GPCRdb: an information system for G protein-coupled receptors

Molecular recognition of an odorant by the murine trace amine-associated receptor TAAR7f

There are two main families of G protein-coupled receptors that detect odours in humans, the odorant receptors (ORs) and the trace amine-associated receptors (TAARs). Their amino acid sequences are distinct, with the TAARs being most similar to the aminergic receptors such as those activated by adrenaline, serotonin, dopamine and histamine. To elucidate the structural determinants of ligand recognition by TAARs, we have determined the cryo-EM structure of a murine receptor, mTAAR7f, coupled to the heterotrimeric G protein Gs and bound to the odorant N,N-dimethylcyclohexylamine (DMCHA) to an overall resolution of 2.9 Å. DMCHA is bound in a hydrophobic orthosteric binding site primarily through van der Waals interactions and a strong charge-charge interaction between the tertiary amine of the ligand and an aspartic acid residue. This site is distinct and non-overlapping with the binding site for the odorant propionate in the odorant receptor OR51E2. The structure, in combination with mutagenesis data and molecular dynamics simulations suggests that the activation of the receptor follows a similar pathway to that of the β-adrenoceptors, with the significant difference that DMCHA interacts directly with one of the main activation microswitch residues, Trp6.48.

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study

With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. In this study, we leveraged the availability of hundreds of peptide GPCRs in the active state and both classical homology and artificial intelligence (AI) based protein modeling combined with docking and AI-based peptide structure prediction approaches to predict the nociceptin/orphanin FQ-NOP receptor active state complex (N/OFQ-NOPa). The In Silico generated hypotheses were validated via the design, synthesis, and pharmacological characterization of novel linear N/OFQ(1-13)-NH2 analogues, leading to the discovery of a novel antagonist (3B; pKB = 6.63) bearing a single ring-constrained residue in place of the Gly2-Gly3 motif of the N/OFQ message sequence (FGGF). While the experimental validation was ongoing, the availability of the Cryo-EM structure of the predicted complex enabled us to unambiguously validate the generated hypotheses. To the best of our knowledge, this is the first example of a peptide-GPCR complex predicted with atomistic accuracy (full complex Cα RMSD < 1.0 Å) and of the N/OFQ message moiety being successfully modified with a rigid scaffold.

Structural and Computational Insights into Dynamics and Intermediate States of Orexin 2 Receptor Signaling

Orexin 2 receptor (OX2R) is a G protein-coupled receptor (GPCR) whose activation is crucial to regulation of the sleep-wake cycle. Recently, inactive and active state structures were determined from X-ray crystallography and cryo-electron microscopy single particle analysis, and the activation mechanisms have been discussed based on these static data. GPCRs have multiscale intermediate states during activation, and insights into these dynamics and intermediate states may aid the precise control of intracellular signaling by ligands in drug discovery. Molecular dynamics (MD) simulations are used to investigate dynamics induced in response to thermal perturbations, such as structural fluctuations of main and side chains. In this study, we proposed collective motions of the TM domain during activation by performing 30 independent microsecond-scale MD simulations for various OX2R systems and applying relaxation mode analysis. The analysis results suggested that TM3 had a vertical structural movement relative to the membrane surface during activation. In addition, we extracted three characteristic amino acid residues on TM3, i.e., Q1343.32, V1423.40, and R1523.50, which exhibited large conformational fluctuations. We quantitatively evaluated the changes in their equilibrium during activation in relation to the movement of TM3. We also discuss the regulation of ligand binding recognition and intracellular signal selectivity by changes in the equilibrium of Q1343.32 and R1523.50, respectively, according to MD simulations and GPCR database. Additionally, the OX2R-Gi signaling complex is stabilized in the conformation resembling a non-canonical (NC) state, which was previously proposed as an intermediate state during activation of neurotensin 1 receptor. Insights into the dynamics and intermediate states during activation gained from this study may be useful for developing biased agonists for OX2R.

Allosteric Modulators of Serotonin Receptors: A Medicinal Chemistry Survey

Serotonin (5-hydroxytryptamine, 5-HT) is a neurotransmitter regulating numerous physiological functions, and its dysregulation is a crucial component of the pathological processes of schizophrenia, depression, migraines, and obesity. 5-HT interacts with 14 different receptors, of which 5-HT1A-1FRs, 5-HT2A-CRs, and 5-HT4-7Rs are G protein-coupled receptors (GPCRs), while 5-HT3R is a ligand-gated ion channel. Over the years, selective orthosteric ligands have been identified for almost all serotonin receptors, yielding several clinically relevant drugs. However, the high degree of homology between 5-HTRs and other GPCRs means that orthosteric ligands can have severe side effects. Thus, there has recently been increased interest in developing safer ligands of GPCRs, which bind to less conserved, more specific sites, distinct from that of the receptor's natural ligand. The present review describes the identification of allosteric ligands of serotonin receptors, which are largely natural compounds (oleamide, cannabidiol, THC, and aporphine alkaloids), complemented by synthetic modulators developed in large part for the 5-HT2C receptor. The latter are positive allosteric modulators sought after for their potential as drugs preferable over the orthosteric agonists as antiobesity agents for their potentially safer profile. When available, details on the interactions between the ligand and allosteric binding site will be provided. An outlook on future research in the field will also be provided.

Time-resolved cryo-EM of G-protein activation by a GPCR

G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating guanine nucleotide exchange in the Gα subunit1. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G-protein complex. By monitoring the transitions of the stimulatory Gs protein in complex with the β2-adrenergic receptor at short sequential time points after GTP addition, we identified the conformational trajectory underlying G-protein activation and functional dissociation from the receptor. Twenty structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of main events driving G-protein activation in response to GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to Gα switch regions and the α5 helix that weaken the G-protein-receptor interface. Molecular dynamics simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP on closure of the α-helical domain against the nucleotide-bound Ras-homology domain correlates with α5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signalling events.

