Enthalpy-Entropy Trade-Off Underlies Geometric Isomer Selectivity in Histamine H1 Receptor-Doxepin Interaction.

Docking and MD study of histamine H4R based on the crystal structure of H1R

Pancreatic ductal adenocarcinoma (PDAC) is the most common and lethal (5-year survival <10%) type of pancreatic cancer and the 3rd leading cause of cancer death in the U.S. Current treatment options (surgery, radiotherapy, and chemotherapy) rarely produce a cure. New and effective therapies for PDAC are thus an important, urgent need. As a novel approach to address this unmet need, we explored whether G protein-coupled receptors (GPCRs), in particular GPCRs with FDA-approved drugs (which could be repurposed), have altered expression in PDAC compared to healthy pancreatic tissue or cells. We undertook a comprehensive analysis of GPCRs (comparing GPCR expression in PDAC samples in The Cancer Genome Atlas [TCGA] with that in The Genotype-Tissue Expression [GTEx] database) and identified numerous GPCRs with higher expression in PDAC. One such GPCR, histamine receptor H1 (HRH1), which is targeted by many FDA-approved antihistamines, has ~30-fold higher mRNA expression in PDAC. We found that high HRH1 expression is an unfavorable prognostic marker for PDAC. However, the roles of HRH1 in PDAC are unknown. We hypothesized that HRH1 is functional and contributes to the phenotype of PDAC. We initially assessed the mRNA and protein expression of HRH1 in human PDAC cell lines. RNAseq data from The Cancer Cell Line Encyclopedia (CCLE) database revealed that HRH1 is the main histamine receptor expressed in multiple human PDAC cell lines: AsPC-1, MIA PaCa-2, PANC-1 and BxPC-3 (5-19 transcripts/million [TPM] compared to the other 3 HRHs [≤ 0.6 TPM]). We confirmed those results by qPCR. Proteomic analysis (PMID: 31978347 and PMID: 28375945) has identified HRH1 protein expression in AsPC-1, MIA PaCa2 and PANC-1: HRH1 had a strong protein-RNA correlation (Pearson correlation= 0.64 and Spearman correlation= 0.72). We next tested if HRH1 is functional in PDAC cells. We treated BxPC-3 cells with histamine (10µM) and with the FDA-approved HRH1 inhibitors/antihistamines loratadine or clemastine (both 1µM) in a wound healing assay. We found that histamine, via HRH1, increased BxPC-3 cell migration. Moreover, histamine (in a time- and concentration-dependent manner) increased intracellular Ca2+ in BxPC-3, AsPC-1 and Capan-2 cells. Multiple HRH1 antagonists blocked this response. We also found high expression of HRH1 (by qPCR) in pancreatic tumors of KPC (LSL-KrasG12D/+; Trp53f/f; Ptf1a-Cre) mice, which spontaneously develop pancreatic cancer. We isolated cancer cell lines from the KPC pancreatic tumors by multiple passage of the cells and found that: 1) the cells highly express HRH1 mRNA and 2) histamine increases intracellular Ca2+ via HRH1, i.e., inhibition by multiple HRH1 antihistamines. Together, these data indicate the presence and functional activity of HRH1 in human PDAC and a mouse model and suggest that HRH1 may be a novel therapeutic target for PDAC.

The 5-year survival of patients with pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer (90%), is very low (~9% all stages). PDAC thus requires new, effective and safe therapies. By comparing transcriptomic data for PDAC (in The Cancer Genome Atlas) with that of normal pancreas (in the GTEx database), we discovered that many G protein-coupled receptors (GPCRs) are increased in expression in PDAC. One such GPCR is the histamine receptor H1 (HRH1). GPCRs regulate metabolism, growth/death and functional activities of normal and cancer cells, including features of the malignant phenotype. GPCRs are the largest family of targets of approved drugs but have been largely ignored in cancer therapy. We found that HRH1 is prominently (~32-fold) overexpressed in PDAC tumors compared to normal pancreatic tissue and that high HRH1 expression is an unfavorable prognostic marker for PDAC patients. HRH1 mRNA is also highly expressed in multiple human PDAC cell lines. Studies with such cell lines revealed that histamine, acting via HRH1, increases intracellular Ca2+, cell proliferation and migration, effects blocked by multiple FDA-approved HRH1 antihistamines. PDAC tumors and cancer cells isolated from KPC mice also have high HRH1 expression compared to normal mouse pancreas. Similar to human PDAC cells, the KPC cells showed histamine/HRH1-promoted increase in intracellular Ca2+. Altogether, our findings identify HRH1 as a prominently overexpressed, functional GPCR in human and mouse PDAC tumors and cells. HRH1 may thus be a novel therapeutic target; its blockade by FDA-approved antihistamines represents a novel potential repurposing approach for the treatment of PDAC. Citation Format: Cristina Salmerón, Krishna Sriram, Alyssa Baird, Paul A. Insel. A GPCR candidate in pancreatic ductal adenocarcinoma: A potential repurposing opportunity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5160.

