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肝X受体β(liver X receptorβ,LXRβ)与体内胆固醇代谢密切相关,是治疗高脂血症的药物新靶点。该文以LXRβ激动剂为载体,利用3D-QSAR pharmacophore(Hypogen)模块构建定量药效团,得到最优的药效团模型包含1个氢键受体,1个芳环基团和2个疏水基团,药效团的5项评价指标分别为:训练集化合物的预测活性值和实验活性值的相关系数(correlation)为0.95、模型的费用函数(Δcost值)为128.65、活性化合物有效命中率(HRA)为84.44%、辨识有效性指数(IEI)为2.58、综合评价指数(CAI)为2.18。利用最优药效团模型筛选中药化学成分数据库(traditional Chinese medicine database,TCMD),初步获得309个潜在的中药活性成分。随后利用Libdock分子对接方法进一步精制筛选结果,基于原配体的打分值以及关键氨基酸建立筛选规则,最终得到去甲氧基姜黄素、异甘草黄酮醇、胀果甘草查尔酮E、水飞蓟宁4个化合物为潜在的LXRβ激动剂。该研究可以高效、低耗的筛选潜在的LXRβ中药激动剂,为抗高血脂新药研发提供助力。
Liver X receptor β (LXRβ) is closely related to the metabolism of cholesterol in vivo and is a new target for the treatment of hyperlipidemia. In this paper, the LXRβ agonist was used as a vector to construct a quantitative pharmacophore using the 3D-QSAR pharmacophore (Hypogen) module. The optimal pharmacophore model was obtained, which contains one hydrogen bond acceptor, one aromatic ring and two hydrophobic The results showed that the correlation coefficient between predicted activity and experimental activity of training set compounds was 0.95, the cost function (Δcost value) of the model was 128.65, the effective hit rate of active compounds (HRA) was 84.44%, IEI was 2.58, and comprehensive evaluation index (CAI) was 2.18. By using the optimal pharmacophore model to screen traditional Chinese medicine database (TCMD), 309 potential TCM active ingredients were initially obtained. Followed by Libdock molecular docking method for further purification of the screening results, based on the original ligand scoring value and key amino acids to establish screening rules, and ultimately get demethoxy curcumin, isol licorice flavonol, bulge Licorice chalcone E, silymarin Four compounds are potential LXR beta agonists. This study can screen latent LXRβ Chinese traditional medicine agonist with high efficiency and low consumption, and provide assistance for the development of anti-hyperlipidemic new drug.