Impact of GPCR Structures on Drug Discovery

Inhibitory effect of truncated isoforms on GPCR dimerization predicted by combinatorial computational strategy

G protein-coupled receptors (GPCRs) play a pivotal role in fundamental biological processes and disease development. GPCR isoforms, derived from alternative splicing, can exhibit distinct signaling patterns. Some highly-truncated isoforms can impact functional performance of full-length receptors, suggesting their intriguing regulatory roles. However, how these truncated isoforms interact with full-length counterparts remains largely unexplored. Here, we computationally investigated the interaction patterns of three human GPCRs from three different classes, ADORA1 (Class A), mGlu2 (Class C) and SMO (Class F) with their respective truncated isoforms because their homodimer structures have been experimentally determined, and they have truncated isoforms deposited and identified at protein level in Uniprot database. Combining the neural network-based AlphaFold2 and two physics-based protein-protein docking tools, we generated multiple complex structures and assessed the binding affinity in the context of atomistic molecular dynamics simulations. Our computational results suggested all the four studied truncated isoforms showed potent binding to their counterparts and overlapping interfaces with homodimers, indicating their strong potential to block homodimerization of their counterparts. Our study offers insights into functional significance of GPCR truncated isoforms and supports the ubiquity of their regulatory roles.

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

Conformational dynamics underlying atypical chemokine receptor 3 activation

Atypical Chemokine Receptor 3 (ACKR3) belongs to the G protein-coupled receptor family but it does not signal through G proteins. The structural properties that govern the functional selectivity and the conformational dynamics of ACKR3 activation are poorly understood. Here, we combined hydrogen/deuterium exchange mass spectrometry, site-directed mutagenesis, and molecular dynamics simulations to examine the binding mode and mechanism of action of ACKR3 ligands of different efficacies. Our results show that activation or inhibition of ACKR3 is governed by intracellular conformational changes of helix 6, intracellular loop 2, and helix 7, while the DRY motif becomes protected during both processes. Moreover, we identified the binding sites and the allosteric modulation of ACKR3 upon β-arrestin 1 binding. In summary, this study highlights the structure-function relationship of small ligands, the binding mode of β-arrestin 1, the activation dynamics, and the atypical dynamic features in ACKR3 that may contribute to its inability to activate G proteins.

Structural Mass Spectrometry Captures Residue-Resolved Comprehensive Conformational Rearrangements of a G Protein-Coupled Receptor

G protein-coupled receptor (GPCR) structural studies with in-solution spectroscopic approaches have offered distinctive insights into GPCR activation and signaling that highly complement those yielded from structural snapshots by crystallography or cryo-EM. While most current spectroscopic approaches allow for probing structural changes at selected residues or loop regions, they are not suitable for capturing a holistic view of GPCR conformational rearrangements across multiple domains. Herein, we develop an approach based on limited proteolysis mass spectrometry (LiP-MS) to simultaneously monitor conformational alterations of a large number of residues spanning both flexible loops and structured transmembrane domains for a given GPCR. To benchmark LiP-MS for GPCR conformational profiling, we studied the adenosine 2A receptor (A2AR) in response to different ligand binding (agonist/antagonist/allosteric modulators) and G protein coupling. Systematic and residue-resolved profiling of A2AR conformational rearrangements by LiP-MS precisely captures structural mechanisms in multiple domains underlying ligand engagement, receptor activation, and allostery, and may also reflect local conformational flexibility. Furthermore, these residue-resolution structural fingerprints of the A2AR protein allow us to readily classify ligands of different pharmacology and distinguish the G protein-coupled state. Thus, our study provides a new structural MS approach that would be generalizable to characterizing conformational transition and plasticity for challenging integral membrane proteins.

Binding characteristics of the doxepin E/Z-isomers to the histamine H1 receptor revealed by receptor-bound ligand analysis and molecular dynamics study

Doxepin is an antihistamine and tricyclic antidepressant that binds to the histamine H1 receptor (H1R) with high affinity. Doxepin is an 85:15 mixture of the E- and Z-isomers. The Z-isomer is well known to be more effective than the E-isomer, whereas based on the crystal structure of the H1R/doxepin complex, the hydroxyl group of Thr1123.37 is close enough to form a hydrogen bond with the oxygen atom of the E-isomer. The detailed binding characteristics and reasons for the differences remain unclear. In this study, we analyzed doxepin isomers bound to the receptor following extraction from a purified H1R protein complexed with doxepin. The ratio of the E- and Z-isomers bound to wild-type (WT) H1R was 55:45, indicating that the Z-isomer was bound to WT H1R with an approximately 5.2-fold higher affinity than the E-isomer. For the T1123.37V mutant, the E/Z ratio was 89:11, indicating that both isomers have similar affinities. Free energy calculations using molecular dynamics (MD) simulations also reproduced the experimental results of the relative binding free energy differences between the isomers for WT and T1123.37V. Furthermore, MD simulations revealed that the hydroxyl group of T1123.37 did not form hydrogen bonds with the E-isomer, but with the adjacent residues in the binding pocket. Analysis of the receptor-bound doxepin and MD simulations suggested that the hydroxyl group of T1123.37 contributes to the formation of a chemical environment in the binding pocket, which is slightly more favorable for the Z-isomer without hydrogen bonding with doxepin.

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

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

A Study on the Robustness and Stability of Explainable Deep Learning in an Imbalanced Setting: The Exploration of the Conformational Space of G Protein-Coupled Receptors

G-protein coupled receptors (GPCRs) are transmembrane proteins that transmit signals from the extracellular environment to the inside of the cells. Their ability to adopt various conformational states, which influence their function, makes them crucial in pharmacoproteomic studies. While many drugs target specific GPCR states to exert their effects-thereby regulating the protein's activity-unraveling the activation pathway remains challenging due to the multitude of intermediate transformations occurring throughout this process, and intrinsically influencing the dynamics of the receptors. In this context, computational modeling, particularly molecular dynamics (MD) simulations, may offer valuable insights into the dynamics and energetics of GPCR transformations, especially when combined with machine learning (ML) methods and techniques for achieving model interpretability for knowledge generation. The current study builds upon previous work in which the layer relevance propagation (LRP) technique was employed to interpret the predictions in a multi-class classification problem concerning the conformational states of the β2-adrenergic (β2AR) receptor from MD simulations. Here, we address the challenges posed by class imbalance and extend previous analyses by evaluating the robustness and stability of deep learning (DL)-based predictions under different imbalance mitigation techniques. By meticulously evaluating explainability and imbalance strategies, we aim to produce reliable and robust insights.

RNA therapeutics in targeting G protein-coupled receptors: Recent advances and challenges

G protein-coupled receptors (GPCRs) are the major targets of existing drugs for a plethora of human diseases and dominate the pharmaceutical market. However, over 50% of the GPCRs remain undruggable. To pursue a breakthrough and overcome this situation, there is significant clinical research for developing RNA-based drugs specifically targeting GPCRs, but none has been approved so far. RNA therapeutics represent a unique and promising approach to selectively targeting previously undruggable targets, including undruggable GPCRs. However, the development of RNA therapeutics faces significant challenges in areas of RNA stability and efficient in vivo delivery. This review presents an overview of the advances in RNA therapeutics and the diverse types of nanoparticle RNA delivery systems. It also describes the potential applications of GPCR-targeted RNA drugs for various human diseases.

