Glucagon Receptor

Adomeglivant cannot block the cAMP-increasing effect of pancreatic islets [2]. Adomeglivant exhibits high resistance to group B GPCRs and resonates with the oscillatory binding motif potential in GluR, GLP-1R and GIP-R [2].

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Glucagon and LY2409021 both target glucagon and GLP-1 receptors. LY2409021 blocks GLP-1 and Ex-4 agonist action at the GLP-1R. LY2409021 is a GIP-R antagonist but fails to block adenosine action at A2B receptors. LY2409021 blocks GGP817 agonist action at the GluR and GLP-1R. The GluR allosteric inhibitors LY2409021 and MK 0893 antagonized glucagon and GLP-1 action at the GLP-1R, whereas des-His1-[Glu9]glucagon antagonized glucagon action at the GluR, while having minimal inhibitory action versus glucagon or GLP-1 at the GLP-1R [2].

Adomeglivant (LY2409021) (5 mg/kg; ip) completely eliminates the hypertensive effects of CNO (clozapine-N-oxide) in Avpires-Cre+ electrodes. (CNO is a cardiovascular drug stimulant that can induce hM3Dq-induced membrane myocardial infarction and increase the firing rate of hM3Dq-expressing arginine vasopressin (AVP) neurons) [3] Animal model: Avpires-Cre+ small Rat [3] Dosage: 5 mg/kg Administration method: intraperitoneal injection, 30 minutes before CNO. Results: The hyperglycemic effect of CNO was completely eliminated.

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To establish the contribution of glucagon to this hyperglycaemic response, we pre-treated mice with the glucagon receptor antagonist Adomeglivant (LY2409021) . This completely abolished the hyperglycaemic action of CNO (Fig. 4b). Similarly, to understand the contribution of vasopressin 1b receptor (V1bR) signalling, we pre-treated mice with the V1bR antagonist SSR149415. This also abolished the hyperglycaemic effect of CNO (Fig. 4b). Measurements of plasma glucagon during CNO treatment revealed it was elevated by ~40% [3].

FRET reporter assay in a 96-well format [2]
HEK293 cells stably expressing recombinant GPCRs were plated at 80% confluence on 96-well clear-bottom assay plates coated with rat tail collagen. Cells were then transduced for 16 h with H188 virus at a density of ∼60,000 cells/well under conditions in which the multiplicity of infection was equivalent to 25 viral particles per cell. The culture media were removed and replaced by 200 μl/well of a standard extracellular saline (SES) solution supplemented with 11 mm glucose and 0.1% BSA. The composition of the SES was (in mm): 138 NaCl, 5.6 KCl, 2.6 CaCl2, 1.2 MgCl2, 11.1 glucose, and 10 Hepes (295 mosmol, pH 7.4). Real-time kinetic assays of FRET were performed using a FlexStation 3 microplate reader equipped with excitation and emission light monochromators. Excitation light was delivered at 435/9 nm (455 nm cutoff), and emitted light was detected at 485/15 nm (cyan fluorescent protein) or 535/15 nm (yellow fluorescent protein). The emission intensities were the averages of 12 excitation flashes for each time point per well. Test solutions dissolved in SES were placed in V-bottom 96-well plates, and an automated pipetting procedure was used to transfer 50 μl of each test solution to each well of the assay plate containing monolayers of these cells. The 485/535 emission ratio was calculated for each well, and the mean ± S.D. values for 12 wells were averaged. These FRET ratio values were normalized using baseline subtraction so that a y axis value of 0 corresponds to the initial baseline FRET ratio, whereas a value of 100 corresponds to a 100% increase (i.e. doubling) of the FRET ratio. The time course of the ΔFRET ratio was plotted after exporting data to Origin 8.0. Origin 8.0 was also used for nonlinear regression analysis to quantify dose-response relationships.

HEK293 cells stably expressing the human GLP-1R at a density of 150,000 receptors/cell were used. HEK293 cells stably expressing the rat GlucR at a density of 250,000 receptors/cell were obtained from T. P. Sakmar, A. M. Cypess, and C. G. Unson. HEK293 cells stably expressing the rat GIP-R at a receptor density that has yet to be determined were obtained from T. J. Kieffer. HEK293 cells stably expressing H188 were generated by O. G. Chepurny in the Holz laboratory. All cell cultures were maintained in Dulbecco's modified Eagle's medium containing 25 mm glucose and supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin. Cell cultures equilibrated at 37 °C in a humidified incubator that was gassed with 5% CO2 were passaged once a week [2].

