Department of Chemistry, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455, USA.
J Med Chem. 2010 Mar 25;53(6):2464-71. doi: 10.1021/jm901613f.
The similarity ensemble approach (SEA) relates proteins based on the set-wise chemical similarity among their ligands. It can be used to rapidly search large compound databases and to build cross-target similarity maps. The emerging maps relate targets in ways that reveal relationships one might not recognize based on sequence or structural similarities alone. SEA has previously revealed cross talk between drugs acting primarily on G-protein coupled receptors (GPCRs). Here we used SEA to look for potential off-target inhibition of the enzyme protein farnesyltransferase (PFTase) by commercially available drugs. The inhibition of PFTase has profound consequences for oncogenesis, as well as a number of other diseases. In the present study, two commercial drugs, Loratadine and Miconazole, were identified as potential ligands for PFTase and subsequently confirmed as such experimentally. These results point toward the applicability of SEA for the prediction of not only GPCR-GPCR drug cross talk but also GPCR-enzyme and enzyme-enzyme drug cross talk.
相似性集成方法 (SEA) 根据配体之间的化学相似性来关联蛋白质。它可用于快速搜索大型化合物数据库并构建跨靶标相似性图。新兴的图谱以一种仅基于序列或结构相似性可能无法识别的方式来关联靶标。SEA 先前已经揭示了主要作用于 G 蛋白偶联受体 (GPCR) 的药物之间的串扰。在这里，我们使用 SEA 来寻找商业可用药物对酶蛋白法呢基转移酶 (PFTase) 潜在的非靶标抑制作用。PFTase 的抑制对肿瘤发生以及许多其他疾病都有深远的影响。在本研究中，两种商业药物，氯雷他定和咪康唑，被鉴定为 PFTase 的潜在配体，并随后通过实验证实了这一点。这些结果表明 SEA 不仅可用于预测 GPCR-GPCR 药物串扰，还可用于预测 GPCR-酶和酶-酶药物串扰。
