The construction and optimization of a surface plasmon resonance sensor for the studies of bio-molecular interactions

Bio-molecular interactions exist ubiquitously in all biological systems. This dissertation project was to construct a powerful surface plasmon resonance (SPR) sensor. The SPR system is used to study bio-molecular interactions in real time and without labeling. Surface plasmon is the oscillation of free electrons in metals coupled with surface electromagnetic waves. These surface electromagnetic waves provide a sensitive probe to study bio-molecular interactions on metal surfaces. This project resulted in the successful construction and optimization of a homemade SPR sensor and the development of several new powerful protocols to study bio-molecular interactions. It was discovered through this project that the limitations of earlier SPR sensors are related not only to the instrumentation design and operating procedures, but also to the complex behaviors of bio-molecules on sensor surfaces that were very different from that in solution. Based on these discoveries the instrumentation design and operating procedures were fully optimized. A set of existing sensor surface treatment protocols were tested and evaluated and new protocols were developed in this project. The new protocols have demonstrated excellent performance to study biomolecular interactions. The optimized home-made SPR sensor was used to study protein-surface interactions. These protein-surface interactions are responsible for many complex organic cell activities. The co-existence of different driving forces and their correlation with the structure of the protein and the surface make the understanding of the fundamental mechanism of protein-surface interactions a very challenging task. Using the improved SPR sensor, the electrostatic interaction and hydrophobic interaction were studied separately. The results of this project directly confirmed the theoretical predictions for electrostatic force between the protein and surface. In addition, this project demonstrated that the strength of the protein-surface hydrophobic interaction does not solely depend on the hydrophobicity as reported earlier. Surface structure also plays a significant role.

An investigation of the molecular interactions between statins and bacterial pathogens, and their combined impact on the human immune system

Statins are a class of drug that inhibits cholesterol biosynthesis, and are used to treat patients with high serum cholesterol levels. They exert this function by competitively binding to the enzyme 3-hydroxy-3-methylglutaryl-CoenzymeA reductase (HMGR), which catalyses the formation of mevalonate, a rate-limiting step in cholesterol biosynthesis. In addition, statins have what are called “pleiotropic effects”, which include the reduction of inflammation, immunomodulation, and antimicrobial effects. Statins can also improve survival of patients with sepsis and pneumonia. Cystic fibrosis (CF) is the most common recessive inherited disease in the Caucasian population, which is characterised by factors including, but not limited to, excessive lung inflammation and increased susceptibility to infection. Therefore, the overall objective of this study was to examine the effects of statins on CFassociated bacterial pathogens and the host response. In this work, the prevalence of HMGR was examined in respiratory pathogens, and several CF-associated pathogens were found to possess homologues of this enzyme. HMGR homology was analysed in Staphylococcus aureus, Burkholderia cenocepacia and Streptococcus pneumoniae, and the HMGR of B. cenocepacia was found to have significant conservation to that of Pseudomonas mevalonii, which is the most widely-characterised bacterial HMGR. However, in silico analysis revealed that, unlike S. aureus and S. pneumoniae, B. cenocepacia did not possess homologues of other mevalonate pathway proteins, and that the HMGR of B. cenocepacia appeared to be involved in an alternative metabolic pathway. The effect of simvastatin was subsequently tested on the growth and virulence of S. aureus, B. cenocepacia and S. pneumoniae. Simvastatin inhibited the growth of all 3 species in a dose-dependent manner. In addition, statin treatment also attenuated biofilm formation of all 3 species, and reduced in vitro motility of S. aureus. Interestingly, simvastatin also increased the potency of the aminoglycoside antibiotic gentamicin against B. cenocepacia. The impact of statins was subsequently tested on the predominant CF-associated pathogen Pseudomonas aeruginosa, which does not possess a HMGR homologue. Mevastatin, lovastatin and simvastatin did not influence the growth of this species. However, sub-inhibitory statin concentrations reduced the swarming motility and biofilm formation of P. aeruginosa. The influence of statins was also examined on Type 3 toxin secretion, quorum sensing and chemotaxis, and no statin effect was observed on any of these phenotypes. Statins did not appear to have a characteristic effect on the P. aeruginosa transcriptome. However, a mutant library screen revealed that the effect of statins on P. aeruginosa biofilm was mediated through the PvrR regulator and the Cup fimbrial biosynthesis genes. Furthermore, proteomic analysis demonstrated that 6 proteins were reproducibly induced by simvastatin in the P. aeruginosa swarming cells. The effect of statins on the regulation of the host-P. aeruginosa immune response was also investigated. Statin treatment increased expression of the pro-inflammatory cytokines IL-8 and CCL20 in lung epithelial cells, but did not attenuate P. aeruginosa-mediated inflammatory gene induction. In fact, simvastatin and P. aeruginosa caused a synergistic effect on CCL20 expression. The expression of the transcriptional regulators KLF2 and KLF6 was also increased by statins and P. aeruginosa, with the induction of KLF6 by simvastatin proving to be a novel effect. Interestingly, both statins and P. aeruginosa were capable of inducing alternative splicing of KLF6. P. aeruginosa was found to induce KLF6 alternative splicing by way of the type 3 secreted toxin ExoS. In addition, a mechanistic role was elucidated for KLF6 in the lung, as it was determined that statin-mediated induction of this protein was responsible for the induction of the host response genes CCL20 and iNOS. Moreover, statin treatment caused a slight increase in infection-related cytotoxicity, and increased bacterial adhesion to cells. Taken together, these data demonstrate that statins can reduce the virulence of CFassociated bacterial pathogens and alter host response effectors. Furthermore, novel statin effectors were identified in both bacterial and host cells.

