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Background: There is increasing interest in developing FPR2 agonists (compound 43, ACT‐389949 and BMS‐986235) as potential pro‐resolving therapeutics, with ACT‐389949 and BMS‐986235 having entered phase I clinical development. FPR2 activation leads to diverse downstream outputs. ACT‐389949 was observed to cause rapid tachyphylaxis, while BMS‐986235 and compound 43 induced cardioprotective effects in preclinical models. We aim to characterise the differences in ligand‐receptor engagement and downstream signalling and trafficking bias profile. Experimental Approach: Concentration‐response curves to G protein dissociation, β‐arrestin recruitment, receptor trafficking and second messenger signalling were generated using FPR2 ligands (BMS‐986235, ACT‐389949, compound 43 and WKYMVm), in HEK293A cells. Log(τ/KA) was obtained from the operational model for bias analysis using WKYMVm as a reference ligand. Docking of FPR2 ligands into the active FPR2 cryoEM structure (PDBID: 7T6S) was performed using ICM pro software. Key Results: Bias analysis revealed that WKYMVm and ACT‐389949 shared a very similar bias profile. In comparison, BMS‐986235 and compound 43 displayed approximately 5‐ to 50‐fold bias away from β‐arrestin recruitment and trafficking pathways, while being 35‐ to 60‐fold biased towards cAMP inhibition and pERK1/2. Molecular docking predicted key amino acid interactions at the FPR2 shared between WKYMVm and ACT‐389949, but not with BMS‐986235 and compound 43. Conclusion and Implications: In vitro characterisation demonstrated that WKYMVm and ACT‐389949 differ from BMS‐986235 and compound 43 in their signalling and protein coupling profile. This observation may be explained by differences in the ligand‐receptor interactions. In vitro characterisation provided significant insights into identifying the desired bias profile for FPR2‐based pharmacotherapy. [ABSTRACT FROM AUTHOR]

The adenosine A.sub.1 receptor (A.sub.1R) is a promising therapeutic target for non-opioid analgesic agents to treat neuropathic pain.sup.1,2. However, development of analgesic orthosteric A.sub.1R agonists has failed because of a lack of sufficient on-target selectivity as well as off-tissue adverse effects.sup.3. Here we show that [2-amino-4-(3,5-bis(trifluoromethyl)phenyl)thiophen-3-yl)(4-chlorophenyl)methanone] (MIPS521), a positive allosteric modulator of the A.sub.1R, exhibits analgesic efficacy in rats in vivo through modulation of the increased levels of endogenous adenosine that occur in the spinal cord of rats with neuropathic pain. We also report the structure of the A.sub.1R co-bound to adenosine, MIPS521 and a G.sub.i2 heterotrimer, revealing an extrahelical lipid-detergent-facing allosteric binding pocket that involves transmembrane helixes 1, 6 and 7. Molecular dynamics simulations and ligand kinetic binding experiments support a mechanism whereby MIPS521 stabilizes the adenosine-receptor-G protein complex. This study provides proof of concept for structure-based allosteric drug design of non-opioid analgesic agents that are specific to disease contexts. MIPS521, a positive allosteric modulator of the adenosine A.sub.1 receptor, has analgesic properties in a rat model of neuropathic pain through a mechanism by which MIPS521 stabilizes the complex between adenosine, receptor and G protein., Author(s): Christopher J. Draper-Joyce [sup.1] [sup.10] , Rebecca Bhola [sup.2] , Jinan Wang [sup.3] , Apurba Bhattarai [sup.3] , Anh T. N. Nguyen [sup.1] , India Cowie-Kent [sup.2] , Kelly [...]

The application of artificial intelligence (AI) approaches to drug discovery for G protein‐coupled receptors (GPCRs) is a rapidly expanding area. Artificial intelligence can be used at multiple stages during the drug discovery process, from aiding our understanding of the fundamental actions of GPCRs to the discovery of new ligand‐GPCR interactions or the prediction of clinical responses. Here, we provide an overview of the concepts behind artificial intelligence, including the subfields of machine learning and deep learning. We summarise the published applications of artificial intelligence to different stages of the GPCR drug discovery process. Finally, we reflect on the benefits and limitations of artificial intelligence and share our vision for the exciting potential for further development of applications to aid GPCR drug discovery. In addition to making the drug discovery process "faster, smarter and cheaper," we anticipate that the application of artificial intelligence will create exciting new opportunities for GPCR drug discovery. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein‐Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc [ABSTRACT FROM AUTHOR]

