Archives

  • 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-07
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • In conclusion adipose PGD suppressed the lipolysis by

    2019-08-14

    In conclusion, adipose PGD2 suppressed the lipolysis by decreasing the intracellular cAMP level through DP2R. Therefore, PGD2 enhanced adipocyte differentiation (lipid accumulation) through both repression of the lipolysis via DP2R and activation of the lipogenesis via PPARγ. Thus, L-PGDS and DP2R are potential therapeutic targets for the treatment of obesity and related diseases.
    Conflicts of interest
    Acknowledgments This work was supported in part by the Grant-in-Aid for Scientific Research (25460079, 16K08256) and Scientific Research on Innovative Areas (23116516) from The Ministry of Education, Culture, Sports, Science and Technology of Japan, and by grants from Japan Foundation for Applied Enzymology, The Research Foundation for Pharmaceutical Sciences, The Naito Foundation, Takeda Science Foundation, and Daiwa Securities Health Foundation.
    Introduction Chemoattractant receptor-homologous molecule expressed on Th2 cells (CRTh2) is a G-protein coupled receptor that plays a recognized role in initiation and perpetuation of allergic diseases (Pettipher and Whittaker, 2012, Shimono et al., 2012, Pothier et al., 2012, Birkinshaw et al., 2006, Bonafoux et al., 2011, Hirai et al., 2001, Nagata et al., 1999a, Gervais et al., 2011, Schroder et al., 2012). CRTh2 is selectively expressed by Th2 cells, eosinophils, and basophils and mediates chemotactic activation of these cells in response to prostaglandin D2 (PGD2) (Pettipher and Whittaker, 2012, Nagata et al., 1999b, Iwasaki et al., 2002, Uller et al., 2007, Sykes et al., 2012) which is produced in high quantities by mast cells during allergic attacks (Birkinshaw et al., 2006, Huang et al., 2004, Takeshita et al., 2004, Pettipher, 2008). PGD2 exhibit its biological responses by activating the classical DP1 receptor and CRTh2 receptor (also known as DP2) which is linked to different signalling pathways and it negatively regulates adenylyl cyclases and stimulates phosphoinositide 3-kinase, mitogen-activated protein kinases and phospholipase C (Hata et al., 2005, Hata et al., 2005, Jain et al., 2008, Nagata and Hirai, 2003, Mathiesen et al., 2005, Hata and Breyer, 2004Nagata and Hirai, 2003, Mathiesen et al., 2005, Hata and Breyer, 2004). To date, CRTh2 is the only receptor that links a major lipid mediator of mast cells with Th2 cells, eosinophils, and basophils (Nagata and Hirai, 2003). There has been a dramatic increase in the number of published articles and patents describing the identification and optimization of potent CRTh2 antagonists in recent years (Ulven and Kostenis, 2010). It has been suggested that antagonizing selectively the CRTh2 receptor could be useful in the treatment of asthma and other inflammatory diseases (Pothier et al., 2012). CRTh2 antagonists had a very strong preference for a carboxylic Sephin1 moiety (Pettipher and Whittaker, 2012) and have variety of fused 6–5-membered ring chemotypes as a core structure such as indole, azaindole, benzimidazole, indolizine, spiro–indoline (Shimono et al., 2012). Ramatroban a drug currently used for treatment of allergic rhinitis also possess CRTh2 antagonist activity (Pettipher and Whittaker, 2012, Shimono et al., 2012, Hata et al., 2005, Hata and Breyer, 2004). More recently, an orally bioavailable CRTh2 antagonist (OC000459) successfully completed Phase IIa trials demonstrating efficacy in asthma and allergic rhinoconjunctivitis (Bonafoux et al., 2011). These suggest that CRTh2 antagonist is a potential therapy in allergic and inflammatory disorders. When 3D structure of the macromolecular target is not available 3D-QSAR is the prominent computational means to support chemistry within drug design projects (Puzyn et al., 2010). The primary objective of 3D QSAR was to understand which properties are important to control a specific biological activity of a series of compounds. The most popular methods are CoMFA and CoMSIA which correlate biological activity with the molecular features (Jain et al., 2008, Doweyko, 2004). Hence, in the present study, ligand-based CoMFA and CoMSIA were performed on a series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids. The selected series satisfies the key requirement of CRTh2 antagonist and have similar structural features to indomethacin which is reported potent agonist for the development of CRTh2 antagonist. The majority of currently available CRTh2 antagonists (Shimono et al., 2012, Birkinshaw et al., 2006, Ulven et al., 2007, Sandham et al., 2009, Tumey et al., 2010, Gallant et al., 2011) have the core structures of indole acetic acid but the series used in our study alone replaces the indole acetic acid by imidazole acetic acid which paves the way for the discovery of novel antagonist against CRTh2. In addition, the compounds have sulfur atom attached to benzimidazole ring which makes the compound to be more potent. The highly active molecule among the dataset was selected as template and its conformation was searched through systematic search and simulated annealing methods. The bioactive conformations using two search methods were taken and the common scaffold was used to align the compounds. We segregated the dataset (65 compounds) into test (15 compounds) and training (50 compounds) set. Ten different combinations of training and test set compounds were used which produced 20 CoMFA models and 100 CoMSIA models. The statistical results of the generated models were found and each model was validated with statistical cut off values such as q2>0.4, r2>0.5 and r2pred>0.5. Based on the predictive ability (r2pred) of the test set the best model was chosen in CoMFA and CoMSIA analysis and it was graphically interpreted by field contribution maps. This 3D-QSAR analysis provides guidelines for the design of next-generation compounds with enhanced bioactivity or specificity and has ability to predict biological activities of novel compounds.