No description available.

SIRT1 and SIRT2 are two NAD⁺-dependent deacetylases which negatively modulate the activity of p53, a protein which is involved in cell cycle arrest, senescence and apoptosis following genotoxic stress. Part I of the thesis describes the exploration of the chemical space around a reported unselective and modest inhibitor of SIRT1 and SIRT2 with the aim of improving the selectivity and potency of the inhibitor against the two isoforms. Particular emphasis is placed upon understanding the mode of binding of the novel analogues within the active site of the enzymes. Chapter 1 reviews the physiological roles of class III NAD⁺-dependent deacetylases, also known as sirtuins. In particular, the application of SIRT1 and SIRT2 inhibitors as potential anticancer agents is described. Amongst these, only cambinol and the tenovins showed in vivo activity in a mouse xenograft model. Previously only one analogue of cambinol had been reported in the literature. Chapter 2 describes the development of a small collection of novel cambinol analogues (First Generation Studies). The role played by different substituents at the phenyl group and at the N-1 of the thiouracil core is discussed. Along with the synthesis and structure activity relationship (SAR) associated with the core structure, in-cell experiments intended to confirm the activity of the most active compounds are reported. Chapter 3 provides a rationalisation for the SAR discussed in Chapter 2. Based on computational molecular modelling studies (GOLD), the activity of the most potent and selective SIRT2 inhibitors is explained. Two series of novel cambinol analogues were designed (Second and Third Generation Analogues) in order to assess further the proposed binding mode. Chapter 4 focuses on the development of the “Second Generation” analogues, characterised by the presence of lipophilic substituents at the sulfur atom and at the N-3 position of the thiouracil core. The synthesis, biological evaluation and SAR are discussed in detail. Chapter 5 reports the development of the “Third Generation” analogues, characterised by either a benzyl group or para-alkoxy-substituted benzyl group at the N-1 position of cambinol. Once again, the synthesis, biological evaluation and SAR data are presented. An improved understanding of the mode of binding of the novel compounds is proposed based on molecular dynamics (MD) studies. Indole-based alkaloids, such as Vincristine and Vinblastine, are well known for their anticancer activity. Recently, the anticancer activity of members of the calycanthaceous family of alkaloids has been discovered. Part II of the thesis focuses on model studies aimed at developing the total synthesis of one of these compounds, perophoramidine. Chapter 7 provides an overview of the calycanthaceous alkaloid family of natural products, including their biological properties. The structural features of perophoramidine, along with the previously reported synthetic studies are outlined. Chapter 8 describes the synthesis of an advanced intermediate in the total synthesis of dehaloperophoramidine, a structural analogue of perophoramidine Problems encountered, optimisation studies and the synthesis of a re-designed intermediate are also reported in this chapter.

Computationally driven drug design/discovery efforts generally rely on accurate assessment of the forces that guide the molecular recognition process. HINT (Hydropathic INTeraction) is a natural force field, derived from experimentally determined partition coefficients that quantifies all non-bonded interactions in the biological environment, including hydrogen bonding, electrostatic and hydrophobic interactions, and the energy of desolvation. The overall goal of this work is to apply the HINT-based atomic level description of molecular systems to biologically important proteins, to better understand their biochemistry – a key step in exploiting them for therapeutic purposes. This dissertation discusses the results of three diverse projects: i) structural modeling of human sphingosine kinase 2 (SphK2, a novel anticancer target) and binding mode determination of an isoform selective thiazolidine-2,4-dione (TZD) analog; ii) structural modeling of human cytomegalorvirus (HCMV) alkaline nuclease (AN) UL98 (a novel antiviral target) and subsequent virtual screening of its active site; and iii) explicit treatment of interfacial waters during protein-protein docking process using HINT-based computational tools. SphK2 is a key regulator of the sphingosine-rheostat, and its upregulation /overexpression has been associated with cancer development. We report structural modeling studies of a novel TZD-analog that selectively inhibits SphK2, in a HINT analysis that identifies the key structural features of ligand and protein binding site responsible for isoform selectivity. The second aim was to build a three-dimensional structure of a novel HCMV target – AN UL98, to identify its catalytically important residues. HINT analysis of the interaction of 5’ DNA end at its active site is reported. A parallel aim to perform in silico screening with a site-based pharmacophore model, identified several novel hits with potentially desirable chemical features for interaction with UL98 AN. The majority of current protein-protein docking algorithms fail to account for water molecules involved in bridging interactions between partners, mediating and stabilizing their association. HINT is capable of reproducing the physical and chemical properties of such waters, while accounting for their energetic stabilizing contributions. We have designed a solvated protein-protein docking protocol that explicitly models the Relevant bridging waters, and demonstrate that more accurate results are obtained when water is not ignored.

