92 research outputs found

    Targeting PDE10A GAF Domain with Small Molecules: A Way for Allosteric Modulation with Anti-Inflammatory Effects

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    Phosphodiesterase (PDE) enzymes regulate the levels of cyclic nucleotides, cAMP, and/or cGMP, being attractive therapeutic targets. In order to modulate PDE activity in a selective way, we focused our efforts on the search of allosteric modulators. Based on the crystal structure of the PDE10A GAF-B domain, a virtual screening study allowed the discovery of new hits that were also tested experimentally, showing inhibitory activities in the micromolar range. Moreover, these new PDE10A inhibitors were able to decrease the nitrite production in LPS-stimulated cells, thus demonstrating their potential as anti-inflammatory agentsFinancial support from MINECO and FEDER founds (UE program) (project SAF2012-33600) is acknowledged. A.M.G. acknowledges pre-doctoral grants to the CSIC (JAEPre program)S

    Insights on biodiversity drivers to predict species richness in tropical forests at the local scale

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    Disentangling the relative importance of different biodiversity drivers (i.e., climate, edaphic, historical factors, or human impact) to predict plant species richness at the local scale is one of the most important challenges in ecology. Biodiversity modelling is a key tool for the integration of these drivers and the predictions generated are essential, for example, for climate change forecast and conservation planning. However, the reliability of biodiversity models at the local scale remains poorly understood, especially in tropical species-rich areas, where they are required. We inventoried all woody plants with stems ≥ 2.5 cm in 397 plots across the Andes-Amazon gradient. We generated and mapped 19 uncorrelated biodiversity drivers at 90 m resolution, grouped into four categories: microclimatic, microtopographic, anthropic, and edaphic. In order to evaluate the importance of the different categories, we grouped biodiversity drivers into four different clusters by categories. For each of the four clusters of biodiversity drivers, we modelled the observed species richness using two statistical techniques (random forest and Bayesian inference) and two modelling procedures (including or excluding a spatial component). All the biodiversity models produced were evaluated by cross-validation. Species richness was accurately predicted by random forest (Spearman correlation up to 0.85 and explained variance up to 67%). The results suggest that precipitation and temperature are important driving forces of species richness in the region. Nonetheless, a spatial component should be considered to properly predict biodiversity. This could reflect macroevolutionary underlying forces not considered here, such as colonization time, dispersal capacities, or speciation rates. However, the proposed biodiversity modelling approach can predict accurately species richness at the local scale and detailed resolution (90 m) in tropical areas, something that previous works had found extremely challenging. The innovative methodology presented here could be employed in other areas with conservation needsWe thank the Consejería de Educacion (Comunidad de Madrid, Spain), National Geographic Society (8047-06, 7754-04), National Science Foundation (DEB#0101775, DEB#0743457, DEB#1557094), Spanish Ministry of Economy and Competitiveness (CGL2016-75414-P), Centro de Estudios de América Latina (Universidad Autonoma de Madrid – Banco Santander), Consejería de Educacion, Cultura y Deportes (Junta de Comunidades de Castilla-La Mancha, SBPLY/21/180501/000241), Spanish Ministry of Economy and Competitiveness (PID2019-106341GB-I00) for funding our research. The full dataset can be requested from the Madidi Project (https://madidiproject.weebly.com/

    Perturbation theory/machine learning model of ChEMBL data for dopamine targets: docking, synthesis, and assay of new l-prolyl-l-leucyl-glycinamide peptidomimetics

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    [Abstract] Predicting drug–protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70–91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical–experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC50, EC50, Ki, etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.Ministerio de Economía y Competitividad; CTQ2016-74881-PGobierno Vasco; IT1045-16Xunta de Galicia; GPC2014/003Xunta de Galicia; CN 2012/069Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/23Xunta de Galicia; GRC2014/049Xunta de Galicia; ED431D 2017/2

    Elevational gradients in β-diversity reflect variation in the strength of local community assembly mechanisms across spatial scales