Heart failure remains a leading cause of morbidity and mortality worldwide. Current treatment for patients with heart failure include drugs targeting G protein‐coupled receptors such as β‐adrenoceptor antagonists (β‐blockers) and angiotensin II type 1 receptor antagonists (or angiotensin II receptor blockers). However, many patients progress to advanced heart failure with persistent symptoms, despite treatment with available therapeutics that have been shown to reduce mortality and mortality. GPCR targets currently being explored for the development of novel heart failure therapeutics include adenosine receptor, formyl peptide receptor, relaxin/insulin‐like family peptide receptor, vasopressin receptor, endothelin receptor and the glucagon‐like peptide 1 receptor. Many GPCR drug candidates are limited by insufficient efficacy and/or dose‐limiting unwanted effects. Understanding the current challenges hindering successful clinical translation and the potential to overcome existing limitations will facilitate the future development of novel heart failure therapeutics. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein‐Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc [ABSTRACT FROM AUTHOR]

This is the first empirical study to examine determinants of both the probability and the volume of foreign direct divestment (FDD) between countries, applying sample selection methods for panel data. The data cover 137 host countries and 169 source countries, from 2004 to 2012. Empirical evidence shows that market size and GDP growth of both host and source countries, as well as a bilateral investment treaty, discourage divestment. By contrast, sharing a common currency has a positive impact on divestment. Distance negatively affects the divestment amount but does not show any statistically significant impact on the probability of divestment. Neither do political stability, colonial relationship, common language, or common religion play an important role in FDD. This study opens up an area for future research in terms of both theory and empirics since FDD is still a neglected area in international economics. [ABSTRACT FROM AUTHOR]

The adenosine A1 receptor (A1R) is a promising therapeutic target for non-opioid analgesic agents to treat neuropathic pain1,2. However, development of analgesic orthosteric A1R agonists has failed because of a lack of sufficient on-target selectivity as well as off-tissue adverse effects3. Here we show that [2-amino-4-(3,5-bis(trifluoromethyl)phenyl)thiophen-3-yl)(4-chlorophenyl)methanone] (MIPS521), a positive allosteric modulator of the A1R, exhibits analgesic efficacy in rats in vivo through modulation of the increased levels of endogenous adenosine that occur in the spinal cord of rats with neuropathic pain. We also report the structure of the A1R co-bound to adenosine, MIPS521 and a Gi2 heterotrimer, revealing an extrahelical lipid–detergent-facing allosteric binding pocket that involves transmembrane helixes 1, 6 and 7. Molecular dynamics simulations and ligand kinetic binding experiments support a mechanism whereby MIPS521 stabilizes the adenosine–receptor–G protein complex. This study provides proof of concept for structure-based allosteric drug design of non-opioid analgesic agents that are specific to disease contexts.MIPS521, a positive allosteric modulator of the adenosine A1 receptor, has analgesic properties in a rat model of neuropathic pain through a mechanism by which MIPS521 stabilizes the complex between adenosine, receptor and G protein. [ABSTRACT FROM AUTHOR]

This study examines the determinants of foreign direct investment (FDI) from Europe to Asia based on the knowledge‐capital model. The data include 38 European countries and 24 host Asian countries over the period 1995–2013. Empirical evidence from Poisson‐pseudo maximum likelihood estimation method is in line with hypothesised predictions derived from the knowledge‐capital model. In particular, the total income and the similarity in market size between two countries encourage horizontal FDI. We also find empirical support to vertical FDI in Asia where the difference in skilled labour endowments between European source and Asia host countries has a positive impact on FDI from Europe to Asia. Meanwhile, investment costs in Asian countries, trade costs to both source and host countries, and exchange rate volatility are negatively correlated to FDI. By contrast, sharing a common language, a bilateral investment treaty and a historical colonial relationship encourage FDI from Europe to Asia. In addition, heterogeneities in host countries' geographical regions, exchange rate regimes, and governance system, and source countries' Eurozone membership lead to differences in empirical findings. The results also signal some future trends and the roles of governments in both source and host countries in facilitating FDI. [ABSTRACT FROM AUTHOR]

The class A adenosine A1 receptor (A1R) is a G-protein-coupled receptor that preferentially couples to inhibitory Gi/o heterotrimeric G proteins, has been implicated in numerous diseases, yet remains poorly targeted. Here we report the 3.6 Å structure of the human A1R in complex with adenosine and heterotrimeric Gi2 protein determined by Volta phase plate cryo-electron microscopy. Compared to inactive A1R, there is contraction at the extracellular surface in the orthosteric binding site mediated via movement of transmembrane domains 1 and 2. At the intracellular surface, the G protein engages the A1R primarily via amino acids in the C terminus of the Gαi α5-helix, concomitant with a 10.5 Å outward movement of the A1R transmembrane domain 6. Comparison with the agonist-bound β2 adrenergic receptor-Gs-protein complex reveals distinct orientations for each G-protein subtype upon engagement with its receptor. This active A1R structure provides molecular insights into receptor and G-protein selectivity. The cryo-electron microscopy structure of the human adenosine A1 receptor in complex with adenosine and heterotrimeric Gi2 protein provides molecular insights into receptor and G-protein selectivity. [ABSTRACT FROM AUTHOR]