GPR101: Modeling a constitutively active receptor linked to X-linked acrogigantism

GPR101 is a G protein-coupled receptor (GPCR) implicated in a rare form of genetic gigantism known as X-linked acrogigantism, or X-LAG. In particular, X-LAG patients harbor microduplications in the long arm of the X-chromosome that invariably include the GPR101 gene. Duplications of the GPR101 gene lead to the formation of a new chromatin domain that causes over-expression of the receptor in the pituitary tumors of the patients. Notably, GPR101 is a constitutively active receptor, which stimulates cells to produce the second messenger cyclic AMP (cAMP) in the absence of ligands. Moreover, GPR101 was recently reported to constitutively activate not only the cAMP pathway via Gs, but also other G protein subunits (Gq/11 and G12/13). Hence, chemicals that block the constitutive activity of GPR101, known as inverse agonists, have the potential to be useful for the development of pharmacological tools for the treatment of X-LAG. In this study, we provide structural insights into the putative structure of GPR101 based on in-house built homology models, as well as third party models based on the machine learning methods AlphaFold and AlphaFold-Multistate. Moreover, we report a molecular dynamics study, meant to further probe the constitutive activity of GPR101. Finally, we provide a structural comparison with the closest GPCRs, which suggests that GPR101 does not share their natural ligands. While this manuscript was under review, cryo-electron microscopy structures of GPR101 were reported. These structures are expected to enable computer-aided ligand discovery efforts targeting GPR101.

Biased Signaling in Mutated Variants of β2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations

The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.

Characterizing conformational states in GPCR structures using machine learning

G protein-coupled receptors (GPCRs) play a pivotal role in signal transduction and represent attractive targets for drug development. Recent advances in structural biology have provided insights into GPCR conformational states, which are critical for understanding their signaling pathways and facilitating structure-based drug discovery. In this study, we introduce a machine learning approach for conformational state annotation of GPCRs. We represent GPCR conformations as high-dimensional feature vectors, incorporating information about amino acid residue pairs involved in the activation pathway. Using a dataset of GPCR conformations in inactive and active states obtained through molecular dynamics simulations, we trained machine learning models to distinguish between inactive-like and active-like conformations. The developed model provides interpretable predictions and can be used for the large-scale analysis of molecular dynamics trajectories of GPCRs.

The Pivotal Distinction between Antagonists' and Agonists' Binding into Dopamine D4 Receptor-MD and FMO/PIEDA Studies

The dopamine D4 receptor (D4R) is a promising therapeutic target in widespread diseases, and the search for novel agonists and antagonists appears to be clinically relevant. The mechanism of binding to the receptor (R) for antagonists and agonists varies. In the present study, we conducted an in-depth computational study, teasing out key similarities and differences in binding modes, complex dynamics, and binding energies for D4R agonists and antagonists. The dynamic network method was applied to investigate the communication paths between the ligand (L) and G-protein binding site (GBS) of human D4R. Finally, the fragment molecular orbitals with pair interaction energy decomposition analysis (FMO/PIEDA) scheme was used to estimate the binding energies of L-R complexes. We found that a strong salt bridge with D3.32 initiates the inhibition of the dopamine D4 receptor. This interaction also occurs in the binding of agonists, but the change in the receptor conformation to the active state starts with interaction with cysteine C3.36. Such a mechanism may arise in the case of agonists unable to form a hydrogen bond with the serine S5.46, considered, so far, to be crucial in the activation of GPCRs. The energy calculations using the FMO/PIEDA method indicate that antagonists show higher residue occupancy of the receptor binding site than agonists, suggesting they could form relatively more stable complexes. Additionally, antagonists were characterized by repulsive interactions with S5.46 distinguishing them from agonists.

GproteinDb in 2024: new G protein-GPCR couplings, AlphaFold2-multimer models and interface interactions

G proteins are the major signal proteins of ∼800 receptors for medicines, hormones, neurotransmitters, tastants and odorants. GproteinDb offers integrated genomic, structural, and pharmacological data and tools for analysis, visualization and experiment design. Here, we present the first major update of GproteinDb greatly expanding its coupling data and structural templates, adding AlphaFold2 structure models of GPCR-G protein complexes and advancing the interactive analysis tools for their interfaces underlying coupling selectivity. We present insights on coupling agreement across datasets and parameters, including constitutive activity, agonist-induced activity and kinetics. GproteinDb is accessible at https://gproteindb.org.

Cardiac human bitter taste receptors contain naturally occurring variants that alter function

Bitter taste receptors (T2R) are a subfamily of G protein-coupled receptors that enable humans to detect aversive and toxic substances. The ability to discern bitter compounds varies between individuals and is attributed mainly to naturally occurring T2R polymorphisms. T2Rs are also expressed in numerous non-gustatory tissues, including the heart, indicating potential contributions to cardiovascular physiology. In this study. T2Rs that have previously been identified in human cardiac tissues (T2Rs - 10, 14, 30, 31, 46 and 50) and their naturally occurring polymorphisms were functionally characterised. The ligand-dependent signaling responses of some T2R variants were completely abolished (T2R30 Leu252 and T2R46 Met228), whereas other receptor variants had moderate changes in their maximal response, but not potency, relative to wild type. Using a cAMP fluorescent biosensor, we reveal the productive coupling of T2R14, but not the T2R14 Phe201 variant, to endogenous Gαi. Modeling revealed that these variants resulted in altered interactions that generally affected ligand binding (T2R30 Leu252) or Gα protein interactions (T2R46 Met228 and T2R14 Phe201), rather than receptor structural stability. Interestingly, this study is the first to show a difference in signaling for T2R50 Tyr203 (rs1376251) which has been associated with cardiovascular disease. The observation of naturally occurring functional variation in the T2Rs with the greatest expression in the heart is important, as their discovery should prove useful in deciphering the role of T2Rs within the cardiovascular system.

Endothelin signaling in development

Since the discovery of endothelin 1 (EDN1) in 1988, the role of endothelin ligands and their receptors in the regulation of blood pressure in normal and disease states has been extensively studied. However, endothelin signaling also plays crucial roles in the development of neural crest cell-derived tissues. Mechanisms of endothelin action during neural crest cell maturation have been deciphered using a variety of in vivo and in vitro approaches, with these studies elucidating the basis of human syndromes involving developmental differences resulting from altered endothelin signaling. In this Review, we describe the endothelin pathway and its functions during the development of neural crest-derived tissues. We also summarize how dysregulated endothelin signaling causes developmental differences and how this knowledge may lead to potential treatments for individuals with gene variants in the endothelin pathway.

sBioSITe enables sensitive identification of the cell surface proteome through direct enrichment of biotinylated peptides

BACKGROUND

Cell surface proteins perform critical functions related to immune response, signal transduction, cell-cell interactions, and cell migration. Expression of specific cell surface proteins can determine cell-type identity, and can be altered in diseases including infections, cancer and genetic disorders. Identification of the cell surface proteome remains a challenge despite several enrichment methods exploiting their biochemical and biophysical properties.

