La protéine RAD51 est l’un des acteurs majeurs des mécanismes de la résistance et de la reconstruction des cellules cancéreuses. La modulation de son activité ouvre une nouvelle voie dans la lutte contre le cancer. De nouveaux inhibiteurs potentiels de RAD51 ont été recensés, notamment, les dérives du stilbène disulfonique (SD). Dans cette thèse, nous étudions ces inhibiteurs dans différents milieux (solvant et protéine). La première partie de cette thèse est dédiée à l’étude des propriétés physico-chimiques en solution des dérivés SD. À l’aide de spectres optiques expérimentaux et de simulations par calculs quantiques (DFT et TD-DFT), nous avons montré que les SD se présentent sous leur forme dianionique en condition physiologique et la prise en compte du couplage vibronique est cruciale pour simuler des bandes des spectres d’absorption. La seconde partie se focalise sur la modélisation du complexe SD2- en interaction avec la protéine de transport albumine sérique humaine (ASH), qui joue un rôle prépondérant dans le transport de molécule au sein du corps humain. Elle apparaît être un excellent candidat pour acheminer des inhibiteurs SD2- vers les cellules cancéreuses. Sans donnée cristallographique du complexe ASH-SD2-, la modélisation moléculaire est le seul outil prédictif utilisable pour obtenir des données structurales, et nous avons associé ici des méthodes de docking moléculaire et de dynamique moléculaire. Cette méthodologie nous a permis (i) d’identifier le(s) résidu(s) important(s), (ii) d'évaluer les énergies d'interaction par des calculs MM-GBSA et (iii) d'identifier les sites d’accueil les plus adéquats pour les composés de type SD2-. / In this PhD thesis, the SD behavior is studied in various environments (in solution and within protein). In the first part, the physico-chemical properties of SD molecules in solution are explored in a joint experimental and theoretical (DFT and TD-DFT) investigation. The latter demonstrates the dianionic nature of SD compounds in physiological conditions and indicates that accounting for vibronic coupling is crucial to reproduce the bandshape of the absorption spectra. The second part is focused on the modeling of SD2- complexes within a carrier protein, the human serum albumin (HSA), which is essential for the drug transport process through the human body. HSA appears to be an excellent candidate to carry SD2- compounds into cancer cells. Without any cristallographic structure of HSA-SD2- complex, molecular modelling is the only predictive tool to obtain structural data. We performed molecular docking and molecular dynamic methodology to (i) identify the key residues, (ii) investigate the complex energies by MM-GBSA calculations and (iii) determine the most potent binding sites to host SD2- derivatives.

O surgimento de novas substâncias psicoativas (NPS-New Psychoactive Substances) levantou muitas questões no contexto da aplicação da lei e políticas públicas de drogas. De acordo com o Escritório das Nações Unidas sobre Drogas e Crime (UNODC- United Nations Office on Drugs and Crime) como uma alternativa às drogas proibidas. Esses novos compostos foram projetados e formulados para escapar à legislação de controle de drogas, criando um fenômeno que se tornou um problema internacional. No Brasil, essas substâncias são controladas e penalmente puníveis, no pela Lei 11.343/2006, também conhecida como Lei de Drogas. Este trabalho traz estudos relativos às catinonas sintéticas com metodologia in silico para investigar mecanismos de detecção e tendência de atuação no organismo humano. No estudo relacionado à detecção utilizamos a reação dessas drogas com o isotiocianato de fluoresceína (FITC Fluorescein isothiocyanate). Para essa proposta foram feitos estudos de viabilidade de métodos de cálculo, análise conformacional do FITC, avaliação energética da reação com as catinonas e os espectros de emissão. Em relação à viabilidade dos métodos de cálculo temos que a otimização prévia dos compostos envolvidos com o semi-empírico PM6 e posterior refinamento com o método B3LYP/6-31G** foram adequados para os cálculos. A avaliação energética mostrou que a reação é favorável para anfetaminas, aminoácidos e catinonas, e os menores valores foram encontrados no último caso. Nos estudos de emissão obtivemos resultados semelhantes ao perfil energético; no entanto, observamos que os espectros são únicos, representando uma baixa probabilidade de falsos positivos. Avaliações de docking mostraram que as catinonas têm mais afinidade com o receptor dopaminérgico do que suas anfetaminas homólogas, confirmando dados experimentais relatados na literatura. Por fim, os estudos realizados neste trabalho demonstraram a importância e a capacidade dos métodos in silico que apresentam grau potencial na área e que podem ser amplamente utilizados em investigações com diferentes propósitos no campo forense. / The emergence of new psychoactive substances (NPSs) has raised many issues in the context of law enforcement and public drug policies. According to the United Nations Office on Drugs and Crime (UNODC), NPS were created as an alternative to forbidden drugs. These new compounds were designed and formulated to escape the drug control legislation, creating a phenomenon that has become an international problem. In Brazil, these substances are controlled and punishable by Law 11,343 / 2006, also known as the Drug Law. This work presents studies on synthetic cathinones with in silico methodology to investigate mechanisms of detection and tendency of action in the human organism. In the detection-related study, we used the reaction of these drugs with fluorescein isothiocyanate (FITC). For this proposal were made studies regarding to the viability of the calculation methods, FITC conformational analysis, energetic evaluation of the reaction with the cathinones and the emission spectra. In relation to the viability of the calculation methods we have that the previous optimization of the compounds involved with the semi-empirical PM6 and subsequent refinement with the B3LYP / 6-31G ** method were adequate for the calculations. The energetic evaluation showed that the reaction is favorable for amphetamines, amino acids and cathinones, and the lowest values were found in the last case. In the emission studies we obtained similar results to the energy profile; however, we observed that the spectra are unique representing a low probability of false positive. Docking evaluations have shown that cathinones have more affinity to the dopaminergic receptor than their homologous amphetamines, confirming experimental data reported in the literature. Finally, the studies carried out in this work demonstrated the importance and the capacity of the in silico methods that present with potential grade in the area and that can be widely used in investigations with different purposes in the forensic field.

