Analysis of interaction of cloned human and/or sheep fetal hemoglobin gamma-chain and LPS in augmenting induction of inflammatory cytokine production in vivo and in vitro.

We have reported earlier that purified preparations of sheep fetal hemoglobin, but not adult hemoglobin, in concert with non-stimulatory doses of lipopolysaccharide (LPS) (lipid A), act cooperatively to regulate in vitro production of a number of cytokines, including TNFalpha, TGFbeta and IL-6 from murine and human leukocytes. Following in vivo treatment of mice with the same combination of hemoglobin and LPS, harvested spleen or peritoneal cells showed a similar augmented capacity to release these cytokines into culture supernatants. We report below that genetically cloned gamma-chain of human or sheep fetal hemoglobin, but not cloned alpha- or beta-chains, can produce this cooperative effect, as indeed can HPLC purified, heme-free, gamma-chains derived from cord blood fetal hemoglobin, and that purified haptoglobin completely abolishes the cooperative interaction.

Human topoisomerase II-DNA interaction study by using atomic force microscopy.

Type II topoisomerases (Topo II) are unique enzymes that change the DNA topology by catalyzing the passage of two double-strands across each other by using the energy from ATP hydrolysis. In vitro, human Topo II relaxes positive supercoiled DNA around 10-fold faster than negative supercoiled DNA. By using atomic force microscopy (AFM) we found that human Topo II binds preferentially to DNA cross-overs. Around 50% of the DNA crossings, where Topo II was bound to, presented an angle in the range of 80-90°, suggesting a favored binding geometry in the chiral discrimination by Topo II. Our studies with AFM also helped us visualize the dynamics of the unknotting action of Topo II in knotted molecules.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

Comparison of three commercially available radio frequency coils for human brain imaging at 3 Tesla.

OBJECTIVE: To evaluate a transverse electromagnetic (TEM), a circularly polarized (CP) (birdcage), and a 12-channel phased array head coil at the clinical field strength of B0 = 3T in terms of signal-to-noise ratio (SNR), signal homogeneity, and maps of the effective flip angle alpha. MATERIALS AND METHODS: SNR measurements were performed on low flip angle gradient echo images. In addition, flip angle maps were generated for alpha(nominal) = 30 degrees using the double angle method. These evaluation steps were performed on phantom and human brain data acquired with each coil. Moreover, the signal intensity variation was computed for phantom data using five different regions of interest. RESULTS: In terms of SNR, the TEM coil performs slightly better than the CP coil, but is second to the smaller 12-channel coil for human data. As expected, both the TEM and the CP coils show superior image intensity homogeneity than the 12-channel coil, and achieve larger mean effective flip angles than the combination of body and 12-channel coil with reduced radio frequency power deposition. CONCLUSION: At 3T the benefits of TEM coil design over conventional lumped element(s) coil design start to emerge, though the phased array coil retains an advantage with respect to SNR performance.

Structure-based drug design studies of the interactions ofent-kaurane diterpenes derived from Wedelia paludosa with the Plasmodium falciparumsarco/endoplasmic reticulum Ca2+-ATPase PfATP6

Malaria is responsible for more deaths around the world than any other parasitic disease. Due to the emergence of strains that are resistant to the current chemotherapeutic antimalarial arsenal, the search for new antimalarial drugs remains urgent though hampered by a lack of knowledge regarding the molecular mechanisms of artemisinin resistance. Semisynthetic compounds derived from diterpenes from the medicinal plant Wedelia paludosawere tested in silico against the Plasmodium falciparumCa2+-ATPase, PfATP6. This protein was constructed by comparative modelling using the three-dimensional structure of a homologous protein, 1IWO, as a scaffold. Compound 21 showed the best docking scores, indicating a better interaction with PfATP6 than that of thapsigargin, the natural inhibitor. Inhibition of PfATP6 by diterpene compounds could promote a change in calcium homeostasis, leading to parasite death. These data suggest PfATP6 as a potential target for the antimalarial ent-kaurane diterpenes.