METHODS

Here, we report a novel method for enrichment of proteins localized to cell surface. We developed this new approach designated surface Biotinylation Site Identification Technology (sBioSITe) by adapting our previously published method for direct identification of biotinylated peptides. In this strategy, the primary amine groups of lysines on proteins on the surface of live cells are first labeled with biotin, and subsequently, biotinylated peptides are enriched by anti-biotin antibodies and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

By direct detection of biotinylated lysines from PC-3, a prostate cancer cell line, using sBioSITe, we identified 5851 peptides biotinylated on the cell surface that were derived from 1409 proteins. Of these proteins, 533 were previously shown or predicted to be localized to the cell surface or secreted extracellularly. Several of the identified cell surface markers have known associations with prostate cancer and metastasis including CD59, 4F2 cell-surface antigen heavy chain (SLC3A2) and adhesion G protein-coupled receptor E5 (CD97). Importantly, we identified several biotinylated peptides derived from plectin and nucleolin, both of which are not annotated in surface proteome databases but have been shown to have aberrant surface localization in certain cancers highlighting the utility of this method.

CONCLUSIONS

Detection of biotinylation sites on cell surface proteins using sBioSITe provides a reliable method for identifying cell surface proteins. This strategy complements existing methods for detection of cell surface expressed proteins especially in discovery-based proteomics approaches.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

A tool kit of highly selective and sensitive genetically encoded neuropeptide sensors

Neuropeptides are key signaling molecules in the endocrine and nervous systems that regulate many critical physiological processes. Understanding the functions of neuropeptides in vivo requires the ability to monitor their dynamics with high specificity, sensitivity, and spatiotemporal resolution. However, this has been hindered by the lack of direct, sensitive, and noninvasive tools. We developed a series of GRAB (G protein-coupled receptor activation‒based) sensors for detecting somatostatin (SST), corticotropin-releasing factor (CRF), cholecystokinin (CCK), neuropeptide Y (NPY), neurotensin (NTS), and vasoactive intestinal peptide (VIP). These fluorescent sensors, which enable detection of specific neuropeptide binding at nanomolar concentrations, establish a robust tool kit for studying the release, function, and regulation of neuropeptides under both physiological and pathophysiological conditions.

Stable Binding of Full-Length Chemerin Is Driven by Negative Charges in the CMKLR1 N Terminus

The adipokine chemerin is the endogenous ligand of the chemokine-like receptor 1 (CMKLR1), a member of the family of G protein-coupled receptors (GPCRs). This protein ligand plays an important role in obesity and inflammatory processes. Stable receptor-ligand interactions are highly relevant for its different physiological effects such as the migration of immune cells towards sites of inflammation. Here, we demonstrate that negative charges in the CMKLR1 N terminus are involved in the formation of strong contacts with a specific positively charged patch at the surface of full-length chemerin, which is absent in the short nonapeptide agonist chemerin-9, thus explaining its reduced affinity. Using receptor chimera of G protein-coupled receptor 1 (GPR1) and CMKLR1, we were able to identify the residues of this interaction and its relevance for stable full-length chemerin binding. This could help to develop more potent ligands for the treatment of inflammation-related diseases.

Development of Nanopore sequencing-based full-length transcriptome database toward functional genome annotation of the Pacific oyster, Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is a widely cultivated shellfish in the world, while its transcriptome diversity remains less unexplored due to the limitation of short reads. In this study, we used Oxford Nanopore sequencing to develop the full-length transcriptome database of C. gigas. We identified 77,920 full-length transcripts from 21,523 genes, and uncovered 9668 alternative splicing events and 87,468 alternative polyadenylation sites. Notably, a total of 16,721 novel transcripts were annotated in this work. Furthermore, integrative analysis of 25 publicly available RNA-seq datasets revealed the transcriptome diversity involved in post-transcriptional regulation in C. gigas. We further developed a Drupal based webserver, Cgtdb, which can be used for transcriptome visualization, sequence alignment, and functional genome annotation analyses. This work provides valuable resources and a useful tool for integrative analysis of various transcriptome datasets in C. gigas, which will serve as an essential reference for functional annotation of the oyster genome.

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors

Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.

Molecular recognition of an aversive odorant by the murine trace amine-associated receptor TAAR7f

There are two main families of G protein-coupled receptors that detect odours in humans, the odorant receptors (ORs) and the trace amine-associated receptors (TAARs). Their amino acid sequences are distinct, with the TAARs being most similar to the aminergic receptors such as those activated by adrenaline, serotonin and histamine. To elucidate the structural determinants of ligand recognition by TAARs, we have determined the cryo-EM structure of a murine receptor, mTAAR7f, coupled to the heterotrimeric G protein Gs and bound to the odorant N,N-dimethylcyclohexylamine (DMCH) to an overall resolution of 2.9 Å. DMCH is bound in a hydrophobic orthosteric binding site primarily through van der Waals interactions and a strong charge-charge interaction between the tertiary amine of the ligand and an aspartic acid residue. This site is distinct and non-overlapping with the binding site for the odorant propionate in the odorant receptor OR51E2. The structure, in combination with mutagenesis data and molecular dynamics simulations suggests that the activation of the receptor follows a similar pathway to that of the β-adrenoceptors, with the significant difference that DMCH interacts directly with one of the main activation microswitch residues.

The G protein-coupled receptor neuropeptide receptor-15 modulates larval development via the transforming growth factor-β DAF-7 protein in Caenorhabditis elegans

G protein-coupled receptors (GPCRs) are a major class of membrane receptors that modulate a wide range of physiological functions. These receptors transmit extracellular signals, including secreted bioactive peptides, to intracellular signaling pathways. The nematode Caenorhabditis elegans has FMRFamide-like peptides, which are one of the most diverse neuropeptide families, some of which modulate larval development through GPCRs. In this study, we identified the GPCR neuropeptide receptor (NPR)-15, which modulates C. elegans larval development. Our molecular genetic analyses indicated the following: 1) NPR-15 mainly functions in ASI neurons, which predominantly regulate larval development, 2) NPR-15 interacts with GPA-4, a C. elegans Gα subunit, and 3) NPR-15, along with GPA-4, modulates larval development by regulating the production and secretion of the transforming growth factor-β (TGF-β)-like protein DAF-7. The present study is the first report to demonstrate the importance of a GPCR to the direct regulation of a TGF-β-like protein.