Estrogen and thyroid hormone receptor interactions: physiological flexibility by molecular specificity

The influence of thyroid hormone on estrogen actions has been demonstrated both in vivo and in vitro. In transient transfection assays, the effects of liganded thyroid hormone receptors (TR) on transcriptional facilitation by estrogens bound to estrogen receptors (ER) display specificity according to the following: 1) ER isoform, 2) TR isoform, 3) the promoter through which transcriptional facilitation occurs, and 4) cell type. Some of these molecular phenomena may be related to thyroid hormone signaling of seasonal limitations upon reproduction. The various combinations of these molecular interactions provide multiple and flexible opportunities for relations between two major hormonal systems important for neuroendocrine feedbacks and reproductive behaviors.

High molecular weight kininogen regulates platelet-leukocyte interactions by bridging Mac-1 and glycoprotein Ib

Leukocyte-platelet interaction is important in mediating leukocyte adhesion to a thrombus and leukocyte recruitment to a site of vascular injury. This interaction is mediated at least in part by the beta2-integrin Mac-1 (CD11b/CD18) and its counter-receptor on platelets, glycoprotein Ibalpha (GPIbalpha). High molecular weight kininogen (HK) was previously shown to interact with both GPIbalpha and Mac-1 through its domains 3 and 5, respectively. In this study we investigated the ability of HK to interfere with the leukocyte-platelet interaction. In a purified system, HK binding to GPIbalpha was inhibited by HK domain 3 and the monoclonal antibody (mAb) SZ2, directed against the epitope 269-282 of GPIbalpha, whereas mAb AP1, directed to the region 201-268 of GPIbalpha had no effect. In contrast, mAb AP1 inhibited the Mac-1-GPIbalpha interaction. Binding of GPIbalpha to Mac-1 was enhanced 2-fold by HK. This effect of HK was abrogated in the presence of HK domains 3 or 5 or peptides from the 475-497 region of the carboxyl terminus of domain 5 as well as in the presence of mAb SZ2 but not mAb AP1. Whereas no difference in the affinity of the Mac-1-GPIbalpha interaction was observed in the absence or presence of HK, maximal binding of GPIbalpha to Mac-1 doubled in the presence of HK. Moreover, HK/HKa increased the Mac-1-dependent adhesion of myelomonocytic U937 cells and K562 cells transfected with Mac-1 to immobilized GPIbalpha or to GPIbalpha-transfected Chinese hamster ovary cells. Finally, Mac-1-dependent adhesion of neutrophils to surface-adherent platelets was enhanced by HK. Thus, HK can bridge leukocytes with platelets by interacting via its domain 3 with GPIbalpha and via its domain 5 with Mac-1 thereby augmenting the Mac-1-GPIbalpha interaction. These distinct molecular interactions of HK with leukocytes and platelets contribute to the regulation of the adhesive behavior of vascular cells and provide novel molecular targets for reducing atherothrombotic pathologies.

Molecular modeling study of the binding and signaling properties of the TCRpMHC complex

