Automated design of ligands to polypharmacological profiles

Synthesis and evaluation of 3,4,5-trisubstituted triazoles as G protein-biased kappa opioid receptor agonists

Kappa opioid receptor (KOR) agonists represent promising therapeutics for pain relief due to their analgesic properties along with lower abuse potential than opioids that act at the mu opioid receptor. However, typical KOR agonists produce sedation and dysphoria. Previous studies have shown that G protein signaling-biased KOR agonists may present a means to untangle the desired analgesic properties from undesired side effects. In this paper, we report a new series of G protein signaling-biased KOR agonists entailing -S- → -CH2- replacement in a previously reported KOR agonist, triazole 1.1. With an optimized carbon linker in hand, further development of the scaffold was undertaken to investigate the appendages of the triazole core. The structure-activity relationship study of this series is described, including several analogues that display enhanced potency while maintaining G protein-signaling bias compared to triazole 1.1.

2-(Piperidin-3-yl)phthalimides reduce classical markers of cellular inflammation in LPS-challenged RAW 264.7 cells and also demonstrate potentially relevant sigma and serotonin receptor affinity in membrane preparations

Herein, we report the synthesis of new 4-amino-2-(piperidin-3-yl)isoindoline-1,3-diones and their biological evaluation in a series of in vitro experiments. The synthetic production of these materials was initiated upon the condensation of appropriate nitrophthalic acid derivatives with various 3-aminopiperidines; subsequent reduction provided the final products in moderate to good yields. Readily available chiral pool reagents facilitated entry into optically enriched samples, while the piperidine scaffold furnished a variety of amide and alkylated entries. In total, 16 candidates were produced, and their ensuing treatment in LPS-challenged RAW cells effected slight reductions in secreted TNF-α but provided more robust and dose-dependent declines in nitrite and IL-6 levels relative to basal amounts, all concurrent with maintenance of cellular viability across the concentration ranges screened. The secondary amine cohort including rac-6, (R)-7, and (S)-8 rendered the most pronounced dose-dependent reductions in nitrite and IL-6. When dosed at 30 μM, (R)-7 demonstrated the most compelling effects, with decreases of 32 % and 40 % for nitrite and IL-6, respectively. Notable reductions in the inflammatory markers were also observed for 19 which effected declines in TNF-α (14 %), nitrite (19 %), and IL-6 (11 %) when treated at 30 μM. Additionally, four representative compounds were further evaluated against numerous CNS receptors, channels, and transporters, with 6, 9, and 19 demonstrating varying degrees of nanomolar-to-low-micromolar binding to the σ-1 and σ-2 receptors and also to serotonin receptors 5HT2A, 5HT2B and 5HT3. In this regard, 6 displayed perhaps the most noteworthy affinities, with binding at σ-2 (Ki = 2.2uM), 5HT2B (Ki = 561 nM) and 5HT3 (Ki = 536 nM). Furthermore, no pronounced or dose-dependent Cereblon/DDB1 binding was observed for the screened representative compounds 6, 9, 18 and 19.

Development of non-sedating benzodiazepines with in vivo antischistosomal activity

The neglected tropical disease schistosomiasis infects over 200 million people worldwide and is treated with just one broad-spectrum antiparasitic drug (praziquantel). Alternative drugs are needed in the event of emerging praziquantel resistance or treatment failure. One promising lead that has shown efficacy in animal models and a human clinical trial is the benzodiazepine meclonazepam, discovered by Roche in the 1970s. Meclonazepam was not brought to market because of dose-limiting sedative side effects. However, the human target of meclonazepam that causes sedation (GABAARs) is not orthologous to the parasite targets that cause worm death. Therefore, we were interested in whether the structure of meclonazepam could be modified to produce antiparasitic benzodiazepines that do not cause host sedation. We synthesized 18 meclonazepam derivatives with modifications at different positions on the benzodiazepine ring system and tested them for in vitro antiparasitic activity. This identified five compounds that progressed to in vivo screening in a murine model, two of which cured parasite infections with comparable potency to meclonazepam. When these two compounds were administered to mice that were run on the rotarod test, both were less sedating than meclonazepam. These findings demonstrate the proof of concept that meclonazepam analogs can be designed with an improved therapeutic index and point to the C3 position of the benzodiazepine ring system as a logical site for further structure-activity exploration to further optimize this chemical series.

Finding the most potent compounds using active learning on molecular pairs

Active learning allows algorithms to steer iterative experimentation to accelerate and de-risk molecular optimizations, but actively trained models might still exhibit poor performance during early project stages where the training data is limited and model exploitation might lead to analog identification with limited scaffold diversity. Here, we present ActiveDelta, an adaptive approach that leverages paired molecular representations to predict improvements from the current best training compound to prioritize further data acquisition. We apply the ActiveDelta concept to both graph-based deep (Chemprop) and tree-based (XGBoost) models during exploitative active learning for 99 Ki benchmarking datasets. We show that both ActiveDelta implementations excel at identifying more potent inhibitors compared to the standard exploitative active learning implementations of Chemprop, XGBoost, and Random Forest. The ActiveDelta approach is also able to identify more chemically diverse inhibitors in terms of their Murcko scaffolds. Finally, deep models such as Chemprop trained on data selected through ActiveDelta approaches can more accurately identify inhibitors in test data created through simulated time-splits. Overall, this study highlights the large potential for molecular pairing approaches to further improve popular active learning strategies in low data regimes by enabling faster and more accurate identification of more diverse molecular hits against critical drug targets.

Functionalized Congeners of 2H-Chromene P2Y6 Receptor Antagonists

The P2Y6 receptor (P2Y6R), a Gq-coupled receptor, is a potential drug discovery target for various inflammatory and degenerative conditions. Antagonists have been shown to attenuate colitis, acute lung injury, etc. In the search for competitive antagonists, we have investigated the SAR of 3-nitro-2-(trifluoromethyl)-2H-chromene derivatives, although high affinity is lacking. We now reveal that long-chain amino-functionalized congeners display greatly enhanced affinity in the antagonism of UDP-induced Ca2+ mobilization in human (h) P2Y6R-transfected 1321N1 astrocytoma cells. A 6-(Boc-amino-n-heptylethynyl) analogue 30 (MRS4940) had an IC50 of 162 nM, which was a 123-fold greater affinity than the corresponding unprotected primary alkylamine, 107-fold greater than the corresponding pivaloyl derivative 30, and 132-fold selective compared to the P2Y14R. However, similar Boc-amino chains attached at the 8-position produced weak µM affinity. Thus, the P2Y6R affinity depended on the chain length, attachment point, and terminal functionality. Off-target activities, at 45 sites, were tested for acylamino derivatives 20, 24, 26, 30, 31, and 37, which showed multiple interactions, particularly at the biogenic amine receptors. The more potent analogues may be suitable for evaluation in inflammation and cancer models, which will be performed in future studies.

Lipid Trolling to Optimize A3 Adenosine Receptor-Positive Allosteric Modulators (PAMs)

A3 adenosine receptor (A3AR) positive allosteric modulators (PAMs) (2,4-disubstituted-1H-imidazo[4,5-c]quinolin-4-amines) allosterically increase the Emax of A3AR agonists, but not potency, due to concurrent orthosteric antagonism. Following mutagenesis/homology modeling of the proposed lipid-exposed allosteric binding site on the cytosolic side, we functionalized the scaffold, including heteroatom substitutions and exocyclic phenylamine extensions, to increase allosteric binding. Strategically appended linear alkyl-alkynyl chains with terminal amino/guanidino groups improved allosteric effects at both human and mouse A3ARs. The chain length, functionality, and attachment position were varied to modulate A3AR PAM activity. For example, 26 (MRS8247, p-alkyne-linked 8 methylenes) and homologues increased agonist Cl-IB-MECA's Emax and potency ([35S]GTPγS binding). The putative mechanism involves a flexible, terminally cationic chain penetrating the lipid environment for stable electrostatic anchoring to cytosolic phospholipid head groups, suggesting "lipid trolling", supported by molecular dynamic simulation of the active-state model. Thus, we have improved A3AR PAM activity through rational design based on an extrahelical, lipidic binding site.