Chronic inflammatory diseases such as bronchial asthma, allergic gastrointestinal disease, and atopic dermatitis are characterized by the selective recruitment and activation of distinct subtypes of leukocytes, particularly eosinophils, into the tissue from peripheral blood (Rothenberg, 1998). Eosinophils, along with mast cells, are postulated to play a key role in the pathophysiology of these chronic diseases. The striking accumulation of eosinophils in allergic disease has stimulated intense scientific examination leading to the discovery of numerous molecular mechanisms responsible for this process. Eosinophils, like all leukocytes, migrate from the vascular lumen, across the endothelial cell surface into the appropriate tissue sites. This elaborate mechanism, known as transendothelial migration, has been shown to be a highly orchestrated process (Springer, 1994). The migratory pathway, or chemotaxis, of the leukocyte is directly influenced by soluble molecules known as chemoattractants. These molecules reside along a tissue gradient, and bind to and activate G-protein coupled receptors (GPCRs) on the leukocyte cell surface. Several eosinophil chemoattractants have been extensively studied. Some of these molecules, the classical chemoattractants, include the complement cleavage fragments, leukotrienes and platelet-activating factor (PAF). These chemoattractants have been shown to stimulate the recruitment of a wide variety of leukocyte subtypes, and are therefore nonselective. In contrast, chemotactic cytokines (or chemokines) such as eotaxin-1, -2, -3, and monocyte chemoattractant protein (MCP)-4 are more selective for the recruitment of leukocytes associated with allergic inflammation, such as eosinophils, mast cells, and basophils.

The cytoplasmic sides of transmembrane helices 3 and 6 of G-protein-coupled receptors are connected by a network of ionic interactions that play an important role in maintaining its inactive conformation. To investigate the role of such a network in rhodopsin structure and function, we have constructed single mutants at position 134 in helix 3 and at positions 247 and 251 in helix 6, as well as combinations of these to obtain double mutants involving the two helices. These mutants have been expressed in COS-1 cells, immunopurified using the rho-1D4 antibody, and studied by UV-visible spectrophotometry. Most of the single mutations did not affect chromophore formation, but double mutants, especially those involving the T251K mutant, resulted in low yield of protein and impaired 11-cis-retinal binding. Single mutants E134Q, E247Q, and E247A showed the ability to activate transducin in the dark, and E134Q and E247A enhanced activation upon illumination, with regard to wild-type rhodopsin. Mutations E247A and T251A (in E134Q/E247A and E134Q/T251A double mutants) resulted in enhanced activation compared with the single E134Q mutant in the dark. A role for Thr(251) in this network is proposed for the first time in rhodopsin. As a result of these mutations, alterations in the hydrogen bond interactions between the amino acid side chains at the cytoplasmic region of transmembrane helices 3 and 6 have been observed using molecular dynamics simulations. Our combined experimental and modeling results provide new insights into the details of the structural determinants of the conformational change ensuing photoactivation of rhodopsin.

Histamine H4 receptor (H4R) orthologues are G‐protein‐coupled receptors (GPCRs) that exhibit species‐dependent basal activity. In contrast to the basally inactive mouse H4R (mH4R), human H4R (hH4R) shows a high degree of basal activity. We have performed long‐timescale molecular dynamics simulations and rigidity analyses on wild‐type hH4R, the experimentally characterized hH4R variants S179M, F169V, F169V+S179M, F168A, and on mH4R to investigate the molecular nature of the differential basal activity. H4R variant‐dependent differences between essential motifs of GPCR activation and structural stabilities correlate with experimentally determined basal activities and provide a molecular explanation for the differences in basal activation. Strikingly, during the MD simulations, F16945.55 dips into the orthosteric binding pocket only in the case of hH4R, thus adopting the role of an agonist and contributing to the stabilization of the active state. The results shed new light on the molecular mechanism of basal H4R activation that are of importance for other GPCRs.

The H(4)R (histamine H(4) receptor) is the latest identified member of the histamine receptor subfamily of GPCRs (G-protein-coupled receptors) with potential functional implications in inflammatory diseases and cancer. The H(4)R is primarily expressed in eosinophils and mast cells and has the highest homology with the H(3)R. The occurrence of at least twenty different hH(3)R (human H(3)R) isoforms led us to investigate the possible existence of H(4)R splice variants. In the present paper, we report on the cloning of the first two alternatively spliced H(4)R isoforms from CD34+ cord blood-cell-derived eosinophils and mast cells. These H(4)R splice variants are localized predominantly intracellularly when expressed recombinantly in mammalian cells. We failed to detect any ligand binding, H(4)R-ligand induced signalling or constitutive activity for these H(4)R splice variants. However, when co-expressed with full-length H(4)R [H(4)R((390)) (H(4)R isoform of 390 amino acids)], the H(4)R splice variants have a dominant negative effect on the surface expression of H(4)R((390)). We detected H(4)R((390))-H(4)R splice variant hetero-oligomers by employing both biochemical (immunoprecipitation and cell-surface labelling) and biophysical [time-resolved FRET (fluorescence resonance energy transfer)] techniques. mRNAs encoding the H(4)R splice variants were detected in various cell types and expressed at similar levels to the full-length H(4)R((390)) mRNA in, for example, pre-monocytes. We conclude that the H(4)R splice variants described here have a dominant negative effect on H(4)R((390)) functionality, as they are able to retain H(4)R((390)) intracellularly and inactivate a population of H(4)R((390)), presumably via hetero-oligomerization.

