Le triméthoprime (TMP) est un antibiotique communément utilisé depuis les années 60. Le TMP est un inhibiteur de la dihydrofolate réductase (DHFR) bactérienne chromosomale. Cette enzyme est responsable de la réduction du dihydrofolate (DHF) en tétrahydrofolate (THF) chez les bactéries, qui lui, est essentiel à la synthèse des purines et ainsi, à la prolifération cellulaire. La résistance bactérienne au TMP est documentée depuis plus de 30 ans. Une des causes de cette résistance provient du fait que certaines souches bactériennes expriment une DHFR plasmidique, la DHFR R67. La DHFR R67 n'est pas affectée par le TMP, et peut ainsi remplacer la DHFR chromosomale lorsque celle-ci est inhibée par le TMP. À ce jour, aucun inhibiteur spécifique de la DHFR R67 est connu. En découvrant des inhibiteurs contre la DHFR R67, il serait possible de lever la résistance au TMP que la DHFR R67 confère aux bactéries. Afin de découvrir des inhibiteurs de DHFR R67, les approches de design à base de fragments et de criblage virtuel ont été choisies. L'approche de design à base de fragments a permis d'identifier sept composés simples et de faible poids moléculaire (fragments) inhibant faiblement la DHFR R67. À partir de ces fragments, des composés plus complexes et symétriques, inhibant la DHFR R67 dans l'ordre du micromolaire, ont été élaborés. Des études cinétiques ont montré que ces inhibiteurs sont compétitifs et qu'au moins deux molécules se lient simultanément dans le site actif de la DHFR R67. L'étude d'analogues des inhibiteurs micromolaires de la DHFR R67 a permis de déterminer que la présence de groupements carboxylate, benzimidazole et que la longueur des molécules influencent la puissance des inhibiteurs. Une étude par arrimage moléculaire, appuyée par les résultats in vitro, a permis d'élaborer un modèle qui suggère que les résidus Lys32, Gln67 et Ile68 seraient impliqués dans la liaison avec les inhibiteurs. Le criblage virtuel de la librairie de 80 000 composés de Maybridge avec le logiciel Moldock, et les essais d'inhibition in vitro des meilleurs candidats, a permis d'identifier quatre inhibiteurs micromolaires appartenant à des familles distinctes des composés précédemment identifiés. Un second criblage virtuel, d'une banque de 6 millions de composés, a permis d'identifier trois inhibiteurs micromolaires toujours distincts. Ces résultats offrent la base à partir de laquelle il sera possible de développer iv des composés plus efficaces et possédant des propriétés phamacologiquement acceptables dans le but de développer un antibiotique pouvant lever la résistance au TMP conféré par la DHFR R67. / Trimethoprim (TMP) is a common antibiotic which is used since the 60's. TMP is an inhibitor of the bacterial chromosomal dihydrofolate reductase (DHFR). This enzyme catalyses the reduction of the dihydrofolate (DHF) to tetrahydrofolate (THF) which is essential to the biosynthesis of purines thus to cellular proliferation. Bacterial TMP resistance is documented since about 30 years. One of the cause of this resistance comes from the fact that certain bacteria express a plasmidic DHFR, the R67 DHFR, which confers TMP resistance. The R67 DHFR is not inhibited by TMP and can replace the chromosomal DHFR when the latter is inhibited by TMP. The discovery of R67 DHFR inhibitors would allow to break the trimethoprim resistance granted by R67 DHFR. In order to discover R67 DHFR inhibitors, fragment based design and virtual screening approaches were selected. By fragment based design, seven simple compounds with a low molecular mass which inhibited weakly R67 DHFR (fragments) were identified. From these fragments, more complex and symmetrical compounds inhibiting R67 DHFR in the micromolar range were identified. Kinetic studies showed these inhibitors were competitive and at least two molecules bind simultaneously to the active site of the R67 DHFR. Test of the micromolar inhibitors analog showed that the presence of carboxylate, benzimidazole and the length of the molecule all have an effect on the potency of the inhibitors. Molecular docking of the inhibitors, supported by in vitro data, were used to develop a model which suggest that residue like Lys32, Gln67 and Ile68 would be involved in the binding of the inhibitors to the R67 DHFR. Virtual screening of the 80 000 compound Maybridge library with Moldock software, followed by in vitro test of the best candidate, identified four micromolar inhibitors which are chemically distinct from the inhibitor beforehand identified. A second virtual screening of a 6 million compounds bank identified three micromolar inhibitors which are also distinct from the inhibitor beforehand identified. vi These results offer a basis which will allow further development of more potent inhibitors with more acceptable pharmacologic properties in order to develop an antibiotic which would break the TMP resistance granted by the R67 DHFR.

