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含磷嘧啶类CDK9抑制剂的分子对接、3D-QSAR和分子动力学模拟
引用本文:唐光辉,张娅,张玉萍,周朋朋,林治华,王远强.含磷嘧啶类CDK9抑制剂的分子对接、3D-QSAR和分子动力学模拟[J].高等学校化学学报,2017,38(11).
作者姓名:唐光辉  张娅  张玉萍  周朋朋  林治华  王远强
作者单位:1. 重庆理工大学药学与生物工程学院,重庆,400054;2. 重庆理工大学药学与生物工程学院,重庆400054;药物化学与分子药理学重庆市重点实验室,重庆400054
基金项目:国家自然科学基金,重庆市教委科学技术研究项目,重庆市基础研究与前沿技术研究项目,重庆高校创新团队建设计划项目(批准号:CXTDX201601031)资助.Supported by the National Natural Science Foundation of China,the Scientific and Technological Research Program of Chongqing Municipal Education Commission
摘    要:选取64个具有潜力的含磷嘧啶类细胞周期依赖性蛋白激酶(CDK9)小分子抑制剂,采用分子对接方法研究了该类小分子与CDK9的结合作用,结果表明,分子构象、氢键形成、疏水性和氨基酸残基Cys106在此类抑制剂与CDK9的结合过程中具有重要作用.在配体叠合的基础上,运用比较分子力场分析(Co MFA)、比较分子相似性指数分析(Co MSIA)和Topomer Co MFA(T-COMFA)研究了分子结构与抑制活性的关系,发现由训练集立体场、静电场和疏水场组合的Co MSIA模型为最优模型,其内部交叉验证相关系数(Q2=0.557)、非交叉验证相关系数(R2=0.959)和外部预测相关系数(r2=0.863)具有统计学意义,该模型的三维等值线图直观显示了化合物的活性与其三维结构的关系.根据这些结果设计了10个具有新结构的含磷嘧啶类化合物,分子对接和分子动力学模拟结果表明,新化合物和CDK9的结合模式与原化合物64相同,自由能分析从理论上证明了新化合物64d的CDK9抑制活性优于化合物64,并且显示含磷基团与残基Asp109的静电场能在化合物与CDK9作用过程中有重要作用.

关 键 词:含磷嘧啶类细胞周期依赖性蛋白激酶抑制剂  分子对接  比较分子力场分析  比较分子相似性指数分析  TopomerCoMFA  分子动力学

Molecular Docking,QSAR and Molecular Dynamics Simulation on Phosphorus Containing Pyrimidines as CDK9 Inhibitors
TANG Guanghui,ZHANG Ya,ZHANG Yuping,ZHOU Pengpeng,LIN Zhihua,WANG Yuanqiang.Molecular Docking,QSAR and Molecular Dynamics Simulation on Phosphorus Containing Pyrimidines as CDK9 Inhibitors[J].Chemical Research In Chinese Universities,2017,38(11).
Authors:TANG Guanghui  ZHANG Ya  ZHANG Yuping  ZHOU Pengpeng  LIN Zhihua  WANG Yuanqiang
Abstract:The interaction modes between phosphorus containing pyrimidine cyclin dependent kinase 9 ( CDK9) inhibitors and the protein were studied using the combination of molecular docking and three-dimensional quantitative structure-activity relationships(3D-QSAR). The interaction mode obtained by molecu-lar docking revealed that the molecule conformation, hydrophobic interaction and H-bond, as well as Cys106 played an important role in the binding of phosphorus containing pyrimidines and CDK9. Based on the result of molecular docking, 3D-QSAR models were established by comparative molecular field analysis(CoMFA), comparative molecular similarity indices analysis( CoMSIA) and Topomer CoMFA techniques. With the best CoMSIA-SEH model, the cross-validated value ( Q2 ) was 0. 557, the non-cross-validated value ( R2 ) was 0. 959. The predictive power of the CoMSIA-SEH model was determined from external test sets that were exclu-ded during model development( r2=0. 863) . Ten new compounds were obtained based on the above modeling, and the results of molecular docking and molecular dynamics simulation suggested they could act as potential CDK9 inhibitors, especially compound 64d with more potent inhibitory activity proved by molecular dynamics simulation and binding free energy analysis. It was expected that these results could help establish the binding mechanism between phosphorus containing pyrimidines and CDK9, and provide a valuable reference for future anti-CDK9 drug design.
Keywords:Cyclin dependent kinase ( CDK9 ) inhibitor  Surflex-dock  Comparative molecular field analysis (CoMFA)  Comparative molecular similarity indices analysis(CoMSIA)  Topomer CoMFA  Molecular dy-namics
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