G protein-coupled receptors (GPCRs) represent a major focus in functional genomics programs and drug development research, but their important potential as drug targets contrasts with the still limited data available concerning their activation mechanism. Here, we investigated the activation mechanism of the cholecystokinin-2 receptor (CCK2R). The three-dimensional structure of inactive CCK2R was homology-modeled on the basis of crystal coordinates of inactive rhodopsin. Starting from the inactive CCK2R modeled structure, active CCK2R (namely cholecystokinin-occupied CCK2R) was modeled by means of steered molecular dynamics in a lipid bilayer and by using available data from other GPCRs, including rhodopsin. By comparing the modeled structures of the inactive and active CCK2R, we identified changes in the relative position of helices and networks of interacting residues, which were expected to stabilize either the active or inactive states of CCK2R. Using targeted molecular dynamics simulations capable of converting CCK2R from the inactive to the active state, we delineated structural changes at the atomic level. The activation mechanism involved significant movements of helices VI and V, a slight movement of helices IV and VII, and changes in the position of critical residues within or near the binding site. The mutation of key amino acids yielded inactive or constitutively active CCK2R mutants, supporting this proposed mechanism. Such progress in the refinement of the CCK2R binding site structure and in knowledge of CCK2R activation mechanisms will enable target-based optimization of nonpeptide ligands.

Histamine H3 receptors (H3 R), belonging to G-protein coupled receptors (GPCR) class A superfamily, are responsible for modulating the release of histamine as well as of other neurotransmitters by a negative feedback mechanism mainly in the central nervous system (CNS). These receptors have gained increased attention as therapeutic target for several CNS related neurological diseases. In the current study, we aimed to identify novel H3 R ligands using in silico virtual screening methods. To this end, a combination of ligand- and structure-based approaches was utilized for screening of ZINC database on the homology model of human H3 R. Structural similarity- and pharmacophore-based approaches were employed to generate compound libraries. Various molecular modeling methodologies such as molecular docking and dynamics simulation along with different drug likeness filtering criteria were applied to select anti-H3 R ligands as promising candidate molecules based on different known parent lead compounds. In vitro binding assays of the selected molecules demonstrated three of them being active within the micromolar and submicromolar Ki range. The current integrated computational and experimental methods used in this work can provide new general insights for systematic hit identification for novel anti-H3 R agents from large compound libraries.

