results.This thesis was carried out within the multi-disciplinary Multiscale Modeling and Imaging (MIME) team as part of the CNRS project of the UMR 7369 MEDyC unit, focusing on the characterization of matrix remodeling in pathophysiological conditions and on technological developments for healthcare
Canault, Baptiste. "Développement d'une plateforme de prédiction in silico des propriétés ADME-Tox." Thesis, Orléans, 2018. http://www.theses.fr/2018ORLE2048/document.
Absorption, Distribution, Metabolism, Elimination (ADME) and Toxicity (Tox) properties are crucial for the success of clinical trials of a drug candidate. During this process, chemoinformatics is regularly used to predict the ADME-Tox profile of bioactive compounds and to improve their pharmacokinetic properties. In silico approaches have already been developed to improve poor pharmacokinetics and toxicity of lead compounds. These predictive models, based on the quantification of structure-activity relationships (QSAR), were not always efficient enough due to the low number of accessible biological data and their heterogeneity induced by the differences in experimental assays or the significant experimental error. In this thesis, we first built a database containing 150,000 data points for about 50 ADME-Tox properties. In order to valorize all this data, we then proposed an automatic platform for creating predictive models. This platform, called MetaPredict, has been designed to optimize each step of model development, in order to improve their quality and robustness. Third,, we promoted the statistical models using the online application of MetaPredict platform. This application has been developed to facilitate the use of newly built models, to provide a simplified interpretation of the results and to modulate the obtained observations according to the needs of the researchers. Finally, this platform provides an easy access to the ADME-Tox models for the scientific community
Maes, Hervé. "Etude théorique et expérimentale de la rotation interne dans des molécules d'intérêt astrophysique : réalisation d'un programme informatique calculant le spectre et application à l'analyse en ondes millimétriques de l'acétaldéhyde, du méthylthiocyanate, du méthylthioéthyne et du propanal." Lille 1, 1986. http://www.theses.fr/1986LIL10141.
Martinez, Xavier. "Tracking sans marqueur de modèles physiques modulaires et articulés : vers une interface tangible pour la manipulation de simulations moléculaires." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS231/document.
Physical molecular models have long been used in the structural biology and chemistry fields. Despite the emergence of numerical representations offering various and dynamic molecular visualizations to analyze the simulation results, molecular physical models are still being used. Direct manipulation and assembly of physical models ease to create and memorize a mental representation of 3D molecular structures. Interaction techniques to manipulate virtual 3D objects are not reaching the fineness and the benefits of the perceptual cues and manipulation skills of physical models. Moreover, interacting with virtual molecular representations remains a hard task because of the complexity of molecular structures, their size, their flexibility and the various data that define them. In this thesis, we address this issue by designing a molecular tangible interface combining the perks of physical and virtual representations. To match the flexibility and modularity of biomolecules to manipulate, this work met challenges in different scientific fields with the constraint to not use a tracker based system. The first step was to choose, conceive and build a physical model to handle the manifold degrees of freedom of molecules. The second step consisted in creating a numerical representation of mechanical properties of the physical model. Lastly, we needed to develop tracking methods using real-time image processing algorithms in order to control the virtual representation by coupling it to the physical one. New image processing methods have been implemented and evaluated to identify and track atoms in the image space. A Structure from Motion method was designed and adapted to reconstruct in 3D the atom positions by using a small amount of points and by including biochemical knowledge to guide the reconstruction. At last, we address the visualization of physical and dynamic virtual representations, sometimes co-localized in an Augmented Reality context. High performance visualization methods adapted to this context have been developed to enhance shape and cavity perception, two major specifics of biological molecules. For instance, ambient occlusion or sphere raycasting with dynamic shadows can augment a physical object taking the real illumination of the scene for a better insertion in an Augmented Reality context. The impact of this work targets both the education in molecular biology and the research field: the rational drug design field could benefit from the expertise of the user to optimize the design of drugs by manipulating biomolecule's numerous degrees of freedom using a tangible interface. Just like Fold'It is contributing to solve the folding problem, a similar approach could be used to solve the molecular docking problem using advanced manipulation interfaces
Le, Guilloux Vincent. "Développement de méthodes et d’outils chémoinformatiques pour l’analyse et la comparaison de chimiothèques." Thesis, Orléans, 2013. http://www.theses.fr/2013ORLE2079/document.
Some news areas in biology ,chemistry and computing interface, have emerged in order to respond the numerous problematics linked to the drug research. This is what this thesis is all about, as an interface gathered under the banner of chimocomputing. Though, new on a human scale, these domains are nevertheless, already an integral part of the drugs and medicines research. As the Biocomputing, his fundamental pillar remains storage, representation, management and the exploitation through computing of chemistry data. Chimocomputing is now mostly used in the upstream phases of drug research. Combining methods from various fields ( chime, computing, maths, apprenticeship, statistics, etc…) allows the implantation of computing tools adapted to the specific problematics and data of chime such as chemical database storage, understructure research, data visualisation or physoco-chimecals and biologics properties prediction.In that multidisciplinary frame, the work done in this thesis pointed out two important aspects, both related to chimocomputing : (1) The new methods development allowing to ease the visualization, analysis and interpretation of data related to set of the molecules, currently known as chimocomputing and (2) the computing tools development enabling the implantation of these methods
Ciobanu, Mihai. "DNA display : a novel strategy for the rapid selection of small molecule ligands." Thesis, Strasbourg, 2012. http://www.theses.fr/2012STRAF018.