Engineering G protein-coupled receptors for stabilization

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

Ubiquitin-driven G protein-coupled receptor inflammatory signaling at the endosome

G protein-coupled receptors (GPCRs) are ubiquitously expressed cell surface receptors that mediate numerous physiological responses and are highly druggable. Upon activation, GPCRs rapidly couple to heterotrimeric G proteins and are then phosphorylated and internalized from the cell surface. Recent studies indicate that GPCRs not only localize at the plasma membrane but also exist in intracellular compartments where they are competent to signal. Intracellular signaling by GPCRs is best described to occur at endosomes. Several studies have elegantly documented endosomal GPCR-G protein and GPCR-β-arrestin signaling. Besides phosphorylation, GPCRs are also posttranslationally modified with ubiquitin. GPCR ubiquitination has been studied mainly in the context of receptor endosomal-lysosomal trafficking. However, new studies indicate that ubiquitination of endogenous GPCRs expressed in endothelial cells initiates the assembly of an intracellular p38 mitogen-activated kinase signaling complex that promotes inflammatory responses from endosomes. In this mini-review, we discuss emerging discoveries that provide critical insights into the function of ubiquitination in regulating GPCR inflammatory signaling at endosomes.

Discovery and development of macrocyclic peptide modulators of the cannabinoid 2 receptor

The cannabinoid type 2 receptor (CB2R), a G protein-coupled receptor, is an important regulator of immune cell function and a promising target to treat chronic inflammation and fibrosis. While CB2R is typically targeted by small molecules, including endo-, phyto-, and synthetic cannabinoids, peptides-owing to their size-may offer a different interaction space to facilitate differential interactions with the receptor. Here, we explore plant-derived cyclic cystine-knot peptides as ligands of the CB2R. Cyclotides are known for their exceptional biochemical stability. Recently, they gained attention as G protein-coupled receptor modulators and as templates for designing peptide ligands with improved pharmacokinetic properties over linear peptides. Cyclotide-based ligands for CB2R were profiled based on a peptide-enriched extract library comprising nine plants. Employing pharmacology-guided fractionation and peptidomics, we identified the cyclotide vodo-C1 from sweet violet (Viola odorata) as a full agonist of CB2R with an affinity (Ki) of 1 μM and a potency (EC50) of 8 μM. Leveraging deep learning networks, we verified the structural topology of vodo-C1 and modeled its molecular volume in comparison to the CB2R ligand binding pocket. In a fragment-based approach, we designed and characterized vodo-C1-based bicyclic peptides (vBCL1-4), aiming to reduce size and improve potency. Opposite to vodo-C1, the vBCL peptides lacked the ability to activate the receptor but acted as negative allosteric modulators or neutral antagonists of CB2R. This study introduces a macrocyclic peptide phytocannabinoid, which served as a template for the development of synthetic CB2R peptide modulators. These findings offer opportunities for future peptide-based probe and drug development at cannabinoid receptors.

Systematic characterization of multi-omics landscape between gut microbial metabolites and GPCRome in Alzheimer's disease

Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these metabolites are largely unknown. Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships of gut microbial metabolites with non-olfactory G-protein-coupled receptors (termed the "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites. Using genetics-derived Mendelian randomization and integrative analyses of human brain transcriptomic and proteomic profiles, we identify orphan GPCRs (i.e., GPR84) as potential drug targets in AD and that triacanthine experimentally activates GPR84. We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in AD patient induced pluripotent stem cell-derived neurons. This study demonstrates a systems biology framework to uncover the GPCR targets of human gut microbiota in AD and other complex diseases if broadly applied.

Revolutionizing GPCR-ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery

G-protein coupled receptors (GPCRs), crucial in various diseases, are targeted of over 40% of approved drugs. However, the reliable acquisition of experimental GPCRs structures is hindered by their lipid-embedded conformations. Traditional protein-ligand interaction models falter in GPCR-drug interactions, caused by limited and low-quality structures. Generalized models, trained on soluble protein-ligand pairs, are also inadequate. To address these issues, we developed two models, DeepGPCR_BC for binary classification and DeepGPCR_RG for affinity prediction. These models use non-structural GPCR-ligand interaction data, leveraging graph convolutional networks and mol2vec techniques to represent binding pockets and ligands as graphs. This approach significantly speeds up predictions while preserving critical physical-chemical and spatial information. In independent tests, DeepGPCR_BC surpassed Autodock Vina and Schrödinger Dock with an area under the curve of 0.72, accuracy of 0.68 and true positive rate of 0.73, whereas DeepGPCR_RG demonstrated a Pearson correlation of 0.39 and root mean squared error of 1.34. We applied these models to screen drug candidates for GPR35 (Q9HC97), yielding promising results with three (F545-1970, K297-0698, S948-0241) out of eight candidates. Furthermore, we also successfully obtained six active inhibitors for GLP-1R. Our GPCR-specific models pave the way for efficient and accurate large-scale virtual screening, potentially revolutionizing drug discovery in the GPCR field.

Structure-Based Virtual Screening, ADMET Properties Prediction and Molecular Dynamics Studies Reveal Potential Inhibitors of Mycoplasma pneumoniae HPrK/P

Mycoplasma pneumoniae pneumonia (MPP) is a frequent cause of community-acquired pneumonia (CAP) in children. The incidence of childhood pneumonia caused by M. pneumoniae infection has been rapidly increasing worldwide. M. pneumoniae is naturally resistant to beta-lactam antibiotics due to its lack of a cell wall. Macrolides and related antibiotics are considered the optimal drugs for treating M. pneumoniae infection. However, clinical resistance to macrolides has become a global concern in recent years. Therefore, it is imperative to urgently identify new targets and develop new anti-M. pneumoniae drugs to treat MMP. Previous studies have shown that deficiencies in HPrK/P kinase or phosphorylase activity can seriously affect carbon metabolism, growth, morphology, and other cellular functions of M. pneumoniae. To identify potential drug development targets against M. pneumoniae, this study analyzed the sequence homology and 3D structure alignment of M. pneumoniae HPrK/P. Through sequence and structure analysis, we found that HPrK/P lacks homologous proteins in the human, while its functional motifs are highly conserved in bacteria. This renders it a promising candidate for drug development. Structure-based virtual screening was then used to discover potential inhibitors among 2614 FDA-approved drugs and 948 bioactive small molecules for M. pneumoniae HPrK/P. Finally, we identified three candidate drugs (Folic acid, Protokylol and Gluconolactone) as potential HPrK/P inhibitors through molecular docking, molecular dynamics (MDs) simulations, and ADMET predictions. These drugs offer new strategies for the treatment of MPP.