AAV-DIO-hM3Dq-mCherry was injected bilaterally into the supraoptic nucleus (SON) of Avpires-Cre+ mice. Mice were fasted for 4 hours (beginning at 10:00 am), and then CNO (or saline vehicle) was injected (3 mg/kg i.p.). In the same cohort, during a different trial, the glucagon receptor antagonist Adomeglivant (LY2409021)Adomeglivant (LY2409021) AAV-DIO-hM3Dq was injected into ThCre+ mice, targeting A1/C1 neurons. CNO (1 mg/kg) was then injected (i.p.). Antagonists (or vehicle) for the V1bR (SSR149415, 30 mg/kg) or glucagon receptor (GCGR; Adomeglivant (LY2409021)

Prediction of pharmacokinetics of CAA and PIB in human body and comparison of the results with the already known antagonists [1]
Certain structural and molecular features of compounds govern their pharmacokinetic properties in our body. Qikprop module of Schrodinger was used to evaluated the drug likeliness of all the four inhibitors. The obtained values for molecular weight, number of hydrogen bond donors, number of hydrogen bond acceptors and logP were used to assess violation of Lipinski's rule of five if any. To further account for the potential of the compounds to act as efficient drug candidates, their absorption, distribution, metabolism and excretion (ADME) properties were also calculated in silico using Qikprop.

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Physico-chemical properties and pharmacokinetics of GCGR inhibitors- CAA, PIB, MK-0893, LY2409021 [1]
To supplement the information gained from binding affinity prediction, Qikprop was used to calculate various other physically significant descriptors and pharmaceutically relevant properties of these small molecules. Qikprop predicts these molecular properties and provides significant ranges for comparing their values with those of 95% of already known pharmaceutical drugs. The descriptor, "#star" denotes the number of outlying properties of the molecule i.e., the properties which do not fall within the range of values for already known drugs. So, lesser the number better is the druglikeness of the small molecule. MK-0893, which showed the highest binding affinity, had a #star value of 4 whereas all the other three compounds had 0 #star. Hence, except for MK-0893, the computed properties for the other three compounds did not lie outside the required range and were very similar to that of the known drugs. Lipinski's rule of five is a thumb rule which determines the likeliness of a drug to be orally active based on four molecular properties. Table 1 lists the values of all four properties for these four compounds. MK-0893 with a molecular weight of 588.48 and logP value of 8.18 was not satisfying the lipinski's rule (molecular weight < 500, no. of hydrogen bond donors < 5, no. of hydrogen bond acceptors < 10, logP < 5). Solvent accessible surface area (SASA) and especially polar surface area (PSA) dictate the passive transport of molecules through membranes thereby giving an estimate about the transport properties of the drugs. The total SASA for MK-0893, CAA, PIB and LY2409021 was well within the range given by QikProp. Using some knowledge based set of rules Qikprop also calculates the percentage probability of the drug getting orally absorbed in the human body. This value has been shown to correlate well with the human oral absorption. PIB showed the highest oral absorption with a percentage value of 100%. Out of rest three, LY2409021 had the least value of 28.78 %. Central nervous system activity is another parameter that needs to be considered for assessing the safety issue. CAA was found to be highly CNS inactive whereas PIB was predicted to possess some minimal amount of CNS activity. Blood brain barrier (BBB) separates the human brain from the direct contact of circulatory system, thus protecting the brain for unwanted solute particles. Both the predicted compounds were shown to be BBB negative ensuring their administration safe for the brain. Even though MK-0893 had higher affinity for GCGR, CAA and PIB were found to be better than this known inhibitor in many aspects. The new compounds showed better druglikeness with acceptable values of ADME properties. This clearly delineates the distinctive potential of CAA and PIB as prospective lead inhibitors of GCGR for the treatment of type II diabetes mellitus.

[1]. Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus. BMC Bioinformatics. 2014; 15(Suppl 16): S13.

[2]. Non-conventional glucagon and GLP-1 receptor agonist and antagonist interplay at the GLP-1 receptor revealed in high-throughput FRET assays for cAMP. J Biol Chem. 2019 Mar 8;294(10):3514-3531.

