Nanostructure des particules polymériques : aspects physiques, chimiques et biologiques

Les nanotechnologies appliquées aux sciences pharmaceutiques ont pour but d’améliorer l’administration de molécules actives par l’intermédiaire de transporteurs nanométriques. Parmi les différents types de véhicules proposés pour atteindre ce but, on retrouve les nanoparticules polymériques (NP) constituées de copolymères “en bloc”. Ces copolymères permettent à la fois l’encapsulation de molécules actives et confèrent à la particule certaines propriétés de surface (dont l’hydrophilicité) nécessaires à ses interactions avec les milieux biologiques. L’architecture retenue pour ces copolymères est une structure constituée le plus fréquemment de blocs hydrophiles de poly(éthylène glycol) (PEG) associés de façon linéaire à des blocs hydrophobes de type polyesters. Le PEG est le polymère de choix pour conférer une couronne hydrophile aux NPs et son l’efficacité est directement liée à son organisation et sa densité de surface. Néanmoins, malgré les succès limités en clinique de ces copolymères linéaires, peu de travaux se sont attardés à explorer les effets sur la structure des NPs d’architectures alternatives, tels que les copolymères en peigne ou en brosse. Durant ce travail, plusieurs stratégies ont été mises au point pour la synthèse de copolymères en peigne, possédant un squelette polymérique polyesters-co-éther et des chaines de PEG liées sur les groupes pendants disponibles (groupement hydroxyle ou alcyne). Dans la première partie de ce travail, des réactions d’estérification par acylation et de couplage sur des groupes pendants alcool ont permis le greffage de chaîne de PEG. Cette méthode génère des copolymères en peigne (PEG-g-PLA) possédant de 5 à 50% en poids de PEG, en faisant varier le nombre de chaînes branchées sur un squelette de poly(lactique) (PLA). Les propriétés structurales des NPs produites ont été étudiées par DLS, mesure de charge et MET. Une transition critique se situant autour de 15% de PEG (poids/poids) est observée avec un changement de morphologie, d’une particule solide à une particule molle (“nanoagrégat polymére”). La méthode de greffage ainsi que l’addition probable de chaine de PEG en bout de chaîne principale semblent également avoir un rôle dans les changements observés. L’organisation des chaînes de PEG-g-PLA à la surface a été étudiée par RMN et XPS, méthodes permettant de quantifier la densité de surface en chaînes de PEG. Ainsi deux propriétés clés que sont la résistance à l’agrégation en conditions saline ainsi que la résistance à la liaison aux protéines (étudiée par isothermes d’adsorption et microcalorimétrie) ont été reliées à la densité de surface de PEG et à l’architecture des polymères. Dans une seconde partie de ce travail, le greffage des chaînes de PEG a été réalisé de façon directe par cyclo-adition catalysée par le cuivre de mPEG-N3 sur les groupes pendants alcyne. Cette nouvelle stratégie a été pensée dans le but de comprendre la contribution possible des chaines de PEG greffées à l’extrémité de la chaine de PLA. Cette librairie de PEG-g-PLA, en plus d’être composée de PEG-g-PLA avec différentes densités de greffage, comporte des PEG-g-PLA avec des PEG de différent poids moléculaire (750, 2000 et 5000). Les chaines de PEG sont seulement greffées sur les groupes pendants. Les NPs ont été produites par différentes méthodes de nanoprécipitation, incluant la nanoprécipitation « flash » et une méthode en microfluidique. Plusieurs variables de formulation telles que la concentration du polymère et la vitesse de mélange ont été étudiées afin d’observer leur effet sur les caractéristiques structurales et de surface des NPs. Les tailles et les potentiels de charges sont peu affectés par le contenu en PEG (% poids/poids) et la longueur des chaînes de PEG. Les images de MET montrent des objets sphériques solides et l'on n’observe pas d’objets de type agrégat polymériques, malgré des contenus en PEG comparable à la première bibliothèque de polymère. Une explication possible est l’absence sur ces copolymères en peigne de chaine de PEG greffée en bout de la chaîne principale. Comme attendu, les tailles diminuent avec la concentration du polymère dans la phase organique et avec la diminution du temps de mélange des deux phases, pour les différentes méthodes de préparation. Finalement, la densité de surface des chaînes de PEG a été quantifiée par RMN du proton et XPS et ne dépendent pas de la méthode de préparation. Dans la troisième partie de ce travail, nous avons étudié le rôle de l’architecture du polymère sur les propriétés d’encapsulation et de libération de la curcumine. La curcumine a été choisie comme modèle dans le but de développer une plateforme de livraison de molécules actives pour traiter les maladies du système nerveux central impliquant le stress oxydatif. Les NPs chargées en curcumine, montrent la même transition de taille et de morphologie lorsque le contenu en PEG dépasse 15% (poids/poids). Le taux de chargement en molécule active, l’efficacité de changement et les cinétiques de libérations ainsi que les coefficients de diffusion de la curcumine montrent une dépendance à l’architecture des polymères. Les NPs ne présentent pas de toxicité et n’induisent pas de stress oxydatif lorsque testés in vitro sur une lignée cellulaire neuronale. En revanche, les NPs chargées en curcumine préviennent le stress oxydatif induit dans ces cellules neuronales. La magnitude de cet effet est reliée à l’architecture du polymère et à l’organisation de la NP. En résumé, ce travail a permis de mettre en évidence quelques propriétés intéressantes des copolymères en peigne et la relation intime entre l’architecture des polymères et les propriétés physico-chimiques des NPs. De plus les résultats obtenus permettent de proposer de nouvelles approches pour le design des nanotransporteurs polymériques de molécules actives.

