为解决静态和动态细节层次模型存在的数据冗余度大、精度判断标准单一和层次切换跳跃感强的问题,提出了基于四叉树孤立分割和屏幕误差的地形LOD(level of detail)算法.采用该算法,针对于规则格网,通过地形瓦片分割和数据预处理减少实时...为解决静态和动态细节层次模型存在的数据冗余度大、精度判断标准单一和层次切换跳跃感强的问题,提出了基于四叉树孤立分割和屏幕误差的地形LOD(level of detail)算法.采用该算法,针对于规则格网,通过地形瓦片分割和数据预处理减少实时阶段计算量,利用四叉树孤立分割消除结点间依赖关系,并构建保守性屏幕误差评价标准以弱化视觉跳跃感,最后采用添加拆分点和高程平均值法消除相邻瓦片和结点间裂隙.实验结果表明:该算法能较好解决常规方法中存在的问题;可满足大规模地形实时三维显示的要求;实时显示计算量小,帧速可保持在0.03 s以内.展开更多
Protein neddylation is a post-translational modification which transfers the ubiquitin-like protein NEDD8 to a lysine residue of the target substrate through a three-step enzymatic cascade.The bestknown substrates of ...Protein neddylation is a post-translational modification which transfers the ubiquitin-like protein NEDD8 to a lysine residue of the target substrate through a three-step enzymatic cascade.The bestknown substrates of neddylation are cullin family proteins,which are the core component of Cullin-RING E3 ubiquitin ligases(CRLs).Given that cullin neddylation is required for CRL activity,and CRLs control the turn-over of a variety of key signal proteins and are often abnormally activated in cancers,targeting neddylation becomes a promising approach for discovery of novel anti-cancer therapeutics.In the past decade,we have witnessed significant progress in the field of protein neddylation from preclinical target validation,to drug screening,then to the clinical trials of neddylation inhibitors.In this review,we first briefly introduced the nature of protein neddylation and the regulation of neddylation cascade,followed by a summary of all reported chemical inhibitors of neddylation enzymes.We then discussed the structure-based targeting of protein-protein interaction in neddylation cascade,and finally the available approaches for the discovery of new neddylation inhibitors.This review will provide a focused,up-to-date and yet comprehensive overview on the discovery effort of neddylation inhibitors.展开更多
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...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。展开更多
文摘为解决静态和动态细节层次模型存在的数据冗余度大、精度判断标准单一和层次切换跳跃感强的问题,提出了基于四叉树孤立分割和屏幕误差的地形LOD(level of detail)算法.采用该算法,针对于规则格网,通过地形瓦片分割和数据预处理减少实时阶段计算量,利用四叉树孤立分割消除结点间依赖关系,并构建保守性屏幕误差评价标准以弱化视觉跳跃感,最后采用添加拆分点和高程平均值法消除相邻瓦片和结点间裂隙.实验结果表明:该算法能较好解决常规方法中存在的问题;可满足大规模地形实时三维显示的要求;实时显示计算量小,帧速可保持在0.03 s以内.
基金the financial support by the National Key R&D Program of China(2016YFA0501800 to YS)
文摘Protein neddylation is a post-translational modification which transfers the ubiquitin-like protein NEDD8 to a lysine residue of the target substrate through a three-step enzymatic cascade.The bestknown substrates of neddylation are cullin family proteins,which are the core component of Cullin-RING E3 ubiquitin ligases(CRLs).Given that cullin neddylation is required for CRL activity,and CRLs control the turn-over of a variety of key signal proteins and are often abnormally activated in cancers,targeting neddylation becomes a promising approach for discovery of novel anti-cancer therapeutics.In the past decade,we have witnessed significant progress in the field of protein neddylation from preclinical target validation,to drug screening,then to the clinical trials of neddylation inhibitors.In this review,we first briefly introduced the nature of protein neddylation and the regulation of neddylation cascade,followed by a summary of all reported chemical inhibitors of neddylation enzymes.We then discussed the structure-based targeting of protein-protein interaction in neddylation cascade,and finally the available approaches for the discovery of new neddylation inhibitors.This review will provide a focused,up-to-date and yet comprehensive overview on the discovery effort of neddylation inhibitors.
文摘肝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。