O surgimento de novas substâncias psicoativas (NPS-New Psychoactive Substances) levantou muitas questões no contexto da aplicação da lei e políticas públicas de drogas. De acordo com o Escritório das Nações Unidas sobre Drogas e Crime (UNODC- United Nations Office on Drugs and Crime) como uma alternativa às drogas proibidas. Esses novos compostos foram projetados e formulados para escapar à legislação de controle de drogas, criando um fenômeno que se tornou um problema internacional. No Brasil, essas substâncias são controladas e penalmente puníveis, no pela Lei 11.343/2006, também conhecida como Lei de Drogas. Este trabalho traz estudos relativos às catinonas sintéticas com metodologia in silico para investigar mecanismos de detecção e tendência de atuação no organismo humano. No estudo relacionado à detecção utilizamos a reação dessas drogas com o isotiocianato de fluoresceína (FITC Fluorescein isothiocyanate). Para essa proposta foram feitos estudos de viabilidade de métodos de cálculo, análise conformacional do FITC, avaliação energética da reação com as catinonas e os espectros de emissão. Em relação à viabilidade dos métodos de cálculo temos que a otimização prévia dos compostos envolvidos com o semi-empírico PM6 e posterior refinamento com o método B3LYP/6-31G** foram adequados para os cálculos. A avaliação energética mostrou que a reação é favorável para anfetaminas, aminoácidos e catinonas, e os menores valores foram encontrados no último caso. Nos estudos de emissão obtivemos resultados semelhantes ao perfil energético; no entanto, observamos que os espectros são únicos, representando uma baixa probabilidade de falsos positivos. Avaliações de docking mostraram que as catinonas têm mais afinidade com o receptor dopaminérgico do que suas anfetaminas homólogas, confirmando dados experimentais relatados na literatura. Por fim, os estudos realizados neste trabalho demonstraram a importância e a capacidade dos métodos in silico que apresentam grau potencial na área e que podem ser amplamente utilizados em investigações com diferentes propósitos no campo forense. / The emergence of new psychoactive substances (NPSs) has raised many issues in the context of law enforcement and public drug policies. According to the United Nations Office on Drugs and Crime (UNODC), NPS were created as an alternative to forbidden drugs. These new compounds were designed and formulated to escape the drug control legislation, creating a phenomenon that has become an international problem. In Brazil, these substances are controlled and punishable by Law 11,343 / 2006, also known as the Drug Law. This work presents studies on synthetic cathinones with in silico methodology to investigate mechanisms of detection and tendency of action in the human organism. In the detection-related study, we used the reaction of these drugs with fluorescein isothiocyanate (FITC). For this proposal were made studies regarding to the viability of the calculation methods, FITC conformational analysis, energetic evaluation of the reaction with the cathinones and the emission spectra. In relation to the viability of the calculation methods we have that the previous optimization of the compounds involved with the semi-empirical PM6 and subsequent refinement with the B3LYP / 6-31G ** method were adequate for the calculations. The energetic evaluation showed that the reaction is favorable for amphetamines, amino acids and cathinones, and the lowest values were found in the last case. In the emission studies we obtained similar results to the energy profile; however, we observed that the spectra are unique representing a low probability of false positive. Docking evaluations have shown that cathinones have more affinity to the dopaminergic receptor than their homologous amphetamines, confirming experimental data reported in the literature. Finally, the studies carried out in this work demonstrated the importance and the capacity of the in silico methods that present with potential grade in the area and that can be widely used in investigations with different purposes in the forensic field.