Despite intense interest in designing positive allosteric modulators (PAMs) as selective drugs of the adenosine A1 receptor (A1AR), structural binding modes of the receptor PAMs remain unknown. Using the first X-ray structure of the A1AR, we have performed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) technique to determine binding modes of the A1AR allosteric drug leads. Two prototypical PAMs, PD81723 and VCP171, were selected. Each PAM was initially placed at least 20 Å away from the receptor. Extensive GaMD simulations using the AMBER and NAMD simulation packages at different acceleration levels captured spontaneous binding of PAMs to the A1AR. The simulations allowed us to identify low-energy binding modes of the PAMs at an allosteric site formed by the receptor extracellular loop 2 (ECL2), which are highly consistent with mutagenesis experimental data. Furthermore, the PAMs stabilized agonist binding in the receptor. In the absence of PAMs at the ECL2 allosteric site, the agonist sampled a significantly larger conformational space and even dissociated from the A1AR alone. In summary, the GaMD simulations elucidated structural binding modes of the PAMs and provided important insights into allostery in the A1AR, which will greatly facilitate the receptor structure-based drug design. [ABSTRACT FROM AUTHOR]

The application of Artificial Intelligence (AI) to screen drug molecules with potential therapeutic effects has revolutionized the drug discovery process, with significantly lower economic cost and time consumption than the traditional drug discovery pipeline. With the great power of AI, it is possible to rapidly search the vast chemical space for potential drug-target interactions (DTIs) between candidate drug molecules and disease protein targets. However, only a small proportion of molecules have labelled DTIs, consequently limiting the performance of AI-based drug screening. To solve this problem, a machine learning-based approach with great ability to generalize DTI prediction across molecules is desirable. Many existing machine learning approaches for DTI identification failed to exploit the full information with respect to the topological structures of candidate molecules. To develop a better approach for DTI prediction, we propose GraphormerDTI, which employs the powerful Graph Transformer neural network to model molecular structures. GraphormerDTI embeds molecular graphs into vector-format representations through iterative Transformer-based message passing, which encodes molecules' structural characteristics by node centrality encoding, node spatial encoding and edge encoding. With a strong structural inductive bias, the proposed GraphormerDTI approach can effectively infer informative representations for out-of-sample molecules and as such, it is capable of predicting DTIs across molecules with an exceptional performance. GraphormerDTI integrates the Graph Transformer neural network with a 1-dimensional Convolutional Neural Network (1D-CNN) to extract the drugs' and target proteins' representations and leverages an attention mechanism to model the interactions between them. To examine GraphormerDTI's performance for DTI prediction, we conduct experiments on three benchmark datasets, where GraphormerDTI achieves a superior performance than five state-of-the-art baselines for out-of-molecule DTI prediction, including GNN-CPI, GNN-PT, DeepEmbedding-DTI, MolTrans and HyperAttentionDTI, and is on a par with the best baseline for transductive DTI prediction. The source codes and datasets are publicly accessible at https://github.com/mengmeng34/GraphormerDTI., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

G protein-coupled receptors (GPCRs) represent the target for approximately a third of FDA-approved small molecule drugs. The adenosine A 1 receptor (A 1 R), one of four adenosine GPCR subtypes, has important (patho)physiological roles in humans. A 1 R has well-established roles in the regulation of the cardiovascular and nervous systems, where it has been identified as a potential therapeutic target for a number of conditions, including cardiac ischemia-reperfusion injury, cognition, epilepsy, and neuropathic pain. A 1 R small molecule drugs, typically orthosteric ligands, have undergone clinical trials. To date, none have progressed into the clinic, predominantly due to dose-limiting unwanted effects. The development of A 1 R allosteric modulators that target a topographically distinct binding site represent a promising approach to overcome current limitations. Pharmacological parameters of allosteric ligands, including affinity, efficacy and cooperativity, can be optimized to regulate A 1 R activity with high subtype, spatial and temporal selectivity. This review aims to offer insights into the A 1 R as a potential therapeutic target and highlight recent advances in the structural understanding of A 1 R allosteric modulation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Nguyen, Tran, Baltos, McNeill, Nguyen and May.)