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    Despite long-standing interest in elevational-diversity gradients, little is known about the processes that cause changes in the compositional variation of communities (β-diversity) across elevations. Recent studies have suggested that β-diversity gradients are driven by variation in species pools, rather than by variation in the strength of local community assembly mechanisms such as dispersal limitation, environmental filtering, or local biotic interactions. However, tests of this hypothesis have been limited to very small spatial scales that limit inferences about how the relative importance of assembly mechanisms may change across spatial scales. Here, we test the hypothesis that scale-dependent community assembly mechanisms shape biogeographic β-diversity gradients using one of the most well-characterized elevational gradients of tropical plant diversity. Using an extensive dataset on woody plant distributions along a 4,000-m elevational gradient in the Bolivian Andes, we compared observed patterns of β-diversity to null-model expectations. β-deviations (standardized differences from null values) were used to measure the relative effects of local community assembly mechanisms after removing sampling effects caused by variation in species pools. To test for scale-dependency, we compared elevational gradients at two contrasting spatial scales that differed in the size of local assemblages and regions by at least an order of magnitude. Elevational gradients in β-diversity persisted after accounting for regional variation in species pools. Moreover, the elevational gradient in β-deviations changed with spatial scale. At small scales, local assembly mechanisms were detectable, but variation in species pools accounted for most of the elevational gradient in β-diversity. At large spatial scales, in contrast, local assembly mechanisms were a dominant force driving changes in β-diversity. In contrast to the hypothesis that variation in species pools alone drives β-diversity gradients, we show that local community assembly mechanisms contribute strongly to systematic changes in β-diversity across elevations.We conclude that scale-dependent variation in community assembly mechanisms underlies these iconic gradients in global biodiversityThe Madidi Project has been funded by the National Science Foundation (DEB-0101775 and DEB-0743457), the Comunidad de Madrid, the National Geographic Society (NGS 7754-04 and NGS 8047-06), the Taylor Fund for Ecological Research, the Andrew W. Mellon Foundation, the Centro de Estudios de América Latina, Universidad Autónoma de Madrid, and Christopher Davidson and Sharon Christoph. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscrip

    His452Tyr polymorphism in the human 5-HT2A receptor affects clozapine-induced signaling networks revealed by quantitative phosphoproteomics

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    Antipsychotic drugs remain the current standard for schizophrenia treatment. Although they directly recognize the orthosteric binding site of numerous monoaminergic G protein-coupled receptors (GPCRs), these drugs, and particularly second-generation antipsychotics such as clozapine, all have in common a very high affinity for the serotonin 5-HT receptor (5-HTR). Using classical pharmacology and targeted signaling pathway assays, previous findings suggest that clozapine and other atypical antipsychotics behave principally as 5-HTR neutral antagonists and/or inverse agonists. However, more recent findings showed that antipsychotics may also behave as pathway-specific agonists. Reversible phosphorylation is a common element in multiple signaling networks. Combining a quantitative phosphoproteomic method with signaling network analysis, we tested the effect of clozapine treatment on the overall level of protein phosphorylation and signal transduction cascades in vitro in mammalian cell lines induced to express either the human 5-HTR or the H452Y variant of the gene encoding the 5-HTR receptor. This naturally occurring variation within the 5-HTR gene was selected because it has been repeatedly associated with schizophrenia patients who do not respond to clozapine treatment. Our data show that short time exposure (5 or 10 min) to clozapine (10 M) led to phosphorylation of numerous signaling components of pathways involved in processes such as endocytosis, ErbB signaling, insulin signaling or estrogen signaling. Cells induced to express the H452Y variant showed a different basal phosphoproteome, with increases in the phosphorylation of mTOR signaling components as a translationally relevant example. However, the effect of clozapine on the functional landscape of the phosphoproteome was significantly reduced in cells expressing the 5-HTR-H452Y construct. Together, these findings suggest that clozapine behaves as an agonist inducing phosphorylation of numerous pathways downstream of the 5-HTR, and that the single nucleotide polymorphism encoding 5-HTR-H452Y affects these clozapine-induced phosphorylation-dependent signaling networks

    Pharmacological insights emerging from the characterization of a large collection of synthetic cannabinoid receptor agonists designer drugs

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    Synthetic cannabinoid receptor agonists (SCRAs) constitute the largest and most defiant group of abuse designer drugs. These new psychoactive substances (NPS), developed as unregulated alternatives to cannabis, have potent cannabimimetic effects and their use is usually associated with episodes of psychosis, seizures, dependence, organ toxicity and death. Due to their ever-changing structure, very limited or nil structural, pharmacological, and toxicological information is available to the scientific community and the law enforcement offices. Here we report the synthesis and pharmacological evaluation (binding and functional) of the largest and most diverse collection of enantiopure SCRAs published to date. Our results revealed novel SCRAs that could be (or may currently be) used as illegal psychoactive substances. We also report, for the first time, the cannabimimetic data of 32 novel SCRAs containing an (R) configuration at the stereogenic center. The systematic pharmacological profiling of the library enabled the identification of emerging Structure-Activity Relationship (SAR) and Structure-Selectivity Relationship (SSR) trends, the detection of ligands exhibiting incipient cannabinoid receptor type 2 (CB2R) subtype selectivity and highlights the significant neurotoxicity of representative SCRAs on mouse primary neuronal cells. Several of the new emerging SCRAs are currently expected to have a rather limited potential for harm, as the evaluation of their pharmacological profiles revealed lower potencies and/or efficacies. Conceived as a resource to foster collaborative investigation of the physiological effects of SCRAs, the library obtained can contribute to addressing the challenge posed by recreational designer drugsThis work was financially supported by the Consellería de Cultura, Educación e Ordenación Universitaria of the Galician Government: (grant: ED431B 2020/43), Centro Singular de Investigación de Galicia accreditation 2019–2022 (ED431G 2019/03), Ministerio de Ciencia e Innovación (PID2020-113430RB-I00) and the European Regional Development Fund (ERDF)S

