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Design, Synthesis and Biological Evaluation of Novel 1, 3, 4-Oxadiazole PD176252 Analogues as Potential GRPR Inhibitors
- Source: Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry - Anti-Cancer Agents), Volume 22, Issue 17, Oct 2022, p. 3009 - 3024
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- 01 Oct 2022
Abstract
Background: GRPR is over-expressed in cancer cells and is a potential drug target for the treatment of cancer. PD176252, as the most representative non-peptide inhibitor of GRPR, can inhibit the growth of cancer cells, but its low selectivity to cancer cells and normal cells limits its further application. Objective: The aim of this study was to design and synthesize novel GRPR inhibitor with stronger anti-cancer activity and higher affinity with GRPR than the lead compound PD176252. Methods: A series of 1, 3, 4-oxadiazole derivatives as PD176252 analogues (4a-4j, 6a-6q) were synthesized and their cytotoxic activity was investigated on four cancer lines with high expression of GRPR (gastric (HGC-27), colon (HCT- 116), prostate (PC-3), and lung (A549)) and one human cell line (gastric mucosal epithelial (GES-1)) by MTT assay. Flow cytometry analysis and Western Blot were used to determine whether the compound induced programmed apoptosis of cancer cells. Competitive binding experiment was used to verify the affinity between GRPR and the optimal compound. Results: Compound 6m exhibited significant growth inhibition on all tested cancer cell lines, especially gastric cancer cells (HGC-27 cellular IC50 0.37 ± 0.04μM). Also, the selectivity of 6m to HGC-27 was much higher than that of PD176252. Flow cytometric analysis and Western Blot proved that 6m significantly promoted the apoptosis of HGC- 27 cells. Moreover, competitive binding experiment confirmed the close binding of 6m with GRPR, which indicated 6m with a higher affinity than lead compound PD176252. Conclusion: Our results suggested that 6m, as a novel GRPR inhibitor, had a higher affinity with GRPR and potential anti-cancer effect than PD176252, which can be used as a template for further optimization.