Small-molecule CEM3 strengthens single-cell oscillators in the suprachiasmatic nucleus.

A robust endogenous clock is required for proper function of many physiological processes. The suprachiasmatic nucleus (SCN) constitutes our central circadian clock and allows us to adapt to daily changes in the environment. Aging can cause a decline in the amplitude of circadian rhythms in SCN and peripheral clocks, which contributes to increased risk of several chronic diseases. Strengthening clock function would therefore be an effective strategy to improve health. A high-throughput chemical screening has identified clock-enhancing molecule 3 (CEM3) as small molecule that increases circadian rhythm amplitude in cell lines and SCN explants. It is, however, currently not known whether CEM3 acts by enhancing the amplitude of individual single-cell oscillators or by enhancing synchrony among neurons. In view of CEM3's potential, it is of evident importance to clarify the mode of action of CEM3. Here, we investigated the effects of CEM3 on single-cell PERIOD2::LUCIFERASE rhythms in mouse SCN explants. CEM3 increased the amplitude in approximately 80%-90% of the individual cells in the SCN without disrupting the phase and/or period of their rhythms. Noticeably, CEM3's effect on amplitude is independent of the cell's initial amplitude. These findings make CEM3 a potential therapeutic candidate to restore compromised amplitude in circadian rhythms and will boost the development of other molecular approaches to improve health.

International Union of Basic and Clinical Pharmacology. CXII: Adenosine Receptors: A Further Update.

Our previous International Union of Basic and Clinical Pharmacology report on the nomenclature and classification of adenosine receptors (2011) contained a number of emerging developments with respect to this G protein-coupled receptor subfamily, including protein structure, protein oligomerization, protein diversity, and allosteric modulation by small molecules. Since then, a wealth of new data and results has been added, allowing us to explore novel concepts such as target binding kinetics and biased signaling of adenosine receptors, to examine a multitude of receptor structures and novel ligands, to gauge new pharmacology, and to evaluate clinical trials with adenosine receptor ligands. This review should therefore be considered a further update of our previous reports from 2001 and 2011. SIGNIFICANCE STATEMENT: Adenosine receptors (ARs) are of continuing interest for future treatment of chronic and acute disease conditions, including inflammatory diseases, neurodegenerative afflictions, and cancer. The design of AR agonists ("biased" or not) and antagonists is largely structure based now, thanks to the tremendous progress in AR structural biology. The A2A- and A2BAR appear to modulate the immune response in tumor biology. Many clinical trials for this indication are ongoing, whereas an A2AAR antagonist (istradefylline) has been approved as an anti-Parkinson agent.

Pharmacological characterization of allosteric modulators: A case for chemokine receptors.

Chemokine receptors are relevant targets for a multitude of immunological diseases, but drug attrition for these receptors is remarkably high. While many drug discovery programs have been pursued, most prospective drugs failed in the follow-up studies due to clinical inefficacy, and hence there is a clear need for alternative approaches. Allosteric modulators of receptor function represent an excellent opportunity for novel drugs, as they modulate receptor activation in a controlled manner and display increased selectivity, and their pharmacological profile can be insurmountable. Here, we discuss allosteric ligands and their pharmacological characterization for modulation of chemokine receptors. Ligands are included if (1) they show clear signs of allosteric modulation in vitro and (2) display evidence of binding in a topologically distinct manner compared to endogenous chemokines. We discuss how allosteric ligands affect binding of orthosteric (endogenous) ligands in terms of affinity as well as binding kinetics in radioligand binding assays. Moreover, their effects on signaling events in functional assays and how their binding site can be elucidated are specified. We substantiate this with examples of published allosteric ligands targeting chemokine receptors and hypothetical graphs of pharmacological behavior. This review should serve as an effective starting point for setting up assays for characterizing allosteric ligands to develop safer and more efficacious drugs for chemokine receptors and, ultimately, other G protein-coupled receptors.

Kinetic profiling of novel spirobenzo-oxazinepiperidinone derivatives as equilibrative nucleoside transporter 1 inhibitors.

Evaluation of kinetic parameters of drug-target binding, kon, koff, and residence time (RT), in addition to the traditional in vitro parameter of affinity is receiving increasing attention in the early stages of drug discovery. Target binding kinetics emerges as a meaningful concept for the evaluation of a ligand's duration of action and more generally drug efficacy and safety. We report the biological evaluation of a novel series of spirobenzo-oxazinepiperidinone derivatives as inhibitors of the human equilibrative nucleoside transporter 1 (hENT1, SLC29A1). The compounds were evaluated in radioligand binding experiments, i.e., displacement, competition association, and washout assays, to evaluate their affinity and binding kinetic parameters. We also linked these pharmacological parameters to the compounds' chemical characteristics, and learned that separate moieties of the molecules governed target affinity and binding kinetics. Among the 29 compounds tested, 28 stood out with high affinity and a long residence time of 87 min. These findings reveal the importance of supplementing affinity data with binding kinetics at transport proteins such as hENT1.

Exploring novel dilazep derivatives as hENT1 inhibitors and potentially covalent molecular tools.

