Yu Hui, Wang Zhanli, Zhang Liangren, Zhang Jufeng, Huang Qian
Central Experimental Laboratory, The First People's Hospital, Shanghai Jiaotong University, Shanghai, China 200080.
Chem Biol Drug Des. 2007 Mar;69(3):204-11. doi: 10.1111/j.1747-0285.2007.00488.x.
We have applied pharmacophore generation, database searching and docking methodologies to discover new structures for the design of vascular endothelial growth factor receptors, the tyrosine kinase insert domain-containing receptor kinase inhibitors. The chemical function based pharmacophore models were built for kinase insert domain-containing receptor kinase inhibitors from a set of 10 known inhibitors using the algorithm HipHop, which is implemented in the CATALYST software. The highest scoring HipHop model consists of four features: one hydrophobic, one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic function. Using the algorithm CatShape within CATALYST, the bound conformation of 4-amino-furo [2, 3-d] pyrimidine binding to kinase insert domain-containing receptor kinase was used to generate a shape query. A merged shape and hypothesis query that is in an appropriate alignment was then built. The combined shape and hypothesis model was used as a query to search Maybridge database for other potential lead compounds. A total of 39 compounds were retrieved as hits. The hits obtained were docked into kinase insert domain-containing receptor kinase active site. One novel potential lead was proposed based on CATALYST fit value, LigandFit docking scores, and examination of how the hit retain key interactions known to be required for kinase binding. This compound inhibited vascular endothelial growth factor stimulated kinase insert domain-containing receptor phosphorylation in human umbilical vein endothelial cells.
我们应用了药效团生成、数据库搜索和对接方法,以发现用于设计血管内皮生长因子受体(含酪氨酸激酶插入结构域的受体激酶)抑制剂的新结构。使用CATALYST软件中实现的HipHop算法,从一组10种已知抑制剂中构建了基于化学功能的药效团模型,用于含激酶插入结构域的受体激酶抑制剂。得分最高的HipHop模型包含四个特征:一个疏水特征、一个氢键受体、一个氢键供体和一个环状芳香功能。利用CATALYST中的CatShape算法,以4-氨基-呋咱并[2,3-d]嘧啶与含激酶插入结构域的受体激酶结合的构象生成形状查询。然后构建一个经过适当比对的合并形状和假设查询。将合并后的形状和假设模型用作查询,在Maybridge数据库中搜索其他潜在的先导化合物。总共检索到39种命中化合物。将这些命中化合物对接至含激酶插入结构域的受体激酶活性位点。基于CATALYST拟合值、LigandFit对接分数以及对命中化合物如何保留已知激酶结合所需关键相互作用的研究,提出了一种新型潜在先导化合物。该化合物可抑制人脐静脉内皮细胞中血管内皮生长因子刺激的含激酶插入结构域的受体磷酸化。