Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the prog...Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the progress of such serious diseases as end-stage renal disease, idiopathic infantile arterial calcification, ankylosis, osteoarthritis and diabetes. In order to design and optimize the potent TNAP inhibitors, comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) were used to analyze 3D structure-activity relationships(3D-QSAR) of TNAP inhibitors. The 3D-QSAR model(CoMFA with q^2 = 0.521, r^2 = 0.930; CoMSIA with q^2 = 0.529, r^2 = 0.933) had a good predictability. Surflex-dock was used to reveal the binding mode between the inhibitors and TNAP protein. CoMFA, CoMSIA and docking results provide guidance for the discovery of TNAP inhibitors. Finally, eight new compounds as potential TNAP inhibitors were designed.展开更多
血管内皮生长因子VEGF及其受体VEGFR2对于肿瘤血管生成起至关重要的作用。本文旨在研究VEGFR2的咪唑并哒嗪类抑制剂的三维定量构效关系及新抑制剂分子与VEGFR2的作用机制。构建的Topomer Co MFA模型具有较强的预测能力和拟合能力(q^2=0....血管内皮生长因子VEGF及其受体VEGFR2对于肿瘤血管生成起至关重要的作用。本文旨在研究VEGFR2的咪唑并哒嗪类抑制剂的三维定量构效关系及新抑制剂分子与VEGFR2的作用机制。构建的Topomer Co MFA模型具有较强的预测能力和拟合能力(q^2=0.809,r^2=0.968)以及外部预测能力(r_(pred)~2=0.571)。应用Topomer Search技术在含1304868个分子的ZINC数据库中进行了虚拟筛选,采用基于片段的药物设计方法设计了68个高活性的新VEGFR2抑制剂。最后借助Surflex-dock技术研究了新分子与VEFGR2的作用机制,发现新抑制剂与残基Glu885、Cys919、Asn923、Asp1046等作用显著。本研究为VEGFR2抑制剂分子的结构修饰、设计与合成提供了重要的理论指导。展开更多
目的:评估QM/MM方法和Surflex-Dock分子对接程序对DNA-配体复合物模拟的准确性。方法:从蛋白质数据库(Protein Data Bank)下载DNA-配体复合物的三维结构,利用计算机辅助药物设计的分子对接程序Surflex-Dock模拟出147个诱饵化合物(decoys...目的:评估QM/MM方法和Surflex-Dock分子对接程序对DNA-配体复合物模拟的准确性。方法:从蛋白质数据库(Protein Data Bank)下载DNA-配体复合物的三维结构,利用计算机辅助药物设计的分子对接程序Surflex-Dock模拟出147个诱饵化合物(decoys)并计算其结合分数(binding score)。然后将得出的分数与从QM/MM计算的结合能力以Z-score和辨别力(DP)作比较。从而评估Surflex-Dock和QM/MM的准确性。结果:Surflex-Dock的DPi值比QM/MM高,显示Surflex-Dock的辨别力较低。结论:因QM/MM计算速度慢,本研究认为Surflex-Dock可用作快速虚拟筛选,而较准确的QM/MM则适合用于对拥有较高结合分数的化合物进行再评分(rescoring)。展开更多
基金supported by the Key Project of Natural Science Foundation of Chongqing(No.cstc2015jcyjBX0080)Science and Technology project of Chongqing Education Commission(KJ1600907)
文摘Alkaline phosphatases(APs) include the placental AP(PLAP), germ cell AP(GCAP), intestinal AP(IAP) and tissue nonspecific AP(TNAP). Over expression of TNAP in smooth muscle cells of kidney and vessels provokes the progress of such serious diseases as end-stage renal disease, idiopathic infantile arterial calcification, ankylosis, osteoarthritis and diabetes. In order to design and optimize the potent TNAP inhibitors, comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) were used to analyze 3D structure-activity relationships(3D-QSAR) of TNAP inhibitors. The 3D-QSAR model(CoMFA with q^2 = 0.521, r^2 = 0.930; CoMSIA with q^2 = 0.529, r^2 = 0.933) had a good predictability. Surflex-dock was used to reveal the binding mode between the inhibitors and TNAP protein. CoMFA, CoMSIA and docking results provide guidance for the discovery of TNAP inhibitors. Finally, eight new compounds as potential TNAP inhibitors were designed.
文摘血管内皮生长因子VEGF及其受体VEGFR2对于肿瘤血管生成起至关重要的作用。本文旨在研究VEGFR2的咪唑并哒嗪类抑制剂的三维定量构效关系及新抑制剂分子与VEGFR2的作用机制。构建的Topomer Co MFA模型具有较强的预测能力和拟合能力(q^2=0.809,r^2=0.968)以及外部预测能力(r_(pred)~2=0.571)。应用Topomer Search技术在含1304868个分子的ZINC数据库中进行了虚拟筛选,采用基于片段的药物设计方法设计了68个高活性的新VEGFR2抑制剂。最后借助Surflex-dock技术研究了新分子与VEFGR2的作用机制,发现新抑制剂与残基Glu885、Cys919、Asn923、Asp1046等作用显著。本研究为VEGFR2抑制剂分子的结构修饰、设计与合成提供了重要的理论指导。
文摘目的:评估QM/MM方法和Surflex-Dock分子对接程序对DNA-配体复合物模拟的准确性。方法:从蛋白质数据库(Protein Data Bank)下载DNA-配体复合物的三维结构,利用计算机辅助药物设计的分子对接程序Surflex-Dock模拟出147个诱饵化合物(decoys)并计算其结合分数(binding score)。然后将得出的分数与从QM/MM计算的结合能力以Z-score和辨别力(DP)作比较。从而评估Surflex-Dock和QM/MM的准确性。结果:Surflex-Dock的DPi值比QM/MM高,显示Surflex-Dock的辨别力较低。结论:因QM/MM计算速度慢,本研究认为Surflex-Dock可用作快速虚拟筛选,而较准确的QM/MM则适合用于对拥有较高结合分数的化合物进行再评分(rescoring)。