PM 2.5 pollution is a serious problem in Vietnam and around the world, having bad impacts on human health, animals and environment. Regular monitoring at a large scale is important to assess the status of air pollution, develop solutions and evaluate the effectiveness of policy implementation. However, air quality monitoring stations in Vietnam are limited. In this article, we propose an approach to estimate daily PM 2.5 concentration from 2012 to 2020 over the Vietnamese territory, which is strongly affected by cloudy conditions, using a modern statistical model named Mixed Effect Model (MEM) on a dataset consisting of ground PM 2.5 measurements, integrated satellite Aerosol Optical Depth (AOD), meteorological and land use maps. The result of this approach is the first long-term, full coverage and high quality PM 2.5 dataset of Vietnam. The daily mean PM 2.5 maps have high validation results in comparison with ground PM 2.5 measurement (Pearson r of 0.87, R 2 of 0.75, RMSE of 11.76 μg/m 3 , and MRE of 36.57 % on a total of 13,886 data samples). The aggregated monthly and annual average maps from 2012 to 2020 in Vietnam have outstanding quality when compared with another global PM 2.5 product. The PM 2.5 concentration maps has shown spatial distribution and seasonal variations of PM 2.5 concentration in Vietnam in a long period from 2012 to 2020 and has been used in other studies and applications in the environment and public health at the national scale, which has not been possible before because of the lack of monitoring stations and an appropriate PM 2.5 modeling approach., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The adenosine A 1 receptor is a therapeutic target based on its ability to provide cardioprotection during episodes of myocardial ischemia and reperfusion injury. However, the clinical translation of A 1 R agonists has been hindered by dose-limiting adverse effects (bradycardia and hypotension). Previously, we demonstrated that the bitopic agonist VCP746 ( 1 ), consisting of an adenosine pharmacophore linked to an allosteric moiety, can stimulate cardioprotective A 1 R signaling effects in the absence of unwanted bradycardia. This study maps the structure-activity relationships of 1 through modifications to the linker moiety. Derivatives differing in the flexibility, length, and nature of the linker were assessed, which revealed that the linker is tolerant of several modifications including added rigidity. Ligands featuring 1,4-disubstituted 1,2,3-triazoles were the most biased of the novel analogues but also displayed sub-nanomolar potency in a cAMP accumulation assay at the A 2B R. To our knowledge, 10 is the most potent A 2B R agonist published to date.

PolyDADMAC (PD) is a high charge density cationic polymer of diallyldimethylammonium chloride which has been recently developed as a coagulant in water purification. As PD has high affinity to fine negatively-charged colloids, it is worth to ascertain if PD can affect surface properties of clay-size particles in red mud waste and be applied to develop immobilization techniques for red mud storage areas. In the current study, a test tube method in combination with surface charge measurement was used for determination of the colloidal properties of a red mud sample under the variation of PD, soluble Al and Si, and variable pH conditions. Observations for the PD concentration range from 0.25 to 2.0 mM revealed that PD can increase surface charge and enhance aggregation or at least shift the aggregation zone to higher pH. This suggests a possible application of PD for immobilization of red mud in alkaline condition. It was also found that soluble Al and Si acted to modify the effect of PD and aggregation properties of red mud. While soluble Si supported aggregation, Al appeared as an enhancer for dispersion of red mud. It implies that development of PD-based techniques for immobilization of red mud needs to consider the effects of soluble Al and Si., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The adenosine A 1 receptor (A 1 AR) is a potential novel therapeutic target for myocardial ischemia-reperfusion injury. However, to date, clinical translation of prototypical A 1 AR agonists has been hindered due to dose limiting adverse effects. Recently, we demonstrated that the biased bitopic agonist 1, consisting of an adenosine pharmacophore linked to an allosteric moiety, could stimulate cardioprotective A 1 AR signaling in the absence of unwanted bradycardia. Therefore, this study aimed to investigate the structure-activity relationship of compound 1 biased agonism. A series of novel derivatives of 1 were synthesized and pharmacologically profiled. Modifications were made to the orthosteric adenosine pharmacophore, linker, and allosteric 2-amino-3-benzoylthiophene pharmacophore to probe the structure-activity relationships, particularly in terms of biased signaling, as well as A 1 AR activity and subtype selectivity. Collectively, our findings demonstrate that the allosteric moiety, particularly the 4-(trifluoromethyl)phenyl substituent of the thiophene scaffold, is important in conferring bitopic ligand bias at the A 1 AR.

