Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia

Polypharmacology prediction: the long road toward comprehensively anticipating small-molecule selectivity to de-risk drug discovery

INTRODUCTION

Small molecules often bind to multiple targets, a behavior termed polypharmacology. Anticipating polypharmacology is essential for drug discovery since unknown off-targets can modulate safety and efficacy - profoundly affecting drug discovery success. Unfortunately, experimental methods to assess selectivity present significant limitations and drugs still fail in the clinic due to unanticipated off-targets. Computational methods are a cost-effective, complementary approach to predict polypharmacology.

AREAS COVERED

This review aims to provide a comprehensive overview of the state of polypharmacology prediction and discuss its strengths and limitations, covering both classical cheminformatics methods and bioinformatic approaches. The authors review available data sources, paying close attention to their different coverage. The authors then discuss major algorithms grouped by the types of data that they exploit using selected examples.

EXPERT OPINION

Polypharmacology prediction has made impressive progress over the last decades and contributed to identify many off-targets. However, data incompleteness currently limits most approaches to comprehensively predict selectivity. Moreover, our limited agreement on model assessment challenges the identification of the best algorithms - which at present show modest performance in prospective real-world applications. Despite these limitations, the exponential increase of multidisciplinary Big Data and AI hold much potential to better polypharmacology prediction and de-risk drug discovery.

Imaging the Vesicular Acetylcholine Transporter in Schizophrenia: A Positron Emission Tomography Study Using [18F]-VAT

BACKGROUND

Despite longstanding interest in the central cholinergic system in schizophrenia (SCZ), cholinergic imaging studies with patients have been limited to receptors. Here, we conducted a proof-of-concept positron emission tomography study using [18F]-VAT, a new radiotracer that targets the vesicular acetylcholine transporter as a proxy measure of acetylcholine transmission capacity, in patients with SCZ and explored relationships of vesicular acetylcholine transporter with clinical symptoms and cognition.

METHODS

A total of 18 adult patients with SCZ or schizoaffective disorder (the SCZ group) and 14 healthy control participants underwent a positron emission tomography scan with [18F]-VAT. Distribution volume (VT) for [18F]-VAT was derived for each region of interest, and group differences in VT were assessed with 2-sample t tests. Functional significance was explored through correlations between VT and scores on the Positive and Negative Syndrome Scale and a computerized neurocognitive battery (PennCNB).

RESULTS

No group differences in [18F]-VAT VT were observed. However, within the SCZ group, psychosis symptom severity was positively associated with VT in multiple regions of interest, with the strongest effects in the hippocampus, thalamus, midbrain, cerebellum, and cortex. In addition, in the SCZ group, working memory performance was negatively associated with VT in the substantia innominata and several cortical regions of interest including the dorsolateral prefrontal cortex.

CONCLUSIONS

In this initial study, the severity of 2 important features of SCZ-psychosis and working memory deficit-was strongly associated with [18F]-VAT VT in several cortical and subcortical regions. These correlations provide preliminary evidence of cholinergic activity involvement in SCZ and, if replicated in larger samples, could lead to a more complete mechanistic understanding of psychosis and cognitive deficits in SCZ and the development of therapeutic targets.

AlphaFold accelerated discovery of psychotropic agonists targeting the trace amine-associated receptor 1

Artificial intelligence is revolutionizing protein structure prediction, providing unprecedented opportunities for drug design. To assess the potential impact on ligand discovery, we compared virtual screens using protein structures generated by the AlphaFold machine learning method and traditional homology modeling. More than 16 million compounds were docked to models of the trace amine-associated receptor 1 (TAAR1), a G protein-coupled receptor of unknown structure and target for treating neuropsychiatric disorders. Sets of 30 and 32 highly ranked compounds from the AlphaFold and homology model screens, respectively, were experimentally evaluated. Of these, 25 were TAAR1 agonists with potencies ranging from 12 to 0.03 μM. The AlphaFold screen yielded a more than twofold higher hit rate (60%) than the homology model and discovered the most potent agonists. A TAAR1 agonist with a promising selectivity profile and drug-like properties showed physiological and antipsychotic-like effects in wild-type but not in TAAR1 knockout mice. These results demonstrate that AlphaFold structures can accelerate drug discovery.

Advances in yeast synthetic biology for human G protein-coupled receptor biology and pharmacology

G protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors in humans. Over 800 GPCRs regulate the (patho)biology of every organ, tissue, and cell type. Consequently, GPCRs are the most prominent therapeutic targets in medicine. Although over 30% of current U.S. Food and Drug Administration-approved drugs target GPCR signaling, most receptors remain understudied and therapeutically underutilized. Challenges include an incomplete understanding of GPCR signaling, pharmacology, structural biology, and the multiplicity of endogenous GPCR ligands, in addition to a scarcity of biological and pharmacological tools for elucidating GPCR-mediated cellular processes beyond initial signaling events. Various mammalian, insect, and yeast cell models currently address some of these needs. Here, we review recent advances in yeast synthetic biology that are helping to catalyze new and unexpected conceptual and technical breakthroughs in GPCR-based medicine and biotechnology.

Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition

Despite advances in chemical, computational and biological sciences, the rate of attrition of drug candidates in clinical development is still high. A key point in the small-molecule discovery process that could provide opportunities to help address this challenge is the pharmacological characterization of hit and lead compounds, culminating in the selection of a drug candidate. Deeper characterization is increasingly important, because the 'quality' of drug efficacy, at least for G protein-coupled receptors (GPCRs), is now understood to be much more than activation of commonly evaluated pathways such as cAMP signalling, with many more 'efficacies' of ligands that could be harnessed therapeutically. Such characterization is being enabled by novel assays to characterize the complex behaviour of GPCRs, such as biased signalling and allosteric modulation, as well as advances in structural biology, such as cryo-electron microscopy. This article discusses key factors in the assessments of the pharmacology of hit and lead compounds in the context of GPCRs as a target class, highlighting opportunities to identify drug candidates with the potential to address limitations of current therapies and to improve the probability of them succeeding in clinical development.

The effect of second-generation antipsychotics on anxiety/depression in patients with schizophrenia: A systematic review and meta-analysis

OBJECTIVE

Despite the high prevalence of anxiety in schizophrenia, no established guideline exists for the management of these symptoms. We aimed to synthesize evidence on the effect of second-generation antipsychotics (SGAs) on anxiety in patients with schizophrenia.

METHODS

We systematically searched Medline, Embase, PsycInfo, Web of Science, PubMed, and Cochrane library to identify randomized controlled trials of SGAs that reporting anxiety measures in schizophrenia. The search was limited to English-language articles published before February 2024. Data were pooled using a random-effects model.

RESULTS

Among 48 eligible studies, 29 (n = 7712) were included in the meta-analyses comparing SGAs to placebo, haloperidol, or another SGAs for their effect on anxiety/depression. SGAs had a small effect on anxiety/depression versus placebo (SMD = -0.28 (95 % CI [-0.34, -0.21], p < .00001, I2 = 47 %, n = 5576)) associated with efficacy for positive (z = 5.679, p < .001) and negative symptoms (z = 4.490, p < .001). Furthermore, SGAs were superior to haloperidol (SMD = -0.44, 95 % CI [-0.75, -0.13], p = .005, n = 1068) with substantial study-level heterogeneity (I2 = 85 %). Excluding one study of quetiapine in first-episode patients (SMD = -3.05, n = 73), SGAs showed a small effect on anxiety/depression versus haloperidol without heterogeneity (SMD = -0.23, 95 % CI [-0.35, -0.12], p = 01; I2 = %0). Risperidone's effect on anxiety/depression was comparable to olanzapine (SMD = -0.02, 95 % CI [-0.24,0.20], p = .87, I2 = 45 %, n = 753) and amisulpride (SMD = 0.27, 95 % CI [-1.08,0.61], p = .13, I2 = 50 %, n = 315).