Full text Figures and data Side by side Abstract Editor's evaluation Introduction Results Discussion Materials and methods Appendix 1 Data availability References Decision letter Author response Article and author information Metrics Abstract Allosteric modulation of G protein-coupled receptors (GPCRs) is a major paradigm in drug discovery. Despite decades of research, a molecular-level understanding of the general principles that govern the myriad pharmacological effects exerted by GPCR allosteric modulators remains limited. The M4 muscarinic acetylcholine receptor (M4 mAChR) is a validated and clinically relevant allosteric drug target for several major psychiatric and cognitive disorders. In this study, we rigorously quantified the affinity, efficacy, and magnitude of modulation of two different positive allosteric modulators, LY2033298 (LY298) and VU0467154 (VU154), combined with the endogenous agonist acetylcholine (ACh) or the high-affinity agonist iperoxo (Ipx), at the human M4 mAChR. By determining the cryo-electron microscopy structures of the M4 mAChR, bound to a cognate Gi1 protein and in complex with ACh, Ipx, LY298-Ipx, and VU154-Ipx, and applying molecular dynamics simulations, we determine key molecular mechanisms underlying allosteric pharmacology. In addition to delineating the contribution of spatially distinct binding sites on observed pharmacology, our findings also revealed a vital role for orthosteric and allosteric ligand–receptor–transducer complex stability, mediated by conformational dynamics between these sites, in the ultimate determination of affinity, efficacy, cooperativity, probe dependence, and species variability. There results provide a holistic framework for further GPCR mechanistic studies and can aid in the discovery and design of future allosteric drugs. Editor's evaluation This important work advances our understanding of the structural basis of allosteric modulation of the M4 muscarinic receptor but has broad implications for GPCRs. The evidence supporting the conclusions is exceptional, with multiple cryo-EM structures that are complemented by excellent pharmacological and dynamics studies. https://doi.org/10.7554/eLife.83477.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Over the past 40 y, there have been major advances to the analytical methods that allow for the quantitative determination of the pharmacological parameters that characterize G protein-coupled receptor (GPCR) signaling and allosteric modulation (Figure 1A and B). These analytical methods are based on the operational model of agonism (Black and Leff, 1983) and have been extended or modified to account for allosteric modulation (Leach et al., 2007), biased agonism (Kenakin, 2012), and even biased allosteric modulation (Slosky et al., 2021). Collectively, these models and subsequent key parameters (Figure 1B) are used to guide allosteric drug screening, selectivity, efficacy, and ultimately, clinical utility, and provide the foundation for modern GPCR drug discovery (Wootten et al., 2013). Yet, a systematic understanding of how these pharmacological parameters relate to the molecular structure and dynamics of GPCRs remains elusive. Figure 1 with 2 supplements see all Download asset Open asset Pharmacological characterization of the positive allosteric modulators (PAMs), LY298 and VU154, with acetylcholine (ACh) and iperoxo (Ipx) at the human M4 muscarinic acetylcholine receptor (mAChR). (A) Schematic of the pharmacological parameters that define effects of orthosteric and allosteric ligands on a G protein-coupled receptor (GPCR). (B) A simplified schematic diagram of the Black–Leff operational model to quantify agonism, allosteric modulation, and agonist bias with pharmacological parameters defined (Black and Leff, 1983). (C) 2D chemical structures of the orthosteric and allosteric ligands used in this study. (D–G) Key pharmacological parameters for interactions between orthosteric and allosteric ligands in [3H]-N-methylscopolamine ([3H]-NMS) binding assays. (D) Equilibrium binding affinities (pKi and pKB) and (E) the degree of binding modulation (α) between the agonists and PAMs resulting in the modified binding affinities (F) α/KA and (G) α/KB. (H–K) Key pharmacological parameters relating to Gαi1 activation for interactions between orthosteric and allosteric ligands measured with the TruPath assay (Figure 1—figure supplement 1). (H) The signaling efficacy (τA and τB) and (I) transduction coupling coefficients (log (τ/K)) of each ligand. (J) The functional cooperativity (αβ) between ligands and (K) the efficacy modulation (β) between ligands. All data are mean ± SEM of three or more independent experiments performed in duplicate or triplicate with the pharmacological parameters determined using a global fit of the data. The error in (F, G, K) was propagated using the square root of the sum of the squares. See Table 1. Concentration–response curves are shown in Figure 1—figure supplement 1. Figure 1—source data 1 Related to Figure 1D–K. https://cdn.elifesciences.org/articles/83477/elife-83477-fig1-data1-v1.xlsx Download elife-83477-fig1-data1-v1.xlsx The muscarinic acetylcholine receptors (mAChRs) are an important family of five Class A GPCRs that have long served as model systems for understanding GPCR allostery (Conn et al., 2009). The mAChRs have been notoriously difficult to exploit therapeutically and selectively due to high-sequence conservation within their orthosteric binding domains (Burger et al., 2018). However, the discovery of highly selective positive allosteric modulators (PAMs) for some mAChR subtypes has paved the way for novel approaches to exploit these high-value drug targets (Chan et al., 2008; Gentry et al., 2014; Marlo et al., 2009). X-ray crystallography and cryo-electron microscopy (cryo-EM) have been used to determine inactive state structures for all five mAChR subtypes (Haga et al., 2012; Kruse et al., 2012; Thal et al., 2016; Vuckovic et al., 2019) and active state structures of the M1 and M2 mAChRs (Maeda et al., 2019). For the M2 mAChR, this includes structures co-bound with the high-affinity agonist iperoxo (Ipx) and the PAM LY2119620 in complex with a G protein mimetic nanobody (Kruse et al., 2013) and the transducers Go (Maeda et al., 2019) and β-arrestin1 (Staus et al., 2020). These M2 mAChR structures were foundational to validating the canonical mAChR allosteric site but are limited to only one agonist (iperoxo) and one PAM (LY2119620) and do not account for the vast pharmacological properties of ligands targeting mAChRs. A recent nuclear magnetic resonance (NMR) study of the M2 mAChR revealed differences in the conformational landscape of the M2 mAChR when bound to different agonists, but no clear link was established between the properties of the ligands and the conformational states of the receptor (Xu et al., 2019). The M4 mAChR subtype is of major therapeutic interest due to its expression in regions of the brain that are rich in dopamine and dopamine receptors, where it regulates dopaminergic neurons involved in cognition, psychosis, and addiction (Bymaster et al., 2003; Dencker et al., 2011; Foster et al., 2016; Tzavara et al., 2004). Importantly, these findings have been supported by studies utilizing novel PAMs that are highly selective for the M4 mAChR (Bubser et al., 2014; Chan et al., 2008; Leach et al., 2010; Suratman et al., 2011). Among these, LY2033298 (LY298) was the first reported highly selective PAM of the M4 mAChR and displayed antipsychotic efficacy in a preclinical animal model of schizophrenia (Chan et al., 2008). Despite LY298 being one of the best characterized M4 mAChR PAMs, its therapeutic potential has been limited by numerous factors, including its chemical scaffold, which has been difficult to optimize with respect to its molecular allosteric parameters (Figure 1C) and variability of response between species (Suratman et al., 2011; Wood et al., 2017b). In the search for better chemical scaffolds, the PAM, VU0467154 (VU154), was subsequently discovered. VU154 showed robust efficacy in preclinical rodent models; however, it also exhibited species selectivity that prevented its clinical translation (Bubser et al., 2014). Collectively, LY298 and VU154 are exemplar tool molecules that highlight the promises and the challenges in understanding and optimizing allosteric GPCR drug activity for translational and clinical applications. Herein, by examining the pharmacology of the PAMs LY298 and VU154 with the agonists ACh and Ipx across