The A 1 adenosine receptor (A 1 AR) is an important G protein-coupled receptor that regulates a range of physiological functions. Herein we report the discovery of novel irreversible agonists acting at the A 1 AR, which have the potential to serve as useful research tools for studying receptor structure and function. A series of novel adenosine derivatives bearing electrophilic substituents was synthesized, and four compounds, 8b, 15a, 15b, and 15d, were shown to possess similar potency and efficacy to the reference high efficacy agonist, NECA, in an assay of ERK1/2 phosphorylation assay. Insensitivity to antagonist addition in a real-time, label-free, xCELLigence assay was subsequently used to identify compounds that likely mediated their agonism through an irreversible interaction with the A 1 AR. Of these compounds, 15b and 15d were more directly validated as irreversible agonists of the A 1 AR using membrane-based [ 3 H]DPCPX and [ 35 S]GTPγS binding experiments.

The adenosine A 1 G protein-coupled receptor (A 1 AR) is an important therapeutic target implicated in a wide range of cardiovascular and neuronal disorders. Although it is well established that the A 1 AR orthosteric site is located within the receptor's transmembrane (TM) bundle, prior studies have implicated extracellular loop 2 (ECL2) as having a significant role in contributing to orthosteric ligand affinity and signaling for various G protein-coupled receptors (GPCRs). We thus performed extensive alanine scanning mutagenesis of A 1 AR-ECL2 to explore the role of this domain on A 1 AR orthosteric ligand pharmacology. Using quantitative analytical approaches and molecular modeling, we identified ECL2 residues that interact either directly or indirectly with orthosteric agonists and antagonists. Discrete mutations proximal to a conserved ECL2-TM3 disulfide bond selectively affected orthosteric ligand affinity, whereas a cluster of five residues near the TM4-ECL2 juncture influenced orthosteric agonist efficacy. A combination of ligand docking, molecular dynamics simulations, and mutagenesis results suggested that the orthosteric agonist 5'-N-ethylcarboxamidoadenosine binds transiently to an extracellular vestibule formed by ECL2 and the top of TM5 and TM7, prior to entry into the canonical TM bundle orthosteric site. Collectively, this study highlights a key role for ECL2 in A 1 AR orthosteric ligand binding and receptor activation., (Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.)

Previous studies have reported that maternal exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) induces socioemotional and cognitive disturbances in rat offspring. In the present study, the effects of maternal TCDD exposure on putative inhibitory interneurons were investigated in the medial prefrontal cortex (mPFC), basolateral amygdala (BLA), hippocampus (HP), and superior colliculus (SC) in rat offspring. Dams were given TCDD (1.0μg/kg) on gestational day 15. When offspring rats reached adulthood (14 weeks old), parvalbumin (PV)- and calbindin (Calb)-immunoreactive neurons were immunohistochemically investigated. The histological investigations indicated that the mean area of the mPFC had increased, whereas the mean area of the SC decreased in the exposed male rats. In the exposed female rats, the mean SC area increased. Furthermore, the number and area of PV-immunoreactive neurons increased in the mPFC of the female exposed rats. In contrast, the number of PV-immunoreactive neurons in the BLA, HP, and SC decreased in the male and female exposed rats. The number of Calb-immunoreactive neurons decreased in the HP of the male and female exposed rats and the SC of the female exposed rats. Because PV- and Calb-immunoreactive neurons, which are putatively GABAergic, have been implicated in various higher brain functions, the effects of TCDD on socioemotional and cognitive functions might be mediated partly through these alterations in PV- and Calb-immunoreactive neurons in these areas., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Effects of dioxins on cognitive functions were reported in previous studies conducted in humans and animals. In the present study, we investigated the influence of dioxin exposure during pregnancy on social interaction and on the activity of offspring, which are related to neurodevelopmental disturbances. In addition, we analyzed neurochemical alterations of the limbic system of rat brains to suggest one mechanism of dioxin effects on brain function. We believe that this manuscript is suitable for publication in "Environmental Health Insights" because it provides an interesting topic for a wide global audience. To clarify the relationships between maternal dioxin exposure and socioemotional functions of rat offspring, dams were given TCDD (1.0 μg/kg) on gestational day 15. Social interactions and forced swimming time were compared between TCDD-exposed and control offspring in each gender. Frequency and duration of locomotion were higher, and durations per one behavior of proximity and social contact were significantly lower in the exposed males, while only the duration of proximity was lower in the exposed females. Forced swimming time on the first day was significantly longer in the exposed males. In the limbic system of the rat brain, the levels and/or activity of CaMKIIα were decreased in males and were increased in females in the exposed offspring. These results suggest that prenatal TCDD exposure induces hyperactivity and socioemotional deficits, particularly in the male offspring due to alterations in CaMKIIα activity in the limbic system of the brain.