nÃo hà / A tuberculose à uma das principais causas de mortalidade no mundo, porÃm à uma doenÃa negligenciada por ser endÃmica de paÃses em desenvolvimento. Um dos principais pontos de tratamento da tuberculose à a morte do bacilo causador, o Mycobacterium tuberculosis, atravÃs da interrupÃÃo da produÃÃo de Ãcidos micÃlicos, componentes da parede celular do bacilo, usando como um dos alvos a enzima InhA, porÃm esta rota tambÃm à a principal causa de resistÃncia. O presente trabalho se propÃe a estudar a enzima InhA, realizando modelagens in silico de interaÃÃes entre a enzima e ligantes selecionados. Os ligantes estudados fazem parte de duas bibliotecas distintas, sendo uma de compostos orgÃnicos selecionados por sua similaridade com o substrato da enzima. A outra biblioteca à composta de complexos metÃlicos com o nÃcleo pentacianoferrato, variando-se o ligante auxiliar. A justificativa para esta classe de compostos ser utilizada se dà pelo fato de o complexo pentacianoisoniazidaferato (II) ter apresentado atividade anti-tuberculose tanto in vitro como por via oral em ratos. Os ensaios de docking foram realizados utilizando-se duas abordagens, uma completamente rÃgida e outra em que a proteÃna era rÃgida e o ligante era flexÃvel. Ambos os ensaios apresentaram boa correlaÃÃo entre os seus resultados, independentemente da funÃÃo de avaliaÃÃo utilizada. Observou-se que as melhores estruturas em termos de inibiÃÃo possuÃam uma quantidade razoÃvel de interaÃÃes hidrofÃbicas, de modo a manterem-se estÃveis no sÃtio de ligaÃÃo da enzima que possui baixa polaridade. / Tuberculosis is found among the main causes of mortality in the World, although is a neglected disease since it is endemic in developing countries. The main route of therapy of tuberculosis is the inhibition of InhA, enzyme that catalyses the production of mycolic acids, which is a component of bacillus cellular wall. This reaction also is the main point of resistance against TB drugs. In this work proposed the study of InhA enzyme, working specifically in silico modeling of enzyme-ligant interactions. These ligands distinguish themselves between two distinct libraries, one of them containing organic compounds selected by its structural similarity with the enzyme substrate, NADH. Due in vitro and orally activity in murine model against tuberculosis exhibited by the compound pentacianoisoniazideferrate (II), another library, containing the pentacianoferrate II moiety bind to an auxiliary ligand studied against que InhA target. The essays realized using ligand rigid and flexible docking both, although the protein always considered rigid. Both essays had acceptable correlation within its results, regardless the scoring function used. The leading inhibitors structures had in common a high stabilization of ligand-enzyme complex due hydrophobic interactions, something expected due polarity of the enzyme binding site

Molecular docking is a computational tool commonly applied in drug discovery projects and fundamental biological studies of protein-ligand interactions. Traditionally, molecular docking is used to address one of three following questions: (i) given a ligand molecule and a protein receptor, predict the binding mode (pose) of the ligand within the context of a receptor, (ii) screen a collection of small-molecules against a receptor and rank ligands by their likelihood of being active, and (iii) given a ligand molecule and a target receptor, predict the binding affinity of the two. Here, we focus on the first two questions, namely ranking and pose prediction. Currently, state-of-the-art docking algorithms predict poses within 2A of the native pose in a rate lower than ∼60% and in many cases, below 40%. In ranking, their ability to identify active ligands is inconsistent and generally suffers from high false-positive rate. In this thesis we present novel algorithms to enhance the ability of molecular docking to address these two questions. These algorithms do not substitute traditional docking but rather being applied on top of them to provide synergistic effect. Our algorithms improve pose predictions by 0.5-1.0A and ranking order for 23% of the targets in gold-standard benchmarks. As importantly, the algorithms improve the consistence of the posing and ranking predictions over diverse sets of targets and screening libraries. In addition to the posing and ranking, we present the pharmacophore concept. A pharmacophore is an ensemble of physiochemical descriptors associated with a biological target that elucidates common interaction patterns of ligands with that target. We introduce a novel pharmacophore inference algorithm and demonstrate its utilization in molecular docking. This thesis is outlined as follow. First we introduce the molecular docking approach for pose prediction and ranking. Second, we discuss the pharmacophore concept and present algorithms for pharmacophore inference. Third, we demonstrate the utilization of pharmacophores for pose prediction by re-scoring candidate poses generated by docking algorithms. Finally, we present algorithms to improve ranking by reducing bias in scoring functions employed by docking algorithms.

