Drugging specific conformational states of GPCRs: challenges and opportunities for computational chemistry

Relevance of G protein-coupled receptor (GPCR) dynamics for receptor activation, signalling bias and allosteric modulation

G protein-coupled receptors (GPCRs) are one of the major drug targets. In recent years, computational drug design for GPCRs has mainly focused on static structures obtained through X-ray crystallography, cryogenic electron microscopy (cryo-EM) or in silico modelling as a starting point for virtual screening campaigns. However, GPCRs are highly flexible entities with the ability to adopt different conformational states that elicit different physiological responses. Including this knowledge in the drug discovery pipeline can help to tailor novel conformation-specific drugs with an improved therapeutic profile. In this review, we outline our current knowledge about GPCR dynamics that is relevant for receptor activation, signalling bias and allosteric modulation. Ultimately, we highlight new technological implementations such as time-resolved X-ray crystallography and cryo-EM as well as computational algorithms that can contribute to a more comprehensive understanding of receptor dynamics and its relevance for GPCR functionality.

Effects of pH on opioid receptor activation and implications for drug design

G-protein-coupled receptors are integral membrane proteins that transduce chemical signals from the extracellular matrix into the cell. Traditional drug design has considered ligand-receptor interactions only under normal conditions. However, studies on opioids indicate that such interactions are very different in diseased tissues. In such microenvironments, protons play an important role in structural and functional alterations of both ligands and receptors. The pertinent literature strongly suggests that future drug design should take these aspects into account in order to reduce adverse side effects while preserving desired effects of novel compounds.

Structure and function of an intermediate GPCR-Gαβγ complex

Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-Gαβγ structures, these snapshots primarily capture the fully activated end-state complex. Consequently, a comprehensive understanding of the conformational transitions during GPCR activation and the roles of intermediate GPCR-G protein complexes in signaling remain elusive. Guided by a conformational landscape profiled by 19 F quantitative NMR ( 19 F-qNMR) and Molecular Dynamics (MD) simulations, we resolved the structure of an unliganded GPCR-G protein intermediate complex by blocking its transition to the fully activated end-state complex. More importantly, we presented direct evidence that the intermediate GPCR-Gαsβγ complex initiates a rate-limited nucleotide exchange without progressing to the fully activated end-state complex, thereby bridging a significant gap in our understanding the complexity of GPCR signaling. Understanding the roles of individual conformational states and their complexes in signaling efficacy and bias will help us to design drugs that discriminately target a disease-related conformation.

In Silico Study of Allosteric Communication Networks in GPCR Signaling Bias

Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias.

Accelerating GPCR Drug Discovery With Conformation-Stabilizing VHHs

The human genome encodes 850 G protein-coupled receptors (GPCRs), half of which are considered potential drug targets. GPCRs transduce extracellular stimuli into a plethora of vital physiological processes. Consequently, GPCRs are an attractive drug target class. This is underlined by the fact that approximately 40% of marketed drugs modulate GPCRs. Intriguingly 60% of non-olfactory GPCRs have no drugs or candidates in clinical development, highlighting the continued potential of GPCRs as drug targets. The discovery of small molecules targeting these GPCRs by conventional high throughput screening (HTS) campaigns is challenging. Although the definition of success varies per company, the success rate of HTS for GPCRs is low compared to other target families (Fujioka and Omori, 2012; Dragovich et al., 2022). Beyond this, GPCR structure determination can be difficult, which often precludes the application of structure-based drug design approaches to arising HTS hits. GPCR structural studies entail the resource-demanding purification of native receptors, which can be challenging as they are inherently unstable when extracted from the lipid matrix. Moreover, GPCRs are flexible molecules that adopt distinct conformations, some of which need to be stabilized if they are to be structurally resolved. The complexity of targeting distinct therapeutically relevant GPCR conformations during the early discovery stages contributes to the high attrition rates for GPCR drug discovery programs. Multiple strategies have been explored in an attempt to stabilize GPCRs in distinct conformations to better understand their pharmacology. This review will focus on the use of camelid-derived immunoglobulin single variable domains (VHHs) that stabilize disease-relevant pharmacological states (termed ConfoBodies by the authors) of GPCRs, as well as GPCR:signal transducer complexes, to accelerate drug discovery. These VHHs are powerful tools for supporting in vitro screening, deconvolution of complex GPCR pharmacology, and structural biology purposes. In order to demonstrate the potential impact of ConfoBodies on translational research, examples are presented of their role in active state screening campaigns and structure-informed rational design to identify de novo chemical space and, subsequently, how such matter can be elaborated into more potent and selective drug candidates with intended pharmacology.