No description available.

Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-06-05T14:58:52Z No. of bitstreams: 1 TES_RENATA_DE_PARIS_COMPLETO.pdf: 8873897 bytes, checksum: 43b2a883518fc9ce39978e816042ab5f (MD5) / Made available in DSpace on 2017-06-05T14:58:53Z (GMT). No. of bitstreams: 1 TES_RENATA_DE_PARIS_COMPLETO.pdf: 8873897 bytes, checksum: 43b2a883518fc9ce39978e816042ab5f (MD5) Previous issue date: 2016-10-28 / Conselho Nacional de Pesquisa e Desenvolvimento Cient?fico e Tecnol?gico - CNPq / O uso de conforma??es obtidas por trajet?rias da din?mica molecular nos experimentos de docagem molecular ? a abordagem mais precisa para simular o comportamento de receptores e ligantes em ambientes moleculares. Entretanto, tais simula??es exigem alto custo computacional e a sua completa execu??o pode se tornar uma tarefa impratic?vel devido ao vasto n?mero de informa??es estruturais consideradas para representar a expl?cita flexibilidade de receptores. Al?m disso, o problema ? ainda mais desafiante quando deseja-se utilizar modelos de receptores totalmente flex?veis (Fully-Flexible Receptor - FFR) para realizar a triagem virtual em bibliotecas de ligantes. Este estudo apresenta um m?todo inovador para otimizar a triagem virtual baseada em docagem molecular de modelos FFR por meio da redu??o do n?mero de experimentos de docagem e, da invoca??o escalar de workflows de docagem para m?quinas virtuais de plataformas em nuvem. Para esse prop?sito, o workflow cient?fico basedo em nuvem, chamado e-FReDock, foi desenvolvido para acelerar as simula??es da docagem molecular em larga escala. e-FReDock ? baseado em um m?todo seletivo sem param?tros para executar experimentos de docagem ensemble com m?ltiplos ligantes. Como dados de entrada do e-FReDock, aplicou-se seis m?todos de agrupamento para particionar conforma??es com diferentes caracter?sticas estruturais no s?tio de liga??o da cavidade do substrato do receptor, visando identificar grupos de conforma??es favor?veis a interagir com espec?ficos ligantes durante os experimentos de docagem. Os resultados mostram o elevado n?vel de qualidade obtido pelos modelos de receptores totalmente flex?veis reduzidos (Reduced Fully-Flexible Receptor - RFFR) ao final dos experimentos em dois conjuntos de an?lises. O primeiro mostra que e-FReDock ? capaz de preservar a qualidade do modelo FFR entre 84,00% e 94,00%, enquanto a sua dimensionalidade reduz em uma m?dia de 49,68%. O segundo relata que os modelos RFFR resultantes s?o capazes de melhorar os resultados de docagem molecular em 97,00% dos ligantes testados quando comparados com a vers?o r?gida do modelo FFR. / The use of conformations obtained from molecular dynamics trajectories in the molecular docking experiments is the most accurate approach to simulate the behavior of receptors and ligands in molecular environments. However, such simulations are computationally expensive and their execution may become an infeasible task due to the large number of structural information, typically considered to represent the explicit flexibility of receptors. In addition, the computational demand increases when Fully-Flexible Receptor (FFR) models are routinely applied for screening of large compounds libraries. This study presents a novel method to optimize docking-based virtual screening of FFR models by reducing the size of FFR models at docking runtime, and scaling docking workflow invocations out onto virtual machines from cloud platforms. For this purpose, we developed e-FReDock, a cloud-based scientific workflow that assists in faster high-throughput docking simulations of flexible receptors and ligands. e-FReDock is based on a free-parameter selective method to perform ensemble docking experiments with multiple ligands from a clustered FFR model. The e-FReDock input data was generated by applying six clustering methods for partitioning conformations with different features in their substrate-binding cavities, aiming at identifying groups of snapshots with favorable interactions for specific ligands at docking runtime. Experimental results show the high quality Reduced Fully-Flexible Receptor (RFFR) models achieved by e-FReDock in two distinct sets of analyses. The first analysis shows that e-FReDock is able to preserve the quality of the FFR model between 84.00% and 94.00%, while its dimensionality reduces on average 49.68%. The second analysis reports that resulting RFFR models are able to reach better docking results than those obtained from the rigid version of the FFR model in 97.00% of the ligands tested.