The activation of the specific immune response against tumor cells is based on the recognition by the CD8+ Cytotoxic Τ Lymphocytes (CTL), of antigenic peptides (p) presented at the surface of the cell by the class I major histocompatibility complex (MHC). The ability of the so-called T-Cell Receptors (TCR) to discriminate between self and non-self peptides constitutes the most important specific control mechanism against infected cells. The TCR/pMHC interaction has been the subject of much attention in cancer therapy since the design of the adoptive transfer approach, in which Τ lymphocytes presenting an interesting response against tumor cells are extracted from the patient, expanded in vitro, and reinfused after immunodepletion, possibly leading to cancer regression. In the last decade, major progress has been achieved by the introduction of engineered lypmhocytes. In the meantime, the understanding of the molecular aspects of the TCRpMHC interaction has become essential to guide in vitro and in vivo studies. In 1996, the determination of the first structure of a TCRpMHC complex by X-ray crystallography revealed the molecular basis of the interaction. Since then, molecular modeling techniques have taken advantage of crystal structures to study the conformational space of the complex, and understand the specificity of the recognition of the pMHC by the TCR. In the meantime, experimental techniques used to determine the sequences of TCR that bind to a pMHC complex have been used intensively, leading to the collection of large repertoires of TCR sequences that are specific for a given pMHC. There is a growing need for computational approaches capable of predicting the molecular interactions that occur upon TCR/pMHC binding without relying on the time consuming resolution of a crystal structure. This work presents new approaches to analyze the molecular principles that govern the recognition of the pMHC by the TCR and the subsequent activation of the T-cell. We first introduce TCRep 3D, a new method to model and study the structural properties of TCR repertoires, based on homology and ab initio modeling. We discuss the methodology in details, and demonstrate that it outperforms state of the art modeling methods in predicting relevant TCR conformations. Two successful applications of TCRep 3D that supported experimental studies on TCR repertoires are presented. Second, we present a rigid body study of TCRpMHC complexes that gives a fair insight on the TCR approach towards pMHC. We show that the binding mode of the TCR is correctly described by long-distance interactions. Finally, the last section is dedicated to a detailed analysis of an experimental hydrogen exchange study, which suggests that some regions of the constant domain of the TCR are subject to conformational changes upon binding to the pMHC. We propose a hypothesis of the structural signaling of TCR molecules leading to the activation of the T-cell. It is based on the analysis of correlated motions in the TCRpMHC structure. - L'activation de la réponse immunitaire spécifique dirigée contre les cellules tumorales est basée sur la reconnaissance par les Lymphocytes Τ Cytotoxiques (CTL), d'un peptide antigénique (p) présenté à la suface de la cellule par le complexe majeur d'histocompatibilité de classe I (MHC). La capacité des récepteurs des lymphocytes (TCR) à distinguer les peptides endogènes des peptides étrangers constitue le mécanisme de contrôle le plus important dirigé contre les cellules infectées. L'interaction entre le TCR et le pMHC est le sujet de beaucoup d'attention dans la thérapie du cancer, depuis la conception de la méthode de transfer adoptif: les lymphocytes capables d'une réponse importante contre les cellules tumorales sont extraits du patient, amplifiés in vitro, et réintroduits après immunosuppression. Il peut en résulter une régression du cancer. Ces dix dernières années, d'importants progrès ont été réalisés grâce à l'introduction de lymphocytes modifiés par génie génétique. En parallèle, la compréhension du TCRpMHC au niveau moléculaire est donc devenue essentielle pour soutenir les études in vitro et in vivo. En 1996, l'obtention de la première structure du complexe TCRpMHC à l'aide de la cristallographie par rayons X a révélé les bases moléculaires de l'interaction. Depuis lors, les techniques de modélisation moléculaire ont exploité les structures expérimentales pour comprendre la spécificité de la reconnaissance du pMHC par le TCR. Dans le même temps, de nouvelles techniques expérimentales permettant de déterminer la séquence de TCR spécifiques envers un pMHC donné, ont été largement exploitées. Ainsi, d'importants répertoires de TCR sont devenus disponibles, et il est plus que jamais nécessaire de développer des approches informatiques capables de prédire les interactions moléculaires qui ont lieu lors de la liaison du TCR au pMHC, et ce sans dépendre systématiquement de la résolution d'une structure cristalline. Ce mémoire présente une nouvelle approche pour analyser les principes moléculaires régissant la reconnaissance du pMHC par le TCR, et l'activation du lymphocyte qui en résulte. Dans un premier temps, nous présentons TCRep 3D, une nouvelle méthode basée sur les modélisations par homologie et ab initio, pour l'étude de propriétés structurales des répertoires de TCR. Le procédé est discuté en détails et comparé à des approches standard. Nous démontrons ainsi que TCRep 3D est le plus performant pour prédire des conformations pertinentes du TCR. Deux applications à des études expérimentales des répertoires TCR sont ensuite présentées. Dans la seconde partie de ce travail nous présentons une étude de complexes TCRpMHC qui donne un aperçu intéressant du mécanisme d'approche du pMHC par le TCR. Finalement, la dernière section se concentre sur l'analyse détaillée d'une étude expérimentale basée sur les échanges deuterium/hydrogène, dont les résultats révèlent que certaines régions clés du domaine constant du TCR sont sujettes à un changement conformationnel lors de la liaison au pMHC. Nous proposons une hypothèse pour la signalisation structurelle des TCR, menant à l'activation du lymphocyte. Celle-ci est basée sur l'analyse des mouvements corrélés observés dans la structure du TCRpMHC.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Interactions of chitosan/genipin hydrogels during drug delivery: a QSPR approach

A hydrogel comprised of chitosan crosslinked using the low-toxicity crosslinker genipin was prepared, and the absorption of glibenclamide by the hydrogel was investigated. Optimized structures and their molecular electrostatic potentials were calculated using the AM1 method, and the results were used to evaluate the molecular interactions between the three compounds. The quantitative structure-property relationship model was also used to estimate the activity of the chemicals on the basis their molecular structures. In addition, theoretical Fourier transform infrared spectra were calculated to analyze the intermolecular interactions in the proposed system. Finally, the hydrophilicity of the hydrogel and its influence on the absorption process were also estimated.