Disentangling bias between Gq, GRK2, and arrestin3 recruitment to the M3 muscarinic acetylcholine receptor

G protein-coupled receptors (GPCRs) transmit extracellular signals to the inside by activation of intracellular effector proteins. Different agonists can promote differential receptor-induced signaling responses – termed bias – potentially by eliciting different levels of recruitment of effector proteins. As activation and recruitment of effector proteins might influence each other, thorough analysis of bias is difficult. Here, we compared the efficacy of seven agonists to induce G protein, G protein-coupled receptor kinase 2 (GRK2), as well as arrestin3 binding to the muscarinic acetylcholine receptor M₃ by utilizing FRET-based assays. In order to avoid interference between these interactions, we studied GRK2 binding in the presence of inhibitors of G_i and G_q proteins and analyzed arrestin3 binding to prestimulated M₃ receptors to avoid differences in receptor phosphorylation influencing arrestin recruitment. We measured substantial differences in the agonist efficacies to induce M₃R-arrestin3 versus M₃R-GRK2 interaction. However, the rank order of the agonists for G protein- and GRK2-M₃R interaction was the same, suggesting that G protein and GRK2 binding to M₃R requires similar receptor conformations, whereas requirements for arrestin3 binding to M₃R are distinct.

A practical guide to large-scale docking

Structure-based docking screens of large compound libraries have become common in early drug and probe discovery. As computer efficiency has improved and compound libraries have grown, the ability to screen hundreds of millions, and even billions, of compounds has become feasible for modest-sized computer clusters. This allows the rapid and cost-effective exploration and categorization of vast chemical space into a subset enriched with potential hits for a given target. To accomplish this goal at speed, approximations are used that result in undersampling of possible configurations and inaccurate predictions of absolute binding energies. Accordingly, it is important to establish controls, as are common in other fields, to enhance the likelihood of success in spite of these challenges. Here we outline best practices and control docking calculations that help evaluate docking parameters for a given target prior to undertaking a large-scale prospective screen, with exemplification in one particular target, the melatonin receptor, where following this procedure led to direct docking hits with activities in the subnanomolar range. Additional controls are suggested to ensure specific activity for experimentally validated hit compounds. These guidelines should be useful regardless of the docking software used. Docking software described in the outlined protocol (DOCK3.7) is made freely available for academic research to explore new hits for a range of targets.

Ligand with Two Modes of Interaction with the Dopamine D2 Receptor-An Induced-Fit Mechanism of Insurmountable Antagonism

A solid understanding of the mechanisms governing ligand binding is crucial for rational design of therapeutics targeting the dopamine D₂ receptor (D₂R). Here, we use G protein-coupled inward rectifier potassium (GIRK) channel activation in Xenopus oocytes to measure the kinetics of D₂R antagonism by a series of aripiprazole analogues, as well as the recovery of dopamine (DA) responsivity upon washout. The aripiprazole analogues comprise an orthosteric and a secondary pharmacophore and differ by the length of the saturated carbon linker joining these two pharmacophores. Two compounds containing 3- and 5-carbon linkers allowed for a similar extent of recovery from antagonism in the presence of 1 or 100 μM DA (>25 and >90% of control, respectively), whereas recovery was less prominent (∼20%) upon washout of the 4-carbon linker compound, SV-III-130, both with 1 and 100 μM DA. Prolonging the coincubation time with SV-III-130 further diminished recovery. Curve-shift experiments were consistent with competition between SV-III-130 and DA. Two mutations in the secondary binding pocket (V91A and E95A) of D₂R decreased antagonistic potency and increased recovery from SV-III-130 antagonism, whereas a third mutation (L94A) only increased recovery. Our results suggest that the secondary binding pocket influences recovery from inhibition by the studied aripiprazole analogues. We propose a mechanism, supported by in silico modeling, whereby SV-III-130 initially binds reversibly to the D₂R, after which the drug-receptor complex undergoes a slow transition to a second ligand-bound state, which is dependent on secondary binding pocket integrity and irreversible during the time frame of our experiments.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