Medicinal polypharmacology-a scientific glossary of terminology and concepts

Medicinal polypharmacology is one answer to the complex reality of multifactorial human diseases that are often unresponsive to single-targeted treatment. It is an admittance that intrinsic feedback mechanisms, crosstalk, and disease networks necessitate drugs with broad modes-of-action and multitarget affinities. Medicinal polypharmacology grew to be an independent research field within the last two decades and stretches from basic drug development to clinical research. It has developed its own terminology embedded in general terms of pharmaceutical drug discovery and development at the intersection of medicinal chemistry, chemical biology, and clinical pharmacology. A clear and precise language of critical terms and a thorough understanding of underlying concepts is imperative; however, no comprehensive work exists to this date that could support researchers in this and adjacent research fields. In order to explore novel options, establish interdisciplinary collaborations, and generate high-quality research outputs, the present work provides a first-in-field glossary to clarify the numerous terms that have originated from various individual disciplines.

2-Substituted (N)-Methanocarba A3 Adenosine Receptor Agonists: In Silico, In Vitro, and In Vivo Characterization

2-Arylethynyl (N)-methanocarba adenosine 5'-methylamides are selective A3 adenosine receptor (AR) agonists containing a preestablished receptor-preferred pseudoribose conformation. Here, we compare analogues having bulky 2-substitution, either containing or lacking an ethynyl spacer between adenine and a cyclic group. 2-Aryl compounds 9-11, 13, 14, 19, 22, 23, 27, 29, 31, and 34, lacking a spacer, had human (h) A3AR K i values of 2-30 nM, and others displayed lower affinity. Mouse (m) A3AR affinity varied, with 2-arylethynyl having a higher affinity than 2-aryl analogues (7, 8 > 3c, 3d > 3b). However, 2-aryl-4'-truncated derivatives had greatly reduced hA3AR affinity, even containing affinity-enhancing N 6-dopamine-derived substituents. Molecular modeling, including molecular dynamics simulation, predicted stable poses in the canonical A3AR agonist binding site, but 2-aryl (ECL2 interactions) and 2-arylethynyl (TM2 interactions) substituents have different conformations and environments. In a hA3AR miniGαi recruitment assay, 31 (MRS8062) was (slightly) more potent compared to a β-arrestin2 recruitment assay, both in engineered HEK293T cells, and its maximal efficacy (E max) was much higher (165%) than reference agonist NECA's. Thus, in the 2-aryl series, A3AR affinity and selectivity were variable and generally reduced compared to the 2-arylethynyl series, with a greater dependence on the specific aryl group present. Selected compounds were studied in vivo in an ischemic model of peripheral artery disease (PAD). Rigidified 2-arylethynyl analogues 3a-3c were protective in this model of skeletal muscle ischemia-reperfusion injury/claudication, as previously shown only for moderately A3AR-selective ribosides or (N)-methanocarba derivatives. Thus, we have expanded the A3AR agonist SAR for (N)-methanocarba adenosines.

Systematic Investigation of Dual-Target-Directed Ligands

Multitarget-directed ligands (MTDLs) are compounds rationally designed to affect multiple targets, aiming for a better therapeutic profile. For over 20 years, MTDLs have garnered increasing attention, the idea being that their full potential would have been achieved, thanks to unprecedented target combinations and advanced medicinal chemistry strategies. This study presents a literature mining effort resulting in a data set of dual-target-directed ligands (DTDLs), the fundamental example of MTDLs. We used this data set to evaluate the rationale behind target selection and the chemical novelty of DTDLs targeting specific protein combinations. Our analysis focused on DTDL targets in terms of biological function, disease association, structure, and chemogenomic traits. We also compared DTDLs with single-target compounds. We found that well-known target pathology associations often guide DTDL design, leveraging existing chemical scaffolds and binding pocket similarities. These findings highlight the current state of the field and suggest substantial untapped potential for rational polypharmacology.

Discovery of 3-((4-Benzylpyridin-2-yl)amino)benzamides as Potent GPR52 G Protein-Biased Agonists

Orphan GPR52 is emerging as a promising neurotherapeutic target. Optimization of previously reported lead 4a employing an iterative drug design strategy led to the identification of a series of unique GPR52 agonists, such as 10a (PW0677), 15b (PW0729), and 24f (PW0866), with improved potency and efficacy. Intriguingly, compounds 10a and 24f showed greater bias for G protein/cAMP signaling and induced significantly less in vitro desensitization than parent compound 4a, indicating that reducing GPR52 β-arrestin activity with biased agonism results in sustained GPR52 activation. Further exploration of compounds 15b and 24f indicated improved potency and efficacy, and excellent target selectivity, but limited brain exposure warranting further optimization. These balanced and biased GPR52 agonists provide important pharmacological tools to study GPR52 activation, signaling bias, and therapeutic potential for neuropsychiatric and neurological diseases.

Sigma Receptor Ligands Are Potent Antiprion Compounds that Act Independently of Sigma Receptor Binding

Prion diseases are invariably fatal neurodegenerative diseases of humans and other animals for which there are no effective treatment options. Previous work from our laboratory identified phenethylpiperidines as a novel class of anti-prion compounds. While working to identify the molecular target(s) of these molecules, we unexpectedly discovered ten novel antiprion compounds based on their known ability to bind to the sigma receptors, σ1R and σ2R, which are currently being tested as therapeutic or diagnostic targets for cancer and neuropsychiatric disorders. Surprisingly, however, knockout of the respective genes encoding σ1R and σ2R (Sigmar1 and Tmem97) in prion-infected N2a cells did not alter the antiprion activity of these compounds, demonstrating that these receptors are not the direct targets responsible for the antiprion effects of their ligands. Further investigation of the most potent molecules established that they are efficacious against multiple prion strains and protect against downstream prion-mediated synaptotoxicity. While the precise details of the mechanism of action of these molecules remain to be determined, the present work forms the basis for further investigation of these compounds in preclinical studies. Given the therapeutic utility of several of the tested compounds, including rimcazole and haloperidol for neuropsychiatric conditions, (+)-pentazocine for neuropathic pain, and the ongoing clinical trials of SA 4503 and ANAVEX2-73 for ischemic stroke and Alzheimer's disease, respectively, this work has immediate implications for the treatment of human prion disease.

Unleashing the power of generative AI in drug discovery

Artificial intelligence (AI) is revolutionizing drug discovery by enhancing precision, reducing timelines and costs, and enabling AI-driven computer-aided drug design. This review focuses on recent advancements in deep generative models (DGMs) for de novo drug design, exploring diverse algorithms and their profound impact. It critically analyses the challenges that are intricately interwoven into these technologies, proposing strategies to unlock their full potential. It features case studies of both successes and failures in advancing drugs to clinical trials with AI assistance. Last, it outlines a forward-looking plan for optimizing DGMs in de novo drug design, thereby fostering faster and more cost-effective drug development.

An shRNA screen in primary human beta cells identifies the serotonin 1F receptor as a negative regulator of survival during transplant

Islet transplantation can cure type 1 diabetes, but peri-transplant beta cell death limits this procedure to those with low insulin requirements. Improving human beta cell survival or proliferation may make islet transplantation a possibility for more type 1 patients. To identify novel regulators of beta cell survival and proliferation, we conducted a pooled small hairpin RNA (shRNA) screen in primary human beta cells transplanted into immunocompromised mice. shRNAs targeting several cyclin dependent kinase inhibitors were enriched after transplant. Here, we focused on the Gi/o-coupled GPCR, serotonin 1F receptor ( HTR1F, 5-HT 1F ) which our screen identified as a negative regulator of beta cell numbers after transplant. In vitro , 5-HT 1F knockdown induced human beta cell proliferation but only when combined with harmine and exendin-4. In vivo , knockdown of 5-HT 1F reduced beta cell death during transplant. To demonstrate the feasibility of targeting 5-HT 1F in islet transplant, we identified and validated a small molecule 5-HT 1F antagonist. This antagonist increased glucose stimulated insulin secretion from primary human islets and cAMP accumulation in primary human beta cells. Finally, the 5-HT 1F antagonist improved glycemia in marginal mass, human islet transplants into immunocompromised mice. We identify 5-HT 1F as a novel druggable target to improve human beta cell survival in the setting of islet transplantation.