[3]. AVP-induced counter-regulatory glucagon is diminished in type 1 diabetes. bioRxiv. January 31, 2020.

Adomeglivant has been investigated for the basic science of Type 2 Diabetes. ADOMEGLIVANT is a small molecule drug with a maximum clinical trial phase of II (across all indications) and has 3 investigational indications.

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Background: Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus. Results: In the present study, a large library of natural compounds was screened against 7 transmembrane domain of GCGR to identify novel therapeutic molecules that can inhibit the binding of glucagon with GCGR. Molecular dynamics simulations were performed to study the dynamic behaviour of the docked complexes and the molecular interactions between the screened compounds and the ligand binding residues of GCGR were analysed in detail. The top scoring compounds were also compared with already documented GCGR inhibitors- MK-0893 and LY2409021 for their binding affinity and other ADME properties. Finally, we have reported two natural drug like compounds PIB and CAA which showed good binding affinity for GCGR and are potent inhibitor of its functional activity. Conclusion: This study contributes evidence for application of these compounds as prospective small ligand molecules against type II diabetes. Novel natural drug like inhibitors against the 7 transmembrane domain of GCGR have been identified which showed high binding affinity and potent inhibition of GCGR. [1]

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G protein-coupled receptors (GPCRs) for glucagon (GluR) and glucagon-like peptide-1 (GLP-1R) are normally considered to be highly selective for glucagon and GLP-1, respectively. However, glucagon secreted from pancreatic α-cells may accumulate at high concentrations to exert promiscuous effects at the β-cell GLP-1R, as may occur in the volume-restricted microenvironment of the islets of Langerhans. Furthermore, systemic administration of GluR or GLP-1R agonists and antagonists at high doses may lead to off-target effects at other receptors. Here, we used molecular modeling to evaluate data derived from FRET assays that detect cAMP as a read-out for GluR and GLP-1R activation. This analysis established that glucagon is a nonconventional GLP-1R agonist, an effect inhibited by the GLP-1R orthosteric antagonist exendin(9-39) (Ex(9-39)). The GluR allosteric inhibitors LY2409021 and MK 0893 antagonized glucagon and GLP-1 action at the GLP-1R, whereas des-His1-[Glu9]glucagon antagonized glucagon action at the GluR, while having minimal inhibitory action versus glucagon or GLP-1 at the GLP-1R. When testing Ex(9-39) in combination with des-His1-[Glu9]glucagon in INS-1 832/13 cells, we validated a dual agonist action of glucagon at the GluR and GLP-1R. Hybrid peptide GGP817 containing glucagon fused to a fragment of peptide YY (PYY) acted as a triagonist at the GluR, GLP-1R, and neuropeptide Y2 receptor (NPY2R). Collectively, these findings provide a new triagonist strategy with which to target the GluR, GLP-1R, and NPY2R. They also provide an impetus to reevaluate prior studies in which GluR and GLP-1R agonists and antagonists were assumed not to exert promiscuous actions at other GPCRs. [2]

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Hypoglycaemia is a major barrier to the treatment of diabetes. Accordingly, it is important that we understand the mechanisms regulating the circulating levels of glucagon – the body’s principle blood glucose-elevating hormone which is secreted from alpha-cells of the pancreatic islets. In isolated islets, varying glucose over the range of concentrations that occur physiologically between the fed and fuel-deprived states (from 8 to 4 mM) has no significant effect on glucagon secretion and yet associates with dramatic changes in plasma glucagon in vivo. The identity of the systemic factor that stimulates glucagon secretion in vivo remains unknown. Here, we show that arginine-vasopressin (AVP), secreted from the posterior pituitary, stimulates glucagon secretion. Glucagon-secreting alpha-cells express high levels of the vasopressin 1b receptor (V1bR). Activation of AVP neurons in vivo increased circulating AVP, stimulated glucagon release and evoked hyperglycaemia; effects blocked by pharmacological antagonism of either the glucagon receptor or vasopressin 1b receptor. AVP also mediates the stimulatory effects of dehydration and hypoglycaemia produced by exogenous insulin and 2-deoxy-D-glucose on glucagon secretion. We show that the A1/C1 neurons of the medulla oblongata, which are known to be activated by hypoglycaemia, drive AVP neuron activation in response to insulin-induced hypoglycaemia. Hypoglycaemia also increases circulating levels of copeptin (derived from the same pre-pro hormone as AVP) in humans and this hormone stimulates glucagon secretion from isolated human islets. In patients with type 1 diabetes, hypoglycaemia failed to increase both plasma copeptin and glucagon. These findings provide a new mechanism for the central regulation of glucagon secretion in both health and disease.[3]