The discovery of srnall molecules capable of modulating biological systems is of major interest for the understanding of cellular mechanisms as weil as for the drug discovery process. In spite of established high throughput techniques routinely used, there is a clear need to reduce the time and cost •associated to ligand discovery, in order to validate the function of numerous potential targets in our proteome or the one of pathogens. In this perspective, the emergence of technologies based on nucleic acid encoding of chemical libraries presents an alternative that fulfills these criteria. We have developed a system enabling the rapid synthesis of libraries containing various structures, conjugated to unique PNA (peptide nucleic acid) tags, a weil as a screening technique based on affinity selection that allows for the rapid study of the interaction witb a target protein and the consequent identification of new ligands. Several libraries have already been synthesized and screened, and based on the remarkable chemical stability of PNA, we have also developed a new palette of reactions compatible with PNA-encoded synthesis, the path now being open for the generation of more complex libraries, and the study of various biological targets
Malinenko, Alla. "Effet d’ion specifique sur l’auto-assemblage d’amphiphiles cationiques : des approches experimentale et informatique." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0065/document.
The present study is a holistic approach focused on the investigation of ion specific effects on the self-assembly properties of cationic gemini surfactants. Our main focus was on the effect of various counterions on the self-organization features of cationic surfactants in aqueous solution. In order to obtain amore comprehensive understanding of the effect of interfacial ionic and molecular interactions on aggregate properties we used different approaches. We combined an experimental study focused on the bulk solution properties (critical micelle concentration, ionization degree, aggregation number, etc.), with approaches focused on investigating the interfacial micellar properties by analyzing the interfacial counterion and waterconcentrations, experimentally (chemical trapping) and computationally (molecular dynamic simulations). Moreover, the impact of counterion nature was investigated by studying the growth of wormlike micelles using rheology. Besides the examination of the surfactants properties in solution, the ion specific effects onthe crystalline structures of gemini surfactants were studied.We found that ion specific effects which determine the behavior of micellar aggregates of cationic quaternary ammonium gemini in aqueous solutions strongly depend on the free energy of hydration of the counterions, in others words, on their hydrophilic/hydrophobic properties. Contrarily to aqueous solution, in crystals, the size of the ion becomes the determining factor. Comparison of the results obtained for the same system in aqueous solution and in solid state showed the importance of ion-water interactions in ion specific effects. However, one should note that the properties of substrate (the gemini in our case) should be taken into account not less carefully in order to fully predict Hofmeister effects
Ghemtio, Wafo Léo Aymar. "Simulation numérique et approche orientée connaissance pour la découverte de nouvelles molécules thérapeutiques." Thesis, Nancy 1, 2010. http://www.theses.fr/2010NAN10103/document.
Therapeutic innovation has traditionally benefited from the combination of experimental screening and molecular modelling. In practice, however, the latter is often limited by the shortage of structural and biological information. Today, the situation has completely changed with the high-throughput sequencing of the human genome, and the advances realized in the three-dimensional determination of the structures of proteins. This gives access to an enormous amount of data which can be used to search for new treatments for a large number of diseases. In this respect, computational approaches have been used for high-throughput virtual screening (HTVS) and offer an alternative or a complement to the experimental methods, which allow more time for the discovery of new treatments.However, most of these approaches suffer the same limitations. One of these is the cost and the computing time required for estimating the binding of all the molecules from a large data bank to a target, which can be considerable in the context of the high-throughput. Also, the accuracy of the results obtained is another very evident challenge in the domain. The need to manage a large amount of heterogeneous data is also particularly crucial.To try to surmount the current limitations of HTVS and to optimize the first stages of the drug discovery process, I set up an innovative methodology presenting two advantages. Firstly, it allows to manage an important mass of heterogeneous data and to extract knowledge from it. Secondly, it allows distributing the necessary calculations on a grid computing platform that contains several thousand of processors. The whole methodology is integrated into a multiple-step virtual screening funnel. The purpose is the consideration, in the form of constraints, of the knowledge available about the problem posed in order to optimize the accuracy of the results and the costs in terms of time and money at various stages of high-throughput virtual screening
Andronov, Leonid. "Development of advanced methods for super-resolution microscopy data analysis and segmentation." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAJ001.
Among the super-resolution methods single-molecule localization microscopy (SMLM) is remarkable not only for best practically achievable resolution but also for the direct access to properties of individual molecules. The primary data of SMLM are the coordinates of individual fluorophores, which is a relatively rare data type in fluorescence microscopy. Therefore, specially adapted methods for processing of these data have to be developed. I developed the software SharpViSu and ClusterViSu that allow for most important data processing steps, namely for correction of drift and chromatic aberrations, selection of localization events, reconstruction of data in 2D images or 3D volumes using different visualization techniques, estimation of resolution with Fourier ring correlation, and segmentation using K- and L-Ripley functions. Additionally, I developed a method for segmentation of 2D and 3D localization data based on Voronoi diagrams, which allows for automatic and unambiguous cluster analysis thanks to noise modeling with Monte-Carlo simulations. Using advanced data processing methods, I demonstrated clustering of CENP-A in the centromeric regions of the cell nucleus and structural transitions of these clusters upon the CENP-A deposition in early G1 phase of the cell cycle
Dubuisson, Duplessis Guillaume. "Modèle de comportement communicatif conventionnel pour un agent en interaction avec des humains : Approche par jeux de dialogue." Phd thesis, INSA de Rouen, 2014. http://tel.archives-ouvertes.fr/tel-01017542.
Daouda, Tariq. "L’usage des codons régule la présentation des peptides associés aux molécules du CMH-I." Thèse, 2018. http://hdl.handle.net/1866/21796.