CONCLUSION

While SGAs showed a small effect on anxiety/depression, the findings are inconclusive due to scarcity of research on comorbid anxiety in schizophrenia, heterogeneity of anxiety symptoms, and the scales used to measure anxiety. Further studies employing specific anxiety scales are required to explore antipsychotics, considering their receptor affinity and augmentation with serotonin/norepinephrine reuptake inhibitors or benzodiazepines for managing anxiety in schizophrenia.

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.

Molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania based on network pharmacology and molecular docking: Evidence from computational biology

BACKGROUND

Quetiapine monotherapy is recommended as the first-line option for acute mania and acute bipolar depression. However, the mechanism of action of quetiapine is unclear. Network pharmacology and molecular docking were employed to determine the molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania.

METHODS

Putative target genes for quetiapine were collected from the GeneCard, SwissTargetPrediction, and DrugBank databases. Targets for bipolar depression and bipolar mania were identified from the DisGeNET and GeneCards databases. A protein-protein interaction (PPI) network was generated using the String database and imported into Cytoscape. DAVID and the Bioinformatics platform were employed to perform the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the top 15 core targets. The drug-pathway-target-disease network was constructed using Cytoscape. Finally, molecular docking was performed to evaluate the interactions between quetiapine and potential targets.

RESULTS

Targets for quetiapine actions against bipolar depression (126 targets) and bipolar mania (81 targets) were identified. Based on PPI and KEGG pathway analyses, quetiapine may affect bipolar depression by targeting the MAPK and PI3K/AKT insulin signaling pathways via BDNF, INS, EGFR, IGF1, and NGF, and it may affect bipolar mania by targeting the neuroactive ligand-receptor interaction signaling pathway via HTR1A, HTR1B, HTR2A, DRD2, and GRIN2B. Molecular docking revealed good binding affinity between quetiapine and potential targets.

LIMITATIONS

Pharmacological experiments should be conducted to verify and further explore these results.

CONCLUSIONS

Our findings suggest that quetiapine affects bipolar depression and bipolar mania through distinct biological core targets, and thus through different mechanisms. Furthermore, our results provide a theoretical basis for the clinical use of quetiapine and possible directions for new drug development.

Systematic Structure-Activity Relationship Study of Nalfurafine Analogues toward Development of Potentially Nonaddictive Pain Management Treatments

Despite the availability of numerous pain medications, the current array of Food and Drug Administration-approved options falls short in adequately addressing pain states for numerous patients and consequently worsens the opioid crisis. Thus, it is imperative for basic research to develop novel and nonaddictive pain medications. Toward addressing this clinical goal, nalfurafine (NLF) was chosen as a lead and its structure-activity relationship (SAR) systematically studied through design, syntheses, and in vivo characterization of 24 analogues. Two analogues, 21 and 23, showed longer durations of action than NLF in a warm-water tail immersion assay, produced in vivo effects primarily mediated by KOR and DOR, penetrated the blood-brain barrier, and did not function as reinforcers. Additionally, 21 produced fewer sedative effects than NLF. Taken together, these results aid the understanding of NLF SAR and provide insights for future endeavors in developing novel nonaddictive therapeutics to treat pain.

A brief history of clozapine use in Taiwan

Blood concentrations of clozapine in Taiwanese patients appeared approximately 30-50 % higher than that from Caucasian patients, and women possessed a higher blood levels. Fluvoxamine was reported to increase the clozapine levels, reduce clozapine-related weight gain and metabolic disturbances, and improved general psychopathology. Clothiapine, a chemical structure analogue of clozapine, showed potential of benefitting patients who are unsuitable for clozapine treatment in Taiwan. Obsessive/compulsive symptom (OCS) is a common side effect of clozapine. Concentrations of clozapine were remarkably higher in patients with OCS than in those without. In conclusion, clozapine is a widely used in patients with schizophrenia in Taiwan.

Chemogenetic Signaling in Space and Time: Considerations for Designing Neuroscience Experiments Using DREADDs

The use of designer receptors exclusively activated by designer drugs (DREADDs) has led to significant advances in our understanding of the neural circuits that govern behavior. By allowing selective control over cellular activity and signaling, DREADDs have become an integral tool for defining the pathways and cellular phenotypes that regulate sleep, pain, motor activity, goal-directed behaviors, and a variety of other processes. In this review, we provide a brief overview of DREADDs and discuss notable discoveries in the neurosciences with an emphasis on circuit mechanisms. We then highlight methodological approaches to achieve pathway specific activation of DREADDs. Finally, we discuss spatial and temporal constraints of DREADDs signaling and how these features can be incorporated into experimental designs to precisely dissect circuits of interest.

Advances in drug design and therapeutic potential of selective or multitarget 5-HT1A receptor ligands

5-HT1A receptor (5-HT1A-R) is a serotoninergic G-protein coupled receptor subtype which contributes to several physiological processes in both central nervous system and periphery. Despite being the first 5-HT-R identified, cloned and studied, it still represents a very attractive target in drug discovery and continues to be the focus of a myriad of drug discovery campaigns due to its involvement in numerous neuropsychiatric disorders. The structure-activity relationship studies (SAR) performed over the last years have been devoted to three main goals: (i) design and synthesis of 5-HT1A-R selective/preferential ligands; (ii) identification of 5-HT1A-R biased agonists, differentiating pre- versus post-synaptic agonism and signaling cellular mechanisms; (iii) development of multitarget compounds endowed with well-defined poly-pharmacological profiles targeting 5-HT1A-R along with other serotonin receptors, serotonin transporter (SERT), D2-like receptors and/or enzymes, such as acetylcholinesterase and phosphodiesterase, as a promising strategy for the management of complex psychiatric and neurodegenerative disorders. In this review, medicinal chemistry aspects of ligands acting as selective/preferential or multitarget 5-HT1A-R agonists and antagonists belonging to different chemotypes and developed in the last 7 years (2017-2023) have been discussed. The development of chemical and pharmacological 5-HT1A-R tools for molecular imaging have also been described. Finally, the pharmacological interest of 5-HT1A-R and the therapeutic potential of ligands targeting this receptor have been considered.

M1/M4 receptors as potential therapeutic treatments for schizophrenia: A comprehensive study

Muscarinic acetylcholine receptors (mAChRs) play a significant role in the pathophysiology of schizophrenia. Although activating mAChRs holds potential in addressing the full range of schizophrenia symptoms, clinical application of many non-selective mAChR agonists in cognitive deficits, positive and negative symptoms is hindered by peripheral side effects (gastrointestinal disturbances and cardiovascular effects) and dosage restrictions. Ligands binding to the allosteric sites of mAChRs, particularly the M1 and M4 subtypes, demonstrate activity in improving cognitive function and amelioration of positive and negative symptoms associated with schizophrenia, enhancing our understanding of schizophrenia. The article aims to critically examine current design concepts and clinical advancements in synthesizing and designing small molecules targeting M1/M4, providing theoretical insights and empirical support for future research in this field.

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.