One Sentence Summary

Serotonin 1F receptor (5-HT 1F ) negatively regulates insulin secretion and beta cell survival during transplant.

Robust Quantification of Phosphodiesterase-4D in Monkey Brain with PET and 11C-Labeled Radioligands That Avoid Radiometabolite Contamination

Phosphodiesterase-4D (PDE4D) has emerged as a significant target for treating neuropsychiatric disorders, but no PET radioligand currently exists for robustly quantifying human brain PDE4D to assist biomedical research and drug discovery. A prior candidate PDE4D PET radioligand, namely [11C]T1650, failed in humans because of poor time stability of brain PDE4D-specific signal (indexed by total volume of distribution), likely due to radiometabolites accumulating in brain. Its nitro group was considered to be a source of the brain radiometabolites. Methods: We selected 5 high-affinity and selective PDE4D inhibitors, absent of a nitro group, from our prior structure-activity relationship study for evaluation as PET radioligands. Results: All 5 radioligands were labeled with 11C (half-time, 20.4 min) in useful yields and with high molar activity. All displayed sizable PDE4D-specific signals in rhesus monkey brain. Notably, [11C]JMJ-81 and [11C]JMJ-129 exhibited excellent time stability of signal (total volume of distribution). Furthermore, as an example, [11C]JMJ-81 was found to be free of radiometabolites in ex vivo monkey brain, affirming that this radioligand can provide robust quantification of brain PDE4D with PET. Conclusion: Given their high similarity in structures and metabolic profiles, both [11C]JMJ-81 and [11C]JMJ-129 warrant further evaluation in human subjects. [11C]JMJ-129 shows a higher PDE4D specific-to-nonspecific binding ratio and will be the first to be evaluated.

Synthesis and Structure-Activity Relationships for Glutamate Transporter Allosteric Modulators

Excitatory amino acid transporters (EAATs) are essential CNS proteins that regulate glutamate levels. Excess glutamate release and alteration in EAAT expression are associated with several CNS disorders. Previously, we identified positive allosteric modulators (PAM) of EAAT2, the main CNS transporter, and have demonstrated their neuroprotective properties in vitro. Herein, we report on the structure-activity relationships (SAR) for the analogs identified from virtual screening and from our medicinal chemistry campaign. This work identified several selective EAAT2 positive allosteric modulators (PAMs) such as compounds 4 (DA-023) and 40 (NA-014) from a library of analogs inspired by GT949, an early generation compound. This series also provides nonselective EAAT PAMs, EAAT inhibitors, and inactive compounds that may be useful for elucidating the mechanism of EAAT allosteric modulation.

Flexible scaffold-based cheminformatics approach for polypharmacological drug design

Effective treatments for complex central nervous system (CNS) disorders require drugs with polypharmacology and multifunctionality, yet designing such drugs remains a challenge. Here, we present a flexible scaffold-based cheminformatics approach (FSCA) for the rational design of polypharmacological drugs. FSCA involves fitting a flexible scaffold to different receptors using different binding poses, as exemplified by IHCH-7179, which adopted a "bending-down" binding pose at 5-HT2AR to act as an antagonist and a "stretching-up" binding pose at 5-HT1AR to function as an agonist. IHCH-7179 demonstrated promising results in alleviating cognitive deficits and psychoactive symptoms in mice by blocking 5-HT2AR for psychoactive symptoms and activating 5-HT1AR to alleviate cognitive deficits. By analyzing aminergic receptor structures, we identified two featured motifs, the "agonist filter" and "conformation shaper," which determine ligand binding pose and predict activity at aminergic receptors. With these motifs, FSCA can be applied to the design of polypharmacological ligands at other receptors.

In vitro characterization of [125I]HY-3-24, a selective ligand for the dopamine D3 receptor

Introduction

Dopamine D3 receptor (D3R) ligands have been studied for the possible treatment of neurological and neuropsychiatric disorders. However, selective D3R radioligands for in vitro binding studies have been challenging to identify due to the high structural similarity between the D2R and D3R. In a prior study, we reported a new conformationally-flexible benzamide scaffold having a high affinity for D3R and excellent selectivity vs. D2R. In the current study, we characterized the in vitro binding properties of a new radioiodinated ligand, [125I]HY-3-24.

Methods

In vitro binding studies were conducted in cell lines expressing D3 receptors, rat striatal homogenates, and rat and non-human primate (NHP) brain tissues to measure regional brain distribution of this radioligand.

Results

HY-3-24 showed high potency at D3R (Ki = 0.67 ± 0.11 nM, IC50 = 1.5 ± 0.58 nM) compared to other D2-like dopamine receptor subtypes (D2R Ki = 86.7 ± 11.9 nM and D4R Ki > 1,000). The Kd (0.34 ± 0.22 nM) and Bmax (38.91 ± 2.39 fmol/mg) values of [125I]HY-3-24 were determined. In vitro binding studies in rat striatal homogenates using selective D2R and D3R antagonists confirmed the D3R selectivity of [125I]HY-3-24. Autoradiography results demonstrated that [125I]HY-3-24 specifically binds to D3Rs in the nucleus accumbens, islands of Calleja, and caudate putamen in rat and NHP brain sections.

Conclusion

These results suggest that [125I]HY-3-24 appears to be a novel radioligand that exhibits high affinity binding at D3R, with low binding to other D2-like dopamine receptors. It is anticipated that [125I]HY-3-24 can be used as the specific D3R radioligand.

Chemoinformatic approaches for navigating large chemical spaces

INTRODUCTION

Large chemical spaces (CSs) include traditional large compound collections, combinatorial libraries covering billions to trillions of molecules, DNA-encoded chemical libraries comprising complete combinatorial CSs in a single mixture, and virtual CSs explored by generative models. The diverse nature of these types of CSs require different chemoinformatic approaches for navigation.

AREAS COVERED

An overview of different types of large CSs is provided. Molecular representations and similarity metrics suitable for large CS exploration are discussed. A summary of navigation of CSs in generative models is provided. Methods for characterizing and comparing CSs are discussed.

EXPERT OPINION

The size of large CSs might restrict navigation to specialized algorithms and limit it to considering neighborhoods of structurally similar molecules. Efficient navigation of large CSs not only requires methods that scale with size but also requires smart approaches that focus on better but not necessarily larger molecule selections. Deep generative models aim to provide such approaches by implicitly learning features relevant for targeted biological properties. It is unclear whether these models can fulfill this ideal as validation is difficult as long as the covered CSs remain mainly virtual without experimental verification.