radioligand binding assays and two different signaling assays and analyzing these results with modern analytical methods, we determined the key parameters that describe signaling and allostery for these ligands. To investigate a structural basis for these pharmacological parameters, we used cryo-EM to determine high-resolution structures of the M4 mAChR in complex with a cognate Gi1 heterotrimer and ACh and Ipx. We also determined structures of receptor complexes with Ipx co-bound with the PAMs LY298 or VU154. Moreover, because protein allostery is a dynamic process (Changeux and Christopoulos, 2016), we performed all-atom simulations using the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling method (Draper-Joyce et al., 2021; Miao et al., 2015; Wang et al., 2021a) on the M4 mAChR using the cryo-EM structures. The structures and GaMD simulations, in combination with detailed molecular pharmacology and receptor mutagenesis experiments, provide fundamental insights into the molecular mechanisms underpinning the hallmarks of GPCR allostery. To further validate these findings, we investigated the differences in the selectivity of VU154 between the human and mouse receptors and established a structural basis for species selectivity. Collectively, these results will enable future GPCR drug discovery research and potentially lead to the development of next generation M4 mAChR PAMs. Results Pharmacological characterization of M4 mAChR PAMs with ACh and Ipx The pharmacology of LY298 or VU154 interacting with ACh has been well characterized in binding and functional assays at the M4 mAChR (Bubser et al., 2014; Chan et al., 2008; Gould et al., 2016; Leach et al., 2010; Suratman et al., 2011; Thal et al., 2016). However, their pharmacology with Ipx has not been reported. Therefore, we characterized both PAMs with ACh and Ipx in binding and in two different functional assays to provide a thorough foundational comparative characterization of the pharmacological parameters of these ligands from the same study. We first used radioligand binding assays (Figure 1—figure supplement 1A) to determine the binding affinities (i.e., equilibrium dissociation constants) of ACh and Ipx (KA) for the orthosteric site and of LY298 and VU154 (KB) for the allosteric site of the unoccupied human M4 mAChR (Figure 1D), along with the degree of binding cooperativity (α) between the agonists and PAMs when the two are co-bound (Figure 1E). Analysis of these experiments revealed that LY298 and VU154 have very similar binding affinities for the allosteric site with values (expressed as negative logarithms; pKB) of 5.65 ± 0.07 and 5.83 ± 0.12, respectively (Table 1), in accordance with previous studies (Bubser et al., 2014; Leach et al., 2011). Both PAMs potentiated the binding affinity of ACh and Ipx (Figure 1E), with the effect being greatest between LY298 and ACh (~400-fold increase in binding affinity). Comparatively, the positive cooperativity between VU154 and ACh was only 40-fold. When Ipx was used as the agonist, the binding affinity modulation mediated by both PAMs was more modest, characterized by an approximately 72-fold potentiation for the combination of Ipx and LY298, and 10-fold potentiation for the combination of Ipx and VU154. These results indicate probe-dependent effects (Valant et al., 2012) with respect to the ability of either PAM to modulate the affinity of each agonist (Figure 1F and G). A probe-dependent effect was also observed with the radioligand, [3H]-NMS, evidenced by a reduction in specific radioligand binding due to negative cooperativity between the antagonist probe and LY298, which has been previously reported (Chan et al., 2008; Leach et al., 2010; Suratman et al., 2011; Thal et al., 2016). It is important to note that binding affinity modulation is thermodynamically reciprocal at equilibrium, and the affinities of LY298 and VU154 were thus also increased in the agonist bound state (Figure 1—figure supplement 1A). This results in LY298 having a fivefold higher binding affinity than VU154 when agonists are bound (Table 1). Table 1 Pharmacological parameters from radioligand binding and functional experiments. [3H]-NMS saturation binding on stable M4 mAChR CHO cellsConstructsSites per cell*pKD†Human WT M4 mAChR598,111 ± 43,067 (7)9.76 ± 0.05 (7)Mouse WT M4 mAChR21,027 ± 2188 (3)9.76 ± 0.05 (3)Human D432E M4 mAChR126,377 ± 10,066 (3)9.60 ± 0.07 (3)Human T433R M4 mAChR157,442 ± 36,658 (6)9.64 ± 0.09 (6)Human V91L, D432E, T433R M4 mAChR205,771 ± 20,975 (4)9.58 ± 0.08 (4)[3H]-NMS interaction binding assays between ACh or Ipx and LY298 or VU154 on stable M4 mAChR constructs in Flp-In CHO cellsConstructsPAMpKi ACh ‡pKi Ipx ‡pKB PAM ‡log αACh §log αIpx §Human WT M4 mAChRLY2984.50 ± 0.06 (4)8.30 ± 0.06 (4)5.65 ± 0.07 (8) ¶2.59 ± 0.10 (4)1.86 ± 0.10 (4)VU1544.40 ± 0.09 (4)8.19 ± 0.06 (8)5.83 ± 0.11 (12) ¶1.61 ± 0.13 (4)1.03 ± 0.10 (8)Mouse WT M4 mAChRLY2984.52 ± 0.07 (4)8.55 ± 0.06 (4)5.74 ± 0.07 (8) ¶1.78 ± 0.10 (4)1.30 ± 0.11 (4)*VU1544.59 ± 0.06 (4)8.57 ± 0.06 (3)6.07 ± 0.09 (7) ¶2.43 ± 0.10 (4)1.75 ± 0.12 (3)*Human D432E M4 mAChRLY298N.T.8.28 ± 0.04 (5)5.86 ± 0.07 (5)N.T.1.59 ± 0.06 (5)VU154N.T.8.27 ± 0.06 (6)6.21 ± 0.12 (6)N.T.1.04 ± 0.09 (6)Human T433R M4 mAChRLY298N.T.8.05 ± 0.08 (5)5.04 ± 0.04 (5)*N.T.1.91 ± 0.11 (5)VU154N.T.7.88 ± 0.04 (5)5.50 ± 0.08 (5)N.T.1.67 ± 0.07 (5)*Human V91L, D432E, T433R M4 mAChRLY298N.T.7.95 ± 0.10 (4)5.29 ± 0.26 (4)N.T.1.80 ± 0.22 (4)VU154N.T.7.89 ± 0.12 (4)6.34 ± 0.16 (4)*N.T.1.35 ± 0.16 (4)Gαi1 activation (TruPath) interaction assays between ACh or Ipx and LY298 or VU154 on transiently expressed M4 mAChR constructs in HEK293A cellsConstructsPAMlog τ ACh**log τ Ipx**pKB PAM ‡log τ PAM**log αβACh††log αβIpx††Human WT M4 mAChRLY2982.71 ± 0.14 (4)1.49 ± 0.12 (4)= 5.651.02 ± 0.03 (8) ¶2.01 ± 0.14 (4)1.96 ± 0.16 (4)VU154= 5.83–0.55 ± 0.08 (8) ¶1.22 ± 0.13 (4)0.20 ± 0.13 (4)pERK1/2 interaction assays between ACh or Ipx and LY298 or VU154 on stable M4 mAChR constructs in Flp-In CHO cellsConstructsPAMlog τ ACh**log τ Ipx**pKB PAM ‡log τC PAM ‡ ‡log αβACh††log αβIpx††Human WT M4 mAChRLY2983.27 ± 0.06 (8) ¶1.74 ± 0.03 (16) ¶= 5.651.19 ± 0.05 (12)**2.29 ± 0.22 (4)1.08 ± 0.28 (8)VU154= 5.830.11 ± 0.05 (12)**0.88 ± 0.23 (4)0.66 ± 0.15 (8)Mouse WT M4 mAChRLY298N.T.N.D.= 5.741.32 ± 0.07 (5)N.T.1.24 ± 0.12 (4)VU154N.T.N.D.= 6.071.47 ± 0.08 (5) § §N.T.2.08 ± 0.15 (5) § §Human D432E M4 mAChRLY298N.T.N.D.= 5.861.34 ± 0.08 (5)N.T.1.37 ± 0.28 (5)VU154N.T.N.D.= 6.210.78 ± 0.08 (5) § §N.T.1.02 ± 0.15 (5)Human T433R M4 mAChRLY298N.T.N.D.= 5.041.73 ± 0.13 (5) § §N.T.1.85 ± 0.28 (5)VU154N.T.N.D.= 5.500.95 ± 0.12 (5) § §N.T.1.18 ± 0.14 (5)Human V91L, D432E, T433R M4 mAChRLY298N.T.N.D.= 5.291.62 ± 0.09 (5) § §N.T.1.64 ± 0.30 (5)VU154N.T.N.D.= 6.340.68 ± 0.06 (5) § §N.T.1.34 ± 0.11 (5) § § Values represent the mean ± SEM with the number of independent experiments shown in parenthesis. N.T.: not tested; N.D.: not determined; Ach, acetylcholine; Ipx: iperoxo; PAM: positive allosteric modulator. * Number of [3H]-NMS binding sites per cell. † Negative logarithm of the radioligand equilibrium dissociation constant. ‡ Negative logarithm of the orthosteric (pKi) or allosteric (pKB) equilibrium dissociation constant. § Logarithm of the binding cooperativity factor between the agonist (ACh or Ipx) and the PAM (LY298 or VU154). ¶ Parameter was determined in a shared global analysis between agonists. ** Logarithm of the operational efficacy parameter determined using the Operational Model of Agonism. †† Logarithm of the functional cooperativity factor between the agonist (ACh or Ipx) and the PAM (LY298 or VU154). ‡ ‡ logτC = logarithm of the operational efficacy parameter corrected for receptor expression (methods in Appendix 1). § § Values from pKB PAM, log αIpx, log τC PAM, and log αβIpx that are significantly different from human WT M4 mAChR (p<0.05) calculated by a one-way ANOVA with a Dunnett's post-hoc test. We subsequently used the BRET-based TruPath assay (Olsen et al., 2020) as a proximal measure of G protein activation with Gαi1 (Figure 1—figure supplement 1B). We also used a more amplified downstream signaling assay, extracellular signal-regulated kinases 1/2 phosphorylation (pERK1/2), that is also dependent on Gi activation (Figure 1—figure supplement 2A), to measure the cell-based activity of each PAM with each agonist. These signaling assays allowed us to determine the efficacy of the agonists (τA) and the PAMs (τB) (Figure 1H, Figure 1—figure supplement 2B). Importantly, efficacy (τ), as defined