Revised Pharmacophore Model for 5-HT2A Receptor Antagonists Derived from the Atypical Antipsychotic Agent Risperidone

Selective Potentiation of the (α4)3(β2)2 Nicotinic Acetylcholine Receptor Response by NS9283 Analogues

NS9283, 3-(3-pyridyl)-5-(3-cyanophenyl)-1,2,4-oxadiazole, is a selective positive allosteric modulator of (α4)3(β2)2 nicotinic acetylcholine receptors (nAChRs). It has good subtype selective therapeutic potential afforded by its specific binding to the unique α4-α4 subunit interface present in the (α4)3(β2)2 nAChR. However, there is currently a lack of structure activity relationship (SAR) studies aimed at developing a class of congeners endowed with the same profile of activity that can help consolidate the druggability of the α4-α4 subunit interface. In this study, new NS9283 analogues were designed, synthesized, and characterized for their ability to selectively potentiate the ACh activity at heterologous (α4)3(β2)2 nAChRs vs nAChR subtypes (α4)2(β2)3, α5α4β2, and α7. With few exceptions, all the NS9283 analogues exerted positive modulation of the (α4)3(β2)2 nAChR ACh-evoked responses. Above all, those modified at the 3-cyanophenyl moiety by replacement with 3-nitrophenyl (4), 4-cyanophenyl (10), and N-formyl-4-piperidinyl (20) showed the same efficacy as NS9283, although with lower potency. Molecular dynamics simulations of NS9283 and some selected analogues highlighted consistency between potentiation activity and pose of the ligand inside the α4-α4 site with the main interaction being with the complementary (-) side and induction of a significant conformational change of the Trp156 residue in the principal (+) side.

Merging cultures and disciplines to create a drug discovery ecosystem at Virginia commonwealth university: Medicinal chemistry, structural biology, molecular and behavioral pharmacology and computational chemistry

The Department of Medicinal Chemistry, together with the Institute for Structural Biology, Drug Discovery and Development, at Virginia Commonwealth University (VCU) has evolved, organically with quite a bit of bootstrapping, into a unique drug discovery ecosystem in response to the environment and culture of the university and the wider research enterprise. Each faculty member that joined the department and/or institute added a layer of expertise, technology and most importantly, innovation, that fertilized numerous collaborations within the University and with outside partners. Despite moderate institutional support with respect to a typical drug discovery enterprise, the VCU drug discovery ecosystem has built and maintained an impressive array of facilities and instrumentation for drug synthesis, drug characterization, biomolecular structural analysis and biophysical analysis, and pharmacological studies. Altogether, this ecosystem has had major impacts on numerous therapeutic areas, such as neurology, psychiatry, drugs of abuse, cancer, sickle cell disease, coagulopathy, inflammation, aging disorders and others. Novel tools and strategies for drug discovery, design and development have been developed at VCU in the last five decades; e.g., fundamental rational structure-activity relationship (SAR)-based drug design, structure-based drug design, orthosteric and allosteric drug design, design of multi-functional agents towards polypharmacy outcomes, principles on designing glycosaminoglycans as drugs, and computational tools and algorithms for quantitative SAR (QSAR) and understanding the roles of water and the hydrophobic effect.

Sex-specific role for serotonin 5-HT2A receptor in modulation of opioid-induced antinociception and reward in mice

Opioids are among the most effective analgesics and the mainstay of pain management. However, concerns about safety and abuse liability have challenged their widespread use by the medical community. Opioid-sparing therapies include drugs that in combination with opioids have the ability to enhance analgesia while decreasing opioid requirement as well as their side effects. Sex differences in antinociceptive responses to opioids have received increasing attention in recent years. However, the molecular mechanisms underlying sex differences related to opioid-sparing adjuncts remain largely unexplored. Using warm water tail-withdrawal as a mouse model of acute thermal nociception, our data suggest that adjunctive administration of the serotonin 5-HT_2A receptor (5-HT_2AR) antagonist volinanserin dose-dependently enhanced potency of the opioid analgesic oxycodone in male, but not female, mice. This antinociceptive-like response induced by oxycodone was also augmented in 5-HT_2AR knockout (5-HT_2AR^-/-) male, but not female mice; an effect that was reversed by Cre-loxP-mediated selective expression of 5-HT_2AR in dorsal root ganglion (DRG) neurons of 5-HT_2AR^-/- littermates. Pharmacological inhibition with volinanserin or genetic deletion in 5-HT_2AR^-/- animals potentiated the ability of oxycodone to reduce DRG excitability in male mice. Adjunctive volinanserin did not affect oxycodone-induced conditioned place preference (CPP), whereas it reduced oxycodone-induced locomotor sensitization in male and female mice. Together, these results suggest that adjunctive volinanserin augments opioid-induced antinociception, but not abuse-related behavior, through a sex-specific signaling crosstalk mechanism that requires 5-HT_2AR expression in mouse DRG neurons. Ultimately, our results may pave the way for the clinical evaluation of volinanserin as a potential sex-specific opioid adjuvant.

