Haloperidol bound D2 dopamine receptor structure inspired the discovery of subtype selective ligands

G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction

G protein-coupled receptor (GPCR) transmembrane protein family members play essential roles in physiology. Numerous pharmaceuticals target GPCRs, and many drug discovery programs utilize virtual screening (VS) against GPCR targets. Improvements in the accuracy of predicting new molecules that bind to and either activate or inhibit GPCR function would accelerate such drug discovery programs. This work addresses two significant research questions. First, do ligand interaction fingerprints provide a substantial advantage over automated methods of binding site selection for classical docking? Second, can the functional status of prospective screening candidates be predicted from ligand interaction fingerprints using a random forest classifier? Ligand interaction fingerprints were found to offer modest advantages in sampling accurate poses, but no substantial advantage in the final set of top-ranked poses after scoring, and, thus, were not used in the generation of the ligand-receptor complexes used to train and test the random forest classifier. A binary classifier which treated agonists, antagonists, and inverse agonists as active and all other ligands as inactive proved highly effective in ligand function prediction in an external test set of GPR31 and TAAR2 candidate ligands with a hit rate of 82.6% actual actives within the set of predicted actives.

Antinociceptive effect of LMH-2, a new sigma-1 receptor antagonist analog of haloperidol, on the neuropathic pain of diabetic mice

This study evaluates the antiallodynic and antihyperalgesic effects of LMH-2, a new haloperidol (HAL) analog that acts as sigma-1 receptor (σ1 R) antagonist, in diabetic mice using a model of neuropathic pain induced by chronic hyperglycemia. Additionally, we compared its effects with those of HAL. Hyperglycemia was induced in mice by nicotinamide-streptozotocin administration (NA-STZ, 50-130 mg/kg). Four weeks later, mechanical allodynia was assessed using the up-down method, and hyperalgesia was evoked with formalin 0.5%. We evaluated antiallodynic and antihyperalgesic effects of LMH-2 (5.6-56.2 mg/kg), HAL (0.018-0.18 mg/kg) and gabapentin (GBP, 5.6-56.2 mg/kg). The results showed that LMH-2 had a more significant antiallodynic effect compared to HAL and GBP (90.4±8.7 vs 75.1±3.1 and 41.9±2.3%, respectively; P<0.05), as well as an antihyperalgesic effect (96.3±1.2 vs 86.9±7.41 and 86.9±4.8%, respectively; P<0.05). Moreover, the antiallodynic and antihyperalgesic effect of both LMH-2 and HAL were completely abolished by PRE-084 (σ1 R agonist); and partially by pramipexole (a D2-like receptor agonist). Finally, the effect of all treatments on the rotarod test, barra, open field and exploratory behaviors showed that LMH-2 did not alter the animals' balance or the exploratory behavior, unlike as HAL or GBP. The molecular docking included indicate that LMH-2 has lower affinity to the D2R than HAL. These results provide evidence that LMH-2 exerts its antinociceptive effects as a σ1 R antagonist without the adverse effects induced by HAL or GBP. Consequently, LMH-2 can be considered a good and safe strategy for treating neuropathic pain caused by hyperglycemia in patients with diabetes.

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.

Comparison of the function of two novel human dopamine D2 receptor variants identifies a likely mechanism for their pathogenicity

Two recently discovered DRD2 mutations, c.634A > T, p.Ile212Phe and c.1121T > G, p.Met374Arg, cause hyperkinetic movement disorders that have overlapping features but apparently differ in severity. The two known carriers of the Met374Arg variant had early childhood disease onset and more severe motor, cognitive, and neuropsychiatric deficits than any known carriers of the Ile212Phe variant, whose symptoms were first apparent in adolescence. Here, we evaluated if differences in the function of the two variants in cultured cells could explain differing pathogenicity. Both variants were expressed less abundantly than the wild type receptor and exhibited loss of agonist-induced arrestin binding, but differences in expression and arrestin binding between the variants were minor. Basal and agonist-induced activation of heterotrimeric Gi/o/z proteins, however, showed clear differences; agonists were generally more potent at Met374Arg than at the Ile212Phe or wild type variants. Furthermore, all Gα subtypes tested were constitutively activated more by Met374Arg than by Ile212Phe. Met374Arg produced greater constitutive inhibition of cyclic AMP accumulation than Ile212Phe or the wild type D2 receptor. Met374Arg and Ile212Phe were more sensitive to thermal inactivation than the wild type D2 receptor, as reported for other constitutively active receptors, but Ile212Phe was affected more than Met374Arg. Additional pharmacological characterization suggested that the mutations differentially affect the shape of the agonist binding pocket and the potency of dopamine, norepinephrine, and tyramine. Molecular dynamics simulations provided a structural rationale for enhanced constitutive activation and agonist potency. Enhanced constitutive and agonist-induced G protein-mediated signaling likely contributes to the pathogenicity of these novel variants.

Unraveling Activation-Related Rearrangements and Intrinsic Divergence from Ligand-Specific Conformational Changes of the Dopamine D3 and D2 Receptors

Effective rational drug discovery hinges on understanding the functional states of the target protein and distinguishing it from homologues. However, for the G protein coupled receptors, both activation-related conformational changes (ACCs) and intrinsic divergence among receptors can be misled or obscured by ligand-specific conformational changes (LCCs). Here, we unraveled ACCs and intrinsic divergence from LCCs of the dopamine D3 and D2 receptors (D3R and D2R), by analyzing their experimentally determined structures and the molecular dynamics (MD) simulation results of the receptors bound with various ligands. In addition to the ACCs common to other aminergic receptors, we revealed unique ACCs for these two receptors, including the extracellular portion of TM5 (TM5e) and TM6e shifting away from TM2e and TM3e, with a subtle rotation of TM5e. In identifying intrinsic divergence, we found more outward tilting of TM6e in the D2R compared to the D3R in both the experimental structures and simulations bound with ligands in different scaffolds. However, this difference was drastically reduced in the simulations bound with nonselective agonist quinpirole, suggesting a misleading effect of LCCs. Further, in the quinpirole-bound simulations, TM1 showed a greater disparity between these receptors, indicating that LCCs may also obscure intrinsic divergence. Importantly, our MD simulations revealed divergence in the dynamics of these receptors. Specifically, the D2R exhibited heightened flexibility compared to the D3R in the extracellular loops and TMs 5e, 6e, and 7e, associated with its greater ligand binding site plasticity. Our results lay the groundwork for crafting ligands specifically targeting the D2R and D3R with more precise pharmacological profiles.

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.

Structure, function and drug discovery of GPCR signaling

G protein-coupled receptors (GPCRs) are versatile and vital proteins involved in a wide array of physiological processes and responses, such as sensory perception (e.g., vision, taste, and smell), immune response, hormone regulation, and neurotransmission. Their diverse and essential roles in the body make them a significant focus for pharmaceutical research and drug development. Currently, approximately 35% of marketed drugs directly target GPCRs, underscoring their prominence as therapeutic targets. Recent advances in structural biology have substantially deepened our understanding of GPCR activation mechanisms and interactions with G-protein and arrestin signaling pathways. This review offers an in-depth exploration of both traditional and recent methods in GPCR structure analysis. It presents structure-based insights into ligand recognition and receptor activation mechanisms and delves deeper into the mechanisms of canonical and noncanonical signaling pathways downstream of GPCRs. Furthermore, it highlights recent advancements in GPCR-related drug discovery and development. Particular emphasis is placed on GPCR selective drugs, allosteric and biased signaling, polyphamarcology, and antibody drugs. Our goal is to provide researchers with a thorough and updated understanding of GPCR structure determination, signaling pathway investigation, and drug development. This foundation aims to propel forward-thinking therapeutic approaches that target GPCRs, drawing upon the latest insights into GPCR ligand selectivity, activation, and biased signaling mechanisms.