from the Black–Leff operational model of agonism (Black and Leff, 1983), is determined by the ability of an agonist to promote an active receptor conformation, the receptor density (Bmax), and the subsequent ability of a cellular system to generate a response (Figure 1B). Notably, in both signaling assays, the rank order of efficacy was ACh > Ipx > LY298 > VU154. We subsequently calculated the transducer coupling coefficient (τ/K) (Figure 1I, Figure 1—figure supplement 2C), a parameter often used as a starting point to quantify biased agonism (Kenakin et al., 2012) and that is specific to the intact cellular environment in which a given response occurs. Thus the dissociation constant (K) in the transduction coefficient subsumes the affinity for the ground state (non-bound) receptor, in addition to any isomerization states of the receptor that ultimately yield cellular responses (Kenakin and Christopoulos, 2013). Consequently, in both assays, the rank order of transducer coupling was Ipx >> ACh ~ LY298 > VU154 due to Ipx having a higher binding affinity for the receptor. Overall, these results indicate that although ACh is a more efficacious agonist than Ipx, it has lower transducer coupling coefficient. In contrast, LY298 has both better efficacy and transducer coupling coefficient than VU154 (Table 1). The signaling assays and use of an operational model of allosterism also allowed for the determination of the functional cooperativity (αβ) exerted by the PAMs (Figure 1J, Figure 1—figure supplement 2D), which is a composite parameter accounting for both binding (α) and efficacy (β) modulation. Notably, VU154 displayed lower positive functional cooperativity with ACh than LY298. Strikingly, VU154 had negligible functional modulation with Ipx, in contrast to the cooperativity observed with ACh in the TruPath assay. The tenfold difference in αβ values for VU154 between ACh and Ipx highlights the dependence of the orthosteric probe used in the assay (i.e. probe dependence); on this basis, VU154 would be classified as a 'neutral' allosteric ligand (not a PAM) with Ipx in the TruPath assay, that is, VU154 still binds to the allosteric site, but displays neutral cooperativity (αβ = 1) with Ipx (Table 1). The degree of efficacy modulation (β) that the PAMs have on the agonists can be calculated by subtracting the binding modulation (α) from the functional modulation (αβ) (Figure 1K, Figure 1—figure supplement 2E). A caveat of this analysis is that errors for β are higher due to the error being propagated between calculations. Ideally, the degree of efficacy modulation would be determined in an experimental system where the maximal efficacy of system is not reached by the agonists alone (Berizzi et al., 2016). Nevertheless, our analysis shows the PAMs LY298 and VU154 appear to have a slight negative to neutral effect on agonist efficacy in the Gi1 TruPath and pERK1/2 assays (Table 1), suggesting that the predominant allosteric effect exerted by these PAMs is mediated through modulation of binding affinity. Collectively, our extensive analysis on the pharmacology of LY298 and VU154 with ACh and Ipx offers detailed insight into the key differences between these ligands across a range of pharmacological properties: ligand binding, probe dependence, efficacy, agonist–receptor–transducer interactions, and allosteric modulation (Figure 1, Table 1). We hypothesized that structures of the human M4 mAChR in complex with different agonists and PAMs combined with molecular dynamic simulations could provide high-resolution molecular insights into the different pharmacological profiles of these ligands. Determination of M4R-Gi1 complex structures Similar to the approach used in prior determination of active-state structures of the M1 and M2 mAChRs (Maeda et al., 2019), we used a human M4 mAChR construct that lacked residues 242–387 of the third intracellular loop to improve receptor expression and purification, and made complexes of the receptor with Gi1 protein and either the endogenous agonist, ACh, or Ipx. Due to the higher affinity of Ipx compared to ACh (Schrage et al., 2013), we utilized Ipx to form additional M4R-Gi1 complexes with or without the co-addition of either LY298 or VU154. In all instances, complex formation was initiated by combining purified M4 mAChR on with Gi1 a that binds and and the addition of to (Maeda et al., 2018). For this study, we used a Gi1 heterotrimer of a negative form of human and human and et al., of each complex were using on a et al., 2021). The structures of and M4R-Gi1 complexes were determined to of and respectively (Figure Figure supplement 1, Table For the M4R-Gi1 an additional an of the receptor and binding site for (Figure supplements 2 and The cryo-EM density for all complexes were for of and for of the receptor, and and the bound ligands with of the of Ipx, which was with prior cryo-EM studies (Maeda et al., Figure Figure supplement Figure 2 with supplements see all Download asset Open asset microscopy (cryo-EM) structures of the (A) of complex with from the and the extracellular of the structures are shown in Figure supplement 1. (B) density the ligands in this study. of and were to a of and the of was to of the receptor models with bound ligands and from the (C) (D) extracellular and (E) intracellular Table 2 microscopy (cryo-EM) data and range factor muscarinic acetylcholine acetylcholine; Ipx: iperoxo; In all density the of 1 and the third intracellular loop of the receptor was observed and not the density of the of Gαi1 was and not These regions are highly dynamic and not in A protein complex structures. from these side were well in the density (Figure supplement and dynamics of agonist binding cryo-EM structures of M4R-Gi1 complexes bound to Ipx, Ipx, and the PAM, and a novel allosteric agonist, were determined et al., of the M4R-Gi1 complex structures revealed differences in the of key orthosteric and allosteric site residues than the and complex structures (Figure supplement the of density in the the orthosteric and allosteric sites of these M4R-Gi1 structures et al., was resulting in several key residues being in each site (Figure supplement Therefore, differences between the M4R-Gi1 structures and by Wang et al., are highly to not be due to differences as we compared the prior and complex structures (Maeda et al., 2019) in this study. Overall, our M4R-Gi1 complex structures are similar in to that of A including the and complexes (Figure supplement of the M4R-Gi1 complexes revealed structures with root mean square of for the complexes and for the receptors alone (Figure The differences the extracellular of the receptors (Figure along with slight in the of the of Gαi1 and and with respect to the receptor (Figure supplement The density of side the ACh and Ipx binding sites (Figure and was well the to structural of orthosteric agonist The orthosteric site of the M4 mAChR, in with the mAChR is within the in an that is of two one and and residues (Figure Notably, all of these residues are across all five mAChR the in highly orthosteric agonists (Burger et al., 2018). Both ACh and Ipx have a that interactions with and (Figure to the and for A GPCR and both ACh and Ipx have a that can form a to the of with the of Ipx also being in to with the of (Figure of any of these residues the affinity of ACh, validating their for agonist binding (Leach et al., 2011; Thal et al., 2016). The chemical difference between ACh and Ipx is the of Ipx that a interaction with the (Figure The is of the also as the a that a in between the inactive and active states of A GPCRs et al., Figure with 1 supplement see all Download asset Open asset of acetylcholine (ACh) and iperoxo (Ipx) with the receptor. microscopy (cryo-EM) density of the (A) and (B) structures. at the orthosteric binding site the active state and structures with the inactive state structure of residues between the inactive and active (D) interactions of ACh and Ipx. are shown as from Gaussian accelerated molecular dynamics (GaMD) simulations of the and bound M4R-Gi1 cryo-EM each performed with three simulations are with different The of each to the specific model used in the mean square of (E) ACh and (F) Ipx from simulations of the cryo-EM structures. through the and structures the of the binding in To investigate the structural dynamics of the M4 mAChR, we performed three independent GaMD simulations on the and M4R-Gi1 cryo-EM structures (Table GaMD simulations revealed that ACh higher in the orthosteric site than Ipx (Figure and

