Toward Understanding the Impact of Dimerization Interfaces in Angiotensin II Type 1 Receptor

Orphan GPCR GPRC5C Facilitates Angiotensin II-Induced Smooth Muscle Contraction

BACKGROUND

GPCRs (G-protein-coupled receptors) play a central role in the regulation of smooth muscle cell (SMC) contractility, but the function of SMC-expressed orphan GPCR class C group 5 member C (GPRC5C) is unclear. The aim of this project is to define the role of GPRC5C in SMC in vitro and in vivo.

METHODS

We studied the role of GPRC5C in the regulation of SMC contractility and differentiation in human and murine SMC in vitro, as well as in tamoxifen-inducible, SMC-specific GPRC5C knockout mice under basal conditions and in vascular disease in vivo.

RESULTS

Mesenteric arteries from tamoxifen-inducible, SMC-specific GPRC5C knockout mice showed ex vivo significantly reduced angiotensin II (Ang II)-dependent calcium mobilization and contraction, whereas responses to other relaxant or contractile factors were normal. In vitro, the knockdown of GPRC5C in human aortic SMC resulted in diminished Ang II-dependent inositol phosphate production and lower myosin light chain phosphorylation. In line with this, tamoxifen-inducible, SMC-specific GPRC5C knockout mice showed reduced Ang II-induced arterial hypertension, and acute inactivation of GPRC5C was able to ameliorate established arterial hypertension. Mechanistically, we show that GPRC5C and the Ang II receptor AT1 dimerize, and knockdown of GPRC5C resulted in reduced binding of Ang II to AT1 receptors in HEK293 cells, human and murine SMC, and arteries from tamoxifen-inducible, SMC-specific GPRC5C knockout mice.

CONCLUSIONS

Our data show that GPRC5C regulates Ang II-dependent vascular contraction by facilitating AT1 receptor-ligand binding and signaling.

The World of GPCR dimers - Mapping dopamine receptor D2 homodimers in different activation states and configuration arrangements

G protein-coupled receptors (GPCRs) are known to dimerize, but the molecular and structural basis of GPCR dimers is not well understood. In this study, we developed a computational framework to generate models of symmetric and asymmetric GPCR dimers using different monomer activation states and identified their most likely interfaces with molecular details. We chose the dopamine receptor D2 (D2R) homodimer as a case study because of its biological relevance and the availability of structural information. Our results showed that transmembrane domains 4 and 5 (TM4 and TM5) are mostly found at the dimer interface of the D2R dimer and that these interfaces have a subset of key residues that are mostly nonpolar from TM4 and TM5, which was in line with experimental studies. In addition, TM2 and TM3 appear to be relevant for D2R dimers. In some cases, the inactive configuration is unaffected by the partnered protomer, whereas in others, the active protomer adopts the properties of an inactive receptor. Additionally, the β-arrestin configuration displayed the properties of an active receptor in the absence of an agonist, suggesting that a switch to another meta-state during dimerization occurred. Our findings are consistent with the experimental data, and this method can be adapted to study heterodimers and potentially extended to include additional proteins such as G proteins or β-arrestins. In summary, this approach provides insight into the impact of the conformational status of partnered protomers on the overall quaternary GPCR macromolecular structure and dynamics.

Advances in the allostery of angiotensin II type 1 receptor

Angiotensin II type 1 receptor (AT1R) is a promising therapeutic target for cardiovascular diseases. Compared with orthosteric ligands, allosteric modulators attract considerable attention for drug development due to their unique advantages of high selectivity and safety. However, no allosteric modulators of AT1R have been applied in clinical trials up to now. Except for the classical allosteric modulators of AT1R such as antibody, peptides and amino acids, cholesterol and biased allosteric modulators, there are non-classical allosteric modes including the ligand-independent allosteric mode, and allosteric mode of biased agonists and dimers. In addition, finding the allosteric pockets based on AT1R conformational change and interaction interface of dimers are the future of drug design. In this review, we summarize the different allosteric mode of AT1R, with a view to contribute to the development and utilization of drugs targeting AT1R allostery.

Allosteric Regulation of G-Protein-Coupled Receptors: From Diversity of Molecular Mechanisms to Multiple Allosteric Sites and Their Ligands

Allosteric regulation is critical for the functioning of G protein-coupled receptors (GPCRs) and their signaling pathways. Endogenous allosteric regulators of GPCRs are simple ions, various biomolecules, and protein components of GPCR signaling (G proteins and β-arrestins). The stability and functional activity of GPCR complexes is also due to multicenter allosteric interactions between protomers. The complexity of allosteric effects caused by numerous regulators differing in structure, availability, and mechanisms of action predetermines the multiplicity and different topology of allosteric sites in GPCRs. These sites can be localized in extracellular loops; inside the transmembrane tunnel and in its upper and lower vestibules; in cytoplasmic loops; and on the outer, membrane-contacting surface of the transmembrane domain. They are involved in the regulation of basal and orthosteric agonist-stimulated receptor activity, biased agonism, GPCR-complex formation, and endocytosis. They are targets for a large number of synthetic allosteric regulators and modulators, including those constructed using molecular docking. The review is devoted to the principles and mechanisms of GPCRs allosteric regulation, the multiplicity of allosteric sites and their topology, and the endogenous and synthetic allosteric regulators, including autoantibodies and pepducins. The allosteric regulation of chemokine receptors, proteinase-activated receptors, thyroid-stimulating and luteinizing hormone receptors, and beta-adrenergic receptors are described in more detail.