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Cross-docking is an important transportation logistics strategy in supply chain management which reduces transportation costs, inventory holding costs, order-picking costs and response time. Careful planning is needed for successful cross-dock operations. Uncertainty in cross-dock problems is inevitable and needs to be addressed. Almost all research in the cross-dock area assumes determinism. This dissertation considers uncertainty in cross-dock problems and optimizes these problems under uncertainty. We consider uncertainty in processing times, using scenario-based and protection-based robust approaches. Using a heuristic method, we find a lower and upper bound and combine that with a meta-heuristic method to solve the problem. Also, we consider problems in two different industries (Goodwill and H-E-B) and address the uncertainties that happen frequently in their operations. The scenario-based robust optimization model for the unloading problem using a min max objective is presented with examples. A surrogate heuristic procedure is used to find a robust solution. Next, a two-space genetic algorithm, a meta-heuristic procedure, is applied to the unloading problem using the bounds obtained by the heuristic procedure. The results are closer to the optimal solution than those obtained by the two-space genetic algorithm without bounds. When compared with the regular genetic algorithm with bounds, the two-space algorithm performs well. The protection-based approach considers a limit on the number of coefficients allowed to change with data uncertainty, protecting against the degree of conservatism. The management of trucks and reduction of overtime pay in the cross-dock operations of Goodwill is addressed through two models and uncertainty is applied to those models. A combined cross-dock operations model together with demand is formulated and the uncertainties are discussed for H-E-B operations. This dissertation does not address the recycling operation within the cross-dock of Goodwill, or the uncertainty in H-E-B data. / text

Molecular docking is a computational tool commonly applied in drug discovery projects and fundamental biological studies of protein-ligand interactions. Traditionally, molecular docking is used to address one of three following questions: (i) given a ligand molecule and a protein receptor, predict the binding mode (pose) of the ligand within the context of a receptor, (ii) screen a collection of small-molecules against a receptor and rank ligands by their likelihood of being active, and (iii) given a ligand molecule and a target receptor, predict the binding affinity of the two. Here, we focus on the first two questions, namely ranking and pose prediction. Currently, state-of-the-art docking algorithms predict poses within 2A of the native pose in a rate lower than ∼60% and in many cases, below 40%. In ranking, their ability to identify active ligands is inconsistent and generally suffers from high false-positive rate. In this thesis we present novel algorithms to enhance the ability of molecular docking to address these two questions. These algorithms do not substitute traditional docking but rather being applied on top of them to provide synergistic effect. Our algorithms improve pose predictions by 0.5-1.0A and ranking order for 23% of the targets in gold-standard benchmarks. As importantly, the algorithms improve the consistence of the posing and ranking predictions over diverse sets of targets and screening libraries. In addition to the posing and ranking, we present the pharmacophore concept. A pharmacophore is an ensemble of physiochemical descriptors associated with a biological target that elucidates common interaction patterns of ligands with that target. We introduce a novel pharmacophore inference algorithm and demonstrate its utilization in molecular docking. This thesis is outlined as follow. First we introduce the molecular docking approach for pose prediction and ranking. Second, we discuss the pharmacophore concept and present algorithms for pharmacophore inference. Third, we demonstrate the utilization of pharmacophores for pose prediction by re-scoring candidate poses generated by docking algorithms. Finally, we present algorithms to improve ranking by reducing bias in scoring functions employed by docking algorithms.

<p dir="ltr">Proteins and their interactions with each other, with nucleic acids, and with other molecules are foundational to all known forms of life. The three-dimensional structures of these interactions are an essential component of a comprehensive understanding of how they function. Molecular-biological hypothesis formulation and rational drug design are both often predicated on a particular structure model of the molecule or complex of interest. While experimental methods capable of determining atomic-detail structures of molecules and complexes exist, such as the popular X-ray crystallography and cryo-electron microscopy, these methods require both laborious sample preparation and expensive instruments with limited throughput. Computational methods of predicting complex structures are therefore desirable if they can enable cheap, high-throughput virtual screening of the space of biological hypotheses. Many common biomolecular contexts have largely been blind spots for predictive modeling of complex structures. In this direction, docking methods are proposed to address extreme conformational change, nonuniform environments, and distance-geometric priors. Flex-LZerD deforms a flexible protein using a novel fitting procedure based on iterated normal mode decomposition and was shown to construct accurate complex models even when an initial input subunit structure exhibits extreme conformational differences from its bound state. Mem-LZerD efficiently constrains the docking search space by augmenting the geometric hashing data structure at the core of the LZerD algorithm and enabled membrane protein complexes to be efficiently and accurately modeled. Finally, atomic distance-based approaches developed during modeling competitions and collaborations with wet lab biologists were shown to effectively integrate domain knowledge into complex modeling pipelines.</p>

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / UUV homing and docking and UAV collision avoidance are two seemingly separate research topics for different applications. Upon close examination, these two are a pair of dual problems, with interesting correspondences and commonality. In this paper, we present the theoretical analysis, signal processing, and the field experiments of these two algorithms in UAV and UUV applications in homing and docking as well as collision avoidance.