Thrombosis is the most important pathological process underlying many cardiovascular diseases, which are responsible for high mortality worldwide. In this theses the computer-aided design of new anti-thrombotic agents able to inhibit two types of receptors located on the surface of the platelets has been applied. The first one - αIIbβ3 - is responsible for the interaction of activated platelets with fibrinogen to form clots, whereas the second one - thromboxane A2 - is responsible for platelet activation by one of agonists excreted by activated platelets. To achieve this, different types of models have been developed using experimentally available information and structure of protein-ligand complexes. This concerns: QSAR models, structure-based and ligand-based 3D pharmacophore models, 2D pharmacophore models, shape-based and molecular field-based models. The ensemble of the developed models were used in virtual screening. This study resulted in suggestion of new potential antagonists of αIIbβ3 and thromboxane A2 receptors. Suggested antagonists of αIIbβ3 able to bind either open or closed form of the receptor have been synthesized and tested experimentally. Experiments show that they display high activity; moreover some of theoretically designed compounds are more efficient than Tirofiban - the commercialized drug molecule. The recommended antagonists of thromboxane A2 receptor have been already synthesized but biological tests have not been completed yet.

Biochemical processes all involve associations and dissociations of chemical entities. Understanding these is of substantial importance for many modern pharmaceutical applications. In this thesis, longstanding problems with regard to ligand binding are treated with computational methods, applied to proteins of key pharmaceutical importance. Homology modeling, docking, molecular dynamics simulations and free-energy calculations are used here for quantitative characterization of ligand binding to proteins. By combining computational tools, valuable contributions have been made for pharmaceutically relevant areas: a neglected tropical disease, an ion channel anti-drug-target, and GPCR drug-targets. We report three compounds inhibiting cruzain, the main cysteine protease of the protozoa causing Chagas’ disease. The compounds were found through an extensive virtual screening study and validated with experimental enzymatic assays. The compounds inhibit the enzyme in the μM-range and are therefore valuable in further lead optimization studies. A high-resolution crystal structure of the BRICHOS domain is reported, together with molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry studies. This work revealed a plausible mechanism for how the chaperone activity of the domain may operate. Rationalization of structure-activity relationships for a set of analogous blockers of the hERG potassium channel is given. A homology model of the ion channel was used for docking compounds and molecular dynamics simulations together with the linear interaction energy method employed for calculating the binding free-energies. The three-dimensional coordinates of two GPCRs, 5HT1B and 5HT2B, were derived from homology modeling and evaluated in the GPCR Dock 2013 assessment. Our models were in good correlation with the experimental structures and all of them placed among the top quarter of all models assessed.  Finally, a computational method, based on molecular dynamics free-energy calculations, for performing alanine scanning was validated with the A2A adenosine receptor bound to either agonist or antagonist. The calculated binding free-energies were found to be in good agreement with experimental data and the method was subsequently extended to non-alanine mutations. With extensive experimental mutation data, this scheme is a valuable tool for quantitative understanding of ligand binding and can ultimately be used for structure-based drug design.