Unraveling activation-related rearrangements and intrinsic divergence from ligand-induced conformational changes of the dopamine D3 and D2 receptors

Effective rational drug discovery targeting a specific protein hinges on understanding their functional states and distinguishing it from homologs. However, for the G protein coupled receptors, both the activation-related conformational changes (ACCs) and the intrinsic divergence among receptors can be misled or obscured by ligand-induced conformational changes (LCCs). Here, we unraveled ACCs and intrinsic divergence from LCCs of the dopamine D3 and D2 receptors (D3R and D2R), by analyzing their experimentally determined structures and the molecular dynamics simulation results of the receptors bound with different ligands. In addition to the ACCs common to other aminergic receptors, we revealed unique ACCs for these two receptors including TM5e and TM6e shifting away from TM2e and TM3e, with a subtle rotation of TM5e. In identifying intrinsic divergence, we found pronounced outward tilting of TM6e in the D2R compared to the D3R in both experimental structures and simulations with ligands in different scaffolds. This tilting was drastically reduced in the simulations of the receptors bound with nonselective full agonist quinpirole, suggesting a misleading impact of LCCs. Further, in the quinpirole-bound simulations, TM1 showed a greater disparity between these receptors, indicating that LCCs may obscure intrinsic divergence. In addition, our analysis showed that the impact of the nonconserved TM1 propagated to conserved Trp7.40 and Glu2.65, both are ligand binding residues. We also found that the D2R exhibited heightened flexibility compared to the D3R in the extracellular portions of TMs 5, 6, and 7, potentially associated with its greater ligand binding site plasticity. Our results lay the groundwork for crafting ligands specifically targeting D2R or D3R with more precise pharmacological profiles.

Orthosteric ligand selectivity and allosteric probe dependence at Hydroxycarboxylic acid receptor HCAR2

Hydroxycarboxylic acid receptor 2 (HCAR2), a member of Class A G-protein-coupled receptor (GPCR) family, plays a pivotal role in anti-lipolytic and anti-inflammatory effects, establishing it as a significant therapeutic target for treating dyslipidemia and inflammatory diseases. However, the mechanism underlying the signaling of HCAR2 induced by various types of ligands remains elusive. In this study, we elucidate the cryo-electron microscopy (cryo-EM) structure of Gi-coupled HCAR2 in complex with a selective agonist, MK-6892, resolved to a resolution of 2.60 Å. Our structural analysis reveals that MK-6892 occupies not only the orthosteric binding pocket (OBP) but also an extended binding pocket (EBP) within HCAR2. Pharmacological assays conducted in this study demonstrate that the OBP is a critical determinant for ligand selectivity among the HCARs subfamily. Moreover, we investigate the pharmacological properties of the allosteric modulator compound 9n, revealing its probe-dependent behavior on HCAR2 in response to varying orthosteric agonists. Collectively, our findings provide invaluable structural insights that contribute to a deeper understanding of the regulatory mechanisms governing HCAR2 signaling transduction mediated by both orthosteric and allosteric ligands.

A Novel "Activation Switch" Motif Common to All Aminergic Receptors

Aminergic receptors are G protein-coupled receptors (GPCRs) that transduce signals from small endogenous biogenic amines to regulate intracellular signaling pathways. Agonist binding in the ligand binding pocket on the extracellular side opens and prepares a cavity on the intracellular face of the receptors to interact with and activate G proteins and β-arrestins. Here, by reviewing and analyzing all available aminergic receptor structures, we seek to identify activation-related conformational changes that are independent of the specific scaffold of the bound agonist, which we define as "activation conformational changes" (ACCs). While some common intracellular ACCs have been well-documented, identifying common extracellular ACCs, including those in the ligand binding pocket, is complicated by local adjustments to different ligand scaffolds. Our analysis shows no common ACCs at the extracellular ends of the transmembrane helices. Furthermore, the restricted access to the ligand binding pocket identified previously in some receptors is not universal. Notably, the Trp6.48 toggle switch and the Pro5.50-Ile3.40-Phe6.44 (PIF) motif at the bottom of the ligand binding pocket have previously been proposed to mediate the conformational consequences of ligand binding to the intracellular side of the receptors. Our analysis shows that common ACCs in the ligand binding pocket are associated with the PIF motif and nearby residues, including Trp6.48, but fails to support a shared rotamer toggle associated with activation. However, we identify two common rearrangements between the extracellular and middle subsegments, and propose a novel "activation switch" motif common to all aminergic receptors. This motif includes the middle subsegments of transmembrane helices 3, 5, and 6 and integrates both the PIF motif and Trp6.48.

Hybrid neural network approaches to predict drug-target binding affinity for drug repurposing: screening for potential leads for Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease that primarily affects elderly individuals. Recent studies have found that sigma-1 receptor (S1R) agonists can maintain endoplasmic reticulum stress homeostasis, reduce neuronal apoptosis, and enhance mitochondrial function and autophagy, making S1R a target for AD therapy. Traditional experimental methods are costly and inefficient, and rapid and accurate prediction methods need to be developed, while drug repurposing provides new ways and options for AD treatment. In this paper, we propose HNNDTA, a hybrid neural network for drug-target affinity (DTA) prediction, to facilitate drug repurposing for AD treatment. The study combines protein-protein interaction (PPI) network analysis, the HNNDTA model, and molecular docking to identify potential leads for AD. The HNNDTA model was constructed using 13 drug encoding networks and 9 target encoding networks with 2506 FDA-approved drugs as the candidate drug library for S1R and related proteins. Seven potential drugs were identified using network pharmacology and DTA prediction results of the HNNDTA model. Molecular docking simulations were further performed using the AutoDock Vina tool to screen haloperidol and bromperidol as lead compounds for AD treatment. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation results indicated that both compounds had good pharmacokinetic properties and were virtually non-toxic. The study proposes a new approach to computer-aided drug design that is faster and more economical, and can improve hit rates for new drug compounds. The results of this study provide new lead compounds for AD treatment, which may be effective due to their multi-target action. HNNDTA is freely available at https://github.com/lizhj39/HNNDTA.

Cymbopogon citratus Essential Oil: Extraction, GC-MS, Phytochemical Analysis, Antioxidant Activity, and In Silico Molecular Docking for Protein Targets Related to CNS

This study analyzed the chemical composition of Cymbopogon citratus essential oil from Puebla, México, assessed its antioxidant activity, and evaluated in silico protein-compound interactions related to central nervous system (CNS) physiology. GC-MS analysis identified myrcene (8.76%), Z-geranial (27.58%), and E-geranial (38.62%) as the main components, with 45 other compounds present, which depends on the region and growing conditions. DPPH and Folin-Ciocalteu assays using the leaves extract show a promising antioxidant effect (EC₅₀ = 48.5 µL EO/mL), reducing reactive oxygen species. The bioinformatic tool SwissTargetPrediction (STP) shows 10 proteins as potential targets associated with CNS physiology. Moreover, protein-protein interaction diagrams suggest that muscarinic and dopamine receptors are related to each other through a third party. Molecular docking reveals that Z-geranial has higher binding energy than M1 commercial blocker and blocks M2, but not M4 muscarinic acetylcholine receptors, whereas β-pinene and myrcene block M1, M2, and M4 receptors. These actions may positively affect cardiovascular activity, memory, Alzheimer's disease, and schizophrenia. This study highlights the significance of understanding natural product interactions with physiological systems to uncover potential therapeutic agents and advanced knowledge on their benefits for human health.

