Discovery of novel dual functional agent as PPARgamma agonist and 11beta-HSD1 inhibitor for the treatment of diabetes.

PPARgamma and 11beta-HSD1 are attractive therapeutic targets for type 2 diabetes. However, PPARgamma agonists induce adipogenesis, which causes the side effect of weight gain, whereas 11beta-HSD1 inhibitors prevent adipogenesis and may be beneficial for the treatment of obesity in diabetic patients. For the first time, we designed, synthesized a series of alpha-aryloxy-alpha-methylhydrocinnamic acids as dual functional agents which activate PPARgamma and inhibit 11beta-HSD1 simultaneously. The compound 11e exhibited the most potent inhibitory activity compared to that of the lead compound 2, with PPARgamma (EC(50)=6.76 microM) and 11beta-HSD1 (IC(50)=0.76 microM) in vitro. Molecular modeling study for compound 11e was also presented. Compound 11e showed excellent efficacy for lowering glucose, triglycerides, body fat, in well established mice and rats models of diabetes and obesity and had a favorable ADME profile.

Structure-based drug design of a novel family of chalcones as PPARalpha agonists: virtual screening, synthesis, and biological activities in vitro.

AIM: To design and synthesize a novel class of peroxisome proliferator-activated receptors (PPAR)alpha agonists, which is obtained by the combination of the classical fibrate "head group", a linker with appropriate length and a chalcone. METHODS: Thirty seven compounds were designed and identified employing the virtual screening approach. Six compounds were then selected for synthesis and bioassay according to the virtual screening results, structural similarity, and synthetic complexity. RESULTS: Six new compounds (4b and 4d-h) were synthesized and bioassayed. All were found to be potent PPARalpha agonists, compound 4 h being the most prominent with a 50% effective concentration value of 0.06 micromol/L. CONCLUSION: This study provides a promising novel family of chalcones with a potential hypolipidemic effect.

3D-QSAR study of 20 (S)-camptothecin analogs.

AIM: To build up a quantitative structure-activity relationship (QSAR) model of 20 (S)-camptothecin (CPT) analogs for the prediction of the activity of new CPT analogs for drug design. METHODS: A training set of 43 structurally diverse CPT analogs which were inhibitors of topoisomerase I were used to construct a quantitative structure-activity relationship model with a comparative molecular field analysis (CoMFA). The QSAR model was optimized using partial least squares (PLS) analysis. A test set of 10 compounds was evaluated using the model. RESULTS: The CoMFA model was constructed successfully, and a good cross-validated correlation was obtained in which q(2) was 0.495. Then, the analysis of the non-cross-validated PLS model in which r(2) was 0.935 was built and permitted demonstrations of high predictability for the activities of the 10 CPT analogs in the test set selected in random. CONCLUSION: The CoMFA model indicated that bulky negative-charged group at position 9, 10 and 11 of CPT would increase activity, but excessively increasing bulky group at position 10 is adverse to inhibitory activity; substituents that occupy position 7 with the bulky positive group will enhance the inhibitive activity. The model can be used to design new CPT analogs and understand the mechanism of action.