Integrative Pharmacology in the Treatment of Substance Use Disorders

The detrimental physical, mental, and socioeconomic effects of substance use disorders (SUDs) have been apparent to the medical community for decades. However, it has become increasingly urgent in recent years to develop novel pharmacotherapies to treat SUDs. Currently, practitioners typically rely on monotherapy. Monotherapy has been shown to be superior to no treatment at all for most substance classes. However, many randomized controlled trials (RCTs) have revealed that monotherapy leads to poorer outcomes when compared with combination treatment in all specialties of medicine. The results of RCTs suggest that monotherapy frequently fails since multiple dysregulated pathways, enzymes, neurotransmitters, and receptors are involved in the pathophysiology of SUDs. As such, research is urgently needed to determine how various neurobiological mechanisms can be targeted by novel combination treatments to create increasingly specific yet exceedingly comprehensive approaches to SUD treatment. This article aims to review the neurobiology that integrates many pathophysiologic mechanisms and discuss integrative pharmacology developments that may ultimately improve clinical outcomes for patients with SUDs. Many neurobiological mechanisms are known to be involved in SUDs including dopaminergic, nicotinic, N-methyl-D-aspartate (NMDA), and kynurenic acid (KYNA) mechanisms. Emerging evidence indicates that KYNA, a tryptophan metabolite, modulates all these major pathophysiologic mechanisms. Therefore, achieving KYNA homeostasis by harmonizing integrative pathophysiology and pharmacology could prove to be a better therapeutic approach for SUDs. We propose KYNA-NMDA-α7nAChRcentric pathophysiology, the "conductor of the orchestra," as a novel approach to treat many SUDs concurrently. KYNA-NMDA-α7nAChR pathophysiology may be the "command center" of neuropsychiatry. To date, extant RCTs have shown equivocal findings across comparison conditions, possibly because investigators targeted single pathophysiologic mechanisms, hit wrong targets in underlying pathophysiologic mechanisms, and tested inadequate monotherapy treatment. We provide examples of potential combination treatments that simultaneously target multiple pathophysiologic mechanisms in addition to KYNA. Kynurenine pathway metabolism demonstrates the greatest potential as a target for neuropsychiatric diseases. The investigational medications with the most evidence include memantine, galantamine, and N-acetylcysteine. Future RCTs are warranted with novel combination treatments for SUDs. Multicenter RCTs with integrative pharmacology offer a promising, potentially fruitful avenue to develop novel therapeutics for the treatment of SUDs.

Structure-Based Design of Novel G-Protein-Coupled Receptor TAAR1 Agonists as Potential Antipsychotic Drug Candidates

The existing available antipsychotics have failed to manage the cognitive impairment of schizophrenia and induced a number of seriously undesirable effects. Trace amine-associated receptor 1 (TAAR1) has emerged as an ideal target for the design of antischizophrenia drugs, with the ability to mediate multiple psychological functions by sensing endogenous amine-containing metabolites without the side effects of catalepsy. In this work, a series of novel TAAR1 agonists were designed based on the structural analysis of the TAAR1 activation pocket. Among them, 6e displayed a potent TAAR1-Gs/Gq dual-pathway activation property, being different from that of the clinical drug candidate SEP-363856 with only TAAR1-Gs pathway activation. In rodent models, 6e significantly alleviated MK-801-induced schizophrenia-like cognitive phenotypes without inducing catalepsy. Furthermore, 6e·HCl exhibited favorable pharmacokinetic (T1/2 = 2.31 h, F = 39%) and safety properties. All these demonstrated that 6e·HCl may be used as a novel drug candidate for schizophrenia treatment.

Orphan G protein-coupled receptors: the ongoing search for a home

G protein-coupled receptors (GPCRs) make up the largest receptor superfamily, accounting for 4% of protein-coding genes. Despite the prevalence of such transmembrane receptors, a significant number remain orphans, lacking identified endogenous ligands. Since their conception, the reverse pharmacology approach has been used to characterize such receptors. However, the multifaceted and nuanced nature of GPCR signaling poses a great challenge to their pharmacological elucidation. Considering their therapeutic relevance, the search for native orphan GPCR ligands continues. Despite limited structural input in terms of 3D crystallized structures, with advances in machine-learning approaches, there has been great progress with respect to accurate ligand prediction. Though such an approach proves valuable given that ligand scarcity is the greatest hurdle to orphan GPCR deorphanization, the future pairings of the remaining orphan GPCRs may not necessarily take a one-size-fits-all approach but should be more comprehensive in accounting for numerous nuanced possibilities to cover the full spectrum of GPCR signaling.

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.

Properties of FDA-approved small molecule protein kinase inhibitors: A 2024 update

Owing to the dysregulation of protein kinase activity in many diseases including cancer, this enzyme family has become one of the most important drug targets in the 21st century. There are 80 FDA-approved therapeutic agents that target about two dozen different protein kinases and seven of these drugs were approved in 2023. Of the approved drugs, thirteen target protein-serine/threonine protein kinases, four are directed against dual specificity protein kinases (MEK1/2), twenty block nonreceptor protein-tyrosine kinases, and 43 inhibit receptor protein-tyrosine kinases. The data indicate that 69 of these drugs are prescribed for the treatment of neoplasms. Six drugs (abrocitinib, baricitinib, deucravacitinib, ritlecitinib, tofacitinib, upadacitinib) are used for the treatment of inflammatory diseases (atopic dermatitis, rheumatoid arthritis, psoriasis, alopecia areata, and ulcerative colitis). Of the 80 approved drugs, nearly two dozen are used in the treatment of multiple diseases. The following seven drugs received FDA approval in 2023: capivasertib (HER2-positive breast cancer), fruquintinib (metastatic colorectal cancer), momelotinib (myelofibrosis), pirtobrutinib (mantle cell lymphoma, chronic lymphocytic leukemia, small lymphocytic lymphoma), quizartinib (Flt3-mutant acute myelogenous leukemia), repotrectinib (ROS1-positive lung cancer), and ritlecitinib (alopecia areata). All of the FDA-approved drugs are orally effective with the exception of netarsudil, temsirolimus, and trilaciclib. This review summarizes the physicochemical properties of all 80 FDA-approved small molecule protein kinase inhibitors including the molecular weight, number of hydrogen bond donors/acceptors, polar surface area, potency, solubility, lipophilic efficiency, and ligand efficiency.

Psychedelic-like Activity of Norpsilocin Analogues

Primary metabolites of mushroom tryptamines, psilocybin and baeocystin (i.e., psilocin and norpsilocin), exhibit potent agonist activity at the serotonin 2A receptor (5-HT2A) in vitro but differ in their 5-HT2A-mediated effects in vivo. In particular, psilocin produces centrally mediated psychedelic effects in vivo, whereas norpsilocin, differing only by the loss of an N-methyl group, is devoid of psychedelic-like effects. These observations suggest that the secondary methylamine group in norpsilocin impacts its central nervous system (CNS) bioavailability but not its receptor pharmacodynamics. To test this hypothesis, eight norpsilocin derivatives were synthesized with varied secondary alkyl-, allyl-, and benzylamine groups, primarily aiming to increase their lipophilicity and brain permeability. Structure-activity relationships for the norpsilocin analogues were evaluated using the mouse head-twitch response (HTR) as a proxy for CNS-mediated psychedelic-like effects. HTR studies revealed that extending the N-methyl group of norpsilocin by a single methyl group, to give the corresponding secondary N-ethyl analogue (4-HO-NET), was sufficient to produce psilocin-like activity (median effective dose or ED50 = 1.4 mg/kg). Notably, N-allyl, N-propyl, N-isopropyl, and N-benzyl derivatives also induced psilocin-like HTR activity (ED50 = 1.1-3.2 mg/kg), with variable maximum effects (26-77 total HTR events). By contrast, adding bulkier tert-butyl or cyclohexyl groups in the same position did not elicit psilocin-like HTRs. Pharmacological assessments of the tryptamine series in vitro demonstrated interactions with multiple serotonin receptor subtypes, including 5-HT2A, and other CNS signaling proteins (e.g., sigma receptors). Overall, our data highlight key structural requirements for CNS-mediated psychedelic-like effects of norpsilocin analogues.

Network-Based Methods and Their Applications in Drug Discovery

Drug discovery is time-consuming, expensive, and predominantly follows the "one drug → one target → one disease" paradigm. With the rapid development of systems biology and network pharmacology, a novel drug discovery paradigm, "multidrug → multitarget → multidisease", has emerged. This new holistic paradigm of drug discovery aligns well with the essence of networks, leading to the emergence of network-based methods in the field of drug discovery. In this Perspective, we initially introduce the concept and data sources of networks and highlight classical methodologies employed in network-based methods. Subsequently, we focus on the practical applications of network-based methods across various areas of drug discovery, such as target prediction, virtual screening, prediction of drug therapeutic effects or adverse drug events, and elucidation of molecular mechanisms. In addition, we provide representative web servers for researchers to use network-based methods in specific applications. Finally, we discuss several challenges of network-based methods and the directions for future development. In a word, network-based methods could serve as powerful tools to accelerate drug discovery.