Development and Characterization of Novel Selective, Non-Basic Dopamine D2 Receptor Antagonists for the Treatment of Schizophrenia

The dopamine D₂ receptor, which belongs to the family of G protein-coupled receptors (GPCR), is an important and well-validated drug target in the field of medicinal chemistry due to its wide distribution, particularly in the central nervous system, and involvement in the pathomechanism of many disorders thereof. Schizophrenia is one of the most frequent diseases associated with disorders in dopaminergic neurotransmission, and in which the D₂ receptor is the main target for the drugs used. In this work, we aimed at discovering new selective D₂ receptor antagonists with potential antipsychotic activity. Twenty-three compounds were synthesized, based on the scaffold represented by the D2AAK2 compound, which was discovered by our group. This compound is an interesting example of a D₂ receptor ligand because of its non-classical binding to this target. Radioligand binding assays and SAR analysis indicated structural modifications of D2AAK2 that are possible to maintain its activity. These findings were further rationalized using molecular modeling. Three active derivatives were identified as D₂ receptor antagonists in cAMP signaling assays, and the selected most active compound 17 was subjected to X-ray studies to investigate its stable conformation in the solid state. Finally, effects of 17 assessed in animal models confirmed its antipsychotic activity in vivo.

Dopamine Receptor Ligand Selectivity-An In Silico/In Vitro Insight

Different dopamine receptor (DR) subtypes are involved in pathophysiological conditions such as Parkinson's Disease (PD), schizophrenia and depression. While many DR-targeting drugs have been approved by the U.S. Food and Drug Administration (FDA), only a very small number are truly selective for one of the DR subtypes. Additionally, most of them show promiscuous activity at related G-protein coupled receptors, thus suffering from diverse side-effect profiles. Multiple studies have shown that combined in silico/in vitro approaches are a valuable contribution to drug discovery processes. They can also be applied to divulge the mechanisms behind ligand selectivity. In this study, novel DR ligands were investigated in vitro to assess binding affinities at different DR subtypes. Thus, nine D2R/D3R-selective ligands (micro- to nanomolar binding affinities, D3R-selective profile) were successfully identified. The most promising ligand exerted nanomolar D3R activity (Ki = 2.3 nM) with 263.7-fold D2R/D3R selectivity. Subsequently, ligand selectivity was rationalized in silico based on ligand interaction with a secondary binding pocket, supporting the selectivity data determined in vitro. The developed workflow and identified ligands could aid in the further understanding of the structural motifs responsible for DR subtype selectivity, thus benefitting drug development in D2R/D3R-associated pathologies such as PD.

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.

Molecular and Functional Characterization of Different BrainSphere Models for Use in Neurotoxicity Testing on Microelectrode Arrays

The currently accepted methods for neurotoxicity (NT) testing rely on animal studies. However, high costs and low testing throughput hinder their application for large numbers of chemicals. To overcome these limitations, in vitro methods are currently being developed based on human-induced pluripotent stem cells (hiPSC) that allow higher testing throughput at lower costs. We applied six different protocols to generate 3D BrainSphere models for acute NT evaluation. These include three different media for 2D neural induction and two media for subsequent 3D differentiation resulting in self-organized, organotypic neuron/astrocyte microtissues. All induction protocols yielded nearly 100% NESTIN-positive hiPSC-derived neural progenitor cells (hiNPCs), though with different gene expression profiles concerning regional patterning. Moreover, gene expression and immunocytochemistry analyses revealed that the choice of media determines neural differentiation patterns. On the functional level, BrainSpheres exhibited different levels of electrical activity on microelectrode arrays (MEA). Spike sorting allowed BrainSphere functional characterization with the mixed cultures consisting of GABAergic, glutamatergic, dopaminergic, serotonergic, and cholinergic neurons. A test method for acute NT testing, the human multi-neurotransmitter receptor (hMNR) assay, was proposed to apply such MEA-based spike sorting. These models are promising tools not only in toxicology but also for drug development and disease modeling.

Structure-based pharmacophore modeling 2. Developing a novel framework for structure-based pharmacophore model generation and selection

Pharmacophore models are three-dimensional arrangements of molecular features required for biological activity that are used in ligand identification efforts for many biological targets, including G protein-coupled receptors (GPCR). Though GPCR are integral membrane proteins of considerable interest as targets for drug development, many of these receptors lack known ligands or experimentally determined structures necessary for ligand- or structure-based pharmacophore model generation, respectively. Thus, we here present a structure-based pharmacophore modeling approach that uses fragments placed with Multiple Copy Simultaneous Search (MCSS) to generate high-performing pharmacophore models in the context of experimentally determined, as well as modeled GPCR structures. Moreover, we have addressed the oft-neglected topic of pharmacophore model selection via development of a cluster-then-predict machine learning workflow. Herein score-based pharmacophore models were generated in experimentally determined and modeled structures of 13 class A GPCR and resulted in pharmacophore models exhibiting high enrichment factors when used to search a database containing 569 class A GPCR ligands. In addition, classification of pharmacophore models with the best performing cluster-then-predict logistic regression classifier resulted in positive predictive values (PPV) of 0.88 and 0.76 for selecting high enrichment pharmacophore models from among those generated in experimentally determined and modeled structures, respectively.

Unique effect of clozapine on adenosine A2A-dopamine D2 receptor heteromerization

The striatal dopamine D₂ receptor (D₂R) is generally accepted to be involved in positive symptoms of schizophrenia and is a main target for clinically used antipsychotics. D₂R are highly expressed in the striatum, where they form heteromers with the adenosine A_2A receptor (A_2AR). Changes in the density of A_2AR-D₂R heteromers have been reported in postmortem tissue from patients with schizophrenia, but the degree to which A₂R are involved in schizophrenia and the effect of antipsychotic drugs is unknown. Here, we examine the effect of exposure to three prototypical antipsychotic drugs on A_2AR-D₂R heteromerization in mammalian cells using a NanoBiT assay. After 16 h of exposure, a significant increase in the density of A_2AR-D₂R heteromers was found with haloperidol and aripiprazole, but not with clozapine. On the other hand, clozapine, but not haloperidol or aripiprazole, was associated with a significant decrease in A_2AR-D₂R heteromerization after 2 h of treatment. Computational binding models of these compounds revealed distinctive molecular signatures that explain their different influence on heteromerization. The bulky tricyclic moiety of clozapine displaces TM 5 of D₂R, inducing a clash with A_2AR, while the extended binding mode of haloperidol and aripiprazole stabilizes a specific conformation of the second extracellular loop of D₂R that enhances the interaction with A_2AR. It is proposed that an increase in A_2AR-D₂R heteromerization is involved in the extrapyramidal side effects (EPS) of antipsychotics and that the specific clozapine-mediated destabilization of A_2AR-D₂R heteromerization can explain its low EPS liability.