Class B1 GPCR activation by an intracellular agonist

G protein-coupled receptors (GPCRs) generally accommodate specific ligands in the orthosteric-binding pockets. Ligand binding triggers a receptor allosteric conformational change that leads to the activation of intracellular transducers, G proteins and β-arrestins. Because these signals often induce adverse effects, the selective activation mechanism for each transducer must be elucidated. Thus, many orthosteric-biased agonists have been developed, and intracellular-biased agonists have recently attracted broad interest. These agonists bind within the receptor intracellular cavity and preferentially tune the specific signalling pathway over other signalling pathways, without allosteric rearrangement of the receptor from the extracellular side1-3. However, only antagonist-bound structures are currently available1,4-6, and there is no evidence to support that biased agonist binding occurs within the intracellular cavity. This limits the comprehension of intracellular-biased agonism and potential drug development. Here we report the cryogenic electron microscopy structure of a complex of Gs and the human parathyroid hormone type 1 receptor (PTH1R) bound to a PTH1R agonist, PCO371. PCO371 binds within an intracellular pocket of PTH1R and directly interacts with Gs. The PCO371-binding mode rearranges the intracellular region towards the active conformation without extracellularly induced allosteric signal propagation. PCO371 stabilizes the significantly outward-bent conformation of transmembrane helix 6, which facilitates binding to G proteins rather than β-arrestins. Furthermore, PCO371 binds within the highly conserved intracellular pocket, activating 7 out of the 15 class B1 GPCRs. Our study identifies a new and conserved intracellular agonist-binding pocket and provides evidence of a biased signalling mechanism that targets the receptor-transducer interface.

Targeting biased signaling by PAR1: function and molecular mechanism of parmodulins

The G protein-coupled receptor (GPCR) protease-activated receptor 1 (PAR1) is a therapeutic target that was originally pursued with the aim of restricting platelet activation and the burden of cardiovascular diseases. In clinical studies, the use of orthosteric PAR1 inhibitors was associated with an increased risk of hemorrhage, including intracranial hemorrhage. Because (1) PAR1 is expressed by various cell types, including endothelial cells, (2) conveys in mice a physiological indispensable function for vascular development during embryogenesis, and (3) is subject to biased signaling dependent on the activating proteases, orthosteric PAR1 inhibition may be associated with unwanted side effects. Alternatively, the protease-activated protein C (aPC) and its variants can promote valuable anti-inflammatory signaling via PAR1. Most recently, small molecule allosteric modulators of PAR1 signaling, called parmodulins, have been developed. Parmodulins inhibit coagulation and platelet activation yet maintain cytoprotective effects typically provoked by PAR1 signaling upon the activation by aPC. In this study, we review the discovery of parmodulins and their preclinical data, summarize the current knowledge about their mode of action, and compare the structural interaction of parmodulin and PAR1 with that of other intracellularly binding allosteric GPCR modulators. Thus, we highlight the pharmaceutical potential and challenges associated with the future development of parmodulins.

Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.

Time-resolved cryo-EM of G protein activation by a GPCR

G protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating the exchange of guanine nucleotide in the Gα subunit. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G protein complex. Using variability analysis to monitor the transitions of the stimulatory Gs protein in complex with the β 2 -adrenergic receptor (β 2 AR) at short sequential time points after GTP addition, we identified the conformational trajectory underlying G protein activation and functional dissociation from the receptor. Twenty transition structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of events driving G protein activation upon GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to Gα Switch regions and the α5 helix that weaken the G protein-receptor interface. Molecular dynamics (MD) simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP upon closure of the alpha-helical domain (AHD) against the nucleotide-bound Ras-homology domain (RHD) correlates with irreversible α5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signaling events.

Two-step structural changes in M3 muscarinic receptor activation rely on the coupled Gq protein cycle

G protein-coupled receptors (GPCRs) regulate diverse intracellular signaling pathways through the activation of heterotrimeric G proteins. However, the effects of the sequential activation-deactivation cycle of G protein on the conformational changes of GPCRs remains unknown. By developing a Förster resonance energy transfer (FRET) tool for human M3 muscarinic receptor (hM3R), we find that a single-receptor FRET probe can display the consecutive structural conversion of a receptor by G protein cycle. Our results reveal that the G protein activation evokes a two-step change in the hM3R structure, including the fast step mediated by G_q protein binding and the subsequent slower step mediated by the physical separation of the Gα_q and Gβγ subunits. We also find that the separated Gα_q-GTP forms a stable complex with the ligand-activated hM3R and phospholipase Cβ. In sum, the present study uncovers the real-time conformational dynamics of innate hM3R during the downstream G_q protein cycle.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of ~ 1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.

Structural analysis of human G-protein-coupled receptor 17 ligand binding sites

The human G protein coupled membrane receptor (GPR17), the sensor of brain damage, is identified as a biomarker for many neurological diseases. In human brain tissue, GPR17 exist in two isoforms, long and short. While cryo-electron microscopy technology has provided the structure of the long isoform of GPR17 with Gi complex, the structure of the short isoform and its activation mechanism remains unclear. Recently, we theoretically modeled the structure of the short isoform of GPR17 with Gi signaling protein and identified novel ligands. In the present work, we demonstrated the presence of two distinct ligand binding sites in the short isoform of GPR17. The molecular docking of GPR17 with endogenous (UDP) and synthetic ligands (T0510.3657, MDL29950) found the presence of two distinct binding pockets. Our observations revealed that endogenous ligand UDP can bind stronger in two different binding pockets as evidenced by glide and autodock vina scores, whereas the other two ligand's binding with GPR17 has less docking score. The analysis of receptor-UDP interactions shows complexes' stability in the lipid environment by 100 ns atomic molecular dynamics simulations. The amino acid residues VAL83, ARG87, and PHE111 constitute ligand binding site 1, whereas site 2 constitutes ASN67, ARG129, and LYS232. Root mean square fluctuation analysis showed the residues 83, 87, and 232 with higher fluctuations during molecular dynamics simulation in both binding pockets. Our findings imply that the residues of GPR17's two binding sites are crucial, and their interaction with UDP reveals the protein's hidden signaling and communication properties. Furthermore, this finding may assist in the development of targeted therapies for the treatment of neurological diseases.

Anionic phospholipids control mechanisms of GPCR-G protein recognition

G protein-coupled receptors (GPCRs) are embedded in phospholipids that strongly influence drug-stimulated signaling. Anionic lipids are particularly important for GPCR signaling complex formation, but a mechanism for this role is not understood. Using NMR spectroscopy, we explore the impact of anionic lipids on the function-related conformational equilibria of the human A2A adenosine receptor (A2AAR) in bilayers containing defined mixtures of zwitterionic and anionic phospholipids. Anionic lipids prime the receptor to form complexes with G proteins through a conformational selection process. Without anionic lipids, signaling complex formation proceeds through a less favorable induced fit mechanism. In computational models, anionic lipids mimic interactions between a G protein and positively charged residues in A2AAR at the receptor intracellular surface, stabilizing a pre-activated receptor conformation. Replacing these residues strikingly alters the receptor response to anionic lipids in experiments. High sequence conservation of the same residues among all GPCRs supports a general role for lipid-receptor charge complementarity in signaling.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of ~1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.