G Protein-Coupled Receptors in Asthma Therapy: Pharmacology and Drug Action

Asthma is a heterogeneous inflammatory disease of the airways that is associated with airway hyperresponsiveness and airflow limitation. Although asthma was once simply categorized as atopic or nonatopic, emerging analyses over the last few decades have revealed a variety of asthma endotypes that are attributed to numerous pathophysiological mechanisms. The classification of asthma by endotype is primarily routed in different profiles of airway inflammation that contribute to bronchoconstriction. Many asthma therapeutics target G protein-coupled receptors (GPCRs), which either enhance bronchodilation or prevent bronchoconstriction. Short-acting and long-acting β 2-agonists are widely used bronchodilators that signal through the activation of the β 2-adrenergic receptor. Short-acting and long-acting antagonists of muscarinic acetylcholine receptors are used to reduce bronchoconstriction by blocking the action of acetylcholine. Leukotriene antagonists that block the signaling of cysteinyl leukotriene receptor 1 are used as an add-on therapy to reduce bronchoconstriction and inflammation induced by cysteinyl leukotrienes. A number of GPCR-targeting asthma drug candidates are also in different stages of development. Among them, antagonists of prostaglandin D2 receptor 2 have advanced into phase III clinical trials. Others, including antagonists of the adenosine A2B receptor and the histamine H4 receptor, are in early stages of clinical investigation. In the past decade, significant research advancements in pharmacology, cell biology, structural biology, and molecular physiology have greatly deepened our understanding of the therapeutic roles of GPCRs in asthma and drug action on these GPCRs. This review summarizes our current understanding of GPCR signaling and pharmacology in the context of asthma treatment. SIGNIFICANCE STATEMENT: Although current treatment methods for asthma are effective for a majority of asthma patients, there are still a large number of patients with poorly controlled asthma who may experience asthma exacerbations. This review summarizes current asthma treatment methods and our understanding of signaling and pharmacology of G protein-coupled receptors (GPCRs) in asthma therapy, and discusses controversies regarding the use of GPCR drugs and new opportunities in developing GPCR-targeting therapeutics for the treatment of asthma.

Allosteric modulation of the sarcoplasmic reticulum Ca2+ ATPase by thapsigargin via decoupling of functional motions

The sarcoplasmic reticulum Ca2+-ATPase (SERCA) is a widely studied member of the large family of phosphorylation(P)-type ATPase membrane transporters. Ligands and nucleotide binding naturally modulate the conformational space of P-type ATPases through allosteric inter-domain communications. Whereas many inhibitory ATPase ligands act by directly blocking substrate uptake or release, SERCA is a target for thapsigargin (TG), a plant-derived natural product that allosterically inhibits the transport cycle. While thapsigargin's inhibitory effects on SERCA have been widely studied experimentally, the molecular mechanisms underlying these remain incompletely understood. Here, we apply modelling and molecular simulations to probe the effects of TG binding to the major functional states along SERCA's reaction cycle. Our results provide insight into the atomic-level details of the conformational changes induced by TG binding to SERCA, and suggest mechanisms for its effect. Since other P-type ATPases share closely related reaction cycles, our data suggests that similar modulators might exist for these.

Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots

G-protein coupled receptors (GPCRs) play a pivotal role in transmitting signals at the cellular level. Structural insights can be exploited to support GPCR structure-based drug discovery endeavours. Despite advances in GPCR crystallography, active state structures are scarce. Molecular dynamics (MD) simulations have been used to explore the conformational landscape of GPCRs. Efforts have been made to retrieve active state conformations starting from inactive structures, however to date this has not been possible without using an energy bias. Here, we reconstruct the activation pathways of the apo adenosine receptor (A2A), starting from an inactive conformation, by applying adaptive sampling MD combined with a goal-oriented scoring function. The reconstructed pathways reconcile well with experiments and help deepen our understanding of A2A regulatory mechanisms. Exploration of the apo conformational landscape of A2A reveals the existence of ligand-competent states, active intermediates and state-dependent cholesterol hotspots of relevance for drug discovery. To the best of our knowledge this is the first time an activation process has been elucidated for a GPCR starting from an inactive structure only, using a non-biased MD approach, opening avenues for the study of ligand binding to elusive yet pharmacologically relevant GPCR states.