Design, synthesis and evaluation of 1-(1,5-bis(4-substituted phenyl)-2-methyl-1H-pyrrol-3-yl)-N-methylmethanamines as SERT inhibitors with potential antidepressant action

BM212 is a potent anti-TB agent with pharmacophoric features similar to the antidepressant drug sertraline. The shape-based virtual screening of the DrugBank database on BM212 resulted in the identification of several CNS drugs with appreciable Tanimoto scores. The docking simulations also ascertained the selectivity of BM212 towards the serotonin reuptake transporter protein (SERT) with a docking score of -6.51 kcal mol-1. Based on the SAR data available for sertraline and other antidepressant drugs, we designed, synthesized and screened twelve 1-(1,5-bis(4-substituted phenyl)-2-methyl-1H-pyrrol-3-yl)-N-methylmethanamines (SA-1 to SA-12) for in vitro SERT inhibition and in vivo antidepressant activity. The compounds were screened for in vitro 5HT reuptake inhibition using the platelet model. Among the screened compounds, (1-(1,5-bis(4-chlorophenyl)-2-methyl-1H-pyrrol-3-yl)-N-methylmethanamine) showed the same serotonin uptake inhibition (absorbance 0.22) as that of the standard drug sertraline (absorbance 0.22). BM212 had an effect on 5-HT uptake, albeit a weaker one compared to the standard (absorbance 0.671). Further, SA-5 was screened for in vivo antidepressant activity using the unpredictable chronic mild stress (UCMS) protocol to induce depression in mice. The effect of BM212 and SA-5 on the behaviour of the animals was assessed and compared against the standard drug sertraline. SA-5 at 20 mg per kg body weight was found to have a statistically significant impact on the behaviour of depressed animals.

Recent advances in dopamine D2 receptor ligands in the treatment of neuropsychiatric disorders

Dopamine is a biologically active amine synthesized in the central and peripheral nervous system. This biogenic monoamine acts by activating five types of dopamine receptors (D_1-5 Rs), which belong to the G protein-coupled receptor family. Antagonists and partial agonists of D₂ Rs are used to treat schizophrenia, Parkinson's disease, depression, and anxiety. The typical pharmacophore with high D₂ R affinity comprises four main areas, namely aromatic moiety, cyclic amine, central linker and aromatic/heteroaromatic lipophilic fragment. From the literature reviewed herein, we can conclude that 4-(2,3-dichlorophenyl), 4-(2-methoxyphenyl)-, 4-(benzo[b]thiophen-4-yl)-1-substituted piperazine, and 4-(6-fluorobenzo[d]isoxazol-3-yl)piperidine moieties are critical for high D₂ R affinity. Four to six atoms chains are optimal for D₂ R affinity with 4-butoxyl as the most pronounced one. The bicyclic aromatic/heteroaromatic systems are most frequently occurring as lipophilic appendages to retain high D₂ R affinity. In this review, we provide a thorough overview of the therapeutic potential of D₂ R modulators in the treatment of the aforementioned disorders. In addition, this review summarizes current knowledge about these diseases, with a focus on the dopaminergic pathway underlying these pathologies. Major attention is paid to the structure, function, and pharmacology of novel D₂ R ligands, which have been developed in the last decade (2010-2021), and belong to the 1,4-disubstituted aromatic cyclic amine group. Due to the abundance of data, allosteric D₂ R ligands and D₂ R modulators from patents are not discussed in this review.

Approach to the specificity and selectivity between D2 and D3 receptors by mutagenesis and binding experiments part I: Expression and characterization of D2 and D3 receptor mutants

D3/D2 sub-specificity is a complex problem to solve. Indeed, in the absence of easy structural biology of the G-protein coupled receptors, and despite key progresses in this area, the systematic knowledge of the ligand/receptor relationship is difficult to obtain. Due to these structural biology limitations concerning membrane proteins, we favored the use of directed mutagenesis to document a rational towards the discovery of markedly specific D3 ligands over D2 ligands together with basic binding experiments. Using our methodology of stable expression of receptors in HEK cells, we constructed the gene encoding for 24 mutants and 4 chimeras of either D2 or D3 receptors and expressed them stably. Those cell lines, expressing a single copy of one receptor mutant each, were stably constructed, selected, amplified and the membranes from them were prepared. Binding data at those receptors were obtained using standard binding conditions for D2 and D3 dopamine receptors. We generated 26 new molecules derived from D2 or D3 ligands. Using 8 reference compounds and those 26 molecules, we characterized their binding at those mutants and chimeras, exemplifying an approach to better understand the difference at the molecular level of the D2 and D3 receptors. Although all the individual results are presented and could be used for minute analyses, the present report does not discuss the differences between D2 and D3 data. It simply shows the feasibility of the approach and its potential.

Association of Polymorphism with the Steady-State Concentration of Haloperidol in Patients with Alcohol-Induced Psychotic Disorders

Background

CYP2D6 subfamily isoenzymes play an important role in the biotransformation of haloperidol, and their activity may influence the efficacy and safety of haloperidol. The use of haloperidol is often associated with the occurrence of adverse drug reactions (ADRs), such as dyskinesia, acute dystonia, and orthostatic hypotension. Previous studies have demonstrated the relationship between the CYP2D6*4 genetic polymorphism and CYP2D6 activity, as well as haloperidol efficacy and safety rates.

Purpose

To evaluate the association of CYP2D6*4 genetic polymorphism with the steady-state concentration of haloperidol in patients with acute alcohol-induced psychotic disorders (AIPDs).

Material and methods

The study involved 100 male patients with AIPD (average age 41.4 ± 14.4 years) who received haloperidol by injections in a dose of 5-10 mg/day. The efficacy profile was assessed using a validated psychometric PANSS scale (Positive and Negative Syndrome Scale). Therapy safety was assessed using the internationally validated UKU (Side-Effect Rating Scale) and SAS (Simpson-Angus Scale for Extrapyramidal Symptoms) scales. Genotyping was performed with the real-time polymerase chain reaction.

Results

We revealed the statistically significant results in terms of therapy safety evaluation (dynamics of the UKU scores: (GG) 8.00 [7.00; 10.00], (GA) 15.0 [9.25; 18.0], p < 0.001; dynamics of the SAS scores: (GG) 11.0 [9.0; 14.0], (GA) 14.50 [12.0; 18.0], p < 0.001. Pharmacokinetic study showed a statistically significant difference across the groups with different genotypes: (GG) 3.13 [2.32; 3.95], (GA) 3.89 [2.92; 5.26], p = 0.010.

Conclusion

It can be concluded that patients with the GA genotype have a higher risk of ADRs compared to patients who carry the GG genotype. It was shown that CYP2D6*4 genetic polymorphism has a statistically significant effect on the steady-state concentration of haloperidol.

Developing Photoaffinity Probes for Dopamine Receptor D2 to Determine Targets of Parkinson's Disease Drugs

Dopaminergic pathways control highly consequential aspects of physiology and behavior. One of the most therapeutically important and best-studied receptors in these pathways is dopamine receptor D₂ (DRD2). Unfortunately, DRD2 is challenging to study with traditional molecular biological techniques, and most drugs designed to target DRD2 are ligands for many other receptors. Here, we developed probes able to both covalently bind to DRD2 using photoaffinity labeling and provide a chemical handle for detection or affinity purification. These probes behaved like good DRD2 agonists in traditional biochemical assays and were able to perform in chemical-biological assays of cell and receptor labeling. Rat whole brain labeling and affinity enrichment using the probes permitted proteomic analysis of the probes' interacting proteins. Bioinformatic study of the hits revealed that the probes bound noncanonically targeted proteins in Parkinson's disease network as well as the retrograde endocannabinoid signaling, neuronal nitric oxide synthase, muscarinic acetylcholine receptor M1, GABA receptor, and dopamine receptor D₁ (DRD1) signaling networks. Follow-up analysis may yield insights into how this pathway relates specifically to Parkinson's disease symptoms or provide new targets for treatments. This work reinforces the notion that the combination of chemical biology and omics-based approaches provides a broad picture of a molecule's "interactome" and may also give insight into the pleiotropy of effects observed for a drug or perhaps indicate new applications.