Structural elucidation of ETHR-A and ETHR-B from Plutella xylostella and insight into non-conservative mutations in transmembrane helix-6

The development of Diamondback moth (DBM) depends on the ecdysis triggering hormone receptor (ETHR); a neuronal membrane G-protein coupled receptor (GPCR) connected to the metamorphosis cascade. Lepidopteran insect DBM is an infamous pest of cruciferous plants. This study examined the full-length coding sequences (CDS) of PxETHR-A and PxETHR-B from the DBM genome. The three-dimensional (3 D) models of both receptors were generated in an inactive state. The behaviour and stability of receptors were examined using molecular dynamics simulations in a lipid membrane system for 300 ns and established a GPCR family-based view. Secondary interactions within receptors were studied to know more about factors contributing to their stability. Multiple sequence alignment revealed conserved features of insect ETHRs those compared to the GPCR family proteins. These features were helpful during the evaluation of the molecular models of both receptors. Side-chain orientation of conserved residues, non-conserved and conserved hydrogen-bond networks (HBN) and hydrophobic clusters were examined in the structures of both receptors. The non-conserved residues L6.35, T6.39, C/S6.43, and L6.48, are present in a conserved position on the transmembrane helix-6 (TM6) of ETHRs. In TM6, PxETHR-A and PxETHR-B differ at positions C/S6.43 and Y/F6.51, both being part of the HBN.Communicated by Ramaswamy H. Sarma.

Anionic Phospholipids Control Mechanisms of GPCR-G Protein Recognition

G protein-coupled receptors (GPCRs) are embedded in phospholipids that strongly influence drug-stimulated signaling. Anionic lipids are particularly important for GPCR signaling complex formation, but a mechanism for this role is not understood. Using NMR spectroscopy, we visualized the impact of anionic lipids on the function-related conformational equilibria of the human A 2A adenosine receptor (A 2A AR) in bilayers containing defined mixtures of zwitterionic and anionic phospholipids. Anionic lipids primed the receptor to form complexes with G proteins through a conformational selection process. Without anionic lipids, signaling complex formation proceeded through a less favorable induced fit mechanism. In computational models, anionic lipids mimicked interactions between a G protein and positively charged residues in A 2A AR at the receptor intracellular surface, stabilizing a pre-activated receptor conformation. Replacing these residues strikingly altered the receptor response to anionic lipids in experiments. High sequence conservation of the same residues among all GPCRs supports a general role for lipid-receptor charge complementarity in signaling.

GPCRdb in 2023: state-specific structure models using AlphaFold2 and new ligand resources

G protein-coupled receptors (GPCRs) are physiologically abundant signaling hubs routing hundreds of extracellular signal substances and drugs into intracellular pathways. The GPCR database, GPCRdb supports >5000 interdisciplinary researchers every month with reference data, analysis, visualization, experiment design and dissemination. Here, we present our fifth major GPCRdb release setting out with an overview of the many resources for receptor sequences, structures, and ligands. This includes recently published additions of class D generic residue numbers, a comparative structure analysis tool to identify functional determinants, trees clustering GPCR structures by 3D conformation, and mutations stabilizing inactive/active states. We provide new state-specific structure models of all human non-olfactory GPCRs built using AlphaFold2-MultiState. We also provide a new resource of endogenous ligands along with a larger number of surrogate ligands with bioactivity, vendor, and physiochemical descriptor data. The one-stop-shop ligand resources integrate ligands/data from the ChEMBL, Guide to Pharmacology, PDSP Ki and PubChem database. The GPCRdb is available at https://gpcrdb.org.

Homology Modeling of the G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are therapeutically important family of membrane proteins. Despite growing number of experimental structures available for GPCRs, homology modeling remains a relevant method for studying these receptors and for discovering new ligands for them. Here we describe the state-of-the-art methods for modeling GPCRs, starting from template selection, through fine-tuning sequence alignment to model refinement.

Molecular modeling and dynamics studies of the synthetic small molecule agonists with GPR17 and P2Y1 receptor

The human Guanine Protein coupled membrane Receptor 17 (hGPR17), an orphan receptor that activates uracil nucleotides and cysteinyl leukotrienes is considered as a crucial target for the neurodegenerative diseases. Yet, the detailed molecular interaction of potential synthetic ligands of GPR17 needs to be characterized. Here, we have studied a comparative analysis on the interaction specificity of GPR17-ligands with hGPR17 and human purinergic G protein-coupled receptor (hP2Y1) receptors. Previously, we have simulated the interaction stability of synthetic ligands such as T0510.3657, AC1MLNKK, and MDL29951 with hGPR17 and hP2Y1 receptor in the lipid environment. In the present work, we have comparatively studied the protein-ligand interaction of hGPR17-T0510.3657 and P2Y1-MRS2500. Sequence analysis and structural superimposition of hGPR17 and hP2Y1 receptor revealed the similarities in the structural arrangement with the local backbone root mean square deviation (RMSD) value of 1.16 Å and global backbone RMSD value of 5.30 Å. The comparative receptor-ligand interaction analysis between hGPR17 and hP2Y1 receptor exposed the distinct binding sites in terms of geometrical properties. Further, the molecular docking of T0510.3657 with the hP2Y1 receptor have shown non-specific interaction. The experimental validation also revealed that Gi-coupled activation of GPR17 by specific ligands leads to the adenylyl cyclase inhibition, while there is no inhibition upon hP2Y1 activation. Overall, the above findings suggest that T0510.3657-GPR17 binding specificity could be further explored for the treatment of numerous neuronal diseases. Communicated by Ramaswamy H. Sarma.

Computational study of the conformational ensemble of CX3C chemokine receptor 1 (CX3CR1) and its interactions with antagonist and agonist ligands

The CX3C chemokine receptor 1 (CX3CR1), a member of the class A of G Protein-Coupled Receptors (GPCR) superfamily, and its ligand fractalkine constitute an important biochemical axis that influence many cellular pathways involving homeostatic and inflammatory processes. They participate in the activation, chemotaxis and recruitment of multiple immunological cells such as microglia, macrophages and monocytes, and play a critical role in neuroinflammatory conditions such as Alzheimer's disease and multiple sclerosis, in the recovery from central nervous system injuries, in several chronic, peripheral inflammatory entities and in some infective processes including HIV-AIDS. In this work we present the study of the CX3CR1 receptor employing extensive atomistic Molecular Dynamics (MD) simulations with the aim to characterize the conformational ensemble of the receptor in the presence of its antagonist and agonist ligands. We analyzed the receptor conformational changes and described interactions within its key regions and the bounded ligands to identify their notable differences. Finally, we classify the features that would allow the identification of patterns that characterize a functional state to contribute to the understanding of the complexity of the GPCR superfamily.