Author response: Pharmacological hallmarks of allostery at the M4 muscarinic receptor elucidated through structure and dynamics

It is widely assumed that G protein-coupled receptor kinase 2 (GRK2)-mediated specific inhibition of G protein-coupled receptors (GPCRs) response involves GRK-mediated receptor phosphorylation followed by β-arrestin binding and subsequent uncoupling from the heterotrimeric G protein. It has recently become evident that GRK2-mediated GPCRs regulation also involves phosphorylation-independent mechanisms. In the present study we investigated whether the histamine H2 receptor (H2R), a Gα(s)-coupled GPCR known to be desensitized by GRK2, needs to be phosphorylated for its desensitization and/or internalization and resensitization. For this purpose we evaluated the effect of the phosphorylating-deficient GRK2K220R mutant on H2R signaling in U937, COS7, and HEK293T cells. We found that although this mutant functioned as dominant negative concerning receptor internalization and resensitization, it desensitized H2R signaling in the same degree as the GRK2 wild type. To identify the domains responsible for the kinase-independent receptor desensitization, we co-transfected the receptor with constructions encoding the GRK2 RGS-homology domain (RH) and the RH or the kinase domain fused to the pleckstrin-homology domain. Results demonstrated that the RH domain of GRK2 was sufficient to desensitize the H2R. Moreover, disruption of RGS functions by the use of GRK2D110A/K220R double mutant, although coimmunoprecipitating with the H2R, reversed GRK2K220R-mediated H2R desensitization. Overall, these results indicate that GRK2 induces desensitization of H2R through a phosphorylation-independent and RGS-dependent mechanism and extends the GRK2 RH domain-mediated regulation of GPCRs beyond Gα(q)-coupled receptors. On the other hand, GRK2 kinase activity proved to be necessary for receptor internalization and the resulting resensitization.