Molecular basis of human trace amine-associated receptor 1 activation

The human trace amine-associated receptor 1 (hTAAR1, hTA1) is a key regulator of monoaminergic neurotransmission and the actions of psychostimulants. Despite preclinical research demonstrating its tractability as a drug target, its molecular mechanisms of activation remain unclear. Moreover, poorly understood pharmacological differences between rodent and human TA1 complicate the translation of findings from preclinical disease models into novel pharmacotherapies. To elucidate hTA1's mechanisms on the molecular scale and investigate the underpinnings of its divergent pharmacology from rodent orthologs, we herein report the structure of the human TA1 receptor in complex with a Gαs heterotrimer. Our structure reveals shared structural elements with other TAARs, as well as with its closest monoaminergic orthologue, the serotonin receptor 5-HT4R. We further find that a single mutation dramatically shifts the selectivity of hTA1 towards that of its rodent orthologues, and report on the effects of substituting residues to those found in serotonin and dopamine receptors. Strikingly, we also discover that the atypical antipsychotic medication and pan-monoaminergic antagonist asenapine potently and efficaciously activates hTA1. Together our studies provide detailed insight into hTA1 structure and function, contrast its molecular pharmacology with that of related receptors, and uncover off-target activities of monoaminergic drugs at hTA1.

mtADENet: A novel interpretable method integrating multiple types of network-based inference approaches for prediction of adverse drug events

Identification of adverse drug events (ADEs) is crucial to reduce human health risks and accelerate drug safety assessment. ADEs are mainly caused by unintended interactions with primary or additional targets (off-targets). In this study, we proposed a novel interpretable method named mtADENet, which integrates multiple types of network-based inference approaches for ADE prediction. Different from phenotype-based methods, mtADENet introduced computational target profiles predicted by network-based methods to bridge the gap between chemical structures and ADEs, and hence can not only predict ADEs for drugs and novel compounds within or outside the drug-ADE association network, but also provide insights for the elucidation of molecular mechanisms of the ADEs caused by drugs. We constructed a series of network-based prediction models for 23 ADE categories. These models achieved high AUC values ranging from 0.865 to 0.942 in 10-fold cross validation. The best model further showed high performance on four external validation sets, which outperformed two previous network-based methods. To show the practical value of mtADENet, we performed case studies on developmental neurotoxicity and cardio-oncology, and over 50 % of predicted ADEs and targets for drugs and novel compounds were validated by literature. Moreover, mtADENet is freely available at our web server named NetInfer (http://lmmd.ecust.edu.cn/netinfer/). In summary, mtADENet would be a powerful tool for ADE prediction and drug safety assessment in drug discovery and development.

Neurosteroids: mechanistic considerations and clinical prospects

Like other classes of treatments described in this issue's section, neuroactive steroids have been studied for decades but have risen as a new class of rapid-acting, durable antidepressants with a distinct mechanism of action from previous antidepressant treatments and from other compounds covered in this issue. Neuroactive steroids are natural derivatives of progesterone but are proving effective as exogenous treatments. The best understood mechanism is that of positive allosteric modulation of GABAA receptors, where subunit selectivity may promote their profile of action. Mechanistically, there is some reason to think that neuroactive steroids may separate themselves from liabilities of other GABA modulators, although research is ongoing. It is also possible that intracellular targets, including inflammatory pathways, may be relevant to beneficial actions. Strengths and opportunities for further development include exploiting non-GABAergic targets, structural analogs, enzymatic production of natural steroids, precursor loading, and novel formulations. The molecular mechanisms of behavioral effects are not fully understood, but study of brain network states involved in emotional processing demonstrate a robust influence on affective states not evident with at least some other GABAergic drugs including benzodiazepines. Ongoing studies with neuroactive steroids will further elucidate the brain and behavioral effects of these compounds as well as likely underpinnings of disease.

Cost in the United States of FDA-approved small molecule protein kinase inhibitors used in the treatment of neoplastic and non-neoplastic diseases

Because genetic alterations including mutations, overexpression, translocations, and dysregulation of protein kinases are involved in the pathogenesis of many illnesses, this enzyme family is the target of many drug discovery programs worldwide. The FDA has approved 80 small molecule protein kinase inhibitors with 77 drugs orally bioavailable. The data indicate that 69 of these medicinals are approved for the management of neoplasms including solid tumors such as breast and lung cancer as well as non-solid tumors such as leukemia. Moreover, the remaining 11 drugs target non-neoplastic diseases including psoriasis, rheumatoid arthritis, and ulcerative colitis. The cost of drugs was obtained from www.pharmacychecker.com using the FDA label to determine the dosage and number of tablets required per day. This methodology excludes any private or governmental insurance coverage, which would cover the entire cost or more likely a fraction of the stated price. The average monthly cost for the treatment of neoplastic diseases was $17,900 with a price of $44,000 for futibatinib (used to treat cholangiocarcinomas with FGFR2 fusions) and minimum of $5100 for binimetinib (melanoma). The average monthly cost for the treatment of non-neoplastic diseases was $6800 with a maximum of $17,000 for belumosudil (graft vs. host disease) and a minimum of $200 for netarsudil eye drops (glaucoma). There is a negative correlation of the cost of the drugs and the incidence of the targeted disease. Many of these agents are or were designated as orphan drugs meaning that there are fewer than 200,000 potential patients in the United States.

Study of Drug Targets Associated With Oncogenesis and Cancer Cell Survival and the Therapeutic Activity of Engineered Ashwagandha Extract Having Differential Withanolide Constitutions

Ashwagandha (Withania somnifera) has gained worldwide popularity for a multitude of health benefits inclusive of cancer-preventive and curative effects. Despite numerous research data supporting the benefits of this wonder herb, the actual use of ashwagandha for cancer treatment in clinics is limited. The primary reason for this is the inconsistent therapeutic outcome due to highly variable composition and constitution of active ingredients in the plant extract impacting ashwagandha's pharmacology. We investigate here an engineered yield: an ashwagandha extract (Oncowithanib) that has a unique and fixed portion of active ingredients to achieve consistent and effective therapeutic activity. Using the MCF7 cell line, Oncowithanib was studied for its anti-neoplastic efficacy and drug targets associated with cell cycle regulation, translation machinery, and cell survival and apoptosis. Results demonstrate a dose-dependent decline in Oncowithanib-treated MCF7 cell viability and reduced colony-forming ability. Treated cells showed increased cell death as evidenced by enhancement of Caspase 3 enzyme activity and decreased expressions of cell proliferation markers such as Ki67 and Aurora Kinase A. Oncowithanib treatment was also found to be associated with expressional suppression of key cellular kinases such as RSK1, Akt1, and mTOR in MCF7 cells. Our findings indicate that Oncowithanib decreases MCF7 cell survival and propagation, and sheds light on common drug targets that might be good candidates for the development of cancer therapeutics. Further in-depth investigations are required to fully explore the potency and pharmacology of this novel extract. This study also highlights the importance of the standardization of herbal extracts to get consistent therapeutic activity for the disease indication.