Structure-Affinity relationships of novel σ2R/TMEM97 ligands

The sigma 2 receptor (σ2R), which was recently identified as the transmembrane protein 97 (TMEM97), is increasingly attracting interest as a possible therapeutic target for indications in neuroscience. Toward identifying novel modulators of σ2R/TMEM97, we prepared a collection of benzoxazocine, benzomorphan, and methanobenzazepine ligands related to the known bioactive norbenzomorphans DKR-1677, FEM-1689, and EES-1686 and determined their Ki values for σ2R/TMEM97 and the sigma 1 receptor (σ1R). The σ2R/TMEM97 binding affinities and selectivities relative to σ1R of these new benzoxazocine, benzomorphan, and methanobenzazepine analogs are lower, often significantly lower, than their respective norbenzomorphan counterparts, suggesting the spatial orientation of pharmacophoric substituents is critical for binding to the two proteins. The benzoxazocine, benzomorphan, and methanobenzazepine congeners of DKR-1677 and FEM-1689 tend to be weakly selective for σ2R/TMEM97 versus σ1R, whereas EES-1686 derivatives exhibit the greatest selectivity, suggesting the size and/or nature of the substituent on the nitrogen atom of the scaffold may be important for selectivity. Computational docking studies were performed for the 1S,5R-and 1R,5S-enantiomers of DKR-1677, FEM-1689, and EES-1686 and their benzoxazocine, benzomorphan, and methanobenzazepine counterparts. These computations predict that the protonated amino group of each ligand forms a highly conserved salt bridge and a H-bonding interaction with Asp29 as well as a cation-π interaction with Tyr150 of σ2R/TMEM97. These electrostatic interactions are major driving forces for binding to σ2R/TMEM97 and are similar, though not identical, for each ligand. Other interactions within the well-defined binding pocket also tend to be comparable, but there are some major differences in how the hydrophobic aryl groups of various ligands interact with the protein surface external to the binding pocket. Overall, these studies show that the orientations of aryl and N-substituents on the norbenzomorphan and related scaffolds are important determinants of binding affinity of σ2R/TMEM97 ligands, and small changes can have significant effects upon binding profiles.

The AI-driven Drug Design (AIDD) platform: an interactive multi-parameter optimization system integrating molecular evolution with physiologically based pharmacokinetic simulations

Computer-aided drug design has advanced rapidly in recent years, and multiple instances of in silico designed molecules advancing to the clinic have demonstrated the contribution of this field to medicine. Properly designed and implemented platforms can drastically reduce drug development timelines and costs. While such efforts were initially focused primarily on target affinity/activity, it is now appreciated that other parameters are equally important in the successful development of a drug and its progression to the clinic, including pharmacokinetic properties as well as absorption, distribution, metabolic, excretion and toxicological (ADMET) properties. In the last decade, several programs have been developed that incorporate these properties into the drug design and optimization process and to varying degrees, allowing for multi-parameter optimization. Here, we introduce the Artificial Intelligence-driven Drug Design (AIDD) platform, which automates the drug design process by integrating high-throughput physiologically-based pharmacokinetic simulations (powered by GastroPlus) and ADMET predictions (powered by ADMET Predictor) with an advanced evolutionary algorithm that is quite different than current generative models. AIDD uses these and other estimates in iteratively performing multi-objective optimizations to produce novel molecules that are active and lead-like. Here we describe the AIDD workflow and details of the methodologies involved therein. We use a dataset of triazolopyrimidine inhibitors of the dihydroorotate dehydrogenase from Plasmodium falciparum to illustrate how AIDD generates novel sets of molecules.

Unlocking the Potential of High-Quality Dopamine Transporter Pharmacological Data: Advancing Robust Machine Learning-Based QSAR Modeling

The dopamine transporter (DAT) plays a critical role in the central nervous system and has been implicated in numerous psychiatric disorders. The ligand-based approaches are instrumental to decipher the structure-activity relationship (SAR) of DAT ligands, especially the quantitative SAR (QSAR) modeling. By gathering and analyzing data from literature and databases, we systematically assemble a diverse range of ligands binding to DAT, aiming to discern the general features of DAT ligands and uncover the chemical space for potential novel DAT ligand scaffolds. The aggregation of DAT pharmacological activity data, particularly from databases like ChEMBL, provides a foundation for constructing robust QSAR models. The compilation and meticulous filtering of these data, establishing high-quality training datasets with specific divisions of pharmacological assays and data types, along with the application of QSAR modeling, prove to be a promising strategy for navigating the pertinent chemical space. Through a systematic comparison of DAT QSAR models using training datasets from various ChEMBL releases, we underscore the positive impact of enhanced data set quality and increased data set size on the predictive power of DAT QSAR models.

Large library docking for cannabinoid-1 receptor agonists with reduced side effects

Large library docking can reveal unexpected chemotypes that complement the structures of biological targets. Seeking new agonists for the cannabinoid-1 receptor (CB1R), we docked 74 million tangible molecules, prioritizing 46 high ranking ones for de novo synthesis and testing. Nine were active by radioligand competition, a 20% hit-rate. Structure-based optimization of one of the most potent of these (Ki = 0.7 uM) led to '4042, a 1.9 nM ligand and a full CB1R agonist. A cryo-EM structure of the purified enantiomer of '4042 ('1350) in complex with CB1R-Gi1 confirmed its docked pose. The new agonist was strongly analgesic, with generally a 5-10-fold therapeutic window over sedation and catalepsy and no observable conditioned place preference. These findings suggest that new cannabinoid chemotypes may disentangle characteristic cannabinoid side-effects from their analgesia, supporting the further development of cannabinoids as pain therapeutics.

Advances in structure-based drug design: The potential for precision therapeutics in psychiatric disorders

Over the years, the field of GPCR drug design has undergone a remarkable evolution, fueled by advancements in science and technology. This evolution has given rise to a diverse range of ideas and approaches in structure-based drug design, bolstering the versatility and strength of the GPCR drug design toolbox. This review encapsulates the iterative development process, navigating challenges and opportunities in structure-based drug design within GPCRs. With a focused emphasis on its impact on psychiatric disorders, the review accentuates recent advancements and delves into the potentials unlocked by emerging technologies. The review explores the intricate interplay between scientific progress and iterative refinement, offering profound insights into the potential pathways that lie ahead for GPCR drug design.

12-(S)-Hydroxyeicosatetraenoic Acid and GPR31 Signaling in Spinal Cord in Neuropathic Pain

Neuropathic pain is a pressing unmet medical need requiring novel nonopioid-based therapeutic approaches. Using unbiased transcriptomic analysis, we found that the expression of Gpr31, a G protein-coupled receptor, increased in the dorsal horn of the spinal cord in rats with traumatic nerve injury-induced neuropathic pain. Daily intrathecal injections of siGpr31 reversed behavioral hypersensitivities in a time-dependent manner. GPR31, a Gα i protein-coupled receptor, has recently been cloned and is a receptor for 12-(S)-hydroxyeicosatetraenoic acid [12-(S)-HETE]. The lack of commercially available GPR31 antagonists has hampered the understanding of this receptor in pathophysiological states, including pain. To investigate this, our first approach was to identify novel GPR31 antagonists. Using a multidisciplinary approach, including in silico modeling, we identified the first highly potent and selective small-molecule GPR31 antagonist, SAH2. Here, we characterize the pharmacological activity in well-described models of neuropathic pain in rodents and provide evidence that 12-(S)-HETE/GPR31-dependent behavioral hypersensitivities are mediated through mitogen-activated protein kinase (MAPK) activation in the spinal cord. Our studies provide the pharmacological rationale for investigating contributions of GPR31 along the pain neuroaxis and the development of nonopioid GPR31-targeted strategies. SIGNIFICANCE STATEMENT: We have identified the first highly selective GPR31 antagonist. Using this antagonist, we have demonstrated that GPR31 signaling in the spinal cord is pronociceptive and MAPK pathways provided signaling mechanisms downstream of GPR31 activation in these processes.

In Silico Investigation of Novel Compounds as Inhibitors of Acetylcholinesterase Enzyme for the Treatment of Alzheimer's Diseases

Alzheimer's disease (AD) is a "progressive, neurodegenerative disease that occurs when nerve cells in the brain die." There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool-Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.

AI for targeted polypharmacology: The next frontier in drug discovery

In drug discovery, targeted polypharmacology, i.e., targeting multiple molecular targets with a single drug, is redefining therapeutic design to address complex diseases. Pre-selected pharmacological profiles, as exemplified in kinase drugs, promise enhanced efficacy and reduced toxicity. Historically, many of such drugs were discovered serendipitously, limiting predictability and efficacy, but currently artificial intelligence (AI) offers a transformative solution. Machine learning and deep learning techniques enable modeling protein structures, generating novel compounds, and decoding their polypharmacological effects, opening an avenue for more systematic and predictive multi-target drug design. This review explores the use of AI in identifying synergistic co-targets and delineating them from anti-targets that lead to adverse effects, and then discusses advances in AI-enabled docking, generative chemistry, and proteochemometric modeling of proteome-wide compound interactions, in the context of polypharmacology. We also provide insights into challenges ahead.