Dementia-Associated Compulsive Singing (DACS): Presentation of Unpublished Clinical Cases Miniseries

Dementia-associated compulsive singing (DACS) is a neurotransmettitorial-based behavioral disturbance, characterized by an unabating melodic expression, occurring in patients that suffer from evolved dementia. Previously described only as a "punding" aspect of the dopamine dysregulation syndrome (DDS) in the Parkinson's disease (PD), compulsive singing has now been described, for the first time, in four non-PD patients effectively treated with Haloperidol or Quetiapine. Unlike the DDS-associated conditions, in our cases DACS is not pharmacologically induced, being that all patients were L-dopa-free. We detected a diffuse hyperintensity of the white matter and brain atrophy, with insular shrinkage as well as ventricular system and/or sub-arachnoid space enlargement in our DACS patients. Furthermore, similarly to the other behavioral symptoms of dementia, DACS also seems to be correlated to the degree of cognitive and functional impairment, rather than its subtype. In conclusion, DACS is a non-cognitive, unpublished clinical aspect of evolved dementia, which is interesting due to the involvement of the extra-nigral dopaminergic system, resulting in an unabating altered behavior, but also to the enrichment of our knowledge in the involutional diseases of the central nervous system and their physiopathological manifestations.

Identification of Novel Dopamine D2 Receptor Ligands—A Combined In Silico/In Vitro Approach

Diseases of the central nervous system are an alarming global problem showing an increasing prevalence. Dopamine receptor D2 (D2R) has been shown to be involved in central nervous system diseases. While different D2R-targeting drugs have been approved by the FDA, they all suffer from major drawbacks due to promiscuous receptor activity leading to adverse effects. Increasing the number of potential D2R-targeting drug candidates bears the possibility of discovering molecules with less severe side-effect profiles. In dire need of novel D2R ligands for drug development, combined in silico/in vitro approaches have been shown to be efficient strategies. In this study, in silico pharmacophore models were generated utilizing both ligand- and structure-based approaches. Subsequently, different databases were screened for novel D2R ligands. Selected virtual hits were investigated in vitro, quantifying their binding affinity towards D2R. This workflow successfully identified six novel D2R ligands exerting micro- to nanomolar (most active compound KI = 4.1 nM) activities. Thus, the four pharmacophore models showed prospective true-positive hit rates in between 4.5% and 12%. The developed workflow and identified ligands could aid in developing novel drug candidates for D2R-associated pathologies.

Ligand recognition and biased agonism of the D1 dopamine receptor

Dopamine receptors are widely distributed in the central nervous system and are important therapeutic targets for treatment of various psychiatric and neurological diseases. Here, we report three cryo-electron microscopy structures of the D1 dopamine receptor (D1R)-Gs complex bound to two agonists, fenoldopam and tavapadon, and a positive allosteric modulator LY3154207. The structure reveals unusual binding of two fenoldopam molecules, one to the orthosteric binding pocket (OBP) and the other to the extended binding pocket (EBP). In contrast, one elongated tavapadon molecule binds to D1R, extending from OBP to EBP. Moreover, LY3154207 stabilizes the second intracellular loop of D1R in an alpha helical conformation to efficiently engage the G protein. Through a combination of biochemical, biophysical and cellular assays, we further show that the broad conformation stabilized by two fenoldopam molecules and interaction between TM5 and the agonist are important for biased signaling of D1R.

Evolutionary association of receptor-wide amino acids with G protein-coupling selectivity in aminergic GPCRs

Evolutionary analyses of aminergic G protein–coupled receptors reveal receptor-wide potential determinants of G protein–coupling selectivity.

G protein-coupled receptors (GPCRs) induce signal transduction pathways through coupling to four main subtypes of G proteins (G_s, G_i, G_q, and G_12/13), selectively. However, G protein selective activation mechanisms and residual determinants in GPCRs have remained obscure. Herein, we performed extensive phylogenetic analysis and identified specifically conserved residues for the aminergic receptors having similar coupling profiles. By integrating our methodology of differential evolutionary conservation of G protein–specific amino acids with structural analyses, we identified specific activation networks for G_s, G_i1, G_o, and G_q. To validate that these networks could determine coupling selectivity we further analyzed G_s-specific activation network and its association with G_s selectivity. Through molecular dynamics simulations, we showed that previously uncharacterized Glycine at position 7x41 plays an important role in receptor activation and it may determine G_s coupling selectivity by facilitating a larger TM6 movement. Finally, we gathered our results into a comprehensive model of G protein selectivity called “sequential switches of activation” describing three main molecular switches controlling GPCR activation: ligand binding, G protein selective activation mechanisms, and G protein contact.

Physicochemical Insights on Terahertz Wave Diminished Side Effects of Drugs from Slow Dissociation

Dopamine D2 receptors (D2Rs) are one of the most intensely investigated and well-established drug targets for neuropsychiatric disorders. Selective D2R antagonists have been developed as efficacious antipsychotic drugs. Nevertheless, the potent drugs with necessarily high affinity are prone to slow dissociation, which invokes a plethora of severe side effects such as extrapyramidal symptoms, substantial weight gain, associated diabetes, etc. This has become a major barrier in treating psychiatric patients. In this work, we propose a physical method, terahertz wave modulation, to promote the dissociation of high-affinity antipsychotics and thus diminish the side effects. We have proven that a 4.0 THz wave could reduce the affinity by 71% between the D2R and a risperidone ligand and meanwhile expand the exit via conformation modulation, which promises an accelerated dissociation of risperidone. In addition, it is estimated that the enhancement of the dissociation rate due to lowered binding by terahertz irritation could constitute up to 8 orders of magnitude, which is fairly impressive and resembles the enzyme's catalysis. Also, acceleration of the dissociation rate could be adjusted by the irritation strength. This work elaborates the terahertz wave-modulated noncovalent interactions critical in cell signaling pathways. Most importantly, it demonstrates the feasibility of terahertz technologies intervening in receptor-ligand complex regulated diseases such as neurodegenerative disorders, metabolic diseases, etc.

Creation of targeted compound libraries based on 3D shape recognition

In the emerging field of drug discovery, rapid virtual screening methods become extremely valuable, especially when dealing with ultra-large databases of organic small bioactive molecules. In this work, we present a fast, computationally resource-efficient, and simple workflow for screening targeted compound libraries generated from ultra-large virtual chemical space. This workflow aims to find compounds with similar molecular 3D shapes with reference ones, and at the same time to expand chemical diversity and to identify new and potentially active scaffolds. This pipeline ensures the enrichment of the generated libraries with novel chemotypes. Also, it was shown that delicate tailoring of the physicochemical parameters of the search set ensures that all library compounds will possess desired property distributions. A visual inspection has shown that found structures bind to the receptor in the same way as the reference ones. Using our screening workflow, we have created a number of conventional protein-targeted libraries: the GPCRs Targeted Library (531 K compounds) and the Protein Kinases Targeted Library (113 K compounds). The described pipeline and scripts are freely accessible at: https://github.com/ChemSpace-LLC/usrcat_sim .

Is styrene competitive for dopamine receptor binding?