Therapeutic Potential of TAAR1 Agonists in Schizophrenia: Evidence from Preclinical Models and Clinical Studies

Trace amine-associated receptor 1 (TAAR1) has emerged as a promising therapeutic target for neuropsychiatric disorders due to its ability to modulate monoaminergic and glutamatergic neurotransmission. In particular, agonist compounds have generated interest as potential treatments for schizophrenia and other psychoses due to TAAR1-mediated regulation of dopaminergic tone. Here, we review unmet needs in schizophrenia, the current state of knowledge in TAAR1 circuit biology and neuropharmacology, including preclinical behavioral, imaging, and cellular evidence in glutamatergic, dopaminergic and genetic models linked to the pathophysiology of psychotic, negative and cognitive symptoms. Clinical trial data for TAAR1 drug candidates are reviewed and contrasted with antipsychotics. The identification of endogenous TAAR1 ligands and subsequent development of small-molecule agonists has revealed antipsychotic-, anxiolytic-, and antidepressant-like properties, as well as pro-cognitive and REM-sleep suppressing effects of TAAR1 activation in rodents and non-human primates. Ulotaront, the first TAAR1 agonist to progress to randomized controlled clinical trials, has demonstrated efficacy in the treatment of schizophrenia, while another, ralmitaront, is currently being evaluated in clinical trials in schizophrenia. Coupled with the preclinical findings, this provides a rationale for further investigation and development of this new pharmacological class for the treatment of schizophrenia and other psychiatric disorders.

Novel serotonin 5-HT2A receptor antagonists derived from 4-phenylcyclohexane-5-spiro-and 5-methyl-5-phenyl-hydantoin, for use as potential antiplatelet agents

BACKGROUND

Antiplatelet drugs have been used in the treatment of acute coronary syndromes and for the prevention of recurrent events. Unfortunately, many patients remain resistant to the available antiplatelet treatment. Therefore, there is a clinical need to synthesize novel antiplatelet agents, which would be associated with different pathways of platelet aggregation, to develop an alternative or additional treatment for resistant patients. Recent studies have revealed that 5-HT_2A receptor antagonists could constitute alternative antiplatelet therapy.

METHODS

Based on the structures of the conventional 5-HT_2A receptor ligands, two series of compounds with 4-phenylcyclohexane-5-spiro- or 5-methyl-5-phenyl-hydantoin core linked to various arylpiperazine moieties were synthesized and their affinity for 5-HT_2A receptor was assessed. Further, we evaluated their antagonistic potency at 5-HT_2A receptors using isolated rat aorta and cells expressing human 5-HT_2A receptors. Finally, we studied their anti-aggregation effect and compared it with ketanserin and sarpogrelate, the reference 5-HT_2A receptor antagonists. Moreover, the structure-activity relationships were studied following molecular docking to the 5-HT_2A receptor model.

RESULTS

Functional bioassays revealed some of the synthesized compounds to be moderate antagonists of 5-HT_2A receptors. Among them, 13, 8-phenyl-3-(3-(4-phenylpiperazin-1-yl)propyl)-1,3-diazaspiro[4.5]decane-2,4-dione, inhibited collagen stimulated aggregation (IC₅₀ = 27.3 μM) being more active than sarpogrelate (IC₅₀ = 66.8 μM) and comparable with ketanserin (IC₅₀ = 32.1 μM). Moreover, compounds 2-5, 9-11, 13, 14 inhibited 5-HT amplified, ADP- or collagen-induced aggregation.

CONCLUSIONS

Our study confirmed that the 5-HT_2A antagonists effectively suppress platelet aggregation and remain an interesting option for the development of novel antiplatelet agents with an alternative mechanism of action.

Psychedelic-like Properties of Quipazine and Its Structural Analogues in Mice

Known classic psychedelic serotonin 2A receptor (5-HT2AR) agonists retain a tryptamine or phenethylamine at their structural core. However, activation of the 5-HT2AR can be elicited by drugs lacking these fundamental scaffolds. Such is the case of the N-substituted piperazine quipazine. Here, we show that quipazine bound to and activated 5-HT2AR as measured by [3H]ketanserin binding displacement, Ca2+ mobilization, and accumulation of the canonical Gq/11 signaling pathway mediator inositol monophosphate (IP1) in vitro and in vivo. Additionally, quipazine induced via 5-HT2AR an expression pattern of immediate early genes (IEG) in the mouse somatosensory cortex consistent with that of classic psychedelics. In the mouse head-twitch response (HTR) model of psychedelic-like action, quipazine produced a lasting effect with high maximal responses during the peak effect that were successfully blocked by the 5-HT2AR antagonist M100907 and absent in 5-HT2AR knockout (KO) mice. The acute effect of quipazine on HTR appeared to be unaffected by serotonin depletion and was independent from 5-HT3R activation. Interestingly, some of these features were shared by its deaza bioisostere 2-NP, but not by other closely related piperazine congeners, suggesting that quipazine might represent a distinct cluster within the family of psychoactive piperazines. Together, our results add to the mounting evidence that quipazine's profile matches that of classic psychedelic 5-HT2AR agonists at cellular signaling and behavioral pharmacology levels.

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT_2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.