Latrophilin, an adhesion GPCR with galactose-binding lectin domain involved in the innate immune response of Tribolium castaneum

Latrophilin is a member of adhesion GPCRs involved in various physiological pro1cesses. The extracellular fragment of Tribolium castaneum Latrophilin (TcLph) contains a galactose-binding lectin (GBL) domain. However, the biological function of GBL domain remains mysterious. Here, we initially studied the role of TcLph in recognizing pathogens through its GBL domain and then triggering immune defense in invertebrates. Results showed that GBL domain was highly conserved, and its predicted 3D structure was similar to rhamnose-binding lectin domain of mouse Latrophilin-1 with a unique α/β fold and two long loops. Molecular docking and ELISA results revealed the GBL domain can bind to D-galactose, L-rhamnose, lipopolysaccharide and peptidoglycan. The recombinant extracellular segment of TcLph and the recombinant GBL exhibited strong agglutinating and binding activities to all tested bacteria in a Ca2+-dependent manner. Moreover, TcLph was markedly induced after infection by Escherichia coli or Staphylococcus aureus, while its silencing exacerbated bacterial loads and larvae mortality. TcLph-deficient larvae significantly decreased the transcription levels of antimicrobial peptides and prophenoloxidase activating system-related genes, leading to a significant reduction in phenoloxidase activity. It indicated that TcLph functioned as a pattern recognition receptor in pathogen recognition and activated immune responses to eliminate invasive microbes, suggesting a potential target for insecticides.

The G protein biased serotonin 5-HT2A receptor agonist lisuride exerts anti-depressant drug-like activities in mice

There is now evidence from multiple Phase II clinical trials that psychedelic drugs can exert long-lasting anxiolytic, anti-depressant, and anti-drug abuse (nicotine and ethanol) effects in patients. Despite these benefits, the hallucinogenic actions of these drugs at the serotonin 2A receptor (5-HT2AR) limit their clinical use in diverse settings. Activation of the 5-HT2AR can stimulate both G protein and β-arrestin (βArr) -mediated signaling. Lisuride is a G protein biased agonist at the 5-HT2AR and, unlike the structurally-related lysergic acid diethylamide (LSD), the drug does not typically produce hallucinations in normal subjects at routine doses. Here, we examined behavioral responses to lisuride, in wild-type (WT), βArr1-knockout (KO), and βArr2-KO mice. In the open field, lisuride reduced locomotor and rearing activities, but produced a U-shaped function for stereotypies in both βArr lines of mice. Locomotion was decreased overall in βArr1-KOs and βArr2-KOs relative to wild-type controls. Incidences of head twitches and retrograde walking to lisuride were low in all genotypes. Grooming was decreased in βArr1 mice, but was increased then decreased in βArr2 animals with lisuride. Serotonin syndrome-associated responses were present at all lisuride doses in WTs, but they were reduced especially in βArr2-KO mice. Prepulse inhibition (PPI) was unaffected in βArr2 mice, whereas 0.5 mg/kg lisuride disrupted PPI in βArr1 animals. The 5-HT2AR antagonist MDL100907 failed to restore PPI in βArr1 mice, whereas the dopamine D2/D3 antagonist raclopride normalized PPI in WTs but not in βArr1-KOs. Clozapine, SCH23390, and GR127935 restored PPI in both βArr1 genotypes. Using vesicular monoamine transporter 2 mice, lisuride reduced immobility times in tail suspension and promoted a preference for sucrose that lasted up to 2 days. Together, it appears βArr1 and βArr2 play minor roles in lisuride's actions on many behaviors, while this drug exerts anti-depressant drug-like responses without hallucinogenic-like activities.

NU-1223, a simplified analog of alstonine, with 5-HT2cR agonist-like activity, rescues memory deficit and positive and negative symptoms in subchronic phencyclidine mouse model of schizophrenia

The serotonin (5-HT)2 C receptor(R) is a widely distributed G-protein-coupled receptor, expressed abundantly in the central nervous system. Alstonine is a natural product that has significant properties of atypical antipsychotic drugs (AAPDs), in part attributed to 5-HT2 CR agonism. Based on alstonine, we developed NU-1223, a simplified β carboline analog of alstonine, which shows efficacies comparable to alstonine and to other 5-HT2 CR agonists, Ro-60-0175 and lorcaserin. The 5-HT2 CR antagonism of some APDs, including olanzapine, contributes to weight gain, a major side effect which limits its tolerability, while the 5-HT2 CR agonists and/or modulators, may minimize weight gain. We used the well-established rodent subchronic phencyclidine (PCP) model to test the efficacy of NU-1223 on episodic memory, using novel object recognition (NOR) task, positive (locomotor activity), and negative symptoms (social interaction) of schizophrenia (SCH). We found that NU-1223 produced both transient and prolonged rescue of the subchronic PCP-induced deficits in NOR and SI. Further, NU-1223, but not Ro-60-0175, blocked PCP and amphetamine (AMPH)-induced increase in LMA in subchronic PCP mice. These transient efficacies in LMA were blocked by the 5-HT2 CR antagonist, SB242084. Sub-chronic NU-1223 treatment rescued NOR and SI deficits in subchronic PCP mice for at least 39 days after 3 days injection. Chronic treatment with NU-1223, ip, twice a day for 21 days, did not increase average body weight vs olanzapine. These findings clearly indicate NU-1223 as a class of small molecules with a possible 5-HT2 CR-agonist-like mechanism of action, attributing to its efficacy. Additional in-depth receptor mechanistic studies are warranted, as this small molecule, both transiently and chronically rescued PCP-induced deficits. Furthermore, NU-1223 did not induce weight gain post long-term administrations vs AAPDs such as olanzapine, making NU-1223 a putative therapeutic compound for SCH.

R software for QSAR analysis in phytopharmacological studies

INTRODUCTION

In recent decades, quantitative structure-activity relationship (QSAR) analysis has become an important method for drug design and natural product research. With the availability of bioinformatic and cheminformatic tools, a vast number of descriptors have been generated, making it challenging to select potential independent variables that are accurately related to the dependent response variable.

OBJECTIVE

The objective of this study is to demonstrate various descriptor selection procedures, such as the Boruta approach, all subsets regression, the ANOVA approach, the AIC method, stepwise regression, and genetic algorithm, that can be used in QSAR studies. Additionally, we performed regression diagnostics using R software to test parameters such as normality, linearity, residual histograms, PP plots, multicollinearity, and homoscedasticity.

RESULTS

The workflow designed in this study highlights the different descriptor selection procedures and regression diagnostics that can be used in QSAR studies. The results showed that the Boruta approach and genetic algorithm performed better than other methods in selecting potential independent variables. The regression diagnostics parameters tested using R software, such as normality, linearity, residual histograms, PP plots, multicollinearity, and homoscedasticity, helped in identifying and diagnosing model errors, ensuring the reliability of the QSAR model.

CONCLUSION

QSAR analysis is vital in drug design and natural product research. To develop a reliable QSAR model, it is essential to choose suitable descriptors and perform regression diagnostics. This study offers an accessible, customizable approach for researchers to select appropriate descriptors and diagnose errors in QSAR studies.

Structural studies of serotonin receptor family

Serotonin receptors, also known as 5-HT receptors, belong to the G protein-coupled receptors (GPCRs) superfamily. They mediate the effects of serotonin, a neurotransmitter that plays a key role in a wide range of functions including mood regulation, cognition and appetite. The functions of serotonin are mediated by a family of 5-HT receptors including 12 GPCRs belonging to six major families: 5-HT1, 5-HT2, 5-HT4, 5-HT5, 5-HT6 and 5-HT7. Despite their distinct characteristics and functions, these receptors' subtypes share common structural features and signaling mechanisms. Understanding the structure, functions and pharmacology of the serotonin receptor family is essential for unraveling the complexities of serotonin signaling and developing targeted therapeutics for neuropsychiatric disorders. However, developing drugs that selectively target specific receptor subtypes is challenging due to the structural similarities in their orthosteric binding sites. This review focuses on the recent advancements in the structural studies of 5-HT receptors, highlighting the key structural features of each subtype and shedding light on their potential as targets for mental health and neurological disorders (such as depression, anxiety, schizophrenia, and migraine) drugs. [BMB Reports 2023; 56(10): 527-536].

