Department of Chemistry, Northern Kentucky University, Highland Heights, KY 41099-1905, USA.
Eur J Med Chem. 2011 May;46(5):1512-23. doi: 10.1016/j.ejmech.2011.01.069. Epub 2011 Feb 25.
Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 μM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models.
采用基于递归分区和计算配体对接方法的两种筛选方案，对包含 345000 种化合物的文库进行了肌浆/内质网钙 ATP 酶（SERCA）新型抑制剂的虚拟筛选，SERCA 是癌症化疗的一个潜在靶点。在生物测定中测试了总共 72 种预测为 SERCA 潜在抑制剂的化合物，其中 17 种在低于 100μM 的浓度下表现出抑制效力。这些抑制剂中的大多数由两个通过一到三个原子的短链连接在一起的苯基环组成。通过检查对接预测构象确定了 SERCA 与抑制剂之间的假定相互作用，并且通过分析递归分区模型使用的分类模式确定了有效抑制 SERCA 所需的一些结构特征。
