Azelastine potentiates antiasthmatic dexamethasone effect on a murine asthma model

Glucocorticoids are among the most effective drugs to treat asthma. However, thesevere adverse effects associated generate the need for its therapeutic optimization. Conversely, though histamine is undoubtedly related to asthma development, there is a lack of efficacy of antihistamines in controlling its symptoms, which prevents their clinical application. We have reported that antihistamines potentiate glucocorticoids? responses in vitro and recent observations have indicated that the coadministration of an antihistamine and a synthetic glucocorticoid has synergistic effects on a murine model of allergic rhinitis. Here, the aim of this work is to establish if this therapeutic combination could be beneficial in a murine model of asthma. We used an allergen‐induced model of asthma (employing ovalbumin) to evaluate the effectsof the synthetic glucocorticoid dexamethasone combined with the antihistamineazelastine. Our results indicate that the cotreatment with azelastine and a suboptimal dose of dexamethasone can improve allergic lung inflammation as shown by a decrease in eosinophils in bronchoalveolar lavage, fewer peribronchial and perivascular infiltrates, and mucin‐producing cells. In addition, serum levels of allergen‐specific IgE and IgG1 were also reduced, as well as the expression of lung inflammatory‐related genes IL‐4, IL‐5, Muc5AC, and Arginase I. The potentiation of dexamethasone effects by azelastine could allow to reduce the effective glucocorticoid dose needed to achieve a therapeutic effect. These findings provide first new insights into the potential benefits of glucocorticoids and antihistamines combination for the treatment of asthma and grants further research to evaluate this approach in other related inflammatory conditions.Fil: Zappia, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; ArgentinaFil: Soto, Ariadna Soledad. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro de Estudios en Salud y Medio Ambiente; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Granja Galeano, Gina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; ArgentinaFil: Fenoy, Ignacio Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro de Estudios en Salud y Medio Ambiente; ArgentinaFil: Fernandez, Natalia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; ArgentinaFil: Davio, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; ArgentinaFil: Shayo, Carina Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Fitzsimons, Carlos P.. University of Amsterdam; Países BajosFil: Goldman, Alejandra. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro de Estudios en Salud y Medio Ambiente; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Monczor, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Farmacológicas. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Investigaciones Farmacológicas; Argentin

Scalable rule-based modelling of allosteric proteins and biochemical networks

Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology

Antihistaminergics and inverse agonism: potential therapeutic applications

The accurate characterization of the molecular mechanisms involved in the action of receptor ligands is important for their appropriate therapeutic use and safety. It is well established that ligands acting at the histamine system currently used in the clinic exert their actions by specifically antagonizing G-protein coupled H1 and H2 receptors. However, most of these ligands, assumed to be neutral antagonists, behave as inverse agonists displaying negative efficacy in experimental systems. This suggests that their therapeutic actions may involve not only receptor blockade, but also the decrease of spontaneous receptor activity. The mechanisms whereby inverse agonists achieve negative efficacy are diverse. Theoretical models predict at least three possible mechanisms, all of which are supported by experimental observations. Depending on the mechanism of action engaged, the inverse agonist could interfere specifically with signaling events triggered by unrelated receptors. This possibility opens up new venues to explain the therapeutic actions of inverse agonists of the histamine receptor and perhaps new therapeutic applications

Mepyramine, a histamine H1 receptor inverse agonist, binds preferentially to a G protein-coupled form of the receptor and sequesters G protein

Accurate characterization of the molecular mechanisms of the action of ligands is an extremely important issue for their appropriate research, pharmacological, and therapeutic uses. In view of this fact, the aim of the present work was to investigate the mechanisms involved in the actions of mepyramine at the guinea pig H1 receptor stably expressed in Chinese hamster ovary cells. We found that mepyramine is able to decrease the basal constitutive activity of the guinea pig H1 receptor, to bind with high affinity to a Gq/11 protein-coupled form of the receptor and to promote a G protein-coupled inactive state of the H1 receptor that interferes with the Gq/11-mediated signaling of the endogenously expressed ATP receptor, as predicted by the Cubic Ternary Complex Model of receptor occupancy. The effect of mepyramine on ATP-induced signaling was specifically neutralized by Gα11 overexpression, indicating that mepyramine is able to reduce G protein availability for other non-related receptors associated with the same signaling pathway. Finally, we found a loss of mepyramine efficacy in decreasing basal levels of intracellular calcium at high Gα11 expression levels, which can be theoretically explained in terms of high H1 receptor constitutive activity. The whole of the present work sheds new light on H1 receptor pharmacology and the mechanisms H1 receptor inverse agonists could use to exert their observed negative efficacy.Fil:Fernández, N. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Shayo, C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