Disruption of GIP/GIPR axis in human adipose tissue is linked to obesity and insulin resistance.

CONTEXT Glucose-dependent insulinotropic peptide (GIP) has a central role in glucose homeostasis through its amplification of insulin secretion; however, its physiological role in adipose tissue is unclear. OBJECTIVE Our objective was to define the function of GIP in human adipose tissue in relation to obesity and insulin resistance. DESIGN GIP receptor (GIPR) expression was analyzed in human sc adipose tissue (SAT) and visceral adipose (VAT) from lean and obese subjects in 3 independent cohorts. GIPR expression was associated with anthropometric and biochemical variables. GIP responsiveness on insulin sensitivity was analyzed in human adipocyte cell lines in normoxic and hypoxic environments as well as in adipose-derived stem cells obtained from lean and obese patients. RESULTS GIPR expression was downregulated in SAT from obese patients and correlated negatively with body mass index, waist circumference, systolic blood pressure, and glucose and triglyceride levels. Furthermore, homeostasis model assessment of insulin resistance, glucose, and G protein-coupled receptor kinase 2 (GRK2) emerged as variables strongly associated with GIPR expression in SAT. Glucose uptake studies and insulin signaling in human adipocytes revealed GIP as an insulin-sensitizer incretin. Immunoprecipitation experiments suggested that GIP promotes the interaction of GRK2 with GIPR and decreases the association of GRK2 to insulin receptor substrate 1. These effects of GIP observed under normoxia were lost in human fat cells cultured in hypoxia. In support of this, GIP increased insulin sensitivity in human adipose-derived stem cells from lean patients. GIP also induced GIPR expression, which was concomitant with a downregulation of the incretin-degrading enzyme dipeptidyl peptidase 4. None of the physiological effects of GIP were detected in human fat cells obtained from an obese environment with reduced levels of GIPR. CONCLUSIONS GIP/GIPR signaling is disrupted in insulin-resistant states, such as obesity, and normalizing this function might represent a potential therapy in the treatment of obesity-associated metabolic disorders.

Interaction of cationic ultrasmall superparamagnetic iron oxide nanoparticles with human melanoma cells.

Ultrasmall superparamagnetic iron oxide nanoparticles (USPIONs) are currently under development for the intracellular delivery of therapeutics. However, the mechanisms of cellular uptake and the cellular reaction to this uptake, independent of therapeutics, are not well defined. The interactions of biocompatible cationic aminoUSPIONs with human cells was studied in 2D and 3D cultures using biochemical and electron microscopy techniques. AminoUSPIONs were internalized by human melanoma cells in 2D and 3D cultures. Uptake was clathrin mediated and the particles localized in lysosomes, inducing activation of the lysosomal cathepsin D and decreasing the expression of the transferrin receptor in human melanoma cells and/or skin fibroblasts. AminoUSPIONs deeply invaded 3D spheroids of human melanoma cells. Thus, aminoUSPIONs can invade tumors and their uptake by human cells induces cell reaction.

Exploring unfrequent events with accelerated molecular dynamics simulations: from photochemistry to drug design