Flipping the GPCR Switch: Structure-Based Development of Selective Cannabinoid Receptor 2 Inverse Agonists

We report a blueprint for the rational design of G protein coupled receptor (GPCR) ligands with a tailored functional response. The present study discloses the structure-based design of cannabinoid receptor type 2 (CB2R) selective inverse agonists (S)-1 and (R)-1, which were derived from privileged agonist HU-308 by introduction of a phenyl group at the gem-dimethylheptyl side chain. Epimer (R)-1 exhibits high affinity for CB2R with Kd = 39.1 nM and serves as a platform for the synthesis of a wide variety of probes. Notably, for the first time these fluorescent probes retain their inverse agonist functionality, high affinity, and selectivity for CB2R independent of linker and fluorophore substitution. Ligands (S)-1, (R)-1, and their derivatives act as inverse agonists in CB2R-mediated cAMP as well as G protein recruitment assays and do not trigger β-arrestin-receptor association. Furthermore, no receptor activation was detected in live cell ERK1/2 phosphorylation and Ca2+-release assays. Confocal fluorescence imaging experiments with (R)-7 (Alexa488) and (R)-9 (Alexa647) probes employing BV-2 microglial cells visualized CB2R expressed at endogenous levels. Finally, molecular dynamics simulations corroborate the initial docking data in which inverse agonists restrict movement of toggle switch Trp2586.48 and thereby stabilize CB2R in its inactive state.

Rational Design of Drugs Targeting G-Protein-Coupled Receptors: Ligand Search and Screening

G protein-coupled receptors (GPCRs) are transmembrane proteins that participate in many physiological processes and represent major pharmacological targets. Recent advances in structural biology of GPCRs have enabled the development of drugs based on the receptor structure (structure-based drug design, SBDD). SBDD utilizes information about the receptor-ligand complex to search for suitable compounds, thus expanding the chemical space of possible receptor ligands without the need for experimental screening. The review describes the use of structure-based virtual screening (SBVS) for GPCR ligands and approaches for the functional testing of potential drug compounds, as well as discusses recent advances and successful examples in the application of SBDD for the identification of GPCR ligands.

Virtual Screening of a Chemically Diverse "Superscaffold" Library Enables Ligand Discovery for a Key GPCR Target

The advent of ultra-large libraries of drug-like compounds has significantly broadened the possibilities in structure-based virtual screening, accelerating the discovery and optimization of high-quality lead chemotypes for diverse clinical targets. Compared to traditional high-throughput screening, which is constrained to libraries of approximately one million compounds, the ultra-large virtual screening approach offers substantial advantages in both cost and time efficiency. By expanding the chemical space with compounds synthesized from easily accessible and reproducible reactions and utilizing a large, diverse set of building blocks, we can enhance both the diversity and quality of the discovered lead chemotypes. In this study, we explore new chemical spaces using reactions of sulfur(VI) fluorides to create a combinatorial library consisting of several hundred million compounds. We screened this virtual library for cannabinoid type II receptor (CB2) antagonists using the high-resolution structure in conjunction with a rationally designed antagonist, AM10257. The top-predicted compounds were then synthesized and tested in vitro for CB2 binding and functional antagonism, achieving an experimentally validated hit rate of 55%. Our findings demonstrate the effectiveness of reliable reactions, such as sulfur fluoride exchange, in diversifying ultra-large chemical spaces and facilitate the discovery of new lead compounds for important biological targets.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

Regression-Based Active Learning for Accessible Acceleration of Ultra-Large Library Docking

Structure-based drug discovery is a process for both hit finding and optimization that relies on a validated three-dimensional model of a target biomolecule, used to rationalize the structure-function relationship for this particular target. An ultralarge virtual screening approach has emerged recently for rapid discovery of high-affinity hit compounds, but it requires substantial computational resources. This study shows that active learning with simple linear regression models can accelerate virtual screening, retrieving up to 90% of the top-1% of the docking hit list after docking just 10% of the ligands. The results demonstrate that it is unnecessary to use complex models, such as deep learning approaches, to predict the imprecise results of ligand docking with a low sampling depth. Furthermore, we explore active learning meta-parameters and find that constant batch size models with a simple ensembling method provide the best ligand retrieval rate. Finally, our approach is validated on the ultralarge size virtual screening data set, retrieving 70% of the top-0.05% of ligands after screening only 2% of the library. Altogether, this work provides a computationally accessible approach for accelerated virtual screening that can serve as a blueprint for the future design of low-compute agents for exploration of the chemical space via large-scale accelerated docking. With recent breakthroughs in protein structure prediction, this method can significantly increase accessibility for the academic community and aid in the rapid discovery of high-affinity hit compounds for various targets.

Fenofibrate Recognition and Gq Protein Coupling Mechanisms of the Human Cannabinoid Receptor CB1

The G-protein-coupled human cannabinoid receptor 1 (CB1) is a promising therapeutic target for pain management, inflammation, obesity, and substance abuse disorders. The structures of CB1-Gi complexes in synthetic agonist-bound forms have been resolved to date. However, the commercial drug recognition and Gq coupling mechanisms of CB1 remain elusive. Herein, the cryo-electron microscopy (cryo-EM) structure of CB1-Gq complex, in fenofibrate-bound form, at near-atomic resolution, is reported. The structure elucidates the delicate mechanisms of the precise fenofibrate recognition and Gq protein coupling by CB1 and will facilitate future drug discovery and design.

Orphan GPR52 as an emerging neurotherapeutic target

GPR52 is a highly conserved, brain-enriched, Gs/olf-coupled orphan G protein-coupled receptor (GPCR) that controls various cyclic AMP (cAMP)-dependent physiological and pathological processes. Stimulation of GPR52 activity might be beneficial for the treatment of schizophrenia, psychiatric disorders and other human neurological diseases, whereas inhibition of its activity might provide a potential therapeutic approach for Huntington's disease. Excitingly, HTL0048149 (HTL'149), an orally available GPR52 agonist, has been advanced into phase I human clinical trials for the treatment of schizophrenia. In this concise review, we summarize the current understanding of GPR52 receptor distribution as well as its structure and functions, highlighting the recent advances in drug discovery efforts towards small-molecule GPR52 ligands. The opportunities and challenges presented by targeting GPR52 for novel therapeutics are also briefly discussed.