Nanobodies: New avenues for imaging, stabilizing and modulating GPCRs

The family of G protein-coupled receptors (GPCRs) is the largest class of membrane proteins and an important drug target due to their role in many (patho)physiological processes. Besides small molecules, GPCRs can be targeted by biologicals including antibodies and antibody fragments. This review describes the use of antibodies and in particular antibody fragments from camelid-derived heavy chain-only antibodies (nanobodies/VHHs/sdAbs) for detecting, stabilizing, modulating and therapeutically targeting GPCRs. Altogether, it becomes increasingly clear that the small size, structure and protruding antigen-binding loops of nanobodies are favorable features for the development of selective and potent GPCRs-binding molecules. This makes them attractive tools to modulate GPCR activity but also as targeting modalities for GPCR-directed therapeutics. In addition, these antibody-fragments are important tools in the stabilization of particular conformations of these receptors. Lastly, nanobodies, in contrast to conventional antibodies, can also easily be expressed intracellularly which render nanobodies important tools for studying GPCR function. Hence, GPCR-targeting nanobodies are ideal modalities to image, stabilize and modulate GPCR function.

Biased Agonist TRV027 Determinants in AT1R by Molecular Dynamics Simulations

Functional selectivity is a phenomenon observed in G protein-coupled receptors in which intermediate active-state conformations are stabilized by mutations or ligand binding, resulting in different sets of signaling pathways. Peptides capable of selectively activating β-arrestin, known as biased agonists, have already been characterized in vivo and could correspond to a new therapeutic approach for treatment of cardiovascular diseases. Despite the potential of biased agonism, the mechanism involved in selective signaling remains unclear. In this work, molecular dynamics simulations were employed to compare the conformational profile of the angiotensin II type 1 receptor (AT1R) crystal bound to angiotensin II, bound to the biased ligand TRV027, and in the apo form. Our results show that both ligands induce changes near the NPxxY motif in transmembrane domain 7 that are related to receptor activation. However, the biased ligand does not cause the rotamer toggle alternative positioning and displays an exclusive hydrogen-bonding pattern. Our work sheds light on the biased agonism mechanism and will help in the future design of novel biased agonists for AT1R.

Exploring a new ligand binding site of G protein-coupled receptors

Identifying a target ligand binding site is an important step for structure-based rational drug design as shown here for G protein-coupled receptors (GPCRs), which are among the most popular drug targets. We applied long-time scale molecular dynamics simulations, coupled with mutagenesis studies, to two prototypical GPCRs, the M3 and M4 muscarinic acetylcholine receptors. Our results indicate that unlike synthetic antagonists, which bind to the classic orthosteric site, the endogenous agonist acetylcholine is able to diffuse into a much deeper binding pocket. We also discovered that the most recently resolved crystal structure of the LTB4 receptor comprised a bound inverse agonist, which extended its benzamidine moiety to the same binding pocket discovered in this work. Analysis on all resolved GPCR crystal structures indicated that this new pocket could exist in most receptors. Our findings provide new opportunities for GPCR drug discovery.

Computational modeling approaches to quantitative structure-binding kinetics relationships in drug discovery

Simple comparative correlation analyses and quantitative structure-kinetics relationship (QSKR) models highlight the interplay of kinetic rates and binding affinity as an essential feature in drug design and discovery. The choice of the molecular series, and their structural variations, used in QSKR modeling is fundamental to understanding the mechanistic implications of ligand and/or drug-target binding and/or unbinding processes. Here, we discuss the implications of linear correlations between kinetic rates and binding affinity constants and the relevance of the computational approaches to QSKR modeling.