Building the Chordata Olfactory Receptor Database using more than 400,000 receptors annotated by Genome2OR

Olfactory receptors are poorly annotated for most genome-sequenced chordates. To address this deficiency, we developed a nhmmer-based olfactory receptor annotation tool Genome2OR ( https://github.com/ToHanwei/Genome2OR.git ), and used it to process 1,695 sequenced chordate genomes in the NCBI Assembly database as of January, 2021. In total, 765,248 olfactory receptor genes were annotated, with 404,426 functional genes and 360,822 pseudogenes, which represents a four-fold increase in the number of annotated olfactory receptors. Based on the annotation data, we built a database called Chordata Olfactory Receptor Database (CORD, https://cord.ihuman.shanghaitech.edu.cn ) for archiving, analysing and disseminating the data. Beyond the primary data, we offer derivative information, including pictures of species, cross references to public databases, structural models, sequence similarity networks and sequence profiles in the CORD. Furthermore, we did brief analyses on these receptors, including building a huge protein sequence similarity network covering all receptors in the database, and clustering them into 20 communities, classifying the 20 communities into three categories based on their presences/absences in ray-finned fish and/or lobe-finned fish. We infer that olfactory receptors should have unique activation and desensitization mechanisms by analysing their sequences and structural models. We believe the CORD can benefit the researchers and the general public who are interested in olfaction.

Superconserved receptors expressed in the brain: Expression, function, motifs and evolution of an orphan receptor family

GPR27, GPR85 and GPR173 constitute a small family of G protein-coupled receptors (GPCR) that share the distinctive characteristics of being highly conserved throughout vertebrate evolution and predominantly expressed in the brain. Accordingly, they have been coined as "Superconserved Receptors Expressed in the Brain" (SREB), although their expression profile is more complex than what was originally thought. SREBs have no known validated endogenous ligands and are thus labeled as "orphan" receptors. The investigation of this particular category of uncharacterized receptors holds great promise both in terms of physiology and drug development. In the largest GPCR family, the Rhodopsin-like or Class A, around 100 receptors are considered orphans. Because GPCRs are the most successful source of drug targets, the discovery of a novel function or ligand most likely will lead to significant breakthroughs for the discovery of innovative therapies. The high level of conservation is one of the characteristic features of the SREBs. We propose herein a detailed analysis of the putative evolutionary origin of this family. We highlight the properties that distinguish SREBs from other rhodopsin-like GPCRs. We present the current evidence for these receptors downstream signaling pathways and functions. We discuss the pharmacological challenge for the identification of natural or synthetic ligands of orphan receptors like SREBs. The different SREB-related scientific questions are presented with a highlight on what should be addressed in the near future, including the confirmation of published evidence and their validation as drug targets. In particular, we discuss in which pathological conditions these receptors may be of great relevance to solve unmet medical needs.

Molecular dynamics study of tropical calcific pancreatitis (TCP) associated calcium-sensing receptor single nucleotide variation

Tropical Calcific Pancreatitis (TCP) is a chronic non-alcoholic pancreatitis characterised by extensive calcification. The disease usually appears at a younger age and is more common in tropical regions. This disease’s progression can lead to pancreatic diabetes, which can subsequently lead to pancreatic cancer. The CASR gene encodes a calcium-sensing receptor (CaSR), which is a GPCR protein of class C. It is expressed in the islets of Langerhans, the parathyroid gland, and other tissues. It primarily detects small gradients in circulating calcium concentrations and couples this information to intracellular signalling, which helps to regulate PTH (parathyroid hormone) secretion and mineral ion homeostasis. From co-leading insulin release, CaSR modulates ductal HCO₃₋ secretion, Ca²⁺ concentration, cell-cell communication, β-cell proliferation, and intracellular Ca²⁺ release. In pancreatic cancer, the CaSR limits cell proliferation. TCP-related four novel missense mutations P163R, I427S, D433H and V477A, found in CaSR extracellular domain (ECD) protein, which were reported in the mutTCPdb Database (https://lms.snu.edu.in/mutTCPDB/index.php). P163R mutation occurs in ligand-binding domain 1 (LBD-1) of the CaSR ECD. To investigate the influence of these variations on protein function and structural activity multiple in-silico prediction techniques such as SIFT, PolyPhen, CADD scores, and other methods have been utilized. A 500 ns molecular dynamic simulation was performed on the CaSR ECD crystal structure and the corresponding mutated models. Furthermore, Principal Component Analysis (PCA) and Essential Dynamics analysis were used to forecast collective motions, thermodynamic stabilities, and the critical subspace crucial to CaSR functions. The results of molecular dynamic simulations showed that the mutations P163R, I427S, D433H, and V477A caused conformational changes and decreased the stability of protein structures. This study also demonstrates the significance of TCP associated mutations. As a result of our findings, we hypothesised that the investigated mutations may have an effect on the protein’s structure and ability to interact with other molecules, which may be related to the protein’s functional impairment.

Finding the Perfect Fit: Conformational Biosensors to Determine the Efficacy of GPCR Ligands

G protein-coupled receptors (GPCRs) are highly druggable targets that adopt numerous conformations. A ligand's ability to stabilize specific conformation(s) of its cognate receptor determines its efficacy or ability to produce a biological response. Identifying ligands that produce different receptor conformations and potentially discrete pharmacological effects (e.g., biased agonists, partial agonists, antagonists, allosteric modulators) is a major goal in drug discovery and necessary to develop drugs with better effectiveness and fewer side effects. Fortunately, direct measurements of ligand efficacy, via receptor conformational changes are possible with the recent development of conformational biosensors. In this review, we discuss classical efficacy models, including the two-state model, the ternary-complex model, and multistate models. We describe how nanobody-, transducer-, and receptor-based conformational biosensors detect and/or stabilize specific GPCR conformations to identify ligands with different levels of efficacy. In particular, conformational biosensors provide the potential to identify and/or characterize therapeutically desirable but often difficult to measure conformations of receptors faster and better than current methods. For drug discovery/development, several recent proof-of-principle studies have optimized conformational biosensors for high-throughput screening (HTS) platforms. However, their widespread use is limited by the fact that few sensors are reliably capable of detecting low-frequency conformations and technically demanding assay conditions. Nonetheless, conformational biosensors do help identify desirable ligands such as allosteric modulators, biased ligands, or partial agonists in a single assay, representing a distinct advantage over classical methods.