Machine learning-aided search for ligands of P2Y6 and other P2Y receptors

The P2Y6 receptor, activated by uridine diphosphate (UDP), is a target for antagonists in inflammatory, neurodegenerative, and metabolic disorders, yet few potent and selective antagonists are known to date. This prompted us to use machine learning as a novel approach to aid ligand discovery, with pharmacological evaluation at three P2YR subtypes: initially P2Y6 and subsequently P2Y1 and P2Y14. Relying on extensive published data for P2Y6R agonists, we generated and validated an array of classification machine learning model using the algorithms deep learning (DL), adaboost classifier (ada), Bernoulli NB (bnb), k-nearest neighbors (kNN) classifier, logistic regression (lreg), random forest classifier (rf), support vector classification (SVC), and XGBoost (XGB) classifier models, and the common consensus was applied to molecular selection of 21 diverse structures. Compounds were screened using human P2Y6R-induced functional calcium transients in transfected 1321N1 astrocytoma cells and fluorescent binding inhibition at closely related hP2Y14R expressed in CHO cells. The hit compound ABBV-744, an experimental anticancer drug with a 6-methyl-7-oxo-6,7-dihydro-1H-pyrrolo[2,3-c]pyridine scaffold, had multifaceted interactions with the P2YR family: hP2Y6R inhibition in a non-surmountable fashion, suggesting that noncompetitive antagonism, and hP2Y1R enhancement, but not hP2Y14R binding inhibition. Other machine learning-selected compounds were either weak (experimental anti-asthmatic drug AZD5423 with a phenyl-1H-indazole scaffold) or inactive in inhibiting the hP2Y6R. Experimental drugs TAK-593 and GSK1070916 (100 µM) inhibited P2Y14R fluorescent binding by 50% and 38%, respectively, and all other compounds by < 20%. Thus, machine learning has led the way toward revealing previously unknown modulators of several P2YR subtypes that have varied effects.

Proton-sensing ion channels, GPCRs and calcium signaling regulated by them: implications for cancer

Extracellular acidification of tumors is common. Through proton-sensing ion channels or proton-sensing G protein-coupled receptors (GPCRs), tumor cells sense extracellular acidification to stimulate a variety of intracellular signaling pathways including the calcium signaling, which consequently exerts global impacts on tumor cells. Proton-sensing ion channels, and proton-sensing GPCRs have natural advantages as drug targets of anticancer therapy. However, they and the calcium signaling regulated by them attracted limited attention as potential targets of anticancer drugs. In the present review, we discuss the progress in studies on proton-sensing ion channels, and proton-sensing GPCRs, especially emphasizing the effects of calcium signaling activated by them on the characteristics of tumors, including proliferation, migration, invasion, metastasis, drug resistance, angiogenesis. In addition, we review the drugs targeting proton-sensing channels or GPCRs that are currently in clinical trials, as well as the relevant potential drugs for cancer treatments, and discuss their future prospects. The present review aims to elucidate the important role of proton-sensing ion channels, GPCRs and calcium signaling regulated by them in cancer initiation and development. This review will promote the development of drugs targeting proton-sensing channels or GPCRs for cancer treatments, effectively taking their unique advantage as anti-cancer drug targets.

Exploring Novel Antidepressants Targeting G Protein-Coupled Receptors and Key Membrane Receptors Based on Molecular Structures

Major Depressive Disorder (MDD) is a complex mental disorder that involves alterations in signal transmission across multiple scales and structural abnormalities. The development of effective antidepressants (ADs) has been hindered by the dominance of monoamine hypothesis, resulting in slow progress. Traditional ADs have undesirable traits like delayed onset of action, limited efficacy, and severe side effects. Recently, two categories of fast-acting antidepressant compounds have surfaced, dissociative anesthetics S-ketamine and its metabolites, as well as psychedelics such as lysergic acid diethylamide (LSD). This has led to structural research and drug development of the receptors that they target. This review provides breakthroughs and achievements in the structure of depression-related receptors and novel ADs based on these. Cryo-electron microscopy (cryo-EM) has enabled researchers to identify the structures of membrane receptors, including the N-methyl-D-aspartate receptor (NMDAR) and the 5-hydroxytryptamine 2A (5-HT2A) receptor. These high-resolution structures can be used for the development of novel ADs using virtual drug screening (VDS). Moreover, the unique antidepressant effects of 5-HT1A receptors in various brain regions, and the pivotal roles of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and tyrosine kinase receptor 2 (TrkB) in regulating synaptic plasticity, emphasize their potential as therapeutic targets. Using structural information, a series of highly selective ADs were designed based on the different role of receptors in MDD. These molecules have the favorable characteristics of rapid onset and low adverse drug reactions. This review offers researchers guidance and a methodological framework for the structure-based design of ADs.

Novel Cocrystal Structures of Peptide Antagonists Bound to the Human Melanocortin Receptor 4 Unveil Unexplored Grounds for Structure-Based Drug Design

Melanocortin 4 receptor (MC4-R) antagonists are actively sought for treating cancer cachexia. We determined the structures of complexes with PG-934 and SBL-MC-31. These peptides differ from SHU9119 by substituting His6 with Pro6 and inserting Gly10 or Arg10. The structures revealed two subpockets at the TM7-TM1-TM2 domains, separated by N2857.36. Two peptide series based on the complexed peptides led to an antagonist activity and selectivity SAR study. Most ligands retained the SHU9119 potency, but several SBL-MC-31-derived peptides significantly enhanced MC4-R selectivity over MC1-R by 60- to 132-fold. We also investigated MC4-R coupling to the K+ channel, Kir7.1. Some peptides activated the channel, whereas others induced channel closure independently of G protein coupling. In cell culture studies, channel activation correlated with increased feeding, while a peptide with Kir7.1 inhibitory activity reduced eating. These results highlight the potential for targeting the MC4-R:Kir7.1 complex for treating positive and restrictive eating disorders.

The Role of G Protein-Coupled Receptors and Receptor Kinases in Pancreatic β-Cell Function and Diabetes

Type 2 diabetes (T2D) mellitus has emerged as a major global health concern that has accelerated in recent years due to poor diet and lifestyle. Afflicted individuals have high blood glucose levels that stem from the inability of the pancreas to make enough insulin to meet demand. Although medication can help to maintain normal blood glucose levels in individuals with chronic disease, many of these medicines are outdated, have severe side effects, and often become less efficacious over time, necessitating the need for insulin therapy. G protein-coupled receptors (GPCRs) regulate many physiologic processes, including blood glucose levels. In pancreatic β cells, GPCRs regulate β-cell growth, apoptosis, and insulin secretion, which are all critical in maintaining sufficient β-cell mass and insulin output to ensure euglycemia. In recent years, new insights into the signaling of incretin receptors and other GPCRs have underscored the potential of these receptors as desirable targets in the treatment of diabetes. The signaling of these receptors is modulated by GPCR kinases (GRKs) that phosphorylate agonist-activated GPCRs, marking the receptor for arrestin binding and internalization. Interestingly, genome-wide association studies using diabetic patient cohorts link the GRKs and arrestins with T2D. Moreover, recent reports show that GRKs and arrestins expressed in the β cell serve a critical role in the regulation of β-cell function, including β-cell growth and insulin secretion in both GPCR-dependent and -independent pathways. In this review, we describe recent insights into GPCR signaling and the importance of GRK function in modulating β-cell physiology. SIGNIFICANCE STATEMENT: Pancreatic β cells contain a diverse array of G protein-coupled receptors (GPCRs) that have been shown to improve β-cell function and survival, yet only a handful have been successfully targeted in the treatment of diabetes. This review discusses recent advances in our understanding of β-cell GPCR pharmacology and regulation by GPCR kinases while also highlighting the necessity of investigating islet-enriched GPCRs that have largely been unexplored to unveil novel treatment strategies.