Development of non-sedating antischistosomal benzodiazepines

The neglected tropical disease schistosomiasis infects over 200 million people worldwide and is treated with just one broad spectrum antiparasitic drug (praziquantel). Alternative drugs are needed in the event of emerging praziquantel resistance or treatment failure. One promising lead that has shown efficacy in animal models and a human clinical trial is the benzodiazepine meclonazepam, discovered by Roche in the 1970's. Meclonazepam was not brought to market because of dose-limiting sedative side effects. However, the human target of meclonazepam that causes sedation (GABAARs) are not orthologous to the parasite targets that cause worm death. Therefore, we were interested in whether the structure of meclonazepam could be modified to produce antiparasitic benzodiazepines that do not cause host sedation. We synthesized 18 meclonazepam derivatives with modifications at different positions on the benzodiazepine ring system and tested them for in vitro antiparasitic activity. This identified five compounds that progressed to in vivo screening in a murine model, two of which cured parasite infections with comparable potency to meclonazepam. When these two compounds were administered to mice that were run on the rotarod test, both were less sedating than meclonazepam. These findings demonstrate the proof of concept that meclonazepam analogs can be designed with an improved therapeutic index, and point to the C3 position of the benzodiazepine ring system as a logical site for further structure-activity exploration to further optimize this chemical series.

Artificial Intelligence for Drug Discovery: Are We There Yet?

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small-molecule drugs. AI technologies, such as generative chemistry, machine learning, and multiproperty optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages.

Synthesis of α3β4 Nicotinic Acetylcholine Receptor Modulators Derived from Aristoquinoline That Reduce Reinstatement of Cocaine-Seeking Behavior

Growing evidence suggests that inhibition of the α3β4 nicotinic acetylcholine receptor (nAChR) represents a promising therapeutic strategy to treat cocaine use disorder. Recently, aristoquinoline (1), an alkaloid from Aristotelia chilensis, was identified as an α3β4-selective nAChR inhibitor. Here, we prepared 22 derivatives of 1 and evaluated their ability to inhibit the α3β4 nAChR. These studies revealed structure-activity trends and several compounds with increased potency compared to 1 with few off-target liabilities. Additional mechanistic studies indicated that these compounds inhibit the α3β4 nAChR noncompetitively, but do not act as channel blockers, suggesting they are negative allosteric modulators. Finally, using a cocaine-primed reinstatement paradigm, we demonstrated that 1 significantly attenuates drug-seeking behavior in an animal model of cocaine relapse. The results from these studies further support a role for the α3β4 nAChR in the addictive properties of cocaine and highlight the possible utility of aristoquinoline derivatives in treating cocaine use disorder.

Trajectories of sentiment in 11,816 psychoactive narratives

OBJECTIVE

Can machine learning (ML) enable data-driven discovery of how changes in sentiment correlate with different psychoactive experiences? We investigate by training models directly on text testimonials from a diverse 52-drug pharmacopeia.

METHODS

Using large language models (i.e. BERT) and 11,816 publicly-available testimonials, we predicted 28-dimensions of sentiment across each narrative, and then validated these predictions with adjudication by a clinical psychiatrist. BERT was then fine-tuned to predict biochemical and demographic information from these narratives. Lastly, canonical correlation analysis linked the drugs' receptor affinities with word usage, revealing 11 statistically-significant latent receptor-experience factors, each mapped to a 3D cortical Atlas.

RESULTS

These methods elucidate a neurobiologically-informed, sequence-sensitive portrait of drug-induced subjective experiences. The models' results converged, revealing a pervasive distinction between the universal psychedelic heights of feeling in contrast to the grim, mundane, and personal experiences of addiction and mental illness. Notably, MDMA was linked to "Love", DMT and 5-MeO-DMT to "Mystical Experiences" and "Entities and Beings", and other tryptamines to "Surprise", "Curiosity" and "Realization".

CONCLUSIONS

ML methods can create unified and robust quantifications of subjective experiences with many different psychoactive substances and timescales. The representations learned are evocative and mutually confirmatory, indicating great potential for ML in characterizing psychoactivity.

SSRIs in the Treatment of Depression: A Pharmacological CUL-DE-SAC?

The widespread adoption of selective serotonin reuptake inhibitors (SSRIs) as first-line pharmacological treatments in the management of clinical depression transformed the landscape of drug therapy for this condition. SSRIs are safer and better tolerated than the tricyclic antidepressants (TCAs) that they replaced. However, they have limitations that may have placed a ceiling on the expectations of first-line pharmacological treatment. Notable problems with SSRIs include induction of anxiety on treatment initiation, delayed onset of significant therapeutic effect, sexual dysfunction, sleep disturbance and overall modest efficacy. The latter is linked with an inability of SSRIs to effectively treat syndromes of anhedonia and cognitive impairment. Combined serotonin and noradrenaline reuptake inhibitors (SNRIs), such as venlafaxine, have produced some limited improvements over SSRIs in efficacy, at the cost of a greater side-effect burden. Attempts to supplement serotonin reuptake activity with actions at serotonin receptor sub-types have not yet yielded substantial benefits; however, vortioxetine may provide more utility in the management of cognitive impairment. Future advances might come from the development of SNRIs, which more closely mimic the actions of effective TCAs. There may also be possible benefits to be derived from combining SSRIs with 5-HT4 receptor agonists and 5-HT7 receptor antagonists.

Identification of 5-HT2A receptor signaling pathways associated with psychedelic potential

Serotonergic psychedelics possess considerable therapeutic potential. Although 5-HT2A receptor activation mediates psychedelic effects, prototypical psychedelics activate both 5-HT2A-Gq/11 and β-arrestin2 transducers, making their respective roles unclear. To elucidate this, we develop a series of 5-HT2A-selective ligands with varying Gq efficacies, including β-arrestin-biased ligands. We show that 5-HT2A-Gq but not 5-HT2A-β-arrestin2 recruitment efficacy predicts psychedelic potential, assessed using head-twitch response (HTR) magnitude in male mice. We further show that disrupting Gq-PLC signaling attenuates the HTR and a threshold level of Gq activation is required to induce psychedelic-like effects, consistent with the fact that certain 5-HT2A partial agonists (e.g., lisuride) are non-psychedelic. Understanding the role of 5-HT2A Gq-efficacy in psychedelic-like psychopharmacology permits rational development of non-psychedelic 5-HT2A agonists. We also demonstrate that β-arrestin-biased 5-HT2A receptor agonists block psychedelic effects and induce receptor downregulation and tachyphylaxis. Overall, 5-HT2A receptor Gq-signaling can be fine-tuned to generate ligands distinct from classical psychedelics.

2-Amino-5-arylethynyl-thiophen-3-yl-(phenyl)methanones as A1 Adenosine Receptor Positive Allosteric Modulators

A1 adenosine receptor (A1AR) agonists have cerebroprotective, cardioprotective, antinociceptive, and other pharmaceutical applications. We explored the structure-activity relationship of 5-arylethynyl aminothiophenes as A1AR positive allosteric modulators (PAMs). The derivatives were compared in binding and functional assays at the human A1AR, indicating that some fluoro-substituted analogues have enhanced PAM activity. We identified substitution of the terminal phenyl ring in 12 (2-F-Ph), 15 (3,4-F2-Ph, MRS7935), and 21 (2-CF3-Ph) as particularly enhancing the PAM activity. 15 was also shown to act as an A1 ago-PAM with EC50 ≈ 2 μM, without activity (30 μM) at other ARs. Molecular modeling indicated that both the 5-arylethynyl and the 4-neopentyl groups are located in a region outside the receptor transmembrane helix bundle that is in contact with the phospholipid bilayer, consistent with the preference for nonpolar substitution of the aryl moiety. Although they are hydrophobic, these PAMs could provide potential drug candidate molecules for engaging protective A1ARs.