A suite of engineered mice for interrogating psychedelic drug actions

Psychedelic drugs like lysergic acid diethylamide (LSD) and psilocybin have emerged as potentially transformative therapeutics for many neuropsychiatric diseases, including depression, anxiety, post-traumatic stress disorder, migraine, and cluster headaches. LSD and psilocybin exert their psychedelic effects via activation of the 5-hydroxytryptamine 2A receptor (HTR2A). Here we provide a suite of engineered mice useful for clarifying the role of HTR2A and HTR2A-expressing neurons in psychedelic drug actions. We first generated Htr2a-EGFP-CT-IRES-CreERT2 mice (CT:C-terminus) to independently identify both HTR2A-EGFP-CT receptors and HTR2A-containing cells thereby providing a detailed anatomical map of HTR2A and identifying cell types that express HTR2A. We also generated a humanized Htr2a mouse line and an additional constitutive Htr2A-Cre mouse line. Psychedelics induced a variety of known behavioral changes in our mice validating their utility for behavioral studies. Finally, electrophysiology studies revealed that extracellular 5-HT elicited a HTR2A-mediated robust increase in firing of genetically-identified pyramidal neurons--consistent with a plasma membrane localization and mode of action. These mouse lines represent invaluable tools for elucidating the molecular, cellular, pharmacological, physiological, behavioral, and other actions of psychedelic drugs in vivo.

Molecular Basis of Human Trace Amine-Associated Receptor 1 Activation

The human trace amine-associated receptor 1 (hTAAR1, hTA1) is a key regulator of monoaminergic neurotransmission and the actions of psychostimulants. Despite preclinical research demonstrating its tractability as a drug target, its molecular mechanisms of activation remain unclear. Moreover, poorly understood pharmacological differences between rodent and human TA1 complicate the translation of findings from preclinical disease models into novel pharmacotherapies. To elucidate hTA1's mechanisms on the molecular scale and investigate the underpinnings of its divergent pharmacology from rodent orthologs, we herein report the structure of the human TA1 receptor in complex with a Gαs heterotrimer. Our structure reveals shared structural elements with other TAARs, as well as with its closest monoaminergic ortholog, the serotonin receptor 5-HT4R. We further find that a single mutation dramatically shifts the selectivity of hTA1 towards that of its rodent orthologs, and report on the effects of substituting residues to those found in serotonin and dopamine receptors. Strikingly, we also discover that the atypical antipsychotic medication and pan-monoaminergic antagonist asenapine potently and efficaciously activates hTA1. Together our studies provide detailed insight into hTA1 structure and function, contrast its molecular pharmacology with that of related receptors, and uncover off-target activities of monoaminergic drugs at hTA1.

Developing kinase inhibitors for malaria: an opportunity or liability?

Highly druggable and essential to almost all aspects of cellular life, the protein and phosphoinositide kinase gene families offer a wealth of potential targets for pharmacological modulation for both noncommunicable and infectious diseases. Despite the success of kinase inhibitors in oncology and other disease indications, targeting kinases comes with significant challenges. Key hurdles for kinase drug discovery include selectivity and acquired resistance. The phosphatidylinositol 4-kinase beta inhibitor MMV390048 showed good efficacy in Phase 2a clinical trials, demonstrating the potential of kinase inhibitors for malaria treatment. Here we argue that the potential benefits of Plasmodium kinase inhibitors outweigh the risks, and we highlight the opportunity for designed polypharmacology to reduce the risk of resistance.

Antipsychotic drug efficacy correlates with the modulation of D1 rather than D2 receptor-expressing striatal projection neurons

Elevated dopamine transmission in psychosis is assumed to unbalance striatal output through D1- and D2-receptor-expressing spiny-projection neurons (SPNs). Antipsychotic drugs are thought to re-balance this output by blocking D2 receptors (D2Rs). In this study, we found that amphetamine-driven dopamine release unbalanced D1-SPN and D2-SPN Ca2+ activity in mice, but that antipsychotic efficacy was associated with the reversal of abnormal D1-SPN, rather than D2-SPN, dynamics, even for drugs that are D2R selective or lacking any dopamine receptor affinity. By contrast, a clinically ineffective drug normalized D2-SPN dynamics but exacerbated D1-SPN dynamics under hyperdopaminergic conditions. Consistent with antipsychotic effect, selective D1-SPN inhibition attenuated amphetamine-driven changes in locomotion, sensorimotor gating and hallucination-like perception. Notably, antipsychotic efficacy correlated with the selective inhibition of D1-SPNs only under hyperdopaminergic conditions-a dopamine-state-dependence exhibited by D1R partial agonism but not non-antipsychotic D1R antagonists. Our findings provide new insights into antipsychotic drug mechanism and reveal an important role for D1-SPN modulation.

CovET: A covariation-evolutionary trace method that identifies protein structure-function modules

Measuring the relative effect that any two sequence positions have on each other may improve protein design or help better interpret coding variants. Current approaches use statistics and machine learning but rarely consider phylogenetic divergences which, as shown by Evolutionary Trace studies, provide insight into the functional impact of sequence perturbations. Here, we reframe covariation analyses in the Evolutionary Trace framework to measure the relative tolerance to perturbation of each residue pair during evolution. This approach (CovET) systematically accounts for phylogenetic divergences: at each divergence event, we penalize covariation patterns that belie evolutionary coupling. We find that while CovET approximates the performance of existing methods to predict individual structural contacts, it performs significantly better at finding structural clusters of coupled residues and ligand binding sites. For example, CovET found more functionally critical residues when we examined the RNA recognition motif and WW domains. It correlates better with large-scale epistasis screen data. In the dopamine D2 receptor, top CovET residue pairs recovered accurately the allosteric activation pathway characterized for Class A G protein-coupled receptors. These data suggest that CovET ranks highest the sequence position pairs that play critical functional roles through epistatic and allosteric interactions in evolutionarily relevant structure-function motifs. CovET complements current methods and may shed light on fundamental molecular mechanisms of protein structure and function.

The G protein biased serotonin 5-HT 2A receptor agonist lisuride exerts anti-depressant drug-like activities in mice

There is now evidence from multiple Phase II clinical trials that psychedelic drugs can exert longlasting anxiolytic, anti-depressant, and anti-drug abuse (nicotine and ethanol) effects in patients. Despite these benefits, the hallucinogenic actions of these drugs at the serotonin 2A receptor (5-HT2AR) limit their clinical use in diverse settings. Activation of the 5-HT2AR can stimulate both G protein and β-arrestin (βArr) -mediated signaling. Lisuride is a G protein biased agonist at the 5-HT2AR and, unlike the structurally-related LSD, the drug does not typically produce hallucinations in normal subjects at routine doses. Here, we examined behavioral responses to lisuride, in wild-type (WT), βArr1-KO, and βArr2-KO mice. In the open field, lisuride reduced locomotor and rearing activities, but produced a U-shaped function for stereotypies in both βArr lines of mice. Locomotion was decreased overall in βArr1-KOs and βArr2-KOs, relative to WT controls. Incidences of head twitches and retrograde walking to lisuride were low in all genotypes. Grooming was depressed in βArr1 mice, but was increased then decreased in βArr2 animals with lisuride. Prepulse inhibition (PPI) was unaffected in βArr2 mice, whereas 0.5 mg/kg lisuride disrupted PPI in βArr1 animals. The 5-HT2AR antagonist MDL100907 failed to restore PPI in βArr1 mice, whereas the dopamine D2/D3 antagonist raclopride normalized PPI in WTs but not in βArr1-KOs. Using vesicular monoamine transporter 2 mice, lisuride reduced immobility times in tail suspension and promoted a preference for sucrose that lasted up to 2 days. Together, it appears βArr1 and βArr2 play minor roles in lisuride's actions on many behaviors, while this drug exerts anti-depressant drug-like responses without hallucinogenic-like activities.

Expanding potential targets of herbal chemicals by node2vec based on herb-drug interactions

BACKGROUND

The identification of chemical-target interaction is key to pharmaceutical research and development, but the unclear materials basis and complex mechanisms of traditional medicine (TM) make it difficult, especially for low-content chemicals which are hard to test in experiments. In this research, we aim to apply the node2vec algorithm in the context of drug-herb interactions for expanding potential targets and taking advantage of molecular docking and experiments for verification.