Molecular determinants of antagonist interactions with chemokine receptors CCR2 and CCR5

By driving monocyte chemotaxis, the chemokine receptor CCR2 shapes inflammatory responses and the formation of tumor microenvironments. This makes it a promising target in inflammation and immuno-oncology; however, despite extensive efforts, there are no FDA-approved CCR2-targeting therapeutics. Cited challenges include the redundancy of the chemokine system, suboptimal properties of compound candidates, and species differences that confound the translation of results from animals to humans. Structure-based drug design can rationalize and accelerate the discovery and optimization of CCR2 antagonists to address these challenges. The prerequisites for such efforts include an atomic-level understanding of the molecular determinants of action of existing antagonists. In this study, using molecular docking and artificial-intelligence-powered compound library screening, we uncover the structural principles of small molecule antagonism and selectivity towards CCR2 and its sister receptor CCR5. CCR2 orthosteric inhibitors are shown to universally occupy an inactive-state-specific tunnel between receptor helices 1 and 7; we also discover an unexpected role for an extra-helical groove accessible through this tunnel, suggesting its potential as a new targetable interface for CCR2 and CCR5 modulation. By contrast, only shape complementarity and limited helix 8 hydrogen bonding govern the binding of various chemotypes of allosteric antagonists. CCR2 residues S1012.63 and V2446.36 are implicated as determinants of CCR2/CCR5 and human/mouse orthosteric and allosteric antagonist selectivity, respectively, and the role of S1012.63 is corroborated through experimental gain-of-function mutagenesis. We establish a critical role of induced fit in antagonist recognition, reveal strong chemotype selectivity of existing structures, and demonstrate the high predictive potential of a new deep-learning-based compound scoring function. Finally, this study expands the available CCR2 structural landscape with computationally generated chemotype-specific models well-suited for structure-based antagonist design.

Identification of a Novel Subtype-Selective α1B-Adrenoceptor Antagonist

α1A-, α1B-, and α1D-adrenoceptors (α1-ARs) are members of the adrenoceptor G protein-coupled receptor family that are activated by adrenaline (epinephrine) and noradrenaline. α1-ARs are clinically targeted using antagonists that have minimal subtype selectivity, such as prazosin and tamsulosin, to treat hypertension and benign prostatic hyperplasia, respectively. Abundant expression of α1-ARs in the heart and central nervous system (CNS) makes these receptors potential targets for the treatment of cardiovascular and CNS disorders, such as heart failure, epilepsy, and Alzheimer's disease. Our understanding of the precise physiological roles of α1-ARs, however, and their involvement in disease has been hindered by the lack of sufficiently subtype-selective tool compounds, especially for α1B-AR. Here, we report the discovery of 4-[(2-hydroxyethyl)amino]-6-methyl-2H-chromen-2-one (Cpd1), as an α1B-AR antagonist that has 10-15-fold selectivity over α1A-AR and α1D-AR. Through computational and site-directed mutagenesis studies, we have identified the binding site of Cpd1 in α1B-AR and propose the molecular basis of α1B-AR selectivity, where the nonconserved V19745.52 residue plays a major role, with contributions from L3146.55 within the α1B-AR pocket. By exploring the structure-activity relationships of Cpd1 at α1B-AR, we have also identified 3-[(cyclohexylamino)methyl]-6-methylquinolin-2(1H)-one (Cpd24), which has a stronger binding affinity than Cpd1, albeit with reduced selectivity for α1B-AR. Cpd1 and Cpd24 represent potential leads for α1B-AR-selective drug discovery and novel tool molecules to further study the physiology of α1-ARs.

The novel peptide LCGM-10 attenuates metabotropic glutamate receptor 5 activity and demonstrates behavioral effects in animal models

We employed a structural bioinformatics approach to develop novel peptides with predicted affinity to the binding site for negative allosteric modulators (NAMs) of metabotropic glutamate receptor 5 (mGluR5). Primary screening in zebrafish (Danio rerio) revealed a stimulatory effect of two peptides, LCGM-10 and LCGM-15. Target validation studies using calcium ion flux imaging and a luciferase reporter assay confirmed mGluR5 as the target. LCGM-10 showed greater potency than LCGM-15; it was comparable to that of the mGluR5 NAM 2-methyl-6-(phenylethynyl) pyridine (MPEP). Rodent behavioral screening in the open field and elevated plus maze revealed increased locomotor activity in both tests after acute LCGM-10 treatment, supported by further analysis of home cage spontaneous locomotor activity (SLA). The stimulating effect of a single LCGM-10 administration on SLA was evident up to 60 min after administration and was not accompanied by hypokinetic rebound observed for caffeine. According to our results, LCGM-10 has therapeutic potential to treat hypo- and dyskinesias of various etiologies. Further investigation of LCGM-10 effects in the delay discounting model of impulsive choice in rats revealed reduced trait impulsivity after single and chronic administrations, suggesting potential implication for attention deficit hyperactivity disorder, obsessive compulsive disorder, and addictions.

Imaging GPCR Dimerization in Living Cells with Cucurbit[7]uril and Hemicyanine as a "Turn-On" Fluorescence Probe

Although multiple forms of dimers have been described for GPCR, their dynamics and function are still controversially discussed field. Fluorescence microscopy allows GPCR to be imaged within their native context; however, a key challenge is to site-specifically incorporate reporter moieties that can produce high-quality signals upon formation of GPCR dimers. To this end, we propose a supramolecular sensor approach to detect agonist-induced dimer formation of μ-opioid receptors (μORs) at the surface of intact cells. With the macrocyclic host cucurbit[7]uril and its guest hemicyanine dye tethered to aptamer strands directed against the histidine residues, the sensing module is assembled by host-guest complexation once the histidine-tagged μORs dimerize and bring the discrete supramolecular units into close proximity. With the enhanced sensitivity attributed by the "turn-on" fluorescence emission and high specificity afforded by the intermolecular recognition, in situ visualization of dynamic GPCR dimerization was realized with high precision, thereby validating the supramolecular sensing entity as a sophisticated and versatile strategy to investigate GPCR dimers, which represent an obvious therapeutic target.

CD97 inhibits osteoclast differentiation via Rap1a/ERK pathway under compression

Acceleration of tooth movement during orthodontic treatment is challenging, with osteoclast-mediated bone resorption on the compressive side being the rate-limiting step. Recent studies have demonstrated that mechanoreceptors on the surface of monocytes/macrophages, especially adhesion G protein-coupled receptors (aGPCRs), play important roles in force sensing. However, its role in the regulation of osteoclast differentiation remains unclear. Herein, through single-cell analysis, we revealed that CD97, a novel mechanosensitive aGPCR, was expressed in macrophages. Compression upregulated CD97 expression and inhibited osteoclast differentiation; while knockdown of CD97 partially rescued osteoclast differentiation. It suggests that CD97 may be an important mechanosensitive receptor during osteoclast differentiation. RNA sequencing analysis showed that the Rap1a/ERK signalling pathway mediates the effects of CD97 on osteoclast differentiation under compression. Consistently, we clarified that administration of the Rap1a inhibitor GGTI298 increased osteoclast activity, thereby accelerating tooth movement. In conclusion, our results indicate that CD97 suppresses osteoclast differentiation through the Rap1a/ERK signalling pathway under orthodontic compressive force.