Les biothérapies (anticorps monoclonaux, récepteurs solubles) ciblant les cytokines IL-6 etTNF-alpha pour le traitement des maladies inflammatoires chroniques ont constitué un succèsmajeur de l’industrie pharmaceutique. Elles présentent néanmoins des inconvénientsimportants : résistances, mode d’administration contraignant, coût élevé.Notre équipe travaille sur l’identification de petites molécules inhibant directement cescytokines, afin d’élargir l’offre thérapeutique existante. Administrées par voie orale, ellesconstitueraient une alternative particluièrement favorable aux patients.Durant ma thèse, j’ai réalisé le criblage expérimental (tests cellulaires et tests biochimiquesde liaison) des meilleurs composés identifiés par criblage virtuel d’un grande chimiothèque dediversité, ainsi que de composés dérivés de pyridazine issus d’une chimiothèque médicinale. J’aiainsi pu identifier plusieurs inhibiteurs directs du TNF-alpha et de l’IL-6. De plus, mon travail apermis d’affiner les procédures de criblage du Laboratoire.Ces travaux ouvrent de nouvelles pistes pour le développement de médicaments anti-cytokines. / Anti-cytokine biologics (monoclonal antibodies, soluble receptors) targeting TNF-alpha and IL-6in chronic inflammatory diseases have been a major success for pharmaceutical industry.However, they exhibit several drawbacks : resistance, difficult administration, high costs.Our team works on the discovery of small molecule inhibitors of cytokines suck as TNF-alphaand IL-6, in order to widen the range of therapeutic drugs. Orally active drugs would represent ahighly beneficial alternative for patients.During my PhD, I have performed an experimental screening (using cellular and biochemicalbinding testings) of the best compounds identified through virtual screening of a large chemicallibrary, and on pyridazine compounds of a medicinal chemical library. I have been able toidentify several small molecules inhibiting the interaction of TNF-! and IL-6 with their receptor.Moreover, my work will have an impact on the laboratory screening strategies.Overall, this work opens new avenues for anti-cytokine drug discovery.

Os receptores dos hormônios da tireóide (TRs) são fatores de transcrição envolvidos na diferenciação celular, metabolismo e funções fisiológicas da maioria dos tecidos. Muitos estudos mostram que diversos efeitos farmacológicos mediados pelos TRs podem ser benéficos na farmacoterapia, especialmente aqueles mediados pelo TR que podem ser úteis em condições médicas importantes como obesidade, hipercolesterolemia e diabetes. Além disso, a descoberta que o TR é a isoforma predominante no coração, mediando a maioria dos efeitos cardiovasculares prejudiciais, estimulou a pesquisa por ligantes seletivos para o TR que poderiam ser utilizados em quadros clínicos importantes com perfil de segurança aceitável. Foi realizado um estudo das relações quantitativas entre a estrutura e atividade (QSAR) de um conjunto de compostos com atividade biológica descrita para TR e TR, que gerou modelos de Holograma QSAR com elevada consistência interna e externa, apresentando bom poder de correlação e predição das propriedades biológicas. Também foi realizado um minucioso estudo de triagem virtual, que propiciou a seleção de 7 compostos que foram adquiridos para terem suas atividades biológicas avaliadas. Ensaios de transfecção e gene repórter foram estabelecidos e utilizados na avaliação da atividade biológica dos compostos selecionados pelo ensaio virtual. Finalmente, um ensaio utilizando ressonância plasmônica de superfície (SPR) foi desenvolvido e utilizado para avaliar a atividade agonista desses compostos, e que pode ser útil para avaliar a atividade de novos ligantes. A técnica de SPR também foi empregada em um cuidadoso estudo da interação do TR com seus correguladores, que incluiu estudos cinéticos e termodinâmicos, propiciando a determinação das taxas cinéticas e parâmetros termodinâmicos para a interação do complexo TR-T3 com peptídeos derivados de dois de seus correguladores. Os resultados obtidos são relevantes e devem ser considerados no planejamento de futuros experimentos utilizando o LBD de TR e agonistas. / The thyroid hormone receptors (TRs) are transcriptional factors involved in cell differentiation, development, metabolism and physiological function of most tissues. Many lines of evidence show that several pharmacological actions of TRs might be beneficial in medical therapy, specially those mediated by TR that target important medical conditions like obesity, hypercholesterolemia and diabetes. Additionally, the findings that TR is the predominant isoform in the heart and mediates most of the TRs deleterious cardiovascular effects, stimulated the research for selective TR ligands which could address important medical needs with an acceptable safety profile. In this PhD thesis, studies of the quantitative structure-activity relationships (QSAR) of a dataset of compounds with reported biologic activity for both TR and TR were performed, and statistically significant Hologram QSAR models with good predictive ability for untested compounds were created. In parallel, a careful virtual screening procedure was executed, leading to the selection of 7 compounds which were purchased for the evaluation of their biological activities. Cell transfection and reporter gene assays were developed, validated and used to evaluate the biological activities of these compounds. Finally, a surface plasmon resonance (SPR) assay was developed and used to assess the agonistic activity of these compounds. The SPR technique was also employed in a careful study of the interaction between the ligand binding domain of TR and peptides derived from its coregulators, which included the determination of the kinetic and thermodynamic parameters for this interaction. The results suggest that flexibility plays an important role in the interaction between the receptor and its coregulators, and point out important aspects of experimental design that should be addressed when using TR LBD and its agonists. Furthermore, the methodology described here may be useful for the identification of new TR ligands.