La dihydrofolate réductase R67, comme une cible d’antibiotiques et biocatalyseur potentiel

La dihyrofolate réductase de type II R67 (DHFR R67) est une enzyme bactérienne encodée par un plasmide donc aisément transmissible. Elle catalyse la réaction de réduction du dihydrofolate (DHF) en tétrahydrofolate (THFA) essentiel pour la prolifération cellulaire. La DHFR R67 est une enzyme qui dépend du cofacteur NADPH. La DHFR R67 est différente, structurellement et génétiquement, de l’enzyme DHFR chromosomale présente chez tous les organismes et elle est résistante au triméthoprime (TMP) qui est largement utilisé dans les traitements antibactériens chez l’Homme. Aucun inhibiteur sélectif contre la DHFR R67 n’est actuellement répertorié. Le but de cette étude a été d’identifier des molécules qui pourront inhiber la DHFR R67 sélectivement, sans affecter la DHFR humaine (DHFRh). La vérification de la qualité des essais enzymatiques en conditions déterminées pour le criblage d’inhibiteurs sur plusieurs lectrices à plaques a identifié des appareils appropriés pour l’analyse. L’étude de l’activité enzymatique de la DHFR R67 et de la DHFRh en présence des solvants organiques et liquides ioniques (LIs), comme des co-solvants pour le criblage rationnel d’inhibiteurs, a montré que certains LIs peuvent servir de milieu alternatif pour les essais enzymatiques. Le criblage rationnel basé sur l’approche du design d’un inhibiteur à partir de petites molécules, a révélé des molécules primaires qui inhibent la DHFR R67 de façon faible, mais sélective. Le test des composés biologiquement actifs qui comprennent des petits fragments, a montré l’augmentation de l’affinité entre la DHFR R67 et les composés testés. Trois composés ont été déterminés comme des inhibiteurs sélectifs prometteurs pour la DHFR R67.

Conception, synthèse et diversification de l'azaGly-Pro : un mime de tour beta, outil d'étude structure-activité : application au développement d'un nouvel agent tocolytique