The transmembrane domains of GPCR dimers as targets for drug development

G-protein-coupled receptors (GPCRs) can form homodimers or heterodimers that modulate specific signal transduction pathways to regulate a wide range of physiological and pathological functions. As such, GPCR dimers are novel drug targets for disorders including depression, hypertension, diabetes, and vascular dementia. The interaction between two receptors in a GPCR dimer involves a conformational change in the transmembrane domain (TMD). It has been demonstrated that the TMD has an important role in GPCR dimer formation and stability in vitro and in vivo. Moreover, increasing evidence shows that the TMD of GPCRs affects the function of dimers. Therefore, the TMD of GPCRs is an emerging target for the development of drugs to treat diseases that involve GPCR dimerization.

Biased Activation Mechanism Induced by GPCR Heterodimerization: Observations from μOR/δOR Dimers

GPCRs regulate multiple intracellular signaling cascades. Biasedly activating one signaling pathway over the others provides additional clinical utility to optimize GPCR-based therapies. GPCR heterodimers possess different functions from their monomeric states, including their selectivity to different transducers. However, the biased signaling mechanism induced by the heterodimerization remains unclear. Motivated by the issue, we select an important GPCR heterodimer (μOR/δOR heterodimer) as a case and use microsecond Gaussian accelerated molecular dynamics simulation coupled with potential of mean force and protein structure network (PSN) to probe mechanisms regarding the heterodimerization-induced constitutive β-arrestin activity and efficacy change of the agonist DAMGO. The results show that only the lowest energy state of the μOR/δOR heterodimer, which adopts a slightly outward shift of TM6 and an ICL2 conformation close to the receptor core, can selectively accommodate β-arrestins. PSN further reveals important roles of H8, ICL1, and ICL2 in regulating the constitutive β-arrestin-biased activity for the apo μOR/δOR heterodimer. In addition, the heterodimerization can allosterically alter the binding mode of DAMGO mainly by means of W7.35. Consequently, DAMGO transmits the structural signal mainly through TM6 and TM7 in the dimer, rather than TM3 similar to the μOR monomer, thus changing the efficacy of DAMGO from a balanced agonist to the β-arrestin-biased one. On the other side, the binding of DAMGO to the heterodimer can stabilize μOR/δOR heterodimers through a stronger interaction of TM1/TM1 and H8/H8, accordingly enhancing the interaction of μOR with δOR and the binding affinity of the dimer to the β-arrestin. The agonist DAMGO does not change main compositions of the regulation network from the dimer interface to the transducer binding pocket of the μOR protomer, but induces an increase in the structural communication of the network, which should contribute to the enhanced β-arrestin coupling. Our observations, for the first time, reveal the molecular mechanism of the biased signaling induced by the heterodimerization for GPCRs, which should be beneficial to more comprehensively understand the GPCR bias signaling.

Angiotensin and Endothelin Receptor Structures With Implications for Signaling Regulation and Pharmacological Targeting

In conjunction with the endothelin (ET) type A (ETAR) and type B (ETBR) receptors, angiotensin (AT) type 1 (AT1R) and type 2 (AT2R) receptors, are peptide-binding class A G-protein-coupled receptors (GPCRs) acting in a physiologically overlapping context. Angiotensin receptors (ATRs) are involved in regulating cell proliferation, as well as cardiovascular, renal, neurological, and endothelial functions. They are important therapeutic targets for several diseases or pathological conditions, such as hypertrophy, vascular inflammation, atherosclerosis, angiogenesis, and cancer. Endothelin receptors (ETRs) are expressed primarily in blood vessels, but also in the central nervous system or epithelial cells. They regulate blood pressure and cardiovascular homeostasis. Pathogenic conditions associated with ETR dysfunctions include cancer and pulmonary hypertension. While both receptor groups are activated by their respective peptide agonists, pathogenic autoantibodies (auto-Abs) can also activate the AT1R and ETAR accompanied by respective clinical conditions. To date, the exact mechanisms and differences in binding and receptor-activation mediated by auto-Abs as opposed to endogenous ligands are not well understood. Further, several questions regarding signaling regulation in these receptors remain open. In the last decade, several receptor structures in the apo- and ligand-bound states were determined with protein X-ray crystallography using conventional synchrotrons or X-ray Free-Electron Lasers (XFEL). These inactive and active complexes provide detailed information on ligand binding, signal induction or inhibition, as well as signal transduction, which is fundamental for understanding properties of different activity states. They are also supportive in the development of pharmacological strategies against dysfunctions at the receptors or in the associated signaling axis. Here, we summarize current structural information for the AT1R, AT2R, and ETBR to provide an improved molecular understanding.