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-12T15:19:44Z No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-12T15:21:40Z (GMT) No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-06-12T15:21:40Z (GMT). No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-05-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Introduction: Skin sensitization is a major environmental and human health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. Skin sensitization is commonly evaluated using structural alerts. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. The main goal of this thesis was to develop and apply new cheminformatics methods to predict skin sensitization of chemical compounds that lack experimental data. Methodology: It has been compiled, curated, analyzed, and compared the available human data and the murine (performed in mice) animal model data, named LLNA (local lymph node assay). Using these data, it was developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. It was developed a freely accessible web-based application for the identification of potential skin sensitizers. In addition, it was demonstrated that contrary to the common perception of QSAR models as “black boxes” they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. Results and discussion: The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher correct classification rate of 82% but at the expense of the reduced external dataset coverage (52 %). We used the developed QSAR models for virtual screening of CosIng database and identified 1,061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. The developed Pred-Skin web app (http://www.labmol.com.br/predskin/) is based on binary QSAR models of human (109 compounds) and LLNA (515 compounds) data with good external correct classification rate (70-81% and 72-84%, respectively). It is also included a multiclass potency model based on LLNA data (accuracy ranging between 73-76%). Conclusions: Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential. The Pred-Skin web app is a fast, reliable, and user-friendly tool for early assessment of chemically-induced skin sensitization. A new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals was also proposed. / Introdução: A sensibilização cutânea é um importante parâmetro de avaliação de toxicidade humana e ambiental. Embora muitos compostos tenham sido avaliados em seres humanos, não foi reportado até o momento modelos de QSAR (do inglês, quantitative structure-activity relationships) gerados com esses dados. Comumente, a sensibilização cutânea é avaliada computacionalmente usando-se alertas estruturais. No entanto, tem havido uma preocupação crescente de que alertas sinalizam a maioria dos compostos como tóxicos, o que questiona sua confiabilidade como marcadores de toxicidade. O objetivo geral do presente trabalho foi desenvolver e aplicar novos métodos de quimioinformática para predizer a sensibilização cutânea de compostos químicos que carecem de dados experimentais. Metodologia: Foram compilados, preparados, analisados e comparados os dados de sensibilização cutânea de pele humana e do modelo animal murino (realizado em camundongos), denominado LLNA (local lymph node assay). Modelos de QSAR foram desenvolvidos utilizando esses dados e aplicados para a triagem de quimiotecas virtuais para identificar potenciais sensibilizadores. Foi desenvolvido um aplicativo gratuito para a identificação de potenciais sensibilizadores cutâneos. Além disso, foi demonstrado que modelos de QSAR podem ser usados para identificar subestruturas químicas estatisticamente significativas (alertas estruturais baseados em QSAR) que influenciam a toxicidade. Resultados e discussão: A concordância global (R) entre respostas de sensibilização cutânea humana e murina para um conjunto de 135 substâncias químicas únicas foi baixa (R = 28-43%), embora várias classes químicas apresentassem alta concordância. Foi possível desenvolver modelos de QSAR preditivos com taxa de classificação correta externa de 71%. Um modelo de consenso que integrava predições concordantes de QSAR e dados de LLNA proporcionaram uma acurácia 82%. Utilizou-se os modelos de QSAR desenvolvidos para a triagem virtual da base de dados CosIng e foram identificados 1061 potenciais sensibilizadores cutâneos. Para dezessete desses compostos, encontrou-se evidências publicadas de seus efeitos de sensibilização cutânea em seres humanos. O aplicativo desenvolvido, Pred-Skin (http://www.labmol.com.br/predskin/), baseia-se em modelos de QSAR classificatórios de dados humanos (109 compostos) e murinos (515 compostos) com boa taxa de classificação correta externa (70-81% e 72-84%, respectivamente). Esse aplicativo também possui um modelo de multiclassificatório desenvolvido com dados de LLNA (precisão que varia entre 73-76%). Conclusões: Os modelos de QSAR desenvolvidos forneceram uma alternativa mais precisa do que o modelo animal para avaliação da sensibilização cutânea humana. Além disso, a interpretação dos modelos de QSAR permitem orientar a otimização estrutural de compostos tóxicos para reduzir o potencial de toxicidade. O aplicativo Pred-Skin é uma ferramenta rápida, confiável e de fácil utilização para a avaliação da sensibilização cutânea de compostos químicos. Foi também proposta uma nova abordagem que integra sinergicamente alertas estruturais e modelos de QSAR rigorosamente validados para uma avaliação de toxicidade mais transparente e precisa de novos produtos químicos.