The cell surface is the place to be for brassinosteroid perception and responses

Adjusting the microenvironment around the cell surface is critical to responding to external cues or endogenous signals and to maintaining cell activities. In plant cells, the plasma membrane is covered by the cell wall and scaffolded with cytoskeletal networks, which altogether compose the cell surface. It has long been known that these structures mutually interact, but the mechanisms that integrate the whole system are still obscure. Here we spotlight the brassinosteroid (BR) plant hormone receptor BRASSINOSTEROID INSENSITIVE1 (BRI1) since it represents an outstanding model for understanding cell surface signalling and regulation. We summarize how BRI1 activity and dynamics are controlled by plasma membrane components and their associated factors to fine-tune signalling. The downstream signals, in turn, manipulate cell surface structures by transcriptional and post-translational mechanisms. Moreover, the changes in these architectures impact BR signalling, resulting in a feedback loop formation. This Review discusses how BRI1 and BR signalling function as central hubs to integrate cell surface regulation.

AI-driven GPCR analysis, engineering, and targeting

This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.

Optimizing cryo-EM structural analysis of Gi-coupling receptors via engineered Gt and Nb35 application

Cryo-EM single particle analysis has recently facilitated the high-resolution structural determination of numerous GPCR-G complexes. Diverse methodologies have been devised with this trend, and in the case of GPCR-Gi complexes, scFv16, an antibody that recognizes the intricate interface of the complex, has been mainly implemented to stabilize the complex. However, owing to their flexibility and heterogeneity, structural determinations of GPCR-Gi complexes remain both challenging and resource-intensive. By employing eGαt, which exhibits binding affinity to modified nanobody Nb35, the cryo-EM structure of Rhodopsin-eGαt complex was previously reported. Using this modified G protein, we determined the structure of the ETB-eGt complex bound to the modified Nb35. The determined structure of ETB receptor was the same as the previously reported ETB-Gi complex, and the resulting dataset demonstrated significantly improved anisotropy. This modified G protein will be utilized for the structural determination of other GPCR-Gi complexes.

FFAR4 activation inhibits lung adenocarcinoma via blocking respiratory chain complex assembly associated mitochondrial metabolism

Despite notable advancements in the investigation and management of lung adenocarcinoma (LUAD), the mortality rate for individuals afflicted with LUAD remains elevated, and attaining an accurate prognosis is challenging. LUAD exhibits intricate genetic and environmental components, and it is plausible that free fatty acid receptors (FFARs) may bridge the genetic and dietary aspects. The objective of this study is to ascertain whether a correlation exists between FFAR4, which functions as the primary receptor for dietary fatty acids, and various characteristics of LUAD, while also delving into the potential underlying mechanism. The findings of this study indicate a decrease in FFAR4 expression in LUAD, with a positive correlation (P < 0.01) between FFAR4 levels and overall patient survival (OS). Receiver operating characteristic (ROC) curve analysis demonstrated a significant diagnostic value [area under the curve (AUC) of 0.933] associated with FFAR4 expression. Functional investigations revealed that the FFAR4-specific agonist (TUG891) effectively suppressed cell proliferation and induced cell cycle arrest. Furthermore, FFAR4 activation resulted in significant metabolic shifts, including a decrease in oxygen consumption rate (OCR) and an increase in extracellular acidification rate (ECAR) in A549 cells. In detail, the activation of FFAR4 has been observed to impact the assembly process of the mitochondrial respiratory chain complex and the malate-aspartate shuttle process, resulting in a decrease in the transition of NAD+ to NADH and the inhibition of LUAD. These discoveries reveal a previously unrecognized function of FFAR4 in the negative regulation of mitochondrial metabolism and the inhibition of LUAD, indicating its potential as a promising therapeutic target for the treatment and diagnosis of LUAD.

ThermoBRET: A Ligand-Engagement Nanoscale Thermostability Assay Applied to GPCRs

Measurements of membrane protein thermostability reflect ligand binding. Current thermostability assays often require protein purification or rely on pre-existing radiolabelled or fluorescent ligands, limiting their application to established targets. Alternative methods, such as fluorescence-detection size exclusion chromatography thermal shift, detect protein aggregation but are not amenable to high-throughput screening. Here, we present a ThermoBRET method to quantify the relative thermostability of G protein coupled receptors (GPCRs), using cannabinoid receptors (CB1 and CB2 ) and the β2 -adrenoceptor (β2 AR) as model systems. ThermoBRET reports receptor unfolding, does not need labelled ligands and can be used with non-purified proteins. It uses Bioluminescence Resonance Energy Transfer (BRET) between Nanoluciferase (Nluc) and a thiol-reactive fluorescent dye that binds cysteines exposed by unfolding. We demonstrate that the melting point (Tm ) of Nluc-fused GPCRs can be determined in non-purified detergent solubilised membrane preparations or solubilised whole cells, revealing differences in thermostability for different solubilising conditions and in the presence of stabilising ligands. We extended the range of the assay by developing the thermostable tsNLuc by incorporating mutations from the fragments of split-Nluc (Tm of 87 °C versus 59 °C). ThermoBRET allows the determination of GPCR thermostability, which is useful for protein purification optimisation and drug discovery screening.

A cholesterol switch controls phospholipid scrambling by G protein-coupled receptors

Class A G protein-coupled receptors (GPCRs), a superfamily of cell membrane signaling receptors, moonlight as constitutively active phospholipid scramblases. The plasma membrane of metazoan cells is replete with GPCRs, yet has a strong resting trans-bilayer phospholipid asymmetry, with the signaling lipid phosphatidylserine confined to the cytoplasmic leaflet. To account for the persistence of this lipid asymmetry in the presence of GPCR scramblases, we hypothesized that GPCR-mediated lipid scrambling is regulated by cholesterol, a major constituent of the plasma membrane. We now present a technique whereby synthetic vesicles reconstituted with GPCRs can be supplemented with cholesterol to a level similar to that of the plasma membrane and show that the scramblase activity of two prototypical GPCRs, opsin and the β1-adrenergic receptor, is impaired upon cholesterol loading. Our data suggest that cholesterol acts as a switch, inhibiting scrambling above a receptor-specific threshold concentration to disable GPCR scramblases at the plasma membrane.