The potential role of styrene oxide in altering the dopaminergic pathway in the ear is investigated by means of molecular docking and molecular dynamics simulations. We estimate the binding affinity of both styrene oxide and dopamine to the dopaminergic receptor DrD2 by computing the free-energy difference, ∆G, between the configuration where the ligand is bound to the receptor and the situation in which it is “infinitely” far away from it. The results show that the styrene oxide has a somewhat lower affinity for binding with respect to dopamine, which, however, may not be enough to prevent exogenous high concentration styrene oxide to compete with endogenous dopamine for DrD2 binding.

Memory Enhancement with Kynurenic Acid and Its Mechanisms in Neurotransmission

Kynurenic acid (KYNA) is an endogenous tryptophan (Trp) metabolite known to possess neuroprotective property. KYNA plays critical roles in nociception, neurodegeneration, and neuroinflammation. A lower level of KYNA is observed in patients with neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases or psychiatric disorders such as depression and autism spectrum disorders, whereas a higher level of KYNA is associated with the pathogenesis of schizophrenia. Little is known about the optimal concentration for neuroprotection and the threshold for neurotoxicity. In this study the effects of KYNA on memory functions were investigated by passive avoidance test in mice. Six different doses of KYNA were administered intracerebroventricularly to previously trained CFLP mice and they were observed for 24 h. High doses of KYNA (i.e., 20–40 μg/2 μL) significantly decreased the avoidance latency, whereas a low dose of KYNA (0.5 μg/2 μL) significantly elevated it compared with controls, suggesting that the low dose of KYNA enhanced memory function. Furthermore, six different receptor blockers were applied to reveal the mechanisms underlying the memory enhancement induced by KYNA. The series of tests revealed the possible involvement of the serotonergic, dopaminergic, α and β adrenergic, and opiate systems in the nootropic effect. This study confirmed that a low dose of KYNA improved a memory component of cognitive domain, which was mediated by, at least in part, four systems of neurotransmission in an animal model of learning and memory.

Fentanyl Structure as a Scaffold for Opioid/Non-Opioid Multitarget Analgesics

One of the strategies in the search for safe and effective analgesic drugs is the design of multitarget analgesics. Such compounds are intended to have high affinity and activity at more than one molecular target involved in pain modulation. In the present contribution we summarize the attempts in which fentanyl or its substructures were used as a μ-opioid receptor pharmacophoric fragment and a scaffold to which fragments related to non-opioid receptors were attached. The non-opioid ‘second’ targets included proteins as diverse as imidazoline I₂ binding sites, CB₁ cannabinoid receptor, NK₁ tachykinin receptor, D₂ dopamine receptor, cyclooxygenases, fatty acid amide hydrolase and monoacylglycerol lipase and σ₁ receptor. Reviewing the individual attempts, we outline the chemistry, the obtained pharmacological properties and structure-activity relationships. Finally, we discuss the possible directions for future work.

Ligand-directed bias of G protein signaling at the dopamine D2 receptor

G-protein-coupled receptors (GPCRs) represent the largest family of drug targets. Upon activation, GPCRs signal primarily via a diverse set of heterotrimeric G proteins. Most GPCRs can couple to several different G protein subtypes. However, how drugs act at GPCRs contributing to the selectivity of G protein recognition is poorly understood. Here, we examined the G protein selectivity profile of the dopamine D₂ receptor (D₂), a GPCR targeted by antipsychotic drugs. We show that D₂ discriminates between six individual members of the G_i/o family, and its profile of functional selectivity is remarkably different across its ligands, which all engaged D₂ with a distinct G protein coupling pattern. Using structural modeling, receptor mutagenesis, and pharmacological evaluation, we identified residues in the D₂ binding pocket that shape these ligand-directed biases. We further provide pharmacogenomic evidence that natural variants in D₂ differentially affect its G protein biases in response to different ligands.

Interactions of a boron-containing levodopa derivative on D2 dopamine receptor and its effects in a Parkinson disease model

Levodopa is a cornerstone in Parkinson's disease treatment. Beneficial effects are mainly by binding on D₂ receptors. Docking simulations of a set of compounds including well-known D₂-ligands and a pool of Boron-Containing Compounds (BCC), particularly boroxazolidones with a tri/tetra-coordinated boron atom, were performed on the D₂ Dopamine receptor (D2DR). Theoretical results yielded higher affinity of the compound DPBX, a Dopaboroxazolidone, than levodopa on D2DR. Essential interactions with residues in the third and sixth transmembrane domains of the D2DR appear to be crucial to induce and stabilize interactions in the active receptor state. Results from a motor performance evaluation of a murine model of Parkinson's disease agree with theoretical results, as DPBX showed similar efficacy to that of levodopa for diminishing MPTP-induced parkinsonism. This beneficial effect was disrupted with prior Risperidone (D2DR antagonist) administration, supporting the role of D2DR in the biological effect of DPBX. In addition, DPBX limited neuronal loss in substantia nigra in a similar manner to that of levodopa administration.

Crystal structure of the α1B-adrenergic receptor reveals molecular determinants of selective ligand recognition

α-adrenergic receptors (αARs) are G protein-coupled receptors that regulate vital functions of the cardiovascular and nervous systems. The therapeutic potential of αARs, however, is largely unexploited and hampered by the scarcity of subtype-selective ligands. Moreover, several aminergic drugs either show off-target binding to αARs or fail to interact with the desired subtype. Here, we report the crystal structure of human α_1BAR bound to the inverse agonist (+)-cyclazosin, enabled by the fusion to a DARPin crystallization chaperone. The α_1BAR structure allows the identification of two unique secondary binding pockets. By structural comparison of α_1BAR with α₂ARs, and by constructing α_1BAR-α_2CAR chimeras, we identify residues 3.29 and 6.55 as key determinants of ligand selectivity. Our findings provide a basis for discovery of α_1BAR-selective ligands and may guide the optimization of aminergic drugs to prevent off-target binding to αARs, or to elicit a selective interaction with the desired subtype.

This study reports the X-ray structure of the α_1B-adrenergic G protein-coupled receptor bound to an inverse agonist, and unveils key determinants of subtype-selective ligand binding that may help the design of aminergic drugs with fewer side-effects.

Potential Mechanisms for Why Not All Antipsychotics Are Able to Occupy Dopamine D3 Receptors in the Brain in vivo

Dysfunctions of the dopaminergic system are believed to play a major role in the core symptoms of schizophrenia such as positive, negative, and cognitive symptoms. The first line of treatment of schizophrenia are antipsychotics, a class of medications that targets several neurotransmitter receptors in the brain, including dopaminergic, serotonergic, adrenergic and/or muscarinic receptors, depending on the given agent. Although the currently used antipsychotics display in vitro activity at several receptors, majority of them share the common property of having high/moderate in vitro affinity for dopamine D₂ receptors (D₂Rs) and D₃ receptors (D₃Rs). In terms of mode of action, these antipsychotics are either antagonist or partial agonist at the above-mentioned receptors. Although D₂Rs and D₃Rs possess high degree of homology in their molecular structure, have common signaling pathways and similar in vitro pharmacology, they have different in vivo pharmacology and therefore behavioral roles. The aim of this review, with summarizing preclinical and clinical evidence is to demonstrate that while currently used antipsychotics display substantial in vitro affinity for both D₃Rs and D₂Rs, only very few can significantly occupy D₃Rs in vivo. The relative importance of the level of endogenous extracellular dopamine in the brain and the degree of in vitro D₃Rs receptor affinity and selectivity as determinant factors for in vivo D₃Rs occupancy by antipsychotics, are also discussed.

