GraphormerDTI: A graph transformer-based approach for drug-target interaction prediction.

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.

Small molecule allosteric modulation of the adenosine A1 receptor.

G protein-coupled receptors (GPCRs) represent the target for approximately a third of FDA-approved small molecule drugs. The adenosine A1 receptor (A1R), one of four adenosine GPCR subtypes, has important (patho)physiological roles in humans. A1R 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. A1R 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 A1R 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 A1R activity with high subtype, spatial and temporal selectivity. This review aims to offer insights into the A1R as a potential therapeutic target and highlight recent advances in the structural understanding of A1R allosteric modulation.

The application of artificial intelligence to accelerate G protein-coupled receptor drug discovery.

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.

Targeting G protein-coupled receptors for heart failure treatment.

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 ß-adrenoceptor antagonists (ß-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.

A daily and complete PM2.5 dataset derived from space observations for Vietnam from 2012 to 2020.

PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 dataset of Vietnam. The daily mean PM2.5 maps have high validation results in comparison with ground PM2.5 measurement (Pearson r of 0.87, R2 of 0.75, RMSE of 11.76 µg/m3, 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 PM2.5 product. The PM2.5 concentration maps has shown spatial distribution and seasonal variations of PM2.5 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 PM2.5 modeling approach.

Examining the Role of the Linker in Bitopic N6-Substituted Adenosine Derivatives Acting as Biased Adenosine A1 Receptor Agonists.

The adenosine A1 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 A1R 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 A1R 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 A2BR. To our knowledge, 10 is the most potent A2BR agonist published to date.

Positive allosteric mechanisms of adenosine A1 receptor-mediated analgesia.

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.

Colloidal Dynamics of Freshly Formed Iron Oxides under the Influence of Silicic Acid.

Silicic acid and soluble Fe are among the most abundant components in acid mine drainage. During the oxidation of Fe(II), the interaction between silicic acid and freshly formed Fe oxides might change the colloidal dynamics, altering surface charge properties. However, the effects of silicic acid on colloidal Fe oxides formed from acid mine drainage are not fully understood. In this work, we examined the colloidal dynamics of freshly formed Fe oxides in synthetic acid mine drainage (prepared from FeSO solution) under the effect of silicic acid as a function of changes in pH and ionic strength. The results demonstrate that through adsorption, silicic acid progressively slows oxidation and enhances the dispersion of freshly formed Fe oxides by shifting the surface charge toward more negative values. This effect was most prominent between pH 5 and 9. The current results demonstrate that silicic acid enhances the dispersion and transport of freshly formed Fe oxides and suggest that aggregation-based techniques for the treatment of Fe-rich drainage may require further consideration of this effect.

Effect of polyDADMAC on aggregation of clay-size particles in red mud: Implications for immobilization practices.

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.

Structural Basis for Binding of Allosteric Drug Leads in the Adenosine A1 Receptor.

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.

Structure of the adenosine-bound human adenosine A1 receptor-Gi complex.

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 ß2 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.

New paradigms in adenosine receptor pharmacology: allostery, oligomerization and biased agonism.

Adenosine receptors are a family of GPCRs containing four subtypes (A1 , A2A , A2B and A3 receptors), all of which bind the ubiquitous nucleoside adenosine. These receptors play an important role in physiology and pathophysiology and therefore represent attractive drug targets for a range of conditions. The theoretical framework surrounding drug action at adenosine receptors now extends beyond the notion of prototypical agonism and antagonism to encompass more complex pharmacological concepts. New paradigms include allostery, in which ligands bind a topographically distinct receptor site from that of the endogenous agonist, homomeric or heteromeric interactions across receptor oligomers and biased agonism, that is, ligand-dependent differential intracellular signalling. This review provides a concise overview of allostery, oligomerization and biased agonism at adenosine receptors and outlines how these paradigms may enhance future drug discovery endeavours focussed on the development of novel therapeutic agents acting at adenosine receptors. LINKED ARTICLES: This article is part of a themed section on Molecular Pharmacology of GPCRs. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.21/issuetoc.

A Structure-Activity Relationship Study of Bitopic N6-Substituted Adenosine Derivatives as Biased Adenosine A1 Receptor Agonists.