STAGAN: An approach for improve the stability of molecular graph generation based on generative adversarial networks

With the wide application of deep learning in Drug Discovery, deep generative model has shown its advantages in drug molecular generation. Generative adversarial networks can be used to learn the internal structure of molecules, but the training process may be unstable, such as gradient disappearance and model collapse, which may lead to the generation of molecules that do not conform to chemical rules or a single style. In this paper, a novel method called STAGAN was proposed to solve the difficulty of model training, by adding a new gradient penalty term in the discriminator and designing a parallel layer of batch normalization used in generator. As an illustration of method, STAGAN generated higher valid and unique molecules than previous models in training datasets from QM9 and ZINC-250K. This indicates that the proposed method can effectively solve the instability problem in the model training process, and can provide more instructive guidance for the further study of molecular graph generation.

Sigma receptor ligands are potent anti-prion compounds that act independently of sigma receptor binding

Prion diseases are invariably fatal neurodegenerative diseases of humans and other animals for which there are no treatment options. Previous work from our laboratory identified phenethyl piperidines as novel class of anti-prion compounds. While working to identify the molecular target(s) of these molecules, we unexpectedly discovered ten novel anti-prion compounds based on their known ability to bind to the sigma receptors, σ 1 R and 2 R, which are currently being tested as therapeutic or diagnostic targets for cancer and neuropsychiatric disorders. Surprisingly, however, knockout of the respective genes encoding σ 1 R and σ 2 R ( Sigmar1 and Tmem97 ), in prion infected N2a cells did not alter the anti-prion activity of these compounds, demonstrating that these receptors are not the direct targets responsible the anti-prion effects of their ligands. Further investigation of the most potent molecules established that they are efficacious against multiple prion strains and protect against downstream prion-mediated synaptotoxicity. While the precise details of the mechanism of action of these molecules remains to be determined, the present work forms the basis for further investigations of these compounds in pre-clinical studies. Given the therapeutic utility of several of the tested compounds, including rimcazole and haloperidol for neuropsychiatric conditions, (+)-pentazocine for neuropathic pain, and the ongoing clinical trials of SA 4503 and ANAVEX2-73 for ischemic stroke and Alzheimer's disease, respectively, this work has immediate implications for the treatment of human prion disease.

Structure activity relationships of 5-HT2B and 5-HT2C serotonin receptor antagonists: N6, C2 and 5'-Modified (N)-methanocarba-adenosine derivatives

(N)-Methanocarba adenosine derivatives were structurally modified to target 5-HT2B serotonin receptors as antagonists, predominantly containing branched N6-alkyl groups. N6-Dicycloalkyl-methyl groups, including their asymmetric variations, as well as 2-iodo, were found to generally favor 5-HT2Rs, while only N6-dicyclohexyl-methyl derivative 35 showed weak 5-HT2AR affinity (Ki 3.6 μM). The highest 5-HT2BR affinities were Ki 11-23 nM (N6-dicyclopropyl-methyl-2-iodo 11, 2-chloro-5'-deoxy-5'-methylthio 15 and N6-((R)-cyclobuty-cyclopropyl-methyl)-2-iodo 43), and Ki 73 nM at 5-HT2CR for 36. Direct comparison of adenine ribosides and their corresponding rigid (N)-methanocarba derivatives (cf. 51 and MRS8099 45) indicated a multifold affinity enhancement with the bicyclic ring system. Compounds 43, 45 and 48 were functional 5-HT2BR (KB 2-3 nM) and 5-HT2CR (KB 79-328 nM) antagonists in a Gq-mediated calcium flux assay, with 5-HT2BR functional selectivity ranging from 45- (48) to 113-fold (43). Substantial adenosine receptor (AR) affinity (Ki, A1AR < Ki, A3AR < Ki, A2AAR) was still present in this series, suggestive of dual acting compounds: 5-HT2B antagonist and A1AR agonist, potentially useful for treating chronic conditions (fibrosis; pain). Given its affinity (17 nM) and moderate 5-HT2BR binding selectivity (32-fold vs. 5-HT2CR, 4-fold vs. A1AR), 43 (MRS7925) could potentially be useful for anti-fibrotic therapy.

Nonspecific membrane bilayer perturbations by ivermectin underlie SARS-CoV-2 in vitro activity

Since it was proposed as a potential host-directed antiviral agent for SARS-CoV-2, the antiparasitic drug ivermectin has been investigated thoroughly in clinical trials, which have provided insufficient support for its clinical efficacy. To examine the potential for ivermectin to be repurposed as an antiviral agent, we therefore undertook a series of preclinical studies. Consistent with early reports, ivermectin decreased SARS-CoV-2 viral burden in in vitro models at low micromolar concentrations, five- to ten-fold higher than the reported toxic clinical concentration. At similar concentrations, ivermectin also decreased cell viability and increased biomarkers of cytotoxicity and apoptosis. Further mechanistic and profiling studies revealed that ivermectin nonspecifically perturbs membrane bilayers at the same concentrations where it decreases the SARS-CoV-2 viral burden, resulting in nonspecific modulation of membrane-based targets such as G-protein coupled receptors and ion channels. These results suggest that a primary molecular mechanism for the in vitro antiviral activity of ivermectin may be nonspecific membrane perturbation, indicating that ivermectin is unlikely to be translatable into a safe and effective antiviral agent. These results and experimental workflow provide a useful paradigm for performing preclinical studies on (pandemic-related) drug repurposing candidates.

Highly specific σ2R/TMEM97 ligand alleviates neuropathic pain and inhibits the integrated stress response

The Sigma 2 receptor (σ2R) was described pharmacologically more than three decades ago, but its molecular identity remained obscure until recently when it was identified as transmembrane protein 97 (TMEM97). We and others have shown that σ2R/TMEM97 ligands alleviate mechanical hypersensitivity in mouse neuropathic pain models with a time course wherein maximal anti-nociceptive effect is approximately 24 hours following dosing. We sought to understand this unique anti-neuropathic pain effect by addressing two key questions: do these σ2R/TMEM97 compounds act selectively via the receptor, and what is their downstream mechanism on nociceptive neurons? Using male and female conventional knockout (KO) mice for Tmem97, we find that a new σ2R/TMEM97 binding compound, FEM-1689, requires the presence of the gene to produce anti-nociception in the spared nerve injury model in mice. Using primary mouse dorsal root ganglion (DRG) neurons, we demonstrate that FEM-1689 inhibits the integrated stress response (ISR) and promotes neurite outgrowth via a σ2R/TMEM97-specific action. We extend the clinical translational value of these findings by showing that FEM-1689 reduces ISR and p-eIF2α levels in human sensory neurons and that it alleviates the pathogenic engagement of ISR by methylglyoxal. We also demonstrate that σ2R/TMEM97 is expressed in human nociceptors and satellite glial cells. These results validate σ2R/TMEM97 as a promising target for further development for the treatment of neuropathic pain.