La meva incorporació al grup de recerca del Prof. McCammon (University of California San Diego) en qualitat d’investigador post doctoral amb una beca Beatriu de Pinós, va tenir lloc el passat 1 de desembre de 2010; on vaig dur a terme les meves tasques de recerca fins al darrer 1 d’abril de 2012. El Prof. McCammon és un referent mundial en l’aplicació de simulacions de dinàmica molecular (MD) en sistemes biològics d’interès humà. La contribució més important del Prof. McCammon en la simulació de sistemes biològics és el desenvolupament del mètode de dinàmiques moleculars accelerades (AMD). Les simulacions MD convencionals, les quals estan limitades a l’escala de temps del nanosegon (~10-9s), no son adients per l’estudi de sistemes biològics rellevants a escales de temps mes llargues (μs, ms...). AMD permet explorar fenòmens moleculars poc freqüents però que son clau per l’enteniment de molts sistemes biològics; fenòmens que no podrien ser observats d’un altre manera. Durant la meva estada a la “University of California San Diego”, vaig treballar en diferent aplicacions de les simulacions AMD, incloent fotoquímica i disseny de fàrmacs per ordinador. Concretament, primer vaig desenvolupar amb èxit una combinació dels mètodes AMD i simulacions Car-Parrinello per millorar l’exploració de camins de desactivació (interseccions còniques) en reaccions químiques fotoactivades. En segon lloc, vaig aplicar tècniques estadístiques (Replica Exchange) amb AMD en la descripció d’interaccions proteïna-lligand. Finalment, vaig dur a terme un estudi de disseny de fàrmacs per ordinador en la proteïna-G Rho (involucrada en el desenvolupament de càncer humà) combinant anàlisis estructurals i simulacions AMD. Els projectes en els quals he participat han estat publicats (o estan encara en procés de revisió) en diferents revistes científiques, i han estat presentats en diferents congressos internacionals. La memòria inclosa a continuació conté més detalls de cada projecte esmentat.

Design and evaluation of a panel os single-nucleotide polymorphisms in microRNA genomic regions for association studies in human disease

MicroRNAs (miRNA) are recognized posttranscriptional gene repressors involved in the control of almost every biological process. Allelic variants in these regions may be an important source of phenotypic diversity and contribute to disease susceptibility. We analyzed the genomic organization of 325 human miRNAs (release 7.1, miRBase) to construct a panel of 768 single-nucleotide polymorphisms (SNPs) covering approximately 1 Mb of genomic DNA, including 131 isolated miRNAs (40%) and 194 miRNAs arranged in 48 miRNA clusters, as well as their 5-kb flanking regions. Of these miRNAs, 37% were inside known protein-coding genes, which were significantly associated with biological functions regarding neurological, psychological or nutritional disorders. SNP coverage analysis revealed a lower SNP density in miRNAs compared with the average of the genome, with only 24 SNPs located in the 325 miRNAs studied. Further genotyping of 340 unrelated Spanish individuals showed that more than half of the SNPs in miRNAs were either rare or monomorphic, in agreement with the reported selective constraint on human miRNAs. A comparison of the minor allele frequencies between Spanish and HapMap population samples confirmed the applicability of this SNP panel to the study of complex disorders among the Spanish population, and revealed two miRNA regions, hsa-mir-26a-2 in the CTDSP2 gene and hsa-mir-128-1 in the R3HDM1 gene, showing geographical allelic frequency variation among the four HapMap populations, probably because of differences in natural selection. The designed miRNA SNP panel could help to identify still hidden links between miRNAs and human disease.

Rapid prototyping of compliant human aortic roots for assessment of valved stents.

Adequate in-vitro training in valved stents deployment as well as testing of the latter devices requires compliant real-size models of the human aortic root. The casting methods utilized up to now are multi-step, time consuming and complicated. We pursued a goal of building a flexible 3D model in a single-step procedure. We created a precise 3D CAD model of a human aortic root using previously published anatomical and geometrical data and printed it using a novel rapid prototyping system developed by the Fab@Home project. As a material for 3D fabrication we used common house-hold silicone and afterwards dip-coated several models with dispersion silicone one or two times. To assess the production precision we compared the size of the final product with the CAD model. Compliance of the models was measured and compared with native porcine aortic root. Total fabrication time was 3 h and 20 min. Dip-coating one or two times with dispersion silicone if applied took one or two extra days, respectively. The error in dimensions of non-coated aortic root model compared to the CAD design was <3.0% along X, Y-axes and 4.1% along Z-axis. Compliance of a non-coated model as judged by the changes of radius values in the radial direction by 16.39% is significantly different (P<0.001) from native aortic tissue--23.54% at the pressure of 80-100 mmHg. Rapid prototyping of compliant, life-size anatomical models with the Fab@Home 3D printer is feasible--it is very quick compared to previous casting methods.

