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吡唑啉嘧啶类IL-2诱导T细胞激酶抑制剂的三维定量构效关系研究和虚拟筛选 被引量:1

3D-QSAR and virtual screening of inducible T-cell kinase inhibitors of pyrazolopyrimidine
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摘要 为获取结构新颖、高活性的Itk抑制剂,采用Co MFA和Co MSIA两种方法对39个吡唑啉嘧啶类Itk抑制剂进行三维定量构效关系研究,新建模型的交叉验证系数分别为q2=0.771和q2=0.759,拟合验证系数分别为r2=0.948和r2=0.913,结果表明模型具有良好的可信度和预测能力。运用药效团模型虚拟筛选、分子对接和3D-QSAR模型的分子活性预测等方法进行虚拟筛选,最终获得7个高活性的新抑制剂化合物。Surflexdock分析显示新抑制剂与Itk靶点有较强的的氢键作用。各研究结果表明,此定量构效关系研究和虚拟筛选方法可有效地用于吡唑啉嘧啶类Itk抑制剂的分子设计,为Itk靶向药物的研发及合成提供参考。 In order to obtain novel and highly active Itk inhibitors,the three-dimensional quantitative structure-activity relationship of 39 Itk inhibitors of pyrazolopyrimidine was studied by two methods of CoMFA and CoMSIA.The cross validation coefficients of the new models are q 2=0.771 and q 2=0.759 respectively,and the coefficients of determination are r 2=0.948 and r 2=0.913 respectively.The results of 3D-QSAR models show that the models have good reliability and prediction ability.Virtual screening of pharmacophore model,molecular docking and molecular activity prediction of 3D-QSAR model were applied to virtual screening,and seven new highly active inhibitors were obtained.Surflex-dock analysis showedsthat the new inhibitorshashave strong hydrogen bond with Itk target.The research results show that this quantitative structure-activity relationship study and virtual screening method can be effectively used in the molecular design of Itk inhibitors of pyrazolopyrimidine and provide a reference for the development and synthesis of Itk targeted drugs.
作者 刘桦 蒲铃铃 杨菁 宋海星 梁桂兆 LIU Hua;PU Ling-ling;Yang Jing;SONG Hai-xing;Liang Gui-zhao(Provincial Key Laboratory of Biomedical Experimental Teaching,Chengdu Medical College,Chengdu 610050,China;School of Bioengineering,Chongqing University,Key Laboratory of Biorheological Science and Technology,Ministry of Education,Chongqing 400044,China)
出处 《化学研究与应用》 CAS CSCD 北大核心 2018年第8期1318-1327,共10页 Chemical Research and Application
基金 四川省教育厅项目(项目编号:16ZB0277) 四川养老与老年健康协同创新中心招标项目(批准号:YLZBZ1819)
关键词 Itk抑制剂 三维定量构效关系 虚拟筛选 药效团模型 Itk inhibitors 3D-QSAR virtual screening pharmacophore model
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