Discovery of non-peptide GLP-1r natural agonists for enhancing coronary safety in type 2 diabetes patients

This study explores the computational discovery of non-peptide agonists targeting the Glucagon-Like Peptide-1 Receptor (GLP-1R) to enhance the safety of major coronary outcomes in individuals affected by Type 2 Diabetes. The objective is to identify novel compounds that can activate the GLP-1R pathway without the limitations associated with peptide agonists. Type 2 diabetes mellitus (T2DM) is associated with an increased risk of cardiovascular disease (CVD) and mortality, which is attributed to the accumulation of fat in organs, including the heart. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are frequently used to manage T2DM and could potentially offer cardiovascular benefits. Therefore, this study examines non-peptide agonists of GLP-1R to improve coronary safety in type 2 diabetes patients. After rigorous assessments, two standout candidates were identified, with natural compound 12 emerging as the most promising. This study represents a notable advancement in enhancing the management of coronary outcomes among individuals with type 2 diabetes. The computational methodology employed successfully pinpointed potential GLP-1R natural agonists, providing optimism for the development of safer and more effective therapeutic interventions. Although computational methodologies have provided crucial insights, realizing the full potential of these compounds requires extensive experimental investigations, crucial in advancing therapeutic strategies for this critical patient population.Communicated by Ramaswamy H. Sarma.

The role of leucine and isoleucine in tuning the hydropathy of class A GPCRs

Leucine and Isoleucine are two amino acids that differ only by the positioning of one methyl group. This small difference can have important consequences in α-helices, as the β-branching of Ile results in helix destabilization. We set out to investigate whether there are general trends for the occurrences of Leu and Ile residues in the structures and sequences of class A GPCRs (G protein-coupled receptors). GPCRs are integral membrane proteins in which α-helices span the plasma membrane seven times and which play a crucial role in signal transmission. We found that Leu side chains are generally more exposed at the protein surface than Ile side chains. We explored whether this difference might be attributed to different functions of the two amino acids and tested if Leu tunes the hydrophobicity of the transmembrane domain based on the Wimley-White whole-residue hydrophobicity scales. Leu content decreases the variation in hydropathy between receptors and correlates with the non-Leu receptor hydropathy. Both measures indicate that hydropathy is tuned by Leu. To test this idea further, we generated protein sequences with random amino acid compositions using a simple numerical model, in which hydropathy was tuned by adjusting the number of Leu residues. The model was able to replicate the observations made with class A GPCR sequences. We speculate that the hydropathy of transmembrane domains of class A GPCRs is tuned by Leu (and to some lesser degree by Lys and Val) to facilitate correct insertion into membranes and/or to stably anchor the receptors within membranes.

The Structure-property Relationships of Clinically Approved Protease Inhibitors

BACKGROUND

Proteases play important roles in the regulation of many physiological processes, and protease inhibitors have become one of the important drug classes. Especially because the development of protease inhibitors often starts from a substrate- based peptidomimetic strategy, many of the initial lead compounds suffer from pharmacokinetic liabilities.

OBJECTIVE

To reduce drug attrition rates, drug metabolism and pharmacokinetics studies are fully integrated into modern drug discovery research, and the structure-property relationship illustrates how the modification of the chemical structure influences the pharmacokinetic and toxicological properties of drug compounds. Understanding the structure- property relationships of clinically approved protease inhibitor drugs and their analogues could provide useful information on the lead-to-candidate optimization strategies.

METHODS

About 70 inhibitors against human or pathogenic viral proteases have been approved until the end of 2021. In this review, 17 inhibitors are chosen for the structure- property relationship analysis because detailed pharmacological and/or physicochemical data have been disclosed in the medicinal chemistry literature for these inhibitors and their close analogues.

RESULTS

The compiled data are analyzed primarily focusing on the pharmacokinetic or toxicological deficiencies found in lead compounds and the structural modification strategies used to generate candidate compounds.

CONCLUSION

The structure-property relationships hereby summarized how the overall druglike properties could be successfully improved by modifying the structure of protease inhibitors. These specific examples are expected to serve as useful references and guidance for developing new protease inhibitor drugs in the future.

Dissecting the genetic landscape of GPCR signaling through phenotypic profiling in C. elegans

G protein-coupled receptors (GPCRs) mediate responses to various extracellular and intracellular cues. However, the large number of GPCR genes and their substantial functional redundancy make it challenging to systematically dissect GPCR functions in vivo. Here, we employ a CRISPR/Cas9-based approach, disrupting 1654 GPCR-encoding genes in 284 strains and mutating 152 neuropeptide-encoding genes in 38 strains in C. elegans. These two mutant libraries enable effective deorphanization of chemoreceptors, and characterization of receptors for neuropeptides in various cellular processes. Mutating a set of closely related GPCRs in a single strain permits the assignment of functions to GPCRs with functional redundancy. Our analyses identify a neuropeptide that interacts with three receptors in hypoxia-evoked locomotory responses, unveil a collection of regulators in pathogen-induced immune responses, and define receptors for the volatile food-related odorants. These results establish our GPCR and neuropeptide mutant libraries as valuable resources for the C. elegans community to expedite studies of GPCR signaling in multiple contexts.

Ligand recognition and G-protein coupling of trace amine receptor TAAR1

Trace-amine-associated receptors (TAARs), a group of biogenic amine receptors, have essential roles in neurological and metabolic homeostasis1. They recognize diverse endogenous trace amines and subsequently activate a range of G-protein-subtype signalling pathways2,3. Notably, TAAR1 has emerged as a promising therapeutic target for treating psychiatric disorders4,5. However, the molecular mechanisms underlying its ability to recognize different ligands remain largely unclear. Here we present nine cryo-electron microscopy structures, with eight showing human and mouse TAAR1 in a complex with an array of ligands, including the endogenous 3-iodothyronamine, two antipsychotic agents, the psychoactive drug amphetamine and two identified catecholamine agonists, and one showing 5-HT1AR in a complex with an antipsychotic agent. These structures reveal a rigid consensus binding motif in TAAR1 that binds to endogenous trace amine stimuli and two extended binding pockets that accommodate diverse chemotypes. Combined with mutational analysis, functional assays and molecular dynamic simulations, we elucidate the structural basis of drug polypharmacology and identify the species-specific differences between human and mouse TAAR1. Our study provides insights into the mechanism of ligand recognition and G-protein selectivity by TAAR1, which may help in the discovery of ligands or therapeutic strategies for neurological and metabolic disorders.

Functional GPCR Expression in Eukaryotic LEXSY System

G protein-coupled receptors (GPCRs) form the largest superfamily of membrane proteins in the human genome, and represent one of the most important classes of drug targets. Their structural studies facilitate rational drug discovery. However, atomic structures of only about 20% of human GPCRs have been solved to date. Recombinant production of GPCRs for structural studies at a large scale is challenging due to their low expression levels and stability. Therefore, in this study, we explored the efficacy of the eukaryotic system LEXSY (Leishmania tarentolae) for GPCR production. We selected the human A2A adenosine receptor (A2AAR), as a model protein, expressed it in LEXSY, purified it, and compared with the same receptor produced in insect cells, which is the most popular expression system for structural studies of GPCRs. The A2AAR purified from both expression systems showed similar purity, stability, ligand-induced conformational changes and structural dynamics, with a remarkably higher protein yield in the case of LEXSY expression. Overall, our results suggest that LEXSY is a promising platform for large-scale production of GPCRs for structural studies.

Is the Functional Response of a Receptor Determined by the Thermodynamics of Ligand Binding?