Evidence for Two Modes of Binding of the Negative Allosteric Modulator SB269,652 to the Dopamine D2 Receptor

SB269,652 has been described as the first negative allosteric modulator (NAM) of the dopamine D₂ receptor (D₂R), however, the binding mode and allosteric mechanism of action of this ligand remain incompletely understood. SB269,652 comprises an orthosteric, primary pharmacophore and a secondary (or allosteric) pharmacophore joined by a hydrophilic cyclohexyl linker and is known to form corresponding interactions with the orthosteric binding site (OBS) and the secondary binding pocket (SBP) in the D₂R. Here, we observed a surprisingly low potency of SB269,652 to negatively modulate the D₂R-mediated activation of G protein-coupled inward-rectifier potassium channels (GIRK) and decided to perform a more detailed investigation of the interaction between dopamine and SB269,652. The results indicated that the SB269,652 inhibitory potency is increased 6.6-fold upon ligand pre-incubation, compared to the simultaneous co-application with dopamine. Mutagenesis experiments implicated both S193 in the OBS and E95 in the SBP in the effect of pre-application. The present findings extend previous knowledge about how SB269,652 competes with dopamine at the D₂R and may be useful for the development of novel D₂R ligands, such as antipsychotic drug candidates.

Leveraging nonstructural data to predict structures and affinities of protein-ligand complexes

Structure-based drug design depends on the ability to predict both the three-dimensional structures of candidate molecules bound to their targets and the associated binding affinities. We demonstrate that one can substantially improve the accuracy of these predictions using easily obtained data about completely different molecules that bind to the same target without requiring any target-bound structures of these molecules. The approach we developed to integrate physical and data-driven modeling may find a variety of applications in the rapidly growing field of artificial intelligence for drug discovery.

Over the past five decades, tremendous effort has been devoted to computational methods for predicting properties of ligands—i.e., molecules that bind macromolecular targets. Such methods, which are critical to rational drug design, fall into two categories: physics-based methods, which directly model ligand interactions with the target given the target’s three-dimensional (3D) structure, and ligand-based methods, which predict ligand properties given experimental measurements for similar ligands. Here, we present a rigorous statistical framework to combine these two sources of information. We develop a method to predict a ligand’s pose—the 3D structure of the ligand bound to its target—that leverages a widely available source of information: a list of other ligands that are known to bind the same target but for which no 3D structure is available. This combination of physics-based and ligand-based modeling improves pose prediction accuracy across all major families of drug targets. Using the same framework, we develop a method for virtual screening of drug candidates, which outperforms standard physics-based and ligand-based virtual screening methods. Our results suggest broad opportunities to improve prediction of various ligand properties by combining diverse sources of information through customized machine-learning approaches.

Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation

Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and subsequently demonstrated that the inhibition of myofibroblast activation is able to prevent lung fibrosis in bleomycin-treated mice. High-throughput screens are an ideal method of repurposing drugs, yet they contain an intrinsic limitation, which is the size of the library itself. Here, we exploited the data from our "wet" screen and used "dry" machine learning analysis to virtually screen millions of compounds, identifying novel anti-fibrotic hits which target myofibroblast differentiation, many of which were structurally related to dopamine. We synthesized and validated several compounds ex vivo ("wet") and confirmed that both dopamine and its derivative TS1 are powerful inhibitors of myofibroblast activation. We further used RNAi-mediated knock-down and demonstrated that both molecules act through the dopamine receptor 3 and exert their anti-fibrotic effect by inhibiting the canonical transforming growth factor β pathway. Furthermore, molecular modelling confirmed the capability of TS1 to bind both human and mouse dopamine receptor 3. The anti-fibrotic effect on human cells was confirmed using primary fibroblasts from idiopathic pulmonary fibrosis patients. Finally, TS1 prevented and reversed disease progression in a murine model of lung fibrosis. Both our interdisciplinary approach and our novel compound TS1 are promising tools for understanding and combating lung fibrosis.

Structure-based design of a novel third-generation antipsychotic drug lead with potential antidepressant properties

Partial agonist activity at the dopamine D₂ receptor (DRD2) is a key feature of third-generation antipsychotics (TGAs). However, TGAs also act as antagonists or weak partial agonists to the serotonin (5-hydroxytryptamine; 5-HT) 2A receptor (5-HT_2AR). Here we present the crystal structures of aripiprazole- and cariprazine-bound human 5-HT_2AR. Both TGAs adopt an unexpected 'upside-down' pose in the 5-HT_2AR binding pocket, with secondary pharmacophores inserted in a similar way to a 'bolt'. This insight into the binding modes of TGAs offered a structural mechanism underlying their varied partial efficacies at 5-HT_2AR and DRD2. These structures enabled the design of a partial agonist at DRD2/3 and 5-HT_1AR with negligible 5-HT_2AR binding that displayed potent antipsychotic-like activity without motor side effects in mice. This TGA lead also had antidepressant-like effects and improved cognitive performance in mouse models via 5-HT_1AR. This work indicates that 5-HT_2AR affinity is a dispensable contributor to the therapeutic actions of TGAs.

2-Phenylcyclopropylmethylamine Derivatives as Dopamine D2 Receptor Partial Agonists: Design, Synthesis, and Biological Evaluation

Partial agonist activity at the dopamine D₂ receptor (D₂R) is the primary pharmacological feature of the third-generation antipsychotics─aripiprazole, brexpiprazole, and cariprazine. However, all these drugs share a common phenyl-piperazine moiety as the primary pharmacophore. In this study, we designed and synthesized a series of novel compounds based on the 2-phenylcyclopropylmethylamine (PCPMA) scaffold and studied their pharmacological activity at the D₂R. A number of potent D₂R partial agonists were identified through binding affinity screening and functional activity profiling in both G protein and β-arrestin assays. The structure-functional activity relationship results showed that the spacer group is crucial for fine-tuning the intrinsic activity of these compounds. Compounds (+)-14j and (+)-14l showed good pharmacokinetic properties and an unexpected selectivity against the serotonin 2A (5-HT_2A) receptor. Preliminary suppressive effects in a mouse hyperlocomotion model proved that these PCPMA-derived D₂R partial agonists are effective as potential novel antipsychotics.

De Novo Structure-Based Drug Design Using Deep Learning

In recent years, deep learning-based methods have emerged as promising tools for de novo drug design. Most of these methods are ligand-based, where an initial target-specific ligand data set is necessary to design potent molecules with optimized properties. Although there have been attempts to develop alternative ways to design target-specific ligand data sets, availability of such data sets remains a challenge while designing molecules against novel target proteins. In this work, we propose a deep learning-based method, where the knowledge of the active site structure of the target protein is sufficient to design new molecules. First, a graph attention model was used to learn the structure and features of the amino acids in the active site of proteins that are experimentally known to form protein-ligand complexes. Next, the learned active site features were used along with a pretrained generative model for conditional generation of new molecules. A bioactivity prediction model was then used in a reinforcement learning framework to optimize the conditional generative model. We validated our method against two well-studied proteins, Janus kinase 2 (JAK2) and dopamine receptor D2 (DRD2), where we produce molecules similar to the known inhibitors. The graph attention model could identify the probable key active site residues, which influenced the conditional molecule generator to design new molecules with pharmacophoric features similar to the known inhibitors.