RNA Sequencing of Cardiac in a Rat Model Uncovers Potential Target LncRNA of Diabetic Cardiomyopathy

Background: Diabetic cardiomyopathy (DCM) is one of the major causes of heart failure in diabetic patients; however, its pathogenesis remains unclear. Long non-coding RNAs (lncRNAs) are involved in the development of various cardiovascular diseases, but little is known in DCM.

Objective: The present study was conducted to investigate the altered expression signature of lncRNAs and mRNAs by RNA-sequencing and uncovers the potential targets of DCM.

Methods: A DCM rat model was established, and the genome-wide expression profile of cardiac lncRNAs and mRNAs was investigated in the rat model with and without DCM by RNA-sequencing. Bioinformatics analysis included the co-expression, competitive endogenous RNA (ceRNA) network, and functional enrichment analysis of deregulated lncRNAs and mRNAs.

Results: A total of 355 lncRNA transcripts and 828 mRNA transcripts were aberrantly expressed. The ceRNA network showed that lncRNA XR_351927.3, ENSRNOT00000089581, XR_597359.2, XR_591602.2, and XR_001842089.1 are associated with the greatest number of differentially expressed mRNAs and AURKB, MELK, and CDK1 may be the potential regulatory targets of these lncRNAs. Functional analysis showed that these five lncRNAs are closely associated with fibration, cell proliferation, and energy metabolism of cardiac myocytes, indicating that these core lncRNAs have high significance in DCM.

Conclusions: The present study profiled the DCM-specific lncRNAs and mRNAs, constructed the lncRNA-related ceRNA regulatory network, and identified the potential prognostic biomarkers, which provided new insights into the pathogenesis of DCM.

In silico characterization of adipokinetic hormone receptor and screening for pesticide candidates against stick insect, Carausius morosus

Adipokinetic hormone (AKH) is an insect neuropeptide that plays crucial roles in a variety of physiological functions such as regulation of heartbeat frequency, blood hemolymph trehalose levels, and protein synthesis. It exerts its functions through binding to its cognate G protein-coupled receptor (GPCR), named adipokinetic hormone receptor (AKHR). The aim of this study is to characterize AKHR of stick insect, Carausius morosus, which becomes an agricultural and forest pest during its outbreaks, and to screen pesticide candidates that would act through inhibition of AKHR. To this aim, the sequence of the receptor and its ligand were obtained from previously published transcriptome data and homology modeling, molecular docking, and molecular dynamics (MD) simulations were combined to find the ligand-binding pocket of AKHR. As a result, crucial residues in ligand binding were identified. These residues were located at the 6th and 7th transmembrane (TM) domains and the 2nd extracellular loop (ECL) of AKHR model. In order to propose pesticide candidates, virtual screening was performed, and candidate ligands were obtained. Considering the binding energies and the stability of the interaction between the ligand and the receptor, four hit compounds were selected. In conclusion, this study revealed a possible ligand-binding pocket of AKHR and proposed some high-affinity small-molecules to block its function, which would further facilitate pesticide design studies against the same receptor of various pests.

Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2

Antiapoptotic members of B-cell leukemia/lymphoma-2 (BCL-2) family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets. As such, targeting of BCL-2 family proteins raises hopes for new therapeutic discoveries. Thus, we used multistep screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from a small molecule database (Specs SC), which includes more than 210,000 compounds. This database is first filtered based on binary “cancer-QSAR” model constructed with 886 training and 167 test set compounds and common 26 toxicity quantitative structure-activity relationships (QSAR) models. Predicted non-toxic compounds are considered for target-driven studies. Here, we applied two different approaches to filter and select hit compounds for further in vitro biological assays and human cell line experiments. In the first approach, a molecular docking and filtering approach is used to rank compounds based on their docking scores and only a few top-ranked molecules are selected for further long (100-ns) molecular dynamics (MD) simulations and in vitro tests. While docking algorithms are promising in predicting binding poses, they can be less prone to precisely predict ranking of compounds leading to decrease in the success rate of in silico studies. Hence, in the second approach, top-docking poses of each compound filtered through QSAR studies are subjected to initially short (1 ns) MD simulations and their binding energies are calculated via molecular mechanics generalized Born surface area (MM/GBSA) method. Then, the compounds are ranked based on their average MM/GBSA energy values to select hit molecules for further long MD simulations and in vitro studies. Additionally, we have applied text-mining approaches to identify molecules that contain “indol” phrase as many of the approved drugs contain indole and indol derivatives. Around 2700 compounds are filtered based on “cancer-QSAR” model and are then docked into BCL-2. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based on their MM/GBSA values to select hit molecules for further long MD simulations and in vitro studies. In total, seven molecules are subjected to biological activity tests in various human cancer cell lines as well as Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials are assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.