scholarly journals G Protein–Coupled Receptors Targeting Insulin Resistance, Obesity, and Type 2 Diabetes Mellitus

2017 ◽  
Vol 70 (1) ◽  
pp. 39-67 ◽  
Author(s):  
Darren M. Riddy ◽  
Philippe Delerive ◽  
Roger J. Summers ◽  
Patrick M. Sexton ◽  
Christopher J. Langmead
2018 ◽  
Vol 10 (1) ◽  
pp. 84-93 ◽  
Author(s):  
Hirotaka Watada ◽  
Masanari Shiramoto ◽  
Shin Irie ◽  
Yasuo Terauchi ◽  
Yuichiro Yamada ◽  
...  

2001 ◽  
Vol 168 (3) ◽  
pp. 509-515 ◽  
Author(s):  
BD Rodgers ◽  
M Bernier ◽  
MA Levine

Adipocyte beta-adrenergic sensitivity is compromised in animal models of obesity and type 2 diabetes. Although changes in the membrane concentrations of G-protein alpha subunits (Galpha) have been implicated, it remains to be determined how these changes are affected by insulin resistance in the different animal models. Because previous studies used young animals, we measured the concentrations of Galpha and Gbeta subunits in epididymal fat from aged (48 weeks old) db/db mice and from their lean littermates to more closely reproduce the model of type 2 diabetes mellitus. Levels of immunoreactive Galphas, Galphai(1/2), Galphao and Galphaq/11 were all significantly greater in adipocyte membranes from the db/db mice than in membranes from their lean non-diabetic littermate controls. Levels of Galphai(1) and Galphai(2) were also individually determined and although they appeared to be slightly higher in db/db membranes, these differences were not significant. Although the levels of both Galphas isoforms were elevated, levels of the 42 and 46 kDa proteins rose by approximately 42% and 20% respectively, indicating differential protein processing of Galphas. By contrast, levels of Galphai3 were similar in the two groups. The levels of common Gbeta and Gbeta2 were also elevated in db/db mice, whereas Gbeta1 and Gbeta4 levels were not different. To determine whether these changes were due to insulin resistance per se or to elevated glucocorticoid production, G-protein subunit levels were quantified in whole cell lysates from 3T3-L1 adipocytes that were stimulated with different concentrations of either insulin or corticosterone. Although none of the subunit levels was affected by insulin, the levels of both Galphas isoforms were increased equally by corticosterone in a concentration-dependent manner. Since glucocorticoids are known regulators of Galphas gene expression in many cell types and in adipocytes from diabetic rodents, the results presented herein appear to more accurately reflect diabetic pathophysiology than do those of previous studies which report a decrease in Galphas levels. Taken together, these results indicate that most of the selective changes in G-protein subunit production in adipocytes from this animal model of type 2 diabetes may not be due to diminished insulin sensitivity, but may be due to other endocrine or metabolic abnormalities associated with the diabetic phenotype.


Author(s):  
Xu Chen ◽  
Zhidong Chen ◽  
Daiyun Xu ◽  
Yonghui Lyu ◽  
Yongxiao Li ◽  
...  

G protein-coupled receptor 40 (GPR40), one of the G protein-coupled receptors that are available to sense glucose metabolism, is an attractive target for the treatment of type 2 diabetes mellitus (T2DM). Despite many efforts having been made to discover small-molecule agonists, there is limited research focus on developing peptides acting as GPR40 agonists to treat T2DM. Here, we propose a novel strategy for peptide design to generate and determine potential peptide agonists against GPR40 efficiently. A molecular fingerprint similarity (MFS) model combined with a deep neural network (DNN) and convolutional neural network was applied to predict the activity of peptides constructed by unnatural amino acids (UAAs). Site-directed mutagenesis (SDM) further optimized the peptides to form specific favorable interactions, and subsequent flexible docking showed the details of the binding mechanism between peptides and GPR40. Molecular dynamics (MD) simulations further verified the stability of the peptide–protein complex. The R-square of the machine learning model on the training set and the test set reached 0.87 and 0.75, respectively; and the three candidate peptides showed excellent performance. The strategy based on machine learning and SDM successfully searched for an optimal design with desirable activity comparable with the model agonist in phase III clinical trials.


2018 ◽  
Vol 26 (2) ◽  
pp. 201-209 ◽  
Author(s):  
Taedong Han ◽  
Byoung Moon Lee ◽  
Yoo Hoi Park ◽  
Dong Hoon Lee ◽  
Hyun Ho Choi ◽  
...  

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