Nanobodies as Probes and Modulators of Cardiovascular G Protein-Coupled Receptors

ABSTRACT

Understanding the activation of G protein-coupled receptors (GPCRs) is of paramount importance to the field of cardiovascular medicine due to the critical physiological roles of these receptors and their prominence as drug targets. Although many cardiovascular GPCRs have been extensively studied as model receptors for decades, new complexities in their regulation continue to emerge. As a result, there is an ongoing need to develop novel approaches to monitor and to modulate GPCR activation. In less than a decade, nanobodies, or recombinant single-domain antibody fragments from camelids, have become indispensable tools for interrogating GPCRs both in purified systems and in living cells. Nanobodies have gained traction rapidly due to their biochemical tractability and their ability to recognize defined states of native proteins. Here, we review how nanobodies have been adopted to elucidate the structure, pharmacology, and signaling of cardiovascular GPCRs, resolving long-standing mysteries and revealing unexpected mechanisms. We also discuss how advancing technologies to discover nanobodies with tailored specificities may expand the impact of these tools for both basic science and therapeutic applications.

Exploring the deactivation mechanism of human β2 adrenergic receptor by accelerated molecular dynamic simulations

The β2 adrenergic receptor (β2AR), one of important members of the G protein coupled receptors (GPCRs), has been suggested as an important target for cardiac and asthma drugs. Two replicas of Gaussian accelerated molecular dynamics (GaMD) simulations are performed to explore the deactivation mechanism of the active β2AR bound by three different substrates, including the agonist (P0G), antagonist (JTZ) and inverse agonist (JRZ). The simulation results indicate that the Gs protein is needed to stabilize the active state of the β2AR. Without the Gs protein, the receptor could transit from the active state toward the inactive state. During the transition process, helix TM6 moves toward TM3 and TM5 in geometric space and TM5 shrinks upwards. The intermediate state is captured during the transition process of the active β2AR toward the inactive one, moreover the changes in hydrophobic interaction networks between helixes TM3, TM5, and TM6 and the formation of a salt bridge between residues Arg3.50 and Glu6.30 drive the transition process. We expect that this finding can provide energetic basis and molecular mechanism for further understanding the function and target roles of the β2AR.

Exploring the kinetic selectivity of drugs targeting the β1 -adrenoceptor

In this study, we report the β1 -adrenoceptor binding kinetics of several clinically relevant β1/2 -adrenoceptor (β1/2 AR) agonists and antagonists. [3 H]-DHA was used to label CHO-β1 AR for binding studies. The kinetics of ligand binding was assessed using a competition association binding method. Ligand physicochemical properties, including logD7.4 and the immobilized artificial membrane partition coefficient (KIAM ), were assessed using column-based methods. Protein Data Bank (PDB) structures and hydrophobic and electrostatic surface maps were constructed in PyMOL. We demonstrate that the hydrophobic properties of a molecule directly affect its kinetic association rate (kon ) and affinity for the β1 AR. In contrast to our findings at the β2 -adrenoceptor, KIAM , reflecting both hydrophobic and electrostatic interactions of the drug with the charged surface of biological membranes, was no better predictor than simple hydrophobicity measurements such as clogP or logD7.4 , at predicting association rate. Bisoprolol proved kinetically selective for the β1 AR subtype, dissociating 50 times slower and partly explaining its higher measured affinity for the β1 AR. We speculate that the association of positively charged ligands at the β1 AR is curtailed somewhat by its predominantly neutral/positive charged extracellular surface. Consequently, hydrophobic interactions in the ligand-binding pocket dominate the kinetics of ligand binding. In comparison at the β2 AR, a combination of hydrophobicity and negative charge attracts basic, positively charged ligands to the receptor's surface promoting the kinetics of ligand binding. Additionally, we reveal the potential role kinetics plays in the on-target and off-target pharmacology of clinically used β-blockers.

Computational and experimental approaches to probe GPCR activation and signaling

G protein-coupled receptors (GPCRs) regulate different physiological functions, e.g., sensation, growth, digestion, reproductivity, nervous and immune systems response, and many others. In eukaryotes, they are also responsible for intercellular communication in response to pathogens. The major primary messengers binding to these cell-surface receptors constitute small-molecule or peptide hormones and neurotransmitters, nucleotides, lipids as well as small proteins. The simplicity of the way how GPCR signaling can be regulated by their endogenous agonists prompted the usage of GPCRs as major drug targets in modern pharmacology. Drugs targeting GPCRs inhibit pathological processes at the very beginning. This enables to significantly reduce the occurrence of morphological changes caused by diseases. Until recently, X-ray crystallography was the method of the first choice to obtain high-resolution structural information about GPCRs. Following X-ray crystallography, cryo-EM gained attention in GPCR studies as a quick and low-cost alternative. FRET microscopy is also widely used for GPCRs in the analysis of protein-protein interactions (PPIs) in intact cells as well as for screening purposes. Regarding computational methods, molecular dynamics (MD) for many years has proven its usefulness in studying the GPCR activation. MODELLER and Rosetta were widely used to generate preliminary homology models of GPCRs for MD simulation systems. Apart from the conventional all-atom approach with explicitly defined solvent, also other techniques have been applied to GPCRs, e.g., MARTINI or hybrid methods involving the coarse-grained representation, less demanding regarding computational resources, and thus offering much larger simulation timescales.

Structure Prediction, Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.

Learning about allosteric drugs and ways to design them

While the accelerating quest for precision medicine requires new individually targeting and selective drugs, and the ability to work with so-called undruggable targets, the realm of allosteric drugs meeting this need remains largely uncharted. Generalizing the observations on two major drug targets with widely observed inherent allostery, GPCRs and kinases, we describe and discuss basic allosteric modes of action that are universally applicable in all types of structures and functions. Using examples of Class A GPCRs and CMGC protein kinases, we show how Allosteric Signalling and Probing Fingerprints can be used to identify potential allosteric sites and reveal effector-leads that may serve as a starting point for the development of allosteric drugs targeting these regulatory sites. A set of distinct characteristics of allosteric ligands was established, which highlights the versatility of their design and make them advantageous before their orthosteric counterparts in personalized medicine. We argue that rational design of allosteric drugs should begin with the search for latent sites or design of non-natural binding sites followed by fragment-based design of allosteric ligands and by the mutual adjustment of the site-ligand pair in order to achieve required effects. On the basis of the perturbative nature and reversibility of allosteric communication, we propose a generic protocol for computational design of allosteric effectors, enabling also the allosteric tuning of biologics, in obtaining allosteric control over protein functions.