The human equilibrative nucleoside transporter 1 (SLC29A1, hENT1) is a solute carrier that modulates the passive transport of nucleosides and nucleobases, such as adenosine. This nucleoside regulates various physiological processes, such as vasodilation and -constriction, neurotransmission and immune defense. Marketed drugs such as dilazep and dipyridamole have proven useful in cardiovascular afflictions, but the application of hENT1 inhibitors can be beneficial in a number of other diseases. In this study, 39 derivatives of dilazep's close analogue ST7092 were designed, synthesized and subsequently assessed using [3H]NBTI displacement assays and molecular docking. Different substitution patterns of the trimethoxy benzoates of ST7092 reduced interactions within the binding pocket, resulting in diminished hENT1 affinity. Conversely, [3H]NBTI displacement by potentially covalent compounds 14b, 14c, and 14d resulted in high affinities (Ki values between 1.1 and 17.5 nM) for the transporter, primarily by the ability of accommodating the inhibitors in various ways in the binding pocket. However, any indication of covalent binding with amino acid residue C439 remained absent, conceivably as a result of decreased nucleophilic residue reactivity. In conclusion, this research introduces novel dilazep derivatives that are active as hENT1 inhibitors, along with the first high affinity dilazep derivatives equipped with an electrophilic warhead. These findings will aid the rational and structure-based development of novel hENT1 inhibitors and pharmacological tools to study hENT1's function, binding mechanisms, and its relevance in (patho)physiological conditions.

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities.

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of "wet-lab" experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets.

Drug-Target Association Kinetics in Drug Discovery.

The important role of ligand-receptor binding kinetics in drug design and discovery is increasingly recognized by the drug research community. Over the past decade, accumulating evidence has shown that optimizing the ligand's dissociation rate constant can lead to desirable duration of in vivo target occupancy and, hence, improved pharmacodynamic properties. However, the association rate constant as a pharmacological principle remains less investigated, whereas it can play an equally important role in the selection of drug candidates. This review provides a compilation and discussion of otherwise scarce and dispersed information on this topic, bringing to light the importance of drug-target association in kinetics-directed drug design and discovery.

Cancer-related somatic mutations alter adenosine A1 receptor pharmacology-A focus on mutations in the loops and C-terminus.

G protein-coupled receptors (GPCRs) are known to be involved in tumor progression and metastasis. The adenosine A1 receptor (A1 AR) has been detected to be over-expressed in various cancer cell lines. However, the role of A1 AR in tumor development is not yet well characterized. A series of A1 AR mutations were identified in the Cancer Genome Atlas from cancer patient samples. In this study, we have investigated the pharmacology of mutations located outside of the 7-transmembrane domain by using a "single-GPCR-one-G protein" yeast system. Concentration-growth curves were obtained with the full agonist CPA for 12 mutant receptors and compared to the wild-type hA1 AR. Most mutations located at the extracellular loops (EL) reduced the levels of constitutive activity of the receptor and agonist potency. For mutants at the intracellular loops (ILs) of the receptor, an increased constitutive activity was found for mutant receptor L211R5.69 , while a decreased constitutive activity and agonist response were found for mutant receptor L113F34.51 . Lastly, mutations identified on the C-terminus did not significantly influence the pharmacological function of the receptor. A selection of mutations was also investigated in a mammalian system. Overall, similar effects on receptor activation compared to the yeast system were found with mutations located at the EL, but some contradictory effects were observed for mutations located at the IL. Taken together, this study will enrich the insight of A1 AR structure and function, enlightening the consequences of these mutations in cancer. Ultimately, this may provide potential precision medicine in cancer treatment.

Proteochemometric Modeling Identifies Chemically Diverse Norepinephrine Transporter Inhibitors.

Solute carriers (SLCs) are relatively underexplored compared to other prominent protein families such as kinases and G protein-coupled receptors. However, proteins from the SLC family play an essential role in various diseases. One such SLC is the high-affinity norepinephrine transporter (NET/SLC6A2). In contrast to most other SLCs, the NET has been relatively well studied. However, the chemical space of known ligands has a low chemical diversity, making it challenging to identify chemically novel ligands. Here, a computational screening pipeline was developed to find new NET inhibitors. The approach increases the chemical space to model for NETs using the chemical space of related proteins that were selected utilizing similarity networks. Prior proteochemometric models added data from related proteins, but here we use a data-driven approach to select the optimal proteins to add to the modeled data set. After optimizing the data set, the proteochemometric model was optimized using stepwise feature selection. The final model was created using a two-step approach combining several proteochemometric machine learning models through stacking. This model was applied to the extensive virtual compound database of Enamine, from which the top predicted 22,000 of the 600 million virtual compounds were clustered to end up with 46 chemically diverse candidates. A subselection of 32 candidates was synthesized and subsequently tested using an impedance-based assay. There were five hit compounds identified (hit rate 16%) with sub-micromolar inhibitory potencies toward NET, which are promising for follow-up experimental research. This study demonstrates a data-driven approach to diversify known chemical space to identify novel ligands and is to our knowledge the first to select this set based on the sequence similarity of related targets.

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations.

Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.