The histamine H4 receptor (H4R) activatesGαi-mediated signaling and recruits β-arrestin2upon stimulation with histamine. β-Arrestins play a regulatoryrole in G protein-coupled receptor (GPCR) signaling by interactingwith phosphorylated serine and threonine residues in the GPCR C-terminaltail and intracellular loop 3, resulting in receptor desensitizationand internalization. Using bioluminescence resonance energy transfer(BRET)-based biosensors, we show that G protein-coupled receptor kinases(GRK) 2 and 3 are more quickly recruited to the H4R thanβ-arrestin1 and 2 upon agonist stimulation, whereas receptorinternalization dynamics toward early endosomes was slower. Alanine-substitutionrevealed that a serine cluster at the distal end of the H4R C-terminal tail is essential for the recruitment of β-arrestin1/2,and consequently, receptor internalization and desensitization ofG protein-driven extracellular-signal-regulated kinase (ERK)1/2 phosphorylationand label-free cellular impedance. In contrast, alanine substitutionof serines and threonines in the intracellular loop 3 of the H4R did not affect β-arrestin2 recruitment and receptordesensitization, but reduced β-arrestin1 recruitment and internalization.Hence, β-arrestin recruitment to H4R requires theputative phosphorylated serine cluster in the H4R C-terminaltail, whereas putative phosphosites in the intracellular loop 3 havedifferent effects on β-arrestin1 versus β-arrestin2. Mutationof these putative phosphosites in either intracellular loop 3 or theC-terminal tail did not affect the histamine-induced recruitment ofGRK2 and GRK3 but does change the interaction of H4R withGRK5 and GRK6, respectively. Identification of H4R interactionswith these proteins is a first step in the understanding how thisreceptor might be dysregulated in pathophysiological conditions.

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.

Histamine acting on H1 receptor promotes inhibition of proliferation via PLC, RAC, and JNK-dependent pathways