Les accouchements prématurés constituent un problème médical majeur en constante augmentation et ce, malgré tous les efforts mis en œuvre afin de contrer le déclenchement des contractions avant terme. Cette thèse relate du ''design'' rationnel d'un nouvel agent thérapeutique (i.e., tocolytique) qui serait capable de 1) arrêter les contractions, et 2) prolonger la gestation. Pour ce faire, une nouvelle cible, la prostaglandine F2α et son récepteur ont été sélectionnés et le peptidomimétisme a été choisi afin de résoudre cette problématique. L'introduction contient un historique rapide de la conception à la synthèse (''drug design'') du peptide parent, le PDC113, premier peptide a avoir démontré des aptitudes tocolytiques suffisantes pour faire du peptidomimétisme. La deuxième partie de l'introduction présente les concepts du peptidomimétisme appliqués au PDC113 qui ont permis d'accéder au PDC113.824, inhibiteur allostérique du récepteur de la prostaglandine F2α, et explique comment ce mime nous a permis d'élucider les mécanismes de signalisation intracellulaire impliqués dans la contraction musculaire lisse. Cette thèse présente la conception, la synthèse et l'étude structure-activité de mimes de repliement de tour β au sein du mime peptidique original (PDC113.824) dans lequel nous avons remplacé l'azabicycloalkane central (l'indolizidin-2-one) par une série d'autres azabicycloalcanes connus et des acides aza-aminés dont nous avons élaboré la synthèse. Dans un premier temps, une nouvelle stratégie de synthèse en solution de l'aza-glycyl-proline à partir de la diphényle hydrazone et du chloroformate de p-nitrophényle a été réalisée. Cette stratégie a permis d'éliminer les réactions secondaires de cyclisation intramoléculaires communément obtenues lors de l'introduction d'acides aza-aminés avec les protections traditionnelles de type carbamate en présence de phosgène, mais aussi de faciliter l'accès en une étape à des dérivés peptidiques du type aza-glycyle. L'élongation de l'aza-glycyl-proline en solution nous a permis d'accéder à un nouveau mime tetrapeptidique du Smac, un activateur potentiel de l'apoptose au sein de cellules cancéreuses. Par la suite, nous avons développé une stratégie de diversification sélective de l'azote α du résidu azaglycine en utilisant différents types d'halogénures d'alkyle en présence de tert-butoxyde de potassium. Afin de valider le protocole d'alkylation de l'aza-dipeptide, différents halogénures d'alkyle ont été testés. Nous avons également démontré l'utilité des aza-dipeptides résultants en tant que ''building block'' afin d'accéder à une variété d'azapeptides. En effet, l'aza-dipeptide a été déprotégée sélectivement soit en N-terminal soit en C-terminal, respectivement. D'autre part, la libération de l'amine de l'ester méthylique de l'aza-alkylglycyl-proline a conduit à une catégorie de composés à potentiel thérapeutique, les azadicétopipérazines (aza-DKP) par cyclisation intramoléculaire. Enfin, notre intérêt quant au développement d'un nouvel agent tocolytique nous a amené à développer une nouvelle voie de synthèse en solution du PDC113.824 permettant ainsi d'élucider les voies de signalisation intracellulaires du récepteur de la prostaglandine F2α. Afin de valider l'importance de la stéréochimie et d'étudier la relation structure/ activité du mime, nous avons remplacé l'indolizidin-2-one (I2aa) centrale du PDC113.824 par une série d'autres azabicycloalcanes et azadipeptides. Les azabicycloalcanes D-I2aa, quinolizidinone, et indolizidin-9-one ont été synthétisés et incorporés au sein du dit peptide ne donnant aucune activité ni in vitro ni ex vivo, validant ainsi l'importance du tour β de type II' pour le maintien de l'activité biologique du PDC113.824. Finalement, l'insertion d'une série de dérivés aza(alkyl)glycyl-prolyles a mené à de nouveaux inhibiteurs allostériques du récepteur de la PGF2α, l'un contenant l'azaglycine et l'autre, l'azaphénylalanine. Cette thèse a ainsi contribué, grâce à la conception et l'application de nouvelles méthodes de synthèse d'aza-peptides, au développement de nouveaux composés à potentiel thérapeutique afin d'inhiber le travail prématuré.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Learning from Ambiguity

There are many learning problems for which the examples given by the teacher are ambiguously labeled. In this thesis, we will examine one framework of learning from ambiguous examples known as Multiple-Instance learning. Each example is a bag, consisting of any number of instances. A bag is labeled negative if all instances in it are negative. A bag is labeled positive if at least one instance in it is positive. Because the instances themselves are not labeled, each positive bag is an ambiguous example. We would like to learn a concept which will correctly classify unseen bags. We have developed a measure called Diverse Density and algorithms for learning from multiple-instance examples. We have applied these techniques to problems in drug design, stock prediction, and image database retrieval. These serve as examples of how to translate the ambiguity in the application domain into bags, as well as successful examples of applying Diverse Density techniques.

Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models

Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria.

Immersive Projection for biochemical pattern matching

In all biological processes, protein molecules and other small molecules interact to function and form transient macromolecular complexes. This interaction of two or more molecules can be described by a docking event. Docking is an important phase for structure-based drug design strategies, as it can be used as a method to simulate protein-ligand interactions. Various docking programs exist that allow automated docking, but most of them have limited visualization and user interaction. It would be advantageous if scientists could visualize the molecules participating in the docking process, manipulate their structures and manually dock them before submitting the new conformations to an automated docking process in an immersive environment, which can help stimulate the design/docking process. This also could greatly reduce docking time and resources. To achieve this, we propose a new virtual modelling/docking program, whereby the advantages of virtual modelling programs and the efficiency of the algorithms in existing docking programs will be merged.