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.

Conductance of amyloid β based peptide filaments: structure–function relations.

Controlling the morphology of self-assembled peptide nanostructures, particularly those based on amyloid peptides, has been the focus of intense research. In order to exploit these structures in electronic applications, further understanding of their electronic behavior is required. In this work, the role of peptide morphology in determining electronic conduction along self-assembled peptide nanofilament networks is demonstrated. The peptides used in this work were based on the sequence AAKLVFF, which is an extension of a core sequence from the amyloid b peptide. We show that the incorporation of a non-natural amino acid, 2-thienylalanine, instead of phenylalanine improves the obtained conductance with respect to that obtained for a similar structure based on the native sequence, which was not the case for the incorporation of 3-thienylalanine. Furthermore, we demonstrate that the morphology of the self-assembled structures, which can be controlled by the solvent used in the assembly process, strongly affects the conductance, with larger conduction obtained for a morphology of long, straight filaments. Our results demonstrate that, similar to natural systems, the assembly and folding of peptides could be of great importance for optimizing their function as components of electronic devices. Hence, sequence design and assembly conditions can be used to control the performance of peptide based structures in such electronic applications.

Insights into dietary flavonoids as molecular templates for the design of anti-platelet drugs

Flavonoids are low-molecular weight, aromatic compounds derived from fruits, vegetables, and other plant components. The consumption of these phytochemicals has been reported to be associated with reduced cardiovascular disease (CVD) risk, attributed to their anti-inflammatory, anti-proliferative, and anti-thrombotic actions. Flavonoids exert these effects by a number of mechanisms which include attenuation of kinase activity mediated at the cell-receptor level and/or within cells, and are characterized as broad-spectrum kinase inhibitors. Therefore, flavonoid therapy for CVD is potentially complex; the use of these compounds as molecular templates for the design of selective and potent small-molecule inhibitors may be a simpler approach to treat this condition. Flavonoids as templates for drug design are, however, poorly exploited despite the development of analogues based on the flavonol, isoflavonone, and isoflavanone subgroups. Further exploitation of this family of compounds is warranted due to a structural diversity that presents great scope for creating novel kinase inhibitors. The use of computational methodologies to define the flavonoid pharmacophore together with biological investigations of their effects on kinase activity, in appropriate cellular systems, is the current approach to characterize key structural features that will inform drug design. This focussed review highlights the potential of flavonoids to guide the design of clinically safer, more selective, and potent small-molecule inhibitors of cell signalling, applicable to anti-platelet therapy.

Investigating flavonoids as molecular templates for the design of small-molecule inhibitors of cell signaling

Epidemiological and clinical trials reveal compelling evidence for the ability of dietary flavonoids to lower cardiovascular disease risk. The mechanisms of action of these polyphenolic compounds are diverse, and of particular interest is their ability to function as protein and lipid kinase inhibitors. We have previously described structure-activity studies that reinforce the possibility for using flavonoid structures as templates for drug design. In the present study, we aim to begin constructing rational screening strategies for exploiting these compounds as templates for the design of clinically relevant, antiplatelet agents. We used the platelet as a model system to dissect the structural influence of flavonoids, stilbenes, anthocyanidins, and phenolic acids on inhibition of cell signaling and function. Functional groups identified as relevant for potent inhibition of platelet function included at least 2 benzene rings, a hydroxylated B ring, a planar C ring, a C ring ketone group, and a C-2 positioned B ring. Hydroxylation of the B ring with either a catechol group or a single C-4' hydroxyl may be required for efficient inhibition of collagen-stimulated tyrosine phosphorylated proteins of 125 to 130 kDa, but may not be necessary for that of phosphotyrosine proteins at approximately 29 kDa. The removal of the C ring C-3 hydroxyl together with a hydroxylated B ring (apigenin) may confer selectivity for 37 to 38 kDa phosphotyrosine proteins. We conclude that this study may form the basis for construction of maps of flavonoid inhibitory activity on kinase targets that may allow a multitargeted therapeutic approach with analogue counterparts and parent compounds.