Le criblage virtuel est utilisé dans la recherche de médicaments et la construction de modèle de prédiction de toxicité. L’application d’un protocole de criblage est précédée par une étape d’évaluation sur une banque de données de référence. La composition des banques d’évaluation est un point critique ; celles-ci opposent généralement des molécules actives à des molécules supposées inactives, faute de publication des données d’inactivité. Les molécules inactives sont néanmoins porteuses d’information. Nous avons donc créé la banque NR-DBIND composée uniquement de molécules actives et inactives expérimentalement validées et dédiées aux récepteurs nucléaires. L’exploitation de la NR-DBIND nous a permis d’étudier l’importance des molécules inactives dans l’évaluation de modèles de docking et dans la construction de modèles de pharmacophores. L’application de protocoles de criblage a permis d’élucider des modes de liaison potentiels de petites molécules sur FXR, NRP-1 et TNF⍺. / Virtual screening is widely used in early stages of drug discovery and to build toxicity prediction models. Commonly used protocols include an evaluation of the performances of different tools on benchmarking databases before applying them for prospective studies. The content of benchmarking tools is a critical point; most benchmarking databases oppose active data to putative inactive due to the scarcity of published inactive data in the literature. Nonetheless, experimentally validated inactive data also bring information. Therefore, we constructed the NR-DBIND, a database dedicated to nuclear receptors that contains solely experimentally validated active and inactive data. The importance of the integration of inactive data in docking and pharmacophore models construction was evaluated using the NR-DBIND data. Virtual screening protocols were used to resolve the potential binding mode of small molecules on FXR, NRP-1 et TNF⍺.

Cancer is a leading cause of death worldwide. Development of new cancer drugs is increasingly costly and time-consuming. By exploiting massive amounts of biological data, computational repositioning proposes new uses for old drugs to reduce these development hurdles. A promising approach is the systematic analysis of structural data for identification of shared binding pockets and modes of action. In this thesis, I developed the Protein-Ligand Interaction Profiler (PLIP), which characterizes and indexes protein-ligand interactions to enable comparative analyses and searching in all available structures. Following, I applied PLIP to identify new treatment options in cancer: the heat shock protein Hsp27 confers resistance to drugs in cancer cells and is therefore an attractive target with a postulated drug binding site. Starting from Hsp27, I used PLIP to define an interaction profile to screen all structures from the Protein Data Bank (PDB). The top prediction was experimentally validated in vitro. It inhibits Hsp27 and significantly reduces resistance of multiple myeloma cells against the chemotherapeutic agent bortezomib. Besides computational repositioning, PLIP is used in docking, binding mode analysis, quantification of interactions and many other applications as evidenced by over 12,000 users so far. PLIP is provided to the community online and as open source.

No description available.

In recent years, the potential benefits of high-throughput virtual screening to the drug discovery community have been recognized, bringing an increase in the number of tools developed for this purpose. These programs have to process large quantities of data, searching for an optimal solution in a vast combinatorial range. This is particularly the case for protein-ligand docking, since proteins are sophisticated structures with complicated interactions for which either molecule might reshape itself. Even the very limited flexibility model to be considered here, using ligand conformation ensembles, requires six dimensions of exploration - three translations and three rotations - per rigid conformation. The functions for evaluating pose suitability can also be complex to calculate. Consequently, the programs being written for these biochemical simulations are extremely resource-intensive. This work introduces a pure computer science approach to the field, developing techniques to improve the effectiveness of such tools. Their architecture is generalized to an abstract pattern of nested layers for discussion, covering scoring functions, search methods, and screening overall. Based on this, new stratagems for molecular docking software design are described, including lazy or partial evaluation, geometric analysis, and parallel processing implementation. In addition, a range of novel algorithms are presented for applications such as active site detection with linear complexity (PIES) and small molecule shape description (PASTRY) for pre-alignment of ligands. The various stratagems are assessed individually and in combination, using several modified versions of an existing docking program, to demonstrate their benefit to virtual screening in practical contexts. In particular, the importance of appropriate precision in calculations is highlighted.