Developing a Biased Unmatched Bivalent Ligand (BUmBL) Design Strategy to Target the GPCR Homodimer Allosteric Signaling (cAMP over β-Arrestin 2 Recruitment) Within the Melanocortin Receptors

Understanding the functional relevance of G protein-coupled receptor (GPCR) homodimerization has been limited by the insufficient tools to assess asymmetric signaling occurring within dimers comprised of the same receptor type. We present unmatched bivalent ligands (UmBLs) to study the asymmetric function of melanocortin homodimers. UmBLs contain one agonist and one antagonist pharmacophore designed to target a melanocortin homodimer such that one receptor is occupied by an agonist and the other receptor by an antagonist pharmacophore. First-in-class biased UmBLs (BUmBLs) targeting the human melanocortin-4 receptor (hMC4R) were discovered. The BUmBLs displayed biased agonism by potently stimulating cAMP signaling (EC₅₀ ∼ 2-6 nM) but minimally activating the β-arrestin recruitment pathway (≤55% maximum signal at 10 μM). To our knowledge, we report the first single-compound strategy to pharmacologically target melanocortin receptor allosteric signaling that occurs between homodimers that can be applied straightforwardly in vitro and in vivo to other GPCR systems.

Ligand-binding characterization of simulated β-adrenergic-like octopamine receptor in Schistocerca gregaria via progressive structure simulation

It is important to design insecticides having both low drug resistance and less undesirable toxicity for desert locust control. Specific GPCRs of Schistocerca gregaria, especially β-adrenergic-like octopamine receptor (SgOctβR), can be considered as its potential effective insecticide targets. However, either the unavailability of SgOctβR's structure or the inadequate capability of its sequence lead the development of insecticide for Schistocerca gregaria meets its plateau. To relax this difficulty, this paper develops a promising progressive structure simulation from SgOctβR's sequence, to its predicted structure of SgOctβR in vacuum, to its conformation as well as its complex with endogenous ligand octopamine in a solvent-membrane system. The combined approach of multiple sequence alignment, static structural characterization, and dynamic process of conformational change during binding octopamine reveal three important aspects. The first one is the characterization of SgOctβR's active pocket, including the attending secondary structure elements, its hydrophobic residues and nonpolar surface. The second one is the interaction with octopamine, especially the involved hydrogen bonds and an aromatic stacking of pi-pi interactions. The third one is the potential binding sites, including six highly conserved residues and one highly variable residue for locust insecticide design. This work is definitely helpful for the further structure-based drug design for efficient and eco-friendly insecticides, as well as site-directed mutagenesis biochemical research of SgOctβR.

Investigating allosteric effects on the functional dynamics of β2-adrenergic ternary complexes with enhanced-sampling simulations

Signalling by G-protein coupled receptors usually occurs via ternary complexes formed under cooperative binding between the receptor, a ligand and an intracellular binding partner (a G-protein or β-arrestin). While a global rational for allosteric effects in ternary complexes would be of great help in designing ligands with specific effects, the paucity of structural data for ternary complexes with β-arrestin, together with the intrinsic difficulty of characterizing the dynamics involved in the allosteric coupling, have hindered the efforts to devise such a model. Here we have used enhanced-sampling atomistic molecular-dynamics simulations to investigate the dynamics and complex formation mechanisms of both β-arrestin- and Gs-complexes with the β2-adrenergic receptor (ADRB2) in its apo-form and in the presence of four small ligands that exert different allosteric effects. Our results suggest that the structure and dynamics of arrestin-ADRB2 complexes depend strongly on the nature of the small ligands. The complexes exhibit a variety of different coupling orientations in terms of the depth of the finger loop in the receptor and activation states of ADRB2. The simulations also allow us to characterize the cooperativity between the ligand and intracellular binding partner (IBP). Based on the complete and consistent results, we propose an experimentally testable extended ternary complex model, where direction of the cooperative effect between ligand and IBP (positive or negative) and its magnitude are predicted to be a characteristic of the ligand signaling bias. This paves the avenue to the rational design of ligands with specific functional effects.

Leveraging allostery to improve G protein-coupled receptor (GPCR)-directed therapeutics: cannabinoid receptor 1 as discovery target