Cancer-Related Somatic Mutations in Transmembrane Helices Alter Adenosine A1 Receptor Pharmacology

Overexpression of the adenosine A1 receptor (A1AR) has been detected in various cancer cell lines. However, the role of A1AR in tumor development is still unclear. Thirteen A1AR mutations were identified in the Cancer Genome Atlas from cancer patient samples. We have investigated the pharmacology of the mutations located at the 7-transmembrane domain using a yeast system. Concentration-growth curves were obtained with the full agonist CPA and compared to the wild type hA1AR. H78L3.23 and S246T6.47 showed increased constitutive activity, while only the constitutive activity of S246T6.47 could be reduced to wild type levels by the inverse agonist DPCPX. Decreased constitutive activity was observed on five mutant receptors, among which A52V2.47 and W188C5.46 showed a diminished potency for CPA. Lastly, a complete loss of activation was observed in five mutant receptors. A selection of mutations was also investigated in a mammalian system, showing comparable effects on receptor activation as in the yeast system, except for residues pointing toward the membrane. Taken together, this study will enrich the view of the receptor structure and function of A1AR, enlightening the consequences of these mutations in cancer. Ultimately, this may provide an opportunity for precision medicine for cancer patients with pathological phenotypes involving these mutations.

Cancer-related somatic mutations alter adenosine A1 receptor pharmacology-A focus on mutations in the loops and C-terminus

G protein-coupled receptors (GPCRs) are known to be involved in tumor progression and metastasis. The adenosine A₁ receptor (A₁ AR) has been detected to be over-expressed in various cancer cell lines. However, the role of A₁ AR in tumor development is not yet well characterized. A series of A₁ AR mutations were identified in the Cancer Genome Atlas from cancer patient samples. In this study, we have investigated the pharmacology of mutations located outside of the 7-transmembrane domain by using a "single-GPCR-one-G protein" yeast system. Concentration-growth curves were obtained with the full agonist CPA for 12 mutant receptors and compared to the wild-type hA₁ AR. Most mutations located at the extracellular loops (EL) reduced the levels of constitutive activity of the receptor and agonist potency. For mutants at the intracellular loops (ILs) of the receptor, an increased constitutive activity was found for mutant receptor L211R^5.69 , while a decreased constitutive activity and agonist response were found for mutant receptor L113F^34.51 . Lastly, mutations identified on the C-terminus did not significantly influence the pharmacological function of the receptor. A selection of mutations was also investigated in a mammalian system. Overall, similar effects on receptor activation compared to the yeast system were found with mutations located at the EL, but some contradictory effects were observed for mutations located at the IL. Taken together, this study will enrich the insight of A₁ AR structure and function, enlightening the consequences of these mutations in cancer. Ultimately, this may provide potential precision medicine in cancer treatment.

The pocketome of G-protein-coupled receptors reveals previously untargeted allosteric sites

G-protein-coupled receptors do not only feature the orthosteric pockets, where most endogenous agonists bind, but also a multitude of other allosteric pockets that have come into the focus as potential binding sites for synthetic modulators. Here, to better characterise such pockets, we investigate 557 GPCR structures by exhaustively docking small molecular probes in silico and converting the ensemble of binding locations to pocket-defining volumes. Our analysis confirms all previously identified pockets and reveals nine previously untargeted sites. In order to test for the feasibility of functional modulation of receptors through binding of a ligand to such sites, we mutate residues in two sites, in two model receptors, the muscarinic acetylcholine receptor M₃ and β₂-adrenergic receptor. Moreover, we analyse the correlation of inter-residue contacts with the activation states of receptors and show that contact patterns closely correlating with activation indeed coincide with these sites.

Substituted Purines as High-Affinity Histamine H3 Receptor Ligands

Continuing with our program to obtain new histamine H3 receptor (H3R) ligands, in this work we present the synthesis, H3R affinity and in silico studies of a series of eight new synthetically accessible purine derivatives. These compounds are designed from the isosteric replacement of the scaffold presented in our previous ligand, pyrrolo[2,3-d]pyrimidine ring, by a purine core. This design also considers maintaining the fragment of bipiperidine at C-4 and aromatic rings with electron-withdrawing groups at N-9, as these fragments are part of the proposed pharmacophore. The in vitro screening results show that two purine derivatives, 3d and 3h, elicit high affinities to the H3R (Ki values of 2.91 and 5.51 nM, respectively). Both compounds are more potent than the reference drug pitolisant (Ki 6.09 nM) and show low toxicity with in vitro models (IC50 > 30 µM on HEK-293, SH-SY5Y and HepG2 cell lines). Subsequently, binding modes of these ligands are obtained using a model of H3R by docking and molecular dynamics studies, thus determining the importance of the purine ring in enhancing affinity due to the hydrogen bonding of Tyr374 to the N-7 of this heterocycle. Finally, in silico ADME properties are predicted, which indicate a promising future for these molecules in terms of their physical−chemical properties, absorption, oral bioavailability and penetration in the CNS.

The Many Faces of G Protein-Coupled Receptor 143, an Atypical Intracellular Receptor

GPCRs transform extracellular stimuli into a physiological response by activating an intracellular signaling cascade initiated via binding to G proteins. Orphan G protein-coupled receptors (GPCRs) hold the potential to pave the way for development of new, innovative therapeutic strategies. In this review we will introduce G protein-coupled receptor 143 (GPR143), an enigmatic receptor in terms of classification within the GPCR superfamily and localization. GPR143 has not been assigned to any of the GPCR families due to the lack of common structural motifs. Hence we will describe the most important motifs of classes A and B and compare them to the protein sequence of GPR143. While a precise function for the receptor has yet to be determined, the protein is expressed abundantly in pigment producing cells. Many GPR143 mutations cause X-linked Ocular Albinism Type 1 (OA1, Nettleship-Falls OA), which results in hypopigmentation of the eyes and loss of visual acuity due to disrupted visual system development and function. In pigment cells of the skin, loss of functional GPR143 results in abnormally large melanosomes (organelles in which pigment is produced). Studies have shown that the receptor is localized internally, including at the melanosomal membrane, where it may function to regulate melanosome size and/or facilitate protein trafficking to the melanosome through the endolysosomal system. Numerous additional roles have been proposed for GPR143 in determining cancer predisposition, regulation of blood pressure, development of macular degeneration and signaling in the brain, which we will briefly describe as well as potential ligands that have been identified. Furthermore, GPR143 is a promiscuous receptor that has been shown to interact with multiple other melanosomal proteins and GPCRs, which strongly suggests that this orphan receptor is likely involved in many different physiological actions.