An improved trap design for decoupling multinuclear RF coils.

PURPOSE: Multinuclear magnetic resonance spectroscopy and imaging require a radiofrequency probe capable of transmitting and receiving at the proton and non-proton frequencies. To minimize coupling between probe elements tuned to different frequencies, LC (inductor-capacitor) traps blocking current at the (1) H frequency can be inserted in non-proton elements. This work compares LC traps with LCC traps, a modified design incorporating an additional capacitor, enabling control of the trap reactance at the low frequency while maintaining (1) H blocking. METHODS: Losses introduced by both types of trap were analysed using circuit models. Radiofrequency coils incorporating a series of LC and LCC traps were then built and evaluated at the bench. LCC trap performance was then confirmed using (1) H and (13) C measurements in a 7T human scanner. RESULTS: LC and LCC traps both effectively block interaction between non-proton and proton coils at the proton frequency. LCC traps were found to introduce a sensitivity reduction of 5±2%, which was less than half of that caused by LC traps. CONCLUSION: Sensitivity of non-proton coils is critical. The improved trap design, incorporating one extra capacitor, significantly reduces losses introduced by the trap in the non-proton coil. Magn Reson Med 72:584-590, 2014. © 2013 Wiley Periodicals, Inc.

Functional interaction between peroxisome proliferator-activated receptors-alpha and Mef-2C on human carnitine palmitoyltransferase 1beta (CPT1beta) gene activation

Muscle-type carnitine palmitoyltransferase 1 (CPT1β) is considered to be the gene that controls fatty acid mitochondrial β-oxidation. A functional peroxisome proliferator-activated receptor (PPAR) responsive element (PPRE) and a myocite-specific (MEF2) site that binds MEF2A and MEF2C in the promoter of this gene had been previously identified. We investigated the roles of the PPRE and the MEF2 binding sites and the potential interaction between PPARα and MEF2C regulating the CPT1β gene promoter. Mutation analysis indicated that the MEF2 site contributed to the activation of the CPT1β promoter by PPAR in C2C12 cells. The reporter construct containing the PPRE and the MEF2C site was synergistically activated by co-expression of PPAR, retinoid X receptor (RXR) and MEF2C in non-muscle cells. Moreover, protein-binding assays demonstrated that MEF2C and PPAR specifically bound to one another in vitro. Also for the synergistic activation of the CPT1β gene promoter by MEF2C and PPARα-RXRα, a precise arrangement of its binding sites was essential.

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.

Human disease and drug pharmacology, complex as real life

In the past decades drug discovery practice has escaped from the complexity of the formerly used phenotypic screening in animals to focus on assessing drug effects on isolated protein targets in the search for drugs that exclusively and potently hit one selected target, thought to be critical for a given disease, while not affecting at all any other target to avoid the occurrence of side-effects. However, reality does not conform to these expectations, and, conversely, this approach has been concurrent with increased attrition figures in late-stage clinical trials, precisely due to lack of efficacy and safety. In this context, a network biology perspective of human disease and treatment has burst into the drug discovery scenario to bring it back to the consideration of the complexity of living organisms and particularly of the (patho)physiological environment where protein targets are (mal)functioning and where drugs have to exert their restoring action. Under this perspective, it has been found that usually there is not one but several disease-causing genes and, therefore, not one but several relevant protein targets to be hit, which do not work on isolation but in a highly interconnected manner, and that most known drugs are inherently promiscuous. In this light, the rationale behind the currently prevailing single-target-based drug discovery approach might even seem a Utopia, while, conversely, the notion that the complexity of human disease must be tackled with complex polypharmacological therapeutic interventions constitutes a difficult-torefuse argument that is spurring the development of multitarget therapies.