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.

Discovery of novel Trypanosoma cruzi glyceraldehyde-3-phosphate dehydrogenase inhibitors

Based on its essential role in the life cycle of Trypanosoma cruzi, the glycolytic enzyme glyceraldehyde 3-phosphate dehydrogenase (GAPDH) has been considered a promising target for the development of novel chemotherapeutic agents for the treatment of Chagas` disease. In the course of our research program to discover novel inhibitors of this trypanosomatid enzyme, we have explored a combination of structure and ligand-based virtual screening techniques as a complementary approach to a biochemical screening of natural products using a standard biochemical assay. Seven natural products, including anacardic acids,. avonoid derivatives, and one glucosylxanthone were identified as novel inhibitors of T. cruzi GAPDH. Promiscuous inhibition induced by nonspecific aggregation has been discarded as specific inhibition was not reversed or affected in all cases in the presence of Triton X-100, demonstrating the ability of the assay to find authentic inhibitors of the enzyme. The structural diversity of this series of promising natural products is of special interest in drug design, and should therefore be useful in future medicinal chemistry efforts aimed at the development of new GAPDH inhibitors having increased potency. (C) 2009 Elsevier Ltd. All rights reserved.

Classical and hologram QSAR studies on a series of inhibitors of trypanosomatid Glyceraldehyde-3-Phosphate Dehydrogenase

Leishmaniasis and trypanosomiasis are major causes of morbidity and mortality in both tropical and subtropical regions of the world. The current available drugs are limited, ineffective, and require long treatment regimens. Due to the high dependence of trypanosomatids on glycolysis as a source of energy, some glycolytic enzymes have been identified as attractive targets for drug design. In the present work, classical Two-Dimensional Quantitative Structure -Activity Relationships (2D QSAR) and Hologram QSAR (HQSAR) studies were performed on a series of adenosine derivatives as inhibitors of Leishmania mexicana Glyceraldehyde-3-Phosphate Dehydrogenase (LmGAPDH). Significant correlation coefficients (classical QSAR, r(2)=0.83 and q(2) =0.81; HQSAR, r(2)=0.91 and q(2) =0.86) were obtained for the 56 training set compounds, indicating the potential of the models for untested compounds. The models were then externally validated using a test set of 14 structurally related compounds and the predicted values were in good agreement with the experimental results (classical QSAR, r(pred)(2) = 0.94; HQSAR, r(pred)(2) = 0.92).

Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

Natural products biological screening and ligand-based virtual screening for the discovery of new antileishmanial agents

In the course of our research program to discover novel antileishmanial agents, a biological screening of natural products against Leishmania major promastigotes allowed the identification of a furoquinoline alkaloid (1) and a furanocoumarin (2) as new hits. Subsequently, an integrated ligand-based virtual screening approach was employed to search for new antileishmanial compounds using these naturally occurring molecules as templates. Fourteen out of 40 compounds selected from a database of about 800,000 compounds (extracted from ZINC, a free database for virtual screening) were experimentally confirmed to possess significant in vitro antileishmanial properties. The application of ligand-based virtual screening as a complementary approach to experimental natural product screening was a useful strategy to facilitate the identification of new promising lead candidates.

Pharmacophore-based 3D QSAR studies on a series of high affinity 5-HT(1A) receptor ligands

5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds. (C) 2010 Elsevier Masson SAS. All rights reserved.

Structural basis for selective inhibition of purine nucleoside phosphorylase from Schistosoma mansoni: Kinetic and structural studies

Selectivity plays a crucial role in the design of enzyme inhibitors as novel antiparasitic agents, particularly in cases where the target enzyme is also present in the human host. Purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive target for the discovery of potential antischistosomal agents. In the present work, kinetic studies were carried out in order to determine the inhibitory potency, mode of action and enzyme selectivity of a series of inhibitors of SmPNP. In addition, crystallographic studies provided important structural insights for rational inhibitor design, revealing consistent structural differences in the binding mode of the inhibitors in the active sites of the SmPNP and human PNP (HsPNP) structures. The molecular information gathered in this work should be useful for future medicinal chemistry efforts in the design of new inhibitors of SmPNP having increased affinity and selectivity. (C) 2010 Elsevier Ltd. All rights reserved.

Drug delivery systems: Past, present, and future

Drug delivery systems are essential components of drugs controlled release. In the last decades, several drug delivery technologies have emerged including capsules, liposomes. microparticles, nanoparticles, and polymers. These components must be biocompatible, biodegradable, and display a desired biodistribution providing a long-term availability of the therapeutic at specific target over time.

Recent Insights on the Medicinal Chemistry of Sickle Cell Disease

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.