METHODS

Regarding the widely reported risks between cardiovascular drugs and herbs, Salvia miltiorrhiza (Danshen, DS) and Ligusticum chuanxiong (Chuanxiong, CX), which are widely used in the treatment of cardiovascular disease (CVD), and approved drugs for CVD form the new dataset as an example. Three data groups DS-drug, CX-drug, and DS-CX-drug were applied to serve as the context of drug-herb interactions for link prediction. Three types of datasets were set under three groups, containing information from chemical-target connection (CTC), chemical-chemical connection (CCC) and protein-protein interaction (PPI) in increasing steps. Five algorithms, including node2vec, were applied as comparisons. Molecular docking and pharmacological experiments were used for verification.

RESULTS

Node2vec represented the best performance with average AUROC and AP values of 0.91 on the datasets "CTC, CCC, PPI". Targets of 32 herbal chemicals were identified within 43 predicted edges of herbal chemicals and drug targets. Among them, 11 potential chemical-drug target interactions showed better binding affinity by molecular docking. Further pharmacological experiments indicated caffeic acid increased the thermal stability of the protein GGT1 and ligustilide and low-content chemical neocryptotanshinone induced mRNA change of FGF2 and MTNR1A, respectively.

CONCLUSIONS

The analytical framework and methods established in the study provide an important reference for researchers in discovering herb-drug interactions, alerting clinical risks, and understanding complex mechanisms of TM.

Pharmacotherapy for Treatment-Resistant Depression: Antidepressants and Atypical Antipsychotics

Treatment-resistant depression (TRD) affects one in three patients with major depressive disorder and is associated with increased risk of all-cause mortality. Studies of real-world practices suggest that antidepressant monotherapy continues to be the most widely used treatment after inadequate response to a first-line treatment. However, rates of remission with antidepressants in TRD are suboptimal. Atypical antipsychotics are the most widely studied augmentation agent and aripiprazole, brexpiprazole, cariprazine, quetiapine extended-release, and olanzapine-fluoxetine combination are approved for depression. Benefits of using atypical antipsychotics for TRD has to be weighted against their potential adverse events, such as weight gain, akathisia, and tardive dyskinesia.

Activity Models of Key GPCR Families in the Central Nervous System: A Tool for Many Purposes

G protein-coupled receptors (GPCRs) are targets of many drugs, of which ∼25% are indicated for central nervous system (CNS) disorders. Drug promiscuity affects their efficacy and safety profiles. Predicting the polypharmacology profile of compounds against GPCRs can thus provide a basis for producing more precise therapeutics by considering the targets and the anti-targets in that family of closely related proteins. We provide a tool for predicting the polypharmacology of compounds within prominent GPCR families in the CNS: serotonin, dopamine, histamine, muscarinic, opioid, and cannabinoid receptors. Our in-house algorithm, "iterative stochastic elimination" (ISE), produces high-quality ligand-based models for agonism and antagonism at 31 GPCRs. The ISE models correctly predict 68% of CNS drug-GPCR interactions, while the "similarity ensemble approach" predicts only 33%. The activity models correctly predict 56% of reported activities of DrugBank molecules for these CNS receptors. We conclude that the combination of interactions and activity profiles generated by screening through our models form the basis for subsequent designing and discovering novel therapeutics, either single, multitargeting, or repurposed.

Fenfluramine: a plethora of mechanisms?

Developmental and epileptic encephalopathies are rare, treatment-resistant epilepsies with high seizure burden and non-seizure comorbidities. The antiseizure medication (ASM) fenfluramine is an effective treatment for reducing seizure frequency, ameliorating comorbidities, and potentially reducing risk of sudden unexpected death in epilepsy (SUDEP) in patients with Dravet syndrome and Lennox-Gastaut syndrome, among other rare epilepsies. Fenfluramine has a unique mechanism of action (MOA) among ASMs. Its primary MOA is currently described as dual-action sigma-1 receptor and serotonergic activity; however, other mechanisms may be involved. Here, we conduct an extensive review of the literature to identify all previously described mechanisms for fenfluramine. We also consider how these mechanisms may play a role in the reports of clinical benefit in non-seizure outcomes, including SUDEP and everyday executive function. Our review highlights the importance of serotonin and sigma-1 receptor mechanisms in maintaining a balance between excitatory (glutamatergic) and inhibitory (γ-aminobutyric acid [GABA]-ergic) neural networks, and suggests that these mechanisms may represent primary pharmacological MOAs in seizures, non-seizure comorbidities, and SUDEP. We also describe ancillary roles for GABA neurotransmission, noradrenergic neurotransmission, and the endocrine system (especially such progesterone derivatives as neuroactive steroids). Dopaminergic activity underlies appetite reduction, a common side effect with fenfluramine treatment, but any involvement in seizure reduction remains speculative. Further research is underway to evaluate promising new biological pathways for fenfluramine. A better understanding of the pharmacological mechanisms for fenfluramine in reducing seizure burden and non-seizure comorbidities may allow for rational drug design and/or improved clinical decision-making when prescribing multi-ASM regimens.

Does drug use affect the efficacy of amisulpride, aripiprazole and olanzapine in patients with schizophrenia spectrum disorders? Results from a pragmatic, randomised study

OBJECTIVES

Drug use is prevalent in patients with schizophrenia spectrum disorders (SSD) but there is limited knowledge about the influence of drug use on the effectiveness of antipsychotic medication. This secondary explorative study compared the effectiveness of three antipsychotics in patients with SSD, with and without drug use.

METHODS

The BeSt InTro multi-centre, head to head, rater-blinded randomised study compared amisulpride, aripiprazole and olanzapine over a 1-year follow-up period. All patients (n = 144) were aged ≥18 years and met the ICD-10 criteria for SSD (F20-29). Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). The primary outcome was reduction of a PANSS positive subscale score.

RESULTS

At baseline, 38% of all patients reported drug use in the last 6 months before inclusion, with cannabis as the main drug (85%), followed by amphetamine-type stimulants (45%), sedatives (26%), hallucinogens (19%), cocaine (13%), opiates (4%), GHB (4%), solvents (4%), analgesics (4%) and anabolic steroids (2%). The predominant pattern was the use of several drugs. There were no significant overall differences in the PANSS positive subscale score reduction for the three studied antipsychotics among patients either with or without drug use. In the drug use group, older patients treated with amisulpride showed a greater PANSS positive subscale score reduction during the treatment period compared to younger patients.

CONCLUSION

The current study showed that drug use does not appear to affect the overall effectiveness of amisulpride, aripiprazole and olanzapine in patients with SSD. However, amisulpride may be a particularly suitable choice for older patients with drug use.

Transformation of a Dopamine D2 Receptor Agonist to Partial Agonists as Novel Antipsychotic Agents

Designed ligands of G protein-coupled receptors can exert a spectrum of modulating effects, varying from full agonists and partial agonists to antagonists and inverse agonists. For the dopamine D₂ receptor (D₂R), partial agonist activity is the pharmacological feature of the third-generation antipsychotics, including aripiprazole, brexpiprazole, and cariprazine. Started from a benzofuran-derived D₂R full agonist O₄LE₆ (4), which was identified using a structure-based method by us in previous studies, a series of D₂R partial agonists were designed and synthesized by introducing different tail groups. Among them, compound 10b showed excellent activity in D₂R pharmacological assays. Further optimizations using a structural rigidification approach led to the discovery of brain-penetrant compounds 29c and 29d, which exhibited potent antipsychotic effects in the mouse hyperlocomotion model. Compound 29c also showed excellent drug-like pharmacokinetic properties in rats and qualifies as an antipsychotic agent that is worth further evaluations.