Signaling mechanisms of GPCR ligands

G protein-coupled receptors constitute one of the major classes of drug targets, so understanding the mechanisms of signaling through these receptors is of great importance. This review covers some of the recent advances in G protein-coupled receptor signaling. A high resolution structure of the beta(2)-adrenergic receptor has been reported, as well as several molecular switches involved in receptor activation. It has also been realised that receptors and G proteins and their subunits may not always separate upon receptor activation. The definition of the ability of these receptors to signal has been expanded considerably with the realisation that some signaling may occur independently of G proteins, that some signaling events may differ in their pharmacological profiles and that formation of heterodimers of these receptors may provide new avenues for both signaling and drug design.

Antitumor activity of Titanocene Y in xenografted PC3 tumors in mice

Chemotherapeutic options for androgen-independent prostate cancer are extremely limited with minimum survival advantage. The benzyl-substituted unbridged titanocene bis-[(p-methoxybenzyl) cyclopentadienyl] titanium(IV) dichloride (Titanocene Y) was tested in vitro against the human prostate cancer androgen-independent cell, PC-3, which demonstrated an IC50 value of 56 x 10(-6) mol/L compared to 5.6 x 10(-6) mol/L for cisplatin. Then Titanocene Y was given at the maximum tolerable dose of 40 mg/kg/d on five consecutive days to one cohort of eight PC3 tumor-bearing male NMRI: nu/nu mice, while a second cohort was treated similarly with 3 mg/kg/d of cisplatin. Both of these mouse cohorts showed a statistically significant tumor growth reduction with respect to the third solvent-treated control group, which led to T/C values of 42% for cisplatin and 52% for Titanocene Y at the end of the experiment. This encouraging activity of Titanocene Y against prostate tumors in vivo, which is almost comparable with respect to cisplatin hopefully leads to further development of Titanocene Y in the future.

Molecular modelling studies of binding of DACD derivatives into G-Quadruplex DNA: comparison of force field and quantum polarized ligand docking methods

The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

Use of synthetic CaV2.2 Ca2+ channel peptides to study presynaptic function

Small, synthetic peptides based on specific regions of voltage-gated Ca2+ channels (VGCCs) have been widely used to study Ca2+ channel function and have been instrumental in confirming the contribution of specific amino acid sequences to interactions with putative binding partners. In particular, peptides based on the Ca2+ channel Alpha Interaction Domain (AID) on the intracellular region connecting domains I and II (the I-II loop) and the SYNaptic PRotein INTerction (synprint) site on the II-III loop have been widely used. Emerging evidence suggests that such peptides may themselves possess inherent functionality, a property that may be exploitable for future drug design. Here, we review our recent work using synthetic Ca2+ channel peptides based on sequences within the CaV2.2 amino terminal and I-II loop, originally identified as molecular determinates for G protein modulation, and their effects on VGCC function. These CaV2.2 peptides act as inhibitory modules to decrease Ca2+ influx with direct effects on VGCC gating, ultimately leading to a reduction of synaptic transmission. CaV2.2 peptides also attenuate G protein modulation of VGCCs. Amino acid substitutions generate CaV2.2 peptides with increased or decreased inhibitory effects suggesting that synthetic peptides can be used to further probe VGCC function and, potentially, form the basis for novel therapeutic development.

Biochemical and biophysical properties of a highly active recombinant arginase from Leishmania (Leishmania) amazonensis and subcellular localization of native enzyme

