ABSTRACT

Cannabinoid receptor has been shown to be overexpressed in various types of cancers, especially non-small cell lung cancer. As a result, it could be used as novel target for anticancer treatments. Because receptor-dependent 4D-QSAR generates conformational ensemble profiles of compounds by molecular dynamics simulations at the binding site of the enzyme, this work describes the synthesis, biological activity evaluation and 4D-QSAR studies of 4,5-dihydro-1,3,4-oxadiazole derivatives targeting cannabinoid receptor. Compared with WIN55,212–2, compound 5 f showed the best antiproliferative activity. The receptor-dependent 4D-QSAR model was generated by multiple linear regression method using QSARINS. Leave-n-out cross-validation and chemical applicability domain were performed to analyse the independent test set and to verify the robustness of the model. The best 4D-QSAR model showed the following statistics: r² = 0.8487, Q²_LOO = 0.7667, Q²_LNO = 0.7524, and r²_Pred = 0.8358.

摘要

大麻素受体已显示在各种类型的癌症（尤其是非小细胞肺癌）中过表达。结果，它可用作抗癌治疗的新靶标。由于依赖受体的4D-QSAR通过在酶结合位点的分子动力学模拟生成了化合物的构象整体轮廓，因此该工作描述了4,5-二氢-1,3的合成，生物学活性评估和4D-QSAR研究，靶向大麻素受体的4-恶二唑衍生物。与WIN55,212–2相比，化合物5f表现出最佳的抗增殖活性。使用QSARINS通过多元线性回归方法生成受体依赖性4D-QSAR模型。免洗ñ进行交叉验证和化学适用性域分析独立的测试集并验证模型的鲁棒性。最佳4D-QSAR模型显示以下统计信息：r ²  = 0.8487，Q ² _LOO  = 0.7667，Q ² _LNO  = 0.7524，r ² _Pred  = 0.8358。