Una de les àrees més prometedores en recerca biomèdica i farmacèutica és el disseny molecular computacional, que intenta establir relacions entre propietats físico-químiques i activitat biològica. L'èxit d'aquestes tècniques depen críticament de la qualitat de la descripció molecular. En aquest sentit, metodologies basades en potencials d'interacció molecular (MIP) són eines útils per la comparació de compostos que presenten comportaments biològics semblants. Aquest projecte desenvolupa eines per comparar molècules basades en la caracterització de llurs MIPs. El programa de similaritat molecular MIPsim ha estat desenvolupat i aplicat a diferents problemes biològics. Aquesta tesi consisteix en quatre estudis científics que mostren l'ús del MIPSim en aliniament molecular, catalisi enzimàtica, en acoratge de molècules dins el lligand i en estudis 3D-QSAR. / One of the most promising areas in biomedical and pharmaceutical research is computer assisted molecular design, which tries to stablish relationships between physicochemical properties and biological activity. The success of these techniques depends critically on the quality of the molecular description. In this sense, methodologies based on molecular interaction potentials (MIP) are useful tools for the comparison of compounds displaying related biological behaviours. This project aims to develop tools to compare 'molecules based on the characterization 'of their MIPs. To this end, the molecular similarity program MIPSim has been further developed and applied to different biological problems. This thesis consists on four scientific studies showing the use of MIPSim for molecular alignment, enzymatic catalysis, ligand-protein docking and 3D-QSAR analyses.

Macromolecular interactions play very important roles in regulation of all levels of biological processes. Aberrant macromolecular interactions often result in diseases. By applying a combination of spectroscopy, calorimetry, computation and other techniques, the protein-protein interactions in the system of the Shaw2 Kv channel and the protein-RNA interactions in West Nile virus RNA-cellular protein TIAR complex were explored. In the former system, the results shed light on the local structures of the key channel components and their potential interaction mediated by butanol, a general anesthetic. In the later studies, the binding modes of TIAR RRM2 to oligoU RNAs and West Nile virus RNAs were investigated. These findings provided insights into the basis of the specific cellular protein–viral RNA interaction and preliminary data for the development of strategies on how to interfere with virus replication