Rule of five violations among the FDA-approved small molecule protein kinase inhibitors

Because genetic alterations including mutations, overexpression, translocations, and dysregulation of protein kinases are involved in the pathogenesis of many illnesses, this enzyme family is the target of many drug discovery programs in the pharmaceutical industry. Overall, the US FDA has approved 74 small molecule protein kinase inhibitors, nearly all of which are orally effective. Of the 74 approved drugs, forty block receptor protein-tyrosine kinases, eighteen target nonreceptor protein-tyrosine kinases, twelve are directed against protein-serine/threonine protein kinases, and four target dual specificity protein kinases. The data indicate that 63 of these medicinals are approved for the management of neoplasms (51 against solid tumors such as breast, colon, and lung cancers, eight against nonsolid tumors such as leukemia, and four against both types of tumors). Seven of the FDA-approved kinase inhibitors form covalent bonds with their target enzymes and they are accordingly classified as TCIs (targeted covalent inhibitors). Medicinal chemists have examined the physicochemical properties of drugs that are orally effective. Lipinski's rule of five (Ro5) is a computational procedure that is used to estimate solubility, membrane permeability, and pharmacological effectiveness in the drug-discovery setting. It relies on four parameters including molecular weight, number of hydrogen bond donors and acceptors, and the Log of the partition coefficient. Other important descriptors include the lipophilic efficiency, the polar surface area, and the number of rotatable bonds and aromatic rings. We tabulated these and other properties of the FDA-approved kinase inhibitors. Of the 74 approved drugs, 30 fail to comply with the rule of five.

Applications of promiscuity of FDA-approved kinase inhibitors in drug repositioning and toxicity

Promiscuity of therapeutics has important implications in treatment and toxicity. So far, a comprehensive understanding of promiscuity related to kinase inhibitors is lacking and such an analysis may offer potential opportunities for drug repurposing. In the present study, profiling of inhibitor-specific kinases based on the available biochemical IC50s was performed, fold-change of IC50 values for additional targets were calculated by taking the primary target as the reference kinase, and finally the promiscuity degree (PD) for FDA-approved kinase inhibitors was calculated. Surprisingly, class II inhibitors showed more PD than that of the class I inhibitors. We further identified cancer types and sub-types in which additional kinase targets or off-targets of inhibitors were overexpressed for potential drug repurposing. In addition, the expression of these kinases in normal human tissues were also profiled to predict toxicity following drug repositioning. Taken together, the study offers opportunities for cancer treatment in a kinase-specific manner.

Silmitasertib (CX-4945), a Clinically Used CK2-Kinase Inhibitor with Additional Effects on GSK3β and DYRK1A Kinases: A Structural Perspective

A clinical casein kinase 2 inhibitor, CX-4945 (silmitasertib), shows significant affinity toward the DYRK1A and GSK3β kinases, involved in down syndrome phenotypes, Alzheimer's disease, circadian clock regulation, and diabetes. This off-target activity offers an opportunity for studying the effect of the DYRK1A/GSK3β kinase system in disease biology and possible line extension. Motivated by the dual inhibition of these kinases, we solved and analyzed the crystal structures of DYRK1A and GSK3β with CX-4945. We built a quantum-chemistry-based model to rationalize the compound affinity for CK2α, DYRK1A, and GSK3β kinases. Our calculations identified a key element for CK2α's subnanomolar affinity to CX-4945. The methodology is expandable to other kinase selectivity modeling. We show that the inhibitor limits DYRK1A- and GSK3β-mediated cyclin D1 phosphorylation and reduces kinase-mediated NFAT signaling in the cell. Given the CX-4945's clinical and pharmacological profile, this inhibitory activity makes it an interesting candidate with potential for application in additional disease areas.

Exhaustive in silico design and screening of novel antipsychotic compounds with improved pharmacodynamics and blood-brain barrier permeation properties

Antipsychotic drugs or neuroleptics are widely used in the treatment of psychosis as a manifestation of schizophrenia and bipolar disorder. However, their effectiveness largely depends on the blood-brain barrier (BBB) permeation (pharmacokinetics) and drug-receptor pharmacodynamics. Therefore, in this study, we developed and implemented the in silico pipeline to design novel compounds (n = 260) as leads using the standard drug scaffolds with improved PK/PD properties from the standard scaffolds. As a result, the best candidates (n = 3) were evaluated in molecular docking to interact with serotonin and dopamine receptors. Finally, haloperidol (HAL) derivative (1-(4-fluorophenyl)-4-(4-hydroxy-4-{4-[(2-phenyl-1,3-thiazol-4-yl)methyl]phenyl}piperidin-1-yl)butan-1-one) was identified as a "magic shotgun" lead compound with better affinity to the 5-HT2A, 5-HT1D, D2, D3, and 5-HT1B receptors than the control molecule. Additionally, this hit substance was predicted to possess similar BBB permeation properties and much lower toxicological profiles in comparison to HAL. Overall, the proposed rational drug design platform for novel antipsychotic drugs based on the BBB permeation and receptor binding might be an invaluable asset for a medicinal chemist or translational pharmacologist.Communicated by Ramaswamy H. Sarma.

Pharmacotherapies for Treatment-Resistant Depression: How Antipsychotics Fit in the Rapidly Evolving Therapeutic Landscape

One in three adults with major depressive disorder (MDD) do not experience clinically significant improvement after multiple sequential courses of antidepressants and have treatment-resistant depression (TRD). The presence of TRD contributes to the morbidity and excess mortality associated with MDD and has been linked to significantly increased health care expenses. In the absence of a consensus definition of TRD, this report takes a broad approach by considering inadequate response to one or more courses of antidepressants and focuses on atypical antipsychotics that are approved by the U.S. Food and Drug Administration for treatment of depression (aripiprazole, brexpiprazole, cariprazine, extended-release quetiapine, and olanzapine-fluoxetine combination). While multiple acute-phase studies have demonstrated the efficacy of these medications in improving depressive symptoms, clinically meaningful improvement (i.e., remission) remains limited, with significant concerns about side effects (including weight gain, metabolic dysfunction, extrapyramidal symptoms, and tardive dyskinesia), especially with long-term use. With the rapidly evolving landscape of antidepressant treatments over the past few years, which has witnessed approval of rapid-acting antidepressants (e.g., esketamine nasal spray and dextromethorphan-bupropion combination) and several more in the late-stage pipeline (e.g., zuranolone and psilocybin), it remains to be seen whether the use of atypical antipsychotics will go the way of the older and rarely prescribed antidepressants (such as tricyclics and monoamine oxidase inhibitors). Pragmatic clinical trials are needed to compare the effectiveness of atypical antipsychotics with TRD-specific pharmacotherapies and neuromodulation treatments and to identify the optimal sequencing of these varied approaches for patients with MDD. When using atypical antipsychotics, clinicians and patients are encouraged to use a shared decision-making approach by personalizing treatment selection based on anticipated side effects, tolerability, cost, and feasibility.

Exploring the Role of Neurotransmitters in Multiple Sclerosis: An Expanded Review

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease of the central nervous system (CNS). Although emerging evidence has shown that changes in neurotransmitter levels in the synaptic gap may contribute to the pathophysiology of MS, their specific role has not been elucidated yet. In this review, we aim to analyze preclinical and clinical evidence on the structural and functional changes in neurotransmitters in MS and critically discuss their potential role in MS pathophysiology. Preclinical studies have demonstrated that alterations in glutamate metabolism may contribute to MS pathophysiology, by causing excitotoxic neuronal damage. Dysregulated interaction between glutamate and GABA results in synaptic loss. The GABAergic system also plays an important role, by regulating the activity and plasticity of neural networks. Targeting GABAergic/glutamatergic transmission may be effective in fatigue and cognitive impairment in MS. Acetylcholine (ACh) and dopamine can also affect the T-mediated inflammatory responses, thereby being implicated in MS-related neuroinflammation. Also, melatonin might affect the frequency of relapses in MS, by regulating the sleep-wake cycle. Increased levels of nitric oxide in inflammatory lesions of MS patients may be also associated with axonal neuronal degeneration. Therefore, neurotransmitter imbalance may be critically implicated in MS pathophysiology, and future studies are needed for our deeper understanding of their role in MS.