    A Novel NMDA Receptor Antagonist Protects against Cognitive Decline Presented by Senescent Mice

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    Alzheimer’s disease (AD) is the leading cause of dementia. Non-competitive N-Methyl-D-aspartate (NMDA) receptor antagonist memantine improved cognition and molecular alterations after preclinical treatment. Nevertheless, clinical results are discouraging. In vivo efficacy of the RL-208, a new NMDA receptor blocker described recently, with favourable pharmacokinetic properties was evaluated in Senescence accelerated mice prone 8 (SAMP8), a mice model of late-onset AD (LOAD). Oral administration of RL-208 improved cognitive performance assessed by using the three chamber test (TCT), novel object recognition test (NORT), and object location test (OLT). Consistent with behavioural results, RL-208 treated-mice groups significantly changed NMDAR2B phosphorylation state levels but not NMDAR2A. Calpain-1 and Caspase-3 activity was reduced, whereas B-cell lymphoma-2 (BCL-2) levels increased, indicating reduced apoptosis in RL-208 treated SAMP8. Superoxide Dismutase 1 (SOD1) and Glutathione Peroxidase 1 (GPX1), as well as a reduction of hydrogen peroxide (H2O2), was also determined in RL-208 mice. RL-208 treatment induced an increase in mature brain-derived neurotrophic factor (mBDNF), prevented Tropomyosin-related kinase B full-length (TrkB-FL) cleavage, increased protein levels of Synaptophysin (SYN) and Postsynaptic density protein 95 (PSD95). In whole, these results point out to an improvement in synaptic plasticity. Remarkably, RL-208 also decreased the protein levels of Cyclin-Dependent Kinase 5 (CDK5), as well as p25/p35 ratio, indicating a reduction in kinase activity of CDK5/p25 complex. Consequently, lower levels of hyperphosphorylated Tau (p-Tau) were found. In sum, these results demonstrate the neuroprotectant role of RL-208 through NMDAR blockadeThis research was funded by Ministerio de Economía, Industria y Competitividad (Agencia Estatal de Investigación, AEI) and Fondo Europeo de Desarrollo Regional (MINECO-FEDER) (Projects SAF2017-82771-R, SAF2016-77703, SAF2015-68749 and SAF2017-90913), Xunta de Galicia (ED431C 2018/21) and Generalitat de Catalunya (2017 SGR 106)S

    Soluble epoxide hydrolase inhibitors: design, synthesis, in vitro profiling and in vivo evaluation in murine models of pain

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    Trabajo presentado en el ASPET Annual Meeting at Experimental Biology 2022, celebrado en Philadelphia, PA (Estados Unidos), del 2 al 5 de abril de 2022This research by the Grant PID2020-118127RB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” to S.V. Financial support from Fundació Bosch i Gimpera, Universitat de Barcelona (F2I grant), to S.V., and from the Xunta de Galicia (ED431G 2019/02 and ED431C 2018/21) to M.I.L. are acknowledged. Partial support was provided by NIH-NIEHS River Award R35 ES03443, NIH-NIEHS Superfund Program P42 ES004699, NINDS R01 DK107767, and NIDDK R01 DK103616 to B.D.H. S.C. acknowledges a PhD fellowship from the Universitat de Barcelona (APIF grant)

    High-affinity sequence-selective DNA binding by iridium(III) polypyridyl organometallopeptides

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    We demonstrate the application of solid-phase peptide synthesis methods for the straightforward assembly of polynuclear Ir(III) organometallopeptides, and show that their oligoarginine derivatives exhibit high DNA binding affinity, sequence selectivity, and high cytotoxicity towards a set of cancer cell lines

    Synthesis, in Vitro Profiling, and in Vivo Evaluation of Benzohomoadamantane-Based Ureas for Visceral Pain: A New Indication for Soluble Epoxide Hydrolase Inhibitors

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    The soluble epoxide hydrolase (sEH) has been suggested as a pharmacological target for the treatment of several diseases, including pain-related disorders. Herein, we report further medicinal chemistry around new benzohomoadamantane-based sEH inhibitors (sEHI) in order to improve the drug metabolism and pharmacokinetics properties of a previous hit. After an extensive in vitro screening cascade, molecular modeling, and in vivo pharmacokinetics studies, two candidates were evaluated in vivo in a murine model of capsaicin-induced allodynia. The two compounds showed an anti-allodynic effect in a dose-dependent manner. Moreover, the most potent compound presented robust analgesic efficacy in the cyclophosphamide-induced murine model of cystitis, a well-established model of visceral pain. Overall, these results suggest painful bladder syndrome as a new possible indication for sEHI, opening a new range of applications for them in the visceral pain field
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