以20个文献报道的二肽基肽酶Ⅳ(DPP-Ⅳ)抑制剂作为训练集，利用Discovery Studio构建了DPP-Ⅳ抑制剂的三维药效团模型。所得最优药效团模型Hypo1具有一个氢键受体，一个疏水基团，一个可离子化正电中心，一个芳香环和5个排除体积，Fischer交叉验证结果表明该模型具有较高的置信度。Hypo 1对测试集中20个DPP-Ⅳ抑制剂活性进行了预测，结果显示有较好的预测能力。利用该模型进行ZINC数据库搜索，得到预测活性小于10 nmol？L–1的化合物1369个。将这些化合物对接到DPP-Ⅳ的活性位点并根据PLP2评分函数筛选出21个评分较高的化合物，为设计和合成新型的DPP-Ⅳ抑制剂提供了理论参考。
The 3D pharmacophore model of DPP-Ⅳ inhibitors was established using the Discovery Studio software with the training set of 20 DPP-Ⅳ inhibitors. The best pharmacophore hypothesis (Hypo 1) consists of one hydro- gen-bond acceptor, one hydrophobic point, one positive ionizable group, one aromatic ring as well as five excluded volumes. Fischer’s validation clearly shows that proposed Hypo 1 has highly predictive ability and can be efficiently used as a 3D query for virtual screening to retrieve potential inhibitors from ZINC databases. The hit compounds sub- sequently were docked into the DPP-Ⅳ active site and 21 compounds were obtained based on PLP2 scoring function. Therefore, this study could provide scientific basis for denovo design of DPP-Ⅳ inhibitors.
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