Nutrimetabonomics: applications for nutritional sciences, with specific reference to gut microbial interactions

Understanding the role of the diet in determining human health and disease is one major objective of modern nutrition. Mammalian biocomplexity necessitates the incorporation of systems biology technologies into contemporary nutritional research. Metabonomics is a powerful approach that simultaneously measures the low-molecular-weight compounds in a biological sample, enabling the metabolic status of a biological system to be characterized. Such biochemical profiles contain latent information relating to inherent parameters, such as the genotype, and environmental factors, including the diet and gut microbiota. Nutritional metabonomics, or nutrimetabonomics, is being increasingly applied to study molecular interactions between the diet and the global metabolic system. This review discusses three primary areas in which nutrimetabonomics has enjoyed successful application in nutritional research: the illumination of molecular relationships between nutrition and biochemical processes; elucidation of biomarker signatures of food components for use in dietary surveillance; and the study of complex trans-genomic interactions between the mammalian host and its resident gut microbiome. Finally, this review illustrates the potential for nutrimetabonomics in nutritional science as an indispensable tool to achieve personalized nutrition.

Modelagem molecular da interação entre a proteína de fusão do vírus sincicial respiratório humano e inibidores da ação viral. -

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Resistência a cobre em Xanthomonas axonopodis pv. citri. Estudos de caracterização molecular e bioquímica de genes e proteínas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudos computacionais de esfingomielinases D: docking, dinâmica molecular e métodos híbridos QM/MM

Pós-graduação em Biofísica Molecular - IBILCE

Estudos computacionais de esfingomielinases D: docking, dinâmica molecular e métodos híbridos QM/MM

Pós-graduação em Biofísica Molecular - IBILCE

A novel set of ss-N-biaryl ether sulfonamide hydroxamates as potential MMPs inhibitors: Molecular dynamics simulations and molecular properties evaluation

Matrix metalloproteinases (MMPs) constitute a family of zinc-dependent proteases involved in the extracellular matrix degradation. MMP-2 and MMP9 are overexpressed in several human cancer types, including melanoma, thus the development of new compounds to inhibit MMPs' activity is desirable. Molecular dynamic simulation and molecular properties calculations were performed on a set of novel beta-N-biaryl ether sulfonamide-based hydroxamates, reported as MMP-2 and MMP-9 inhibitors, for providing data to develop an exploratory analysis. Thermodynamic, electronic, and steric descriptors have significantly discriminated highly active from moderately and less active inhibitors of MMP-2 whereas apparent partition coefficient at pH 1.5 was also significant for the MMP-9 data set. Compound 47 was considered an outlier in all analysis, indicating the presence of a bulky substituent group in R3 is crucial to this set of inhibitors for the establishment of molecular interactions with the S1 subsite of both enzymes, but there is a limit. (C) 2012 Wiley Periodicals, Inc.

Membrane interactions of S100A12 (calgranulin C)

S100A12 (Calgranulin C) is a small acidic calcium-binding peripheral membrane protein with two EF-hand structural motifs. It is expressed in macrophages and lymphocytes and highly up-regulated in several human inflammatory diseases. In pigs, S100A12 is abundant in the cytosol of granulocytes, where it is believed to be involved in signal modulation of inflammatory process. In this study, we investigated the interaction of the porcine S100A12 with phospholipid bilayers and the effect that ions (Ca2+, Zn2+ or both together) have in modifying protein-lipid interactions. More specifically, we intended to address issues such as: (1) is the protein-membrane interaction modulated by the presence of ions? (2) is the protein overall structure affected by the presence of the ions and membrane models simultaneously? (3) what are the specific conformational changes taking place when ions and membranes are both present? (4) does the protein have any kind of molecular preferences for a specific lipid component? To provide insight into membrane interactions and answer those questions, synchrotron radiation circular dichroism spectroscopy, fluorescence spectroscopy, and surface plasmon resonance were used. The use of these combined techniques demonstrated that this protein was capable of interacting both with lipids and with ions in solution, and enabled examination of changes that occur at different levels of structure organization. The presence of both Ca2+ and Zn2+ ions modify the binding, conformation and thermal stability of the protein in the presence of lipids. Hence, these studies examining molecular interactions of porcine S100A12 in solution complement the previously determined crystal structure information on this family of proteins, enhancing our understanding of its dynamics of interaction with membranes.