Structure-based design of haloperidol analogues as inhibitors of acetyltransferase Eis from Mycobacterium tuberculosis to overcome kanamycin resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a deadly bacterial disease. Drug-resistant strains of Mtb make eradication of TB a daunting task. Overexpression of the enhanced intracellular survival (Eis) protein by Mtb confers resistance to the second-line antibiotic kanamycin (KAN). Eis is an acetyltransferase that acetylates KAN, inactivating its antimicrobial function. Development of Eis inhibitors as KAN adjuvant therapeutics is an attractive path to forestall and overcome KAN resistance. We discovered that an antipsychotic drug, haloperidol (HPD, 1), was a potent Eis inhibitor with IC₅₀ = 0.39 ± 0.08 μM. We determined the crystal structure of the Eis-haloperidol (1) complex, which guided synthesis of 34 analogues. The structure-activity relationship study showed that in addition to haloperidol (1), eight analogues, some of which were smaller than 1, potently inhibited Eis (IC₅₀ ≤ 1 μM). Crystal structures of Eis in complexes with three potent analogues and droperidol (DPD), an antiemetic and antipsychotic, were determined. Three compounds partially restored KAN sensitivity of a KAN-resistant Mtb strain K204 overexpressing Eis. The Eis inhibitors generally did not exhibit cytotoxicity against mammalian cells. All tested compounds were modestly metabolically stable in human liver microsomes, exhibiting 30-60% metabolism over the course of the assay. While direct repurposing of haloperidol as an anti-TB agent is unlikely due to its neurotoxicity, this study reveals potential approaches to modifying this chemical scaffold to minimize toxicity and improve metabolic stability, while preserving potent Eis inhibition.

Optimizing the Expression of Human Dopamine Receptors in Escherichia coli

The human dopamine receptors D_2S and D₃ belong to the group of G protein-coupled receptors (GPCRs) and are important drug targets. Structural analyses and development of new receptor subtype specific drugs have been impeded by low expression yields or receptor instability. Fusing the T4 lysozyme into the intracellular loop 3 improves crystallization but complicates conformational studies. To circumvent these problems, we expressed the human D_2S and D₃ receptors in Escherichia coli using different N- and C-terminal fusion proteins and thermostabilizing mutations. We optimized expression times and used radioligand binding assays with whole cells and membrane homogenates to evaluate K_D-values and the number of receptors in the cell membrane. We show that the presence but not the type of a C-terminal fusion protein is important. Bacteria expressing receptors capable of ligand binding can be selected using FACS analysis and a fluorescently labeled ligand. Improved receptor variants can thus be generated using error-prone PCR. Subsequent analysis of clones showed the distribution of mutations over the whole gene. Repeated cycles of PCR and FACS can be applied for selecting highly expressing receptor variants with high affinity ligand binding, which in the future can be used for analytical studies.

De novo design with deep generative models based on 3D similarity scoring

We have demonstrated the utility of a 3D shape and pharmacophore similarity scoring component in molecular design with a deep generative model trained with reinforcement learning. Using Dopamine receptor type 2 (DRD2) as an example and its antagonist haloperidol 1 as a starting point in a ligand based design context, we have shown in a retrospective study that a 3D similarity enabled generative model can discover new leads in the absence of any other information. It can be efficiently used for scaffold hopping and generation of novel series. 3D similarity based models were compared against 2D QSAR based, indicating a significant degree of orthogonality of the generated outputs and with the former having a more diverse output. In addition, when the two scoring components are combined together for training of the generative model, it results in more efficient exploration of desirable chemical space compared to the individual components.

Docking Screens of Noncovalent Interaction Motifs of the Human Subtype-D2 Receptor-75 Schizophrenia Antipsychotic Complexes with Physicochemical Appraisal of Antipsychotics

Chemoinformatics appraisal and molecular docking were employed to investigate 225 complexes of 75 schizophrenia antipsychotics with the dopamine receptor subtypes D2R, D3R, and D4R. Considering the effective noncovalent interactions in the subtype-D2 receptor selectivity of antipsychotics, this study evaluated the possible physicochemical properties of ligands underlying the design of safer and more effective antipsychotics. The pan-assay interference compounds (PAINs) include about 25% of typical antipsychotics and 5% of atypicals. Popular antipsychotics like haloperidol, clozapine, risperidone, and aripiprazole are not PAINs. They have stronger interactions with D2R and D4R, but their interactions with D3R are slightly weaker, which is similar to the behavior of dopamine. In contrast to typical antipsychotics, atypical antipsychotics exhibit more noncovalent interactions with D4R than with D2R. These results suggest that selectivity to D2R and D4R comes from the synergy between hydrophobic and hydrogen-bonding interactions through their concomitant occurrence in the form of a hydrogen-bonding site adorned with hydrophobic contacts in antipsychotic-receptor complexes. All the antipsychotics had more synergic interactions with D2R and D4R in comparison with D3R. The atypical antipsychotics made a good distinction between the subtype D2 receptors with high selectivity to D4R. Among the popular antipsychotics, haloperidol, clozapine, and risperidone have hydrophobic-hydrogen-bonding synergy with D4R, while aripiprazole profits with D2R. The most important residue participating in the synergic interactions was threonine for D2R and cysteine for D4R. This work could be useful in informing and guiding future drug discovery and development studies aimed at receptor-specific antipsychotics.

Molecular Dynamics Simulations for the Determination of the Characteristic Structural Differences between Inactive and Active States of Wild Type and Mutants of the Orexin2 Receptor

The orexin2 receptor (OX2R), which is classified as a class A G protein-coupled receptor (GPCR), is the target of our study. We performed over 20 several-microsecond-scale molecular dynamics simulations of the wild type and mutants of OX2R to extract the characteristics of the structural changes taking place in the active state. We introduced mutations that exhibited the stable inactive state and the constitutively active state in class A GPCRs. In these simulations, significant characteristic structural changes were observed in the V309^6.40Y mutant, which corresponded to a constitutively active mutant. These conformational changes include the outward movement of the transmembrane helix 6 (TM6) and the inward movement of TM7, which are common structural changes in the activation of GPCRs. In addition, we extracted a suitable index for the quantitative evaluation of the active and inactive states of GPCRs, namely, the inter-atomic distance of Cα atoms between x(3.46) and Y(7.53). The structures of the inactive and active states solved by X-ray crystallography and cryo-electron microscopy can be classified using the inter-atomic distance. Furthermore, we clarified that the inward movement of TM7 requires the swapping of M305^6.36 on TM6 and L367^7.56 on TM7. Finally, we discussed the structural advantages of TM7 inward movement for GPCR activation.

Controlling the selectivity of aminergic GPCR ligands from the extracellular vestibule

In addition to the orthosteric binding pocket (OBP) of GPCRs, recent structural studies have revealed that there are several allosteric sites available for pharmacological intervention. The secondary binding pocket (SBP) of aminergic GPCRs is located in the extracellular vestibule of these receptors, and it has been suggested to be a potential selectivity pocket for bitopic ligands. Here, we applied a virtual screening protocol based on fragment docking to the SBP of the orthosteric ligand-receptor complex. This strategy was employed for a number of aminergic receptors. First, we designed dopamine D₃ preferring bitopic compounds from a D₂ selective orthosteric ligand. Next, we designed 5-HT_2B selective bitopic compounds starting from the 5-HT_1B preferring ergoline core of LSD. Comparing the serotonergic profiles of the new derivatives to that of LSD, we found that these derivatives became significantly biased towards the desired 5-HT_2B receptor target. Finally, addressing the known limitations of H₁ antihistamines, our protocol was successfully used to eliminate the well-known side effects related to the muscarinic M₁ activity of amitriptyline while preserving H₁ potency in some of the designed bitopic compounds. These applications highlight the usefulness of our new virtual screening protocol and offer a powerful strategy towards bitopic GPCR ligands with designed receptor profiles.