In Vitro and In Vivo Evaluation of Pellotine: A Hypnotic Lophophora Alkaloid

Quality of life is often reduced in patients with sleep-wake disorders. Insomnia is commonly treated with benzodiazepines, despite their well-known side effects. Pellotine (1), a Lophophora alkaloid, has been reported to have short-acting sleep-inducing properties in humans. In this study, we set out to evaluate various in vitro and in vivo properties of 1. We demonstrate that 1 undergoes slow metabolism; e.g. in mouse liver microsomes 65% remained, and in human liver microsomes virtually no metabolism was observed after 4 h. In mouse liver microsomes, two phase I metabolites were identified: 7-desmethylpellotine and pellotine-N-oxide. In mice, the two diastereomers of pellotine-O-glucuronide were additionally identified as phase II metabolites. Furthermore, we demonstrated by DESI-MSI that 1 readily enters the central nervous system of rodents. Furthermore, radioligand-displacement assays showed that 1 is selective for the serotonergic system and in particular the serotonin (5-HT)1D, 5-HT6, and 5-HT7 receptors, where it binds with affinities in the nanomolar range (117, 170, and 394 nM, respectively). Additionally, 1 was functionally characterized at 5-HT6 and 5-HT7, where it was found to be an agonist at the former (EC50 = 94 nM, Emax = 32%) and an inverse agonist at the latter (EC50 = 291 nM, Emax = -98.6). Finally, we demonstrated that 1 dose-dependently decreases locomotion in mice, inhibits REM sleep, and promotes sleep fragmentation. Thus, we suggest that pellotine itself, and not an active metabolite, is responsible for the hypnotic effects and that these effects are possibly mediated through modulation of serotonergic receptors.

Pharmacology and Therapeutic Potential of Benzothiazole Analogues for Cocaine Use Disorder

Pharmacological targeting of the dopamine D4 receptor (D4R)─expressed in brain regions that control cognition, attention, and decision-making─could be useful for several neuropsychiatric disorders including substance use disorders (SUDs). This study focused on the synthesis and evaluation of a novel series of benzothiazole analogues designed to target D4R. We identified several compounds with high D4R binding affinity (Ki ≤ 6.9 nM) and >91-fold selectivity over other D2-like receptors (D2R, D3R) with diverse partial agonist and antagonist profiles. Novel analogue 16f is a potent low-efficacy D4R partial agonist, metabolically stable in rat and human liver microsomes, and has excellent brain penetration in rats (AUCbrain/plasma > 3). 16f (5-30 mg/kg, i.p.) dose-dependently decreased iv cocaine self-administration in rats, consistent with previous results produced by D4R-selective antagonists. Off-target antagonism of 5-HT2A or 5-HT2B may also contribute to these effects. Results with 16f support further efforts to target D4R in SUD treatment.

A Novel Brain PET Radiotracer for Imaging Alpha Synuclein Fibrils in Multiple System Atrophy

Abnormal α-synuclein (α-syn) aggregation characterizes α-synucleinopathies, including Parkinson's disease (PD) and multiple system atrophy (MSA). However, no suitable positron emission tomography (PET) radiotracer for imaging α-syn in PD and MSA exists currently. Our structure-activity relationship studies identified 4-methoxy-N-(4-(3-(pyridin-2-yl)-3,8-diazabicyclo[3.2.1]octan-8-yl)phenyl)benzamide (4i) as a PET radiotracer candidate for imaging α-syn. In vitro assays revealed high binding of 4i to recombinant α-syn fibrils (inhibition constant (Ki) = 6.1 nM) and low affinity for amyloid beta (Aβ) fibrils in Alzheimer's disease (AD) homogenates. However, [3H]4i also exhibited high specific binding to AD, progressive supranuclear palsy, and corticobasal degeneration tissues as well as PD and MSA tissues, suggesting notable affinity to tau. Nevertheless, the specific binding to pathologic α-syn aggregates in MSA post-mortem brain tissues was significantly higher than in PD tissues. This finding demonstrated the potential use of [11C]4i as a PET tracer for imaging α-syn in MSA patients. Nonhuman primate PET studies confirmed good brain uptake and rapid washout for [11C]4i.

First Potent Macrocyclic A3 Adenosine Receptor Agonists Reveal G-Protein and β-Arrestin2 Signaling Preferences

(N)-Methanocarba adenosine derivatives (A3 adenosine receptor (AR) agonists containing bicyclo[3.1.0]hexane replacing furanose) were chain-extended at N6 and C2 positions with terminal alkenes for ring closure. The resulting macrocycles of 17-20 atoms retained affinity, indicating a spatially proximal orientation of these receptor-bound chains, consistent with molecular modeling of 12. C2-Arylethynyl-linked macrocycle 19 was more A3AR-selective than 2-ether-linked macrocycle 12 (both 5'-methylamides, human (h) A3AR affinities (Ki): 22.1 and 25.8 nM, respectively), with lower mouse A3AR affinities. Functional hA3AR comparison of two sets of open/closed analogues in β-arrestin2 and Gi/o protein assays showed certain signaling preferences divergent from reference agonist Cl-IB-MECA 1. The potencies of 1 at all three Gαi isoforms were slightly less than its hA3AR binding affinity (Ki: 1.4 nM), while the Gαi1 and Gαi2 potencies of macrocycle 12 were roughly an order of magnitude higher than its radioligand binding affinity. Gαi2-coupling was enhanced in macrocycle 12 (EC50 2.56 nM, ∼40% greater maximal efficacy than 1). Di-O-allyl precursor 18 cyclized to form 19, increasing the Gαi1 potency by 7.5-fold. The macrocycles 12 and 19 and their open precursors 11 and 18 potently stimulated β-arrestin2 recruitment, with EC50 values (nM) of 5.17, 4.36, 1.30, and 4.35, respectively, and with nearly 50% greater efficacy compared to 1. This example of macrocyclization altering the coupling pathways of small-molecule (nonpeptide) GPCR agonists is the first for potent and selective macrocyclic AR agonists. These initial macrocyclic derivatives can serve as a guide for the future design of macrocyclic AR agonists displaying unanticipated pharmacology.

Synthesis and inhibitory activity of euparin derivatives as potential dual inhibitors against α-glucosidase and protein tyrosine phosphatase 1B (PTP1B)

Diabetes mellitus is a serious threat to human life and health. The α-glucosidase and protein tyrosine phosphatase 1B (PTP1B) were important targets for the treatment of type 2 diabetes mellitus. In this paper, euparin, a natural product from Eupatorium chinense possessed extensive pharmacological activities, was selected as the lead compound. It was derived into chalcone compounds with high efficiency, and the inhibitory activities of these 30 products on α-glucosidase and PTP1B were tested. The results showed that compounds 12 and 15 had good inhibitory activities against both enzymes. The IC50 value of 12 to inhibit α-glucosidase and PTP1B was 39.77 and 39.31 μM, and the IC50 value of 15 to inhibit α-glucosidase and PTP1B was 9.02 and 3.47 μM, respectively. In addition, molecular docking results showed that compounds 12 and 15 exhibited good binding affinities toward both α -glucosidase and PTP1B with negative binding energies. The results of the present study demonstrate that compounds 12 and 15 might be beneficial in the treatment of type 2 diabetes.

DT-0111: a novel P2X3 receptor antagonist

Extracellular adenosine 5'-triphosphate (ATP) acts as an autocrine and paracrine agent, the actions of which on affected cells are mediated by P2 receptors (P2R), which include trans cell-membrane cationic channels (P2XRs), and G protein coupled receptors (P2YRs). The mammalian P2X receptors form homotrimeric or heterotrimeric cationic channels, each of which contains three ATP-binding sites. There are seven homotrimeric P2X receptors (P2X1-7) and three heteromeric (P2X2/P2X3, P2X4/P2X6, P2X1/P2X5). In the lungs and airways, ATP activates P2X3 and P2X2/3 receptors (P2X3R, P2X2/3R, respectively) localized on vagal sensory nerve terminals resulting in bronchoconstriction, and cough, and probably also localized release of pro-inflammatory neuropeptides via the axon reflex. Currently, several P2X3R and P2X2/3R antagonists are being developed as drug-candidates for the treatment of chronic cough. This report presents the receptor affinity data of a novel water-soluble small molecule, DT-0111, that acts as a selective P2X3R antagonist.

Trace amine-associated receptor 1 (TAAR1) agonists for psychosis: protocol for a living systematic review and meta-analysis of human and non-human studies

BACKGROUND

There is an urgent need to develop more effective and safer antipsychotics beyond dopamine 2 receptor antagonists. An emerging and promising approach is TAAR1 agonism. Therefore, we will conduct a living systematic review and meta-analysis to synthesize and triangulate the evidence from preclinical animal experiments and clinical studies on the efficacy, safety, and underlying mechanism of action of TAAR1 agonism for psychosis.