For an effective drug, strong binding to the target protein is a prerequisite, but it is not enough. To produce a particular functional response, drugs need to either block the proteins' functions or modulate their activities by changing their conformational equilibrium. The binding free energy of a compound to its target is routinely calculated, but the timescales for the protein conformational changes are prohibitively long to be efficiently modeled via physics-based simulations. Thermodynamic principles suggest that the binding free energies of the ligands with different receptor conformations may infer their efficacy. However, this hypothesis has not been thoroughly validated. We present an actionable protocol and a comprehensive study to show that binding thermodynamics provides a strong predictor of the efficacy of a ligand. We apply the absolute binding free energy perturbation method to ligands bound to active and inactive states of eight G protein-coupled receptors and a nuclear receptor and then compare the resulting binding free energies. We find that carefully designed restraints are often necessary to efficiently model the corresponding conformational ensembles for each state. Our method achieves unprecedented performance in classifying ligands as agonists or antagonists across the various investigated receptors, all of which are important drug targets.

Collective and Coordinated Conformational Changes Determine Agonism or Antagonism at the Human Trace Amine-Associated Receptor 1

The human trace amine-associated receptor (hTAAR1), a G protein-coupled receptor, has been postulated as a new target in the treatment of neuropsychiatric conditions. The mechanism associated with activation or inactivation by agonists or antagonists in hTAAR1 and other GPCRs has not yet been fully elucidated. In this study, we combined computational methods including homology modeling, docking, and molecular dynamic simulations to reveal novel conformational changes associated with agonist and antagonist interactions in hTAAR1. Our findings suggest a differential cascade of coordinated movements based on the presence of either an agonist or antagonist and primarily involving the second extracellular loop, transmembrane domain 5, and the third intracellular domains of hTAAR1. Our study provides an opportunity to predict the effects on new ligands with agonistic or antagonistic activity at hTAAR1 based on the reported conformational changes.

Accessible and Generalizable in Vitro Luminescence Assay for Detecting GPCR Activation

G protein-coupled receptors (GPCRs) serve critical physiological roles as the most abundant family of receptors. Here, we describe the design of a generalizable and cell lysate-based method that leverages the interaction between an agonist-activated GPCR and a conformation-specific binder to reconstitute split nanoluciferase (NanoLuc) in vitro. This tool, In vitro GPCR split NanoLuc ligand Triggered Reporter (IGNiTR), has broad applications. We have demonstrated IGNiTR's use with three Gs-coupled GPCRs, two Gi-coupled GPCRs and three classes of conformation-specific binders: nanobodies, miniG proteins, and G protein peptidomimetics. As an in vitro method, IGNiTR enables the use of synthetic G protein peptidomimetics and provides easily scalable and portable reagents for characterizing GPCRs and ligands. We tested three diverse applications of IGNiTR: (1) proof-of-concept GPCR ligand screening using dopamine receptor D1 IGNiTR; (2) detection of opioids for point-of-care testing; and (3) characterizing GPCR functionality during Nanodisc-based reconstitution processes. Due to IGNiTR's unique advantages and the convenience of its cell lysate-based format, this tool will find extensive applications in GPCR ligand detection, screening, and GPCR characterization.

Understanding the Rhodopsin Worldview Through Atomic Force Microscopy (AFM): Structure, Stability, and Activity Studies

Rhodopsin is a G protein-coupled receptor (GPCR) present in the rod outer segment (ROS) of photoreceptor cells that initiates the phototransduction cascade required for scotopic vision. Due to the remarkable advancements in technological tools, the chemistry of rhodopsin has begun to unravel especially over the past few decades, but mostly at the ensemble scale. Atomic force microscopy (AFM) is a tool capable of providing critical information from a single-molecule point of view. In this regard, to bolster our understanding of rhodopsin at the nanoscale level, AFM-based imaging, force spectroscopy, and nano-indentation techniques were employed on ROS disc membranes containing rhodopsin, isolated from vertebrate species both in normal and diseased states. These AFM studies on samples from native retinal tissue have provided fundamental insights into the structure and function of rhodopsin under normal and dysfunctional states. We review here the findings from these AFM studies that provide important insights on the supramolecular organization of rhodopsin within the membrane and factors that contribute to this organization, the molecular interactions stabilizing the structure of the receptor and factors that can modify those interactions, and the mechanism underlying constitutive activity in the receptor that can cause disease.

Chemokine Binding to Tenascin-C Influences Chemokine-Induced Immune Cell Migration

Tenascin-C (TNC) is a complex glycoprotein of the extracellular matrix (ECM) involved in a plethora of (patho-)physiological processes, such as oncogenesis and inflammation. Since chemokines play an essential role in both disease processes, we have investigated here the binding of TNC to some of the key chemokines, namely CCL2, CCL26, CXCL8, CXCL10, and CXCL12. Thereby, a differential chemokine-TNC binding pattern was observed, with CCL26 exhibiting the highest and CCL2 the lowest affinity for TNC. Heparan sulfate (HS), another member of the ECM, proved to be a similarly high-affinity ligand of TNC, with a Kd value of 730 nM. Chemokines use glycosa-minoglycans such as HS as co-receptors to induce immune cell migration. Therefore, we assumed an influence of TNC on immune cell chemotaxis due to co-localization within the ECM. CCL26- and CCL2-induced mobilization experiments of eosinophils and monocytes, respectively, were thus performed in the presence and the absence of TNC. Pre-incubation of the immune cells with TNC resulted in a 3.5-fold increase of CCL26-induced eosinophil chemotaxis, whereas a 1.3-fold de-crease in chemotaxis was observed when monocytes were pre-incubated with CCL2. As both chemokines have similar HS binding but different TNC binding affinities, we speculate that TNC acts as an attenuator in monocyte and as an amplifier in eosinophil mobilization by impeding CCL2 from binding to HS on the one hand, and by reinforcing CCL26 to bind to HS on the other hand.

Recovery of the histamine H3 receptor activity lost in yeast cells through error-prone PCR and in vivo selection

G protein-coupled receptors (GPCRs) are the largest protein family in humans and are important drug targets. Yeast, especially Saccharomyces cerevisiae, is a useful host for modifying the function and stability of GPCRs through protein engineering, which is advantageous for mammalian cells. When GPCRs are expressed in yeast, their function is often impaired. In this study, we performed random mutagenesis using error-prone PCR and then an in vivo screening to obtain mutants that recovered the activity of the human histamine H3 receptor (H3R), which loses its signaling function when expressed in yeast. Four mutations with recovered activity were identified after screening. Three of the mutations were identified near the DRY and NPxxY motifs of H3R, which are important for activation and are commonly found in class A GPCRs. The mutants responded exclusively to the yeast YB1 strain harboring Gi-chimera proteins, showing retention of G protein specificity. Analysis of one of the mutants with recovered activity, C415R, revealed that it maintained its ligand-binding characteristics. The strategy used in this study may enable the recovery of the activity of other GPCRs that do not function in S. cerevisiae and may be useful in creating GPCRs mutants stabilized in their active conformations.