C32H36F3NO4

555.6278

555.259

C, 69.17; H, 6.53; F, 10.26; N, 2.52; O, 11.52

1488363-78-5

872260-47-4 (racemic); 488363-78-5 (S-isomer); 872260-19-0 (R-isomer)

91933867

White to off-white solid powder

1.2±0.1 g/cm3

656.7±55.0 °C at 760 mmHg

350.9±31.5 °C

0.0±2.1 mmHg at 25°C

1.542

7.53

2

7

11

40

798

1

FC(C([H])([H])C([H])([H])[C@@]([H])(C1C([H])=C([H])C(C(N([H])C([H])([H])C([H])([H])C(=O)O[H])=O)=C([H])C=1[H])OC1C([H])=C(C([H])([H])[H])C(=C(C([H])([H])[H])C=1[H])C1C([H])=C([H])C(=C([H])C=1[H])C(C([H])([H])[H])(C([H])([H])[H])C([H])([H])[H])(F)F

FASLTMSUPQDLIB-MHZLTWQESA-N

InChI=1S/C32H36F3NO4/c1-20-18-26(19-21(2)29(20)23-10-12-25(13-11-23)31(3,4)5)40-27(14-16-32(33,34)35)22-6-8-24(9-7-22)30(39)36-17-15-28(37)38/h6-13,18-19,27H,14-17H2,1-5H3,(H,36,39)(H,37,38)/t27-/m0/s1

3-[[4-[(1S)-1-[4-(4-tert-butylphenyl)-3,5-dimethylphenoxy]-4,4,4-trifluorobutyl]benzoyl]amino]propanoic acid

LY-2409021; LY2409021; LY 2409021

2934.99.9001

Powder      -20°C    3 years

                     4°C     2 years

In solvent   -80°C    6 months

                  -20°C    1 month

Room temperature (This product is stable at ambient temperature for a few days during ordinary shipping and time spent in Customs)

DMSO: ~100 mg/mL (~180 mM)
Ethanol: ~100 mg/mL

Solubility in Formulation 1: ≥ 2.5 mg/mL (4.50 mM) (saturation unknown) in 10% DMSO + 40% PEG300 + 5% Tween80 + 45% Saline (add these co-solvents sequentially from left to right, and one by one), clear solution.
For example, if 1 mL of working solution is to be prepared, you can add 100 μL of 25.0 mg/mL clear DMSO stock solution to 400 μL PEG300 and mix evenly; then add 50 μL Tween-80 to the above solution and mix evenly; then add 450 μL normal saline to adjust the volume to 1 mL.
Preparation of saline: Dissolve 0.9 g of sodium chloride in 100 mL ddH₂ O to obtain a clear solution.

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Solubility in Formulation 2: 2.5 mg/mL (4.50 mM) in 10% DMSO + 90% (20% SBE-β-CD in Saline) (add these co-solvents sequentially from left to right, and one by one), suspension solution; with ultrasonication.
For example, if 1 mL of working solution is to be prepared, you can add 100 μL of 25.0 mg/mL clear DMSO stock solution to 900 μL of 20% SBE-β-CD physiological saline solution and mix evenly.
Preparation of 20% SBE-β-CD in Saline (4°C，1 week): Dissolve 2 g SBE-β-CD in 10 mL saline to obtain a clear solution.

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Solubility in Formulation 3: ≥ 2.5 mg/mL (4.50 mM) (saturation unknown) in 10% DMSO + 90% Corn Oil (add these co-solvents sequentially from left to right, and one by one), clear solution.
For example, if 1 mL of working solution is to be prepared, you can add 100 μL of 25.0 mg/mL clear DMSO stock solution to 900 μL of corn oil and mix evenly.

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 (Please use freshly prepared in vivo formulations for optimal results.)