METHODS

Independent searches will be conducted in multiple electronic databases to identify clinical and animal experimental studies comparing TAAR1 agonists with licensed antipsychotics or other control conditions in individuals with psychosis or animal models for psychosis, respectively. The primary outcomes will be overall psychotic symptoms and their behavioural proxies in animals. Secondary outcomes will include side effects and neurobiological measures. Two independent reviewers will conduct study selection, data extraction using predefined forms, and risk of bias assessment using suitable tools based on the study design. Ontologies will be developed to facilitate study identification and data extraction. Data from clinical and animal studies will be synthesized separately using random-effects meta-analysis if appropriate, or synthesis without meta-analysis. Study characteristics will be investigated as potential sources of heterogeneity. Confidence in the evidence for each outcome and source of evidence will be evaluated, considering the summary of the association, potential concerns regarding internal and external validity, and reporting biases. When multiple sources of evidence are available for an outcome, an overall conclusion will be drawn in a triangulation meeting involving a multidisciplinary team of experts. We plan trimonthly updates of the review, and any modifications in the protocol will be documented. The review will be co-produced by multiple stakeholders aiming to produce impactful and relevant results and bridge the gap between preclinical and clinical research on psychosis.

PROTOCOL REGISTRATION

PROSPERO-ID: CRD42023451628.

Identification of 5-HT2A Receptor Signaling Pathways Responsible for Psychedelic Potential

Serotonergic psychedelics possess considerable therapeutic potential. Although 5-HT2A receptor activation mediates psychedelic effects, prototypical psychedelics activate both 5-HT2A-Gq/11 and β-arrestin2 signaling, making their respective roles unclear. To elucidate this, we developed a series of 5-HT2A-selective ligands with varying Gq efficacies, including β-arrestin-biased ligands. We show that 5-HT2A-Gq but not 5-HT2A-β-arrestin2 efficacy predicts psychedelic potential, assessed using head-twitch response (HTR) magnitude in male mice. We further show that disrupting Gq-PLC signaling attenuates the HTR and a threshold level of Gq activation is required to induce psychedelic-like effects, consistent with the fact that certain 5-HT2A partial agonists (e.g., lisuride) are non-psychedelic. Understanding the role of 5-HT2A-Gq efficacy in psychedelic-like psychopharmacology permits rational development of non-psychedelic 5-HT2A agonists. We also demonstrate that β-arrestin-biased 5-HT2A receptor agonists induce receptor downregulation and tachyphylaxis, and have an anti-psychotic-like behavioral profile. Overall, 5-HT2A receptor signaling can be fine-tuned to generate ligands with properties distinct from classical psychedelics.

Discovery of Novel Oleamide Analogues as Brain-Penetrant Positive Allosteric Serotonin 5-HT2C Receptor and Dual 5-HT2C/5-HT2A Receptor Modulators

The serotonin 5-HT2A receptor (5-HT2AR) and 5-HT2CR localize to the brain and share overlapping signal transduction facets that contribute to their roles in cognition, mood, learning, and memory. Achieving selective targeting of these receptors is challenged by the similarity in their 5-HT orthosteric binding pockets. A fragment-based discovery approach was employed to design and synthesize novel oleamide analogues as selective 5-HT2CR or dual 5-HT2CR/5-HT2AR positive allosteric modulators (PAMs). Compound 13 (JPC0323) exhibited on-target properties, acceptable plasma exposure and brain penetration, as well as negligible displacement to orthosteric sites of ∼50 GPCRs and transporters. Furthermore, compound 13 suppressed novelty-induced locomotor activity in a 5-HT2CR-dependent manner, suggesting 5-HT2CR PAM, but not 5-HT2AR, activity at the level of the whole organism at the employed doses of 13. We discovered new selective 5-HT2CR PAMs and first-in-class 5-HT2CR/5-HT2AR dual PAMs that broaden the pharmacological toolbox to explore the biology of these vital receptors.

Design, Synthesis, and Biological Evaluation of Novel Spiro Imidazobenzodiazepines to Identify Improved Inhaled Bronchodilators

Novel gamma-aminobutyric acid receptor (GABAAR) ligands structurally related to imidazobenzodiazepine MIDD0301 were synthesized using spiro-amino acid N-carboxyanhydrides (NCAs). These compounds demonstrated increased resistance to phase 2 metabolism and avoided the formation of a 6H isomer. Compound design was guided by molecular docking using the available crystal structure of the α1β3γ2 GABAAR and correlated with in vitro binding data. The carboxylic acid containing GABAAR ligands have high aqueous solubility, low permeability, and low cell toxicity. The inability of GABAAR ligands to cross the blood-brain barrier was confirmed in vivo by the absence of sensorimotor inhibition. Pharmacological activities at lung GABAARs were demonstrated by ex vivo relaxation of guinea pig airway smooth muscle and reduction of methacholine-induced airway hyperresponsiveness (AHR) in conscious mice. We identified bronchodilator 5c with an affinity of 9 nM for GABAARs that was metabolically stable in the presence of human and mouse microsomes.

Alicyclic Ring Size Variation of 4-Phenyl-2-naphthoic Acid Derivatives as P2Y14 Receptor Antagonists

P2Y14 receptor (P2Y14R) is activated by extracellular UDP-glucose, a damage-associated molecular pattern that promotes inflammation in the kidney, lung, fat tissue, and elsewhere. Thus, selective P2Y14R antagonists are potentially useful for inflammatory and metabolic diseases. The piperidine ring size of potent, competitive P2Y14R antagonist (4-phenyl-2-naphthoic acid derivative) PPTN 1 was varied from 4- to 8-membered rings, with bridging/functional substitution. Conformationally and sterically modified isosteres included N-containing spirocyclic (6-9), fused (11-13), and bridged (14, 15) or large (16-20) ring systems, either saturated or containing alkene or hydroxy/methoxy groups. The alicyclic amines displayed structural preference. An α-hydroxyl group increased the affinity of 4-(4-((1R,5S,6r)-6-hydroxy-3-azabicyclo[3.1.1]heptan-6-yl)phenyl)-7-(4-(trifluoromethyl)phenyl)-2-naphthoic acid 15 (MRS4833) compared to 14 by 89-fold. 15 but not its double prodrug 50 reduced airway eosinophilia in a protease-mediated asthma model, and orally administered 15 and prodrugs reversed chronic neuropathic pain (mouse CCI model). Thus, we identified novel drug leads having in vivo efficacy.

CYP eicosanoid pathway mediates colon cancer-promoting effects of dietary linoleic acid

Human and animal studies support that consuming a high level of linoleic acid (LA, 18:2ω-6), an essential fatty acid and key component of the human diet, increases the risk of colon cancer. However, results from human studies have been inconsistent, making it challenging to establish dietary recommendations for optimal LA intake. Given the importance of LA in the human diet, it is crucial to better understand the molecular mechanisms underlying its potential colon cancer-promoting effects. Using LC-MS/MS-based targeted lipidomics, we find that the cytochrome P450 (CYP) monooxygenase pathway is a major pathway for LA metabolism in vivo. Furthermore, CYP monooxygenase is required for the colon cancer-promoting effects of LA, since the LA-rich diet fails to exacerbate colon cancer in CYP monooxygenase-deficient mice. Finally, CYP monooxygenase mediates the pro-cancer effects of LA by converting LA to epoxy octadecenoic acids (EpOMEs), which have potent effects on promoting colon tumorigenesis via gut microbiota-dependent mechanisms. Overall, these results support that CYP monooxygenase-mediated conversion of LA to EpOMEs plays a crucial role in the health effects of LA, establishing a unique mechanistic link between dietary fatty acid intake and cancer risk. These results could help in developing more effective dietary guidelines for optimal LA intake and identifying subpopulations that may be especially vulnerable to LA's negative effects.