INTRODUCTION

Allosteric modulators of G-protein coupled receptors (GPCRs) hold the promise of improved pharmacology and safety over typical orthosteric GPCR ligands. These features are particularly relevant to the cannabinoid receptor 1 (CB1R) GPCR, since typical orthosteric CB1R ligands are associated with adverse events that limit their translational potential. Areas covered: The contextual basis for applying allostery to CB1R is considered from pharmacological, drug-discovery, and medicinal standpoints. Rational design of small-molecule CB1R allosteric modulators as potential pharmacotherapeutics would be greatly facilitated by direct experimental characterization of structure-function correlates underlying the biological activity of chemically-diverse CB1R allosteric modulators, CB1R allosteric ligand-binding binding pockets, and amino acid contact residues critical to allosteric ligand engagement and activity. In these regards, designer covalent probes exhibiting well-characterized molecular pharmacology as CB1R allosteric modulators are emerging as valuable molecular reporters enabling experimental interrogation of CB1R allosteric site(s) and informing the design of new CB1R agents as drugs. Expert opinion: Synthesis and pharmacological profiling of CB1R allosteric ligands will continue to provide valuable insights into CB1R structure-function correlates. The resulting data should expand the repertoire of novel agents capable of exerting therapeutic benefit by modulating CB1R-dependent signaling.

Exploiting computationally derived out-of-the-box protein conformations for drug design

Structural plasticity is an intrinsic property of proteins that allows each gene product to accomplish its tasks in a strictly regulated manner at a precise time and cellular location. Moreover, protein motions allow protein-ligand and protein-protein recognition. The knowledge of the conformational ensemble that a drug target populates may be crucial for the design of small molecules that can differently modulate its function. X-ray crystallography and NMR have endlessly provided snapshots of protein states. However, experimental structure determination is not always straightforward. Therefore, attempts have been made to depict protein conformational landscapes through molecular dynamics and enhanced sampling methods. Here, we review how accounting for protein dynamics through in silico generated out-of-the-box protein conformations has started to impact on drug discovery.

Function-specific virtual screening for GPCR ligands using a combined scoring method

The ability of scoring functions to correctly select and rank docking poses of small molecules in protein binding sites is highly target dependent, which presents a challenge for structure-based drug discovery. Here we describe a virtual screening method that combines an energy-based docking scoring function with a molecular interaction fingerprint (IFP) to identify new ligands based on G protein-coupled receptor (GPCR) crystal structures. The consensus scoring method is prospectively evaluated by: 1) the discovery of chemically novel, fragment-like, high affinity histamine H₁ receptor (H₁R) antagonists/inverse agonists, 2) the selective structure-based identification of ß₂-adrenoceptor (ß₂R) agonists, and 3) the experimental validation and comparison of the combined and individual scoring approaches. Systematic retrospective virtual screening simulations allowed the definition of scoring cut-offs for the identification of H₁R and ß₂R ligands and the selection of an optimal ß-adrenoceptor crystal structure for the discrimination between ß₂R agonists and antagonists. The consensus approach resulted in the experimental validation of 53% of the ß₂R and 73% of the H₁R virtual screening hits with up to nanomolar affinities and potencies. The selective identification of ß₂R agonists shows the possibilities of structure-based prediction of GPCR ligand function by integrating protein-ligand binding mode information.

In vitro, molecular modeling and behavioral studies of 3-{[4-(5-methoxy-1H-indol-3-yl)-1,2,3,6-tetrahydropyridin-1-yl]methyl}-1,2-dihydroquinolin-2-one (D2AAK1) as a potential antipsychotic

Antipsychotics currently available to treat schizophrenia suffer several limitations: (1) they are efficient against positive but not negative and cognitive symptoms of the disease; (2) they help only a half of patients; (3) they have severe side effects including neurological and metabolic side effects. Thus, novel drugs to treat schizophrenia are highly demanded. We identified a novel dopamine D2 receptor antagonist, D2AAK1, with Ki of 58 nM using structure-based virtual screening. D2AAK1 possesses additional nanomolar or low micromolar affinity to D1, D3, 5-HT1A and 5-HT2A receptors, making it an ideal candidate for a multi-target drug. Here we present homology modeling, molecular docking and molecular dynamics of D2AAK1 and its molecular targets and animal studies of D2AAK1 as a potential antipsychotic. The main contact of D2AAK1 and all the receptors studied is the electrostatic interaction between the protonable nitrogen atom of the ligand and the conserved Asp(3.32) as typical for orthosteric ligands of aminergic GPCRs. We confirmed antagonistic/partial agonistic properties of D2AAK1 towards all the receptors in in vitro essays and in in silico studies as the ligand stabilizes the ionic lock interaction. We also demonstrated neuroleptic, anxiolytic and, importantly, procognitive properties of D2AAK1 in mouse models.