Arginase (L-arginine amidinohydrolase, E.C. 3.5.3.1) is a metalloenzyme that catalyses the hydrolysis Of L-arginine to L-ornithine and urea. In Leishmania spp., the biological role of the enzyme may be involved in modulating NO production upon macrophage infection. Previously, we cloned and characterized the arginase gene from Leishmania (Leishmania) amazonensis. In the present work, we successfully expressed the recombinant enzyme in E. coli and performed biochemical and biophysical characterization of both the native and recombinant enzymes. We obtained K-M and V-max. values of 23.9(+/- 0.96) mM and 192.3 mu mol/min mg protein (+/- 14.3), respectively, for the native enzyme. For the recombinant counterpart, K-M was 21.5(+/- 0.90) mM and V-max was 144.9(+/- 8.9) mu mol/min mg. Antibody against the recombinant protein confirmed a glycosomal cellular localization of the enzyme in promastigotes. Data from light scattering and small angle X-ray scattering showed that a trimeric state is the active form of the protein. We determined empirically that a manganese wash at room temperature is the best condition to purify active enzyme. The interaction of the recombinant protein with the immobilized nickel also allowed us to confirm the structural disposition of histidine at positions 3 and 324. The determined structural parameters provide substantial data to facilitate the search for selective inhibitors of parasitic sources of arginase, which could subsequently point to a candidate for leishmaniasis therapy. (c) 2008 Elsevier B.V. All rights reserved.

Systematic structural studies of iron superoxide dismutases from human parasites and a statistical coupling analysis of metal binding specificity

Superoxide dismutases (SODs) are a crucial class of enzymes in the combat against intracellular free radical damage. They eliminate superoxide radicals by converting them into hydrogen peroxide and oxygen. In spite of their very different life cycles and infection strategies, the human parasites Plasmodium falciparum, Trypanosoma cruzi and Trypanosoma brucei are known to be sensitive to oxidative stress. Thus the parasite Fe-SODs have become attractive targets for novel drug development. Here we report the crystal structures of FeSODs from the trypanosomes T. brucei at 2.0 angstrom and T. cruzi at 1.9 angstrom resolution, and that from P. falciparum at a higher resolution (2.0 angstrom) to that previously reported. The homodimeric enzymes are compared to the related human MnSOD with particular attention to structural aspects which are relevant for drug design. Although the structures possess a very similar overall fold, differences between the enzymes at the entrance to the channel which leads to the active site could be identified. These lead to a slightly broader and more positively charged cavity in the parasite enzymes. Furthermore, a statistical coupling analysis (SCA) for the whole Fe/MnSOD family reveals different patterns of residue coupling for Mn and Fe SODs, as well as for the dimeric and tetrameric states. In both cases, the statistically coupled residues lie adjacent to the conserved core surrounding the metal center and may be expected to be responsible for its fine tuning, leading to metal ion specificity.

Quantitative structure-activity relationships for a series of inhibitors of cruzain from Trypanosoma cruzi: Molecular modeling, CoMFA and CoMSIA studies

Human parasitic diseases are the foremost threat to human health and welfare around the world. Trypanosomiasis is a very serious infectious disease against which the currently available drugs are limited and not effective. Therefore, there is an urgent need for new chemotherapeutic agents. One attractive drug target is the major cysteine protease from Trypanosoma cruzi, cruzain. In the present work, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted on a series of thiosemicarbazone and semicarbazone derivatives as inhibitors of cruzain. Molecular modeling studies were performed in order to identify the preferred binding mode of the inhibitors into the enzyme active site, and to generate structural alignments for the three-dimensional quantitative structure-activity relationship (3D QSAR) investigations. Statistically significant models were obtained (CoMFA. r(2) = 0.96 and q(2) = 0.78; CoMSIA, r(2) = 0.91 and q(2) = 0.73), indicating their predictive ability for untested compounds. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the information gathered from the 3D CoMFA and CoMSIA contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of cruzain inhibitors, and should be useful for the design of new structurally related analogs with improved potency. (C) 2009 Elsevier Inc. All rights reserved.

Kinetic and Crystallographic Studies on Glyceraldehyde-3-Phosphate Dehydrogenase from Trypanosoma cruzi in Complex with Iodoacetate

Kinetic and crystallographic studies on the formation of the complex between iodoacetate and the enzyme glyceraldehyde-3-phosphate dehydrogenase from Trypanosoma cruzi were conducted in order to investigate the mechanistic and structural basis underlying enzyme inactivation. The crystallographic complex reveal important structural features useful for the design of novel inhibitors.