The adenosine A1 receptor (A1AR) is a potential novel therapeutic target for myocardial ischemia-reperfusion injury. However, to date, clinical translation of prototypical A1AR 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 A1AR 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 A1AR 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 A1AR.

Novel Irreversible Agonists Acting at the A1 Adenosine Receptor.

The A1 adenosine receptor (A1AR) 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 A1AR, 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 A1AR. Of these compounds, 15b and 15d were more directly validated as irreversible agonists of the A1AR using membrane-based [3H]DPCPX and [35S]GTPγS binding experiments.

Role of the Second Extracellular Loop of the Adenosine A1 Receptor on Allosteric Modulator Binding, Signaling, and Cooperativity.

Allosteric modulation of adenosine A1 receptors (A1ARs) offers a novel therapeutic approach for the treatment of numerous central and peripheral disorders; however, despite decades of research, there is a relative paucity of structural information regarding the A1AR allosteric site and mechanisms governing cooperativity with orthosteric ligands. We combined alanine-scanning mutagenesis of the A1AR second extracellular loop (ECL2) with radioligand binding and functional interaction assays to quantify effects on allosteric ligand affinity, cooperativity, and efficacy. Docking and molecular dynamics (MD) simulations were performed using an A1AR homology model based on an agonist-bound A2AAR structure. Substitution of E172ECL2 for alanine reduced the affinity of the allosteric modulators PD81723 and VCP171 for the unoccupied A1AR. Residues involved in cooperativity with the orthosteric agonist NECA were different in PD81723 and VCP171; positive cooperativity between PD81723 and NECA was reduced on alanine substitution of a number of ECL2 residues, including E170ECL2 and K173ECL2, whereas mutation of W146ECL2 and W156ECL2 decreased VCP171 cooperativity with NECA. Molecular modeling localized a likely allosteric pocket for both modulators to an extracellular vestibule that overlaps with a region used by orthosteric ligands as they transit into the canonical A1AR orthosteric site. MD simulations confirmed a key interaction between E172ECL2 and both modulators. Bound PD81723 is flanked by another residue, E170ECL2, which forms hydrogen bonds with adjacent K168ECL2 and K173ECL2. Collectively, our data suggest E172ECL2 is a key allosteric ligand-binding determinant, whereas hydrogen-bonding networks within the extracellular vestibule may facilitate the transmission of cooperativity between orthosteric and allosteric sites.

Extracellular Loop 2 of the Adenosine A1 Receptor Has a Key Role in Orthosteric Ligand Affinity and Agonist Efficacy.

The adenosine A1 G protein-coupled receptor (A1AR) is an important therapeutic target implicated in a wide range of cardiovascular and neuronal disorders. Although it is well established that the A1AR 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 A1AR-ECL2 to explore the role of this domain on A1AR 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 A1AR orthosteric ligand binding and receptor activation.

Structure-Activity Analysis of Biased Agonism at the Human Adenosine A3 Receptor.

Biased agonism at G protein-coupled receptors (GPCRs) has significant implications for current drug discovery, but molecular determinants that govern ligand bias remain largely unknown. The adenosine A3 GPCR (A3AR) is a potential therapeutic target for various conditions, including cancer, inflammation, and ischemia, but for which biased agonism remains largely unexplored. We now report the generation of bias "fingerprints" for prototypical ribose containing A3AR agonists and rigidified (N)-methanocarba 5'-N-methyluronamide nucleoside derivatives with regard to their ability to mediate different signaling pathways. Relative to the reference prototypical agonist IB-MECA, (N)-methanocarba 5'-N-methyluronamide nucleoside derivatives with significant N(6) or C2 modifications, including elongated aryl-ethynyl groups, exhibited biased agonism. Significant positive correlation was observed between the C2 substituent length (in Å) and bias toward cell survival. Molecular modeling suggests that extended C2 substituents on (N)-methanocarba 5'-N-methyluronamide nucleosides promote a progressive outward shift of the A3AR transmembrane domain 2, which may contribute to the subset of A3AR conformations stabilized on biased agonist binding.

Effects of maternal exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin on parvalbumin- and calbindin-immunoreactive neurons in the limbic system and superior colliculus in rat offspring.

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.

Influence of Maternal Exposure to 2,3,7,8-Tetrachlorodibenzo-p-dioxin on Socioemotional Behaviors in Offspring Rats.

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.