Le docking moléculaire est une méthode permettant de prédire l'orientation d'une molécule donnée relativement à une autre lorsque celles-ci forment un complexe. Le premier algorithme de docking moléculaire a vu jour en 1990 afin de trouver de nouveaux candidats face à la protéase du VIH-1. Depuis, l'utilisation de protocoles de docking est devenue une pratique standard dans le domaine de la conception de nouveaux médicaments. Typiquement, un protocole de docking comporte plusieurs phases. Il requiert l'échantillonnage exhaustif du site d'interaction où les éléments impliqués sont considérées rigides. Des algorithmes de clustering sont utilisés afin de regrouper les candidats à l'appariement similaires. Des méthodes d'affinage sont appliquées pour prendre en compte la flexibilité au sein complexe moléculaire et afin d'éliminer de possibles artefacts de docking. Enfin, des algorithmes d'évaluation sont utilisés pour sélectionner les meilleurs candidats pour le docking. Cette thèse présente de nouveaux algorithmes de protocoles de docking qui facilitent la prédiction des structures de complexes protéinaires, une des cibles les plus importantes parmi les cibles visées par les méthodes de conception de médicaments. Une première contribution concerne l‘algorithme Docktrina qui permet de prédire les conformations de trimères protéinaires triangulaires. Celui-ci prend en entrée des prédictions de contacts paire-à-paire à partir d'hypothèse de corps rigides. Ensuite toutes les combinaisons possibles de paires de monomères sont évalués à l'aide d'un test de distance RMSD efficace. Cette méthode à la fois rapide et efficace améliore l'état de l'art sur les protéines trimères. Deuxièmement, nous présentons RigidRMSD une librairie C++ qui évalue en temps constant les distances RMSD entre conformations moléculaires correspondant à des transformations rigides. Cette librairie est en pratique utile lors du clustering de positions de docking, conduisant à des temps de calcul améliorés d'un facteur dix, comparé aux temps de calcul des algorithmes standards. Une troisième contribution concerne KSENIA, une fonction d'évaluation à base de connaissance pour l'étude des interactions protéine-protéine. Le problème de la reconstruction de fonction d'évaluation est alors formulé et résolu comme un problème d'optimisation convexe. Quatrièmement, CARBON, un nouvel algorithme pour l'affinage des candidats au docking basés sur des modèles corps-rigides est proposé. Le problème d'optimisation de corps-rigides est vu comme le calcul de trajectoires quasi-statiques de corps rigides influencés par la fonction énergie. CARBON fonctionne aussi bien avec un champ de force classique qu'avec une fonction d'évaluation à base de connaissance. CARBON est aussi utile pour l'affinage de complexes moléculaires qui comportent des clashes stériques modérés à importants. Finalement, une nouvelle méthode permet d'estimer les capacités de prédiction des fonctions d'évaluation. Celle-ci permet d‘évaluer de façon rigoureuse la performance de la fonction d'évaluation concernée sur des benchmarks de complexes moléculaires. La méthode manipule la distribution des scores attribués et non pas directement les scores de conformations particulières, ce qui la rend avantageuse au regard des critères standard basés sur le score le plus élevé. Les méthodes décrites au sein de la thèse sont testées et validées sur différents benchmarks protéines-protéines. Les algorithmes implémentés ont été utilisés avec succès pour la compétition CAPRI concernant la prédiction de complexes protéine-protéine. La méthodologie développée peut facilement être adaptée pour de la reconnaissance d'autres types d'interactions moléculaires impliquant par exemple des ligands, de l'ARN… Les implémentations en C++ des différents algorithmes présentés seront mises à disposition comme SAMSON Elements de la plateforme logicielle SAMSON sur http://www.samson-connect.net ou sur http://nano-d.inrialpes.fr/software. / Molecular docking is a method that predicts orientation of one molecule with respect to another one when forming a complex. The first computational method of molecular docking was applied to find new candidates against HIV-1 protease in 1990. Since then, using of docking pipelines has become a standard practice in drug discovery. Typically, a docking protocol comprises different phases. The exhaustive sampling of the binding site upon rigid-body approximation of the docking subunits is required. Clustering algorithms are used to group similar binding candidates. Refinement methods are applied to take into account flexibility of the molecular complex and to eliminate possible docking artefacts. Finally, scoring algorithms are employed to select the best binding candidates. The current thesis presents novel algorithms of docking protocols that facilitate structure prediction of protein complexes, which belong to one of the most important target classes in the structure-based drug design. First, DockTrina - a new algorithm to predict conformations of triangular protein trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) is presented. The method takes as input pair-wise contact predictions from a rigid-body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation (RMSD) test. Being fast and efficient, DockTrina outperforms state-of-the-art computational methods dedicated to predict structure of protein oligomers on the collected benchmark of protein trimers. Second, RigidRMSD - a C++ library that in constant time computes RMSDs between molecular poses corresponding to rigid-body transformations is presented. The library is practically useful for clustering docking poses, resulting in ten times speed up compared to standard RMSD-based clustering algorithms. Third, KSENIA - a novel knowledge-based scoring function for protein-protein interactions is developed. The problem of scoring function reconstruction is formulated and solved as a convex optimization problem. As a result, KSENIA is a smooth function and, thus, is suitable for the gradient-base refinement of molecular structures. Remarkably, it is shown that native interfaces of protein complexes provide sufficient information to reconstruct a well-discriminative scoring function. Fourth, CARBON - a new algorithm for the rigid-body refinement of docking candidates is proposed. The rigid-body optimization problem is viewed as the calculation of quasi-static trajectories of rigid bodies influenced by the energy function. To circumvent the typical problem of incorrect stepsizes for rotation and translation movements of molecular complexes, the concept of controlled advancement is introduced. CARBON works well both in combination with a classical force-field and a knowledge-based scoring function. CARBON is also suitable for refinement of molecular complexes with moderate and large steric clashes between its subunits. Finally, a novel method to evaluate prediction capability of scoring functions is introduced. It allows to rigorously assess the performance of the scoring function of interest on benchmarks of molecular complexes. The method manipulates with the score distributions rather than with scores of particular conformations, which makes it advantageous compared to the standard hit-rate criteria. The methods described in the thesis are tested and validated on various protein-protein benchmarks. The implemented algorithms are successfully used in the CAPRI contest for structure prediction of protein-protein complexes. The developed methodology can be easily adapted to the recognition of other types of molecular interactions, involving ligands, polysaccharides, RNAs, etc. The C++ versions of the presented algorithms will be made available as SAMSON Elements for the SAMSON software platform at http://www.samson-connect.net or at http://nano-d.inrialpes.fr/software.