A Model of Glucocorticoid Receptor Interaction With Coregulators Predicts Transcriptional Regulation of Target Genes

Regulatory factors that control gene transcription in multicellular organisms are assembled in multicomponent complexes by combinatorial interactions. In this context, nuclear receptors provide well-characterized and physiologically relevant systems to study ligand-induced transcription resulting from the integration of cellular and genomic information in a cell- and gene-specific manner. Here, we developed a mathematical model describing the interactions between the glucocorticoid receptor (GR) and other components of a multifactorial regulatory complex controlling the transcription of GR-target genes, such as coregulator peptides. We support the validity of the model in relation to gene-specific GR transactivation with gene transcription data from A549 cells and in vitro real time quantification of coregulator-GR interactions. The model accurately describes and helps to interpret ligand-specific and gene-specific transcriptional regulation by the GR. The comprehensive character of the model allows future insight into the function and relative contribution of the molecular species proposed in ligand- and gene-specific transcriptional regulation.Diabetes mellitus: pathophysiological changes and therap

Antihistamines Potentiate Dexamethasone Anti-Inflammatory Effects. Impact on Glucocorticoid Receptor-Mediated Expression of Inflammation-Related Genes

Antihistamines and glucocorticoids (GCs) are often used together in the clinic to treat several inflammation-related situations. Although there is no rationale for this association, clinical practice has assumed that, due to their concomitant anti-inflammatory effects, there should be an intrinsic benefit to their co-administration. In this work, we evaluated the effects of the co-treatment of several antihistamines on dexamethasone-induced glucocorticoid receptor transcriptional activity on the expression of various inflammation-related genes in A549 and U937 cell lines. Our results show that all antihistamines potentiate GCs’ anti-inflammatory effects, presenting ligand-, cell- and gene-dependent effects. Given that treatment with GCs has strong adverse effects, particularly on bone metabolism, we also examined the impact of antihistamine co-treatment on the expression of bone metabolism markers. Using MC3T3-E1 pre-osteoblastic cells, we observed that, though the antihistamine azelastine reduces the expression of dexamethasone-induced bone loss molecular markers, it potentiates osteoblast apoptosis. Our results suggest that the synergistic effect could contribute to reducing GC clinical doses, ineffective by itself but effective in combination with an antihistamine. This could result in a therapeutic advantage, as the addition of an antihistamine may reinforce the wanted effects of GCs, while related adverse effects could be diminished or at least mitigated. By modulating the patterns of gene activation/repression mediated by GR, antihistamines could enhance only the desired effects of GCs, allowing their effective dose to be reduced. Further research is needed to correctly determine the clinical scope, benefits, and potential risks of this therapeutic strategy

Effects of histamine H1 receptor signaling on glucocorticoid receptor activity. Role of canonical and non-canonical pathways

Histamine H1 receptor (H1R) antagonists and glucocorticoid receptor (GR) agonists are used to treat inflammatory conditions such as allergic rhinitis, atopic dermatitis and asthma. Consistent with the high morbidity levels of such inflammatory conditions, these receptors are the targets of a vast number of approved drugs, and in many situations their ligands are co-administered. However, this drug association has no clear rationale and has arisen from clinical practice. We hypothesized that H1R signaling could affect GR-mediated activity, impacting on its transcriptional outcome. Indeed, our results show a dual regulation of GR activity by the H1R: a potentiation mediated by G-protein betagamma subunits and a parallel inhibitory effect mediated by Galphaq-PLC pathway. Activation of the H1R by its full agonists resulted in a composite potentiating effect. Intriguingly, inactivation of the Galphaq-PLC pathway by H1R inverse agonists resulted also in a potentiation of GR activity. Moreover, histamine and clinically relevant antihistamines synergized with the GR agonist dexamethasone to induce gene transactivation and transrepression in a gene-specific manner. Our work provides a delineation of molecular mechanisms underlying the widespread clinical association of antihistamines and GR agonists, which may contribute to future dosage optimization and reduction of well-described side effects associated with glucocorticoid administration