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that leads to degradation of cartilage and bone mainly in peripheral joints. In collagen-induced arthritis (CIA), a mouse model for RA, activation of autoimmune CD4+ T cells depends on a molecular recognition system where T-cell receptors (TCRs) recognize a complex between the class II MHC Aq protein and CII259-273, a glycopeptide epitope from type II collagen (CII). Interestingly, vaccination with the Aq/CII259-273 complex can relieve symptoms and cause disease regression in mice. This thesis describes the use of modified glycopeptides to explore interactions important for binding to the Aq protein and recognition by autoimmune T-cell hybridomas obtained from mice with CIA. The CII259-273 glycopeptide was modified by replacement of backbone amides with different amide bond isosteres, as well as substitution of two residues that anchor the glycopeptide in prominent pockets in the Aq binding site. A three-dimensional structure of the Aq/glycopeptide complex was modeled to provide a structural basis for interpretation of the modified glycopeptide’s immunological activities. Overall, it was found that the amide bond isosteres affected Aq binding more than could be explained by the static model of the Aq/glycopeptide complex. Molecular dynamics (MD) simulations, however, revealed that the introduced amide bond isosteres substantially altered the hydrogen-bonding network formed between the N-terminal 259-265 backbone sequence of CII259-273 and Aq. These results indicated that the N-terminal hydrogen-bonding interactions follow a cooperative model, where the strength and presence of individual hydrogen bonds depended on the neighboring interactions. The two important anchor residues Ile260 and Phe263 were investigated using a designed library of CII259-273 based glycopeptides with substitutions by different (non-)natural amino acids at positions 260 and 263. Evaluation of binding to the Aq protein showed that there was scope for improvement in position 263 while Ile was preferred in position 260. The obtained SAR understanding provided a valuable basis for future development of modified glycopeptides with improved Aq binding. Furthermore, the modified glycopeptides elicited varying T-cell responses that generally could be correlated to their ability to bind to Aq. However, in several cases, there was a lack of correlation between Aq binding and T-cell recognition, which indicated that the interactions with the TCRs were determined by other factors, such as presentation of altered epitopes and changes in the kinetics of the TCR’s interaction with the Aq/glycopeptide complex. Several of the modified glycopeptides were also found to bind well to the human RA-associated DR4 protein and elicit strong responses with T-cell hybridomas obtained from transgenic mice expressing DR4 and the human CD4 co-receptor. This encourages future investigations of modified glycopeptides that can be used to further probe the MHC/glycopeptide/TCR recognition system and that also constitute potential therapeutic vaccines for treatment of RA. As a step towards this goal, three modified glycopeptides presented in this thesis have been identified as candidates for vaccination studies using the CIA mouse model.

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.