Chau De-Ming, Shum David, Radu Constantin, Bhinder Bhavneet, Gin David, Gilchrist M Lane, Djaballah Hakim, Li Yue-Ming
Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, NY 10065, USA.
Comb Chem High Throughput Screen. 2013 Jul;16(6):415-24. doi: 10.2174/1386207311316060001.
The Notch pathway plays a crucial role in cell fate decisions through controlling various cellular processes. Overactive Notch signal contributes to cancer development from leukemias to solid tumors. γ-Secretase is an intramembrane protease responsible for the final proteolytic step of Notch that releases the membrane-tethered Notch fragment for signaling. Therefore, γ-secretase is an attractive drug target in treating Notch-mediated cancers. However, the absence of high throughput γ-secretase assay using Notch substrate has limited the identification and development of γ- secretase inhibitors that specifically target the Notch signaling pathway. Here, we report on the development of a 1536- well γ-secretase assay using a biotinylated recombinant Notch1 substrate. We effectively assimilated and miniaturized this newly developed Notch1 substrate with the AlphaLISA detection technology and demonstrated its robustness with a calculated Z' score of 0.66. We further validated this optimized assay by performing a pilot screening against a chemical library consisting of ~5,600 chemicals and identified known γ-secretase inhibitors e.g. DAPT, and Calpeptin; as well as a novel γ-secretase inhibitor referred to as KD-I-085. This assay is the first reported 1536-well AlphaLISA format and represents a novel high throughput Notch1-γ-secretase assay, which provides an unprecedented opportunity to discover Notch-selective γ-secretase inhibitors that can be potentially used for the treatment of cancer and other human disorders.
Notch信号通路通过控制各种细胞过程在细胞命运决定中发挥关键作用。Notch信号过度激活会导致从白血病到实体瘤等多种癌症的发展。γ-分泌酶是一种膜内蛋白酶,负责Notch的最终蛋白水解步骤,释放与膜相连的Notch片段用于信号传导。因此,γ-分泌酶是治疗Notch介导的癌症的一个有吸引力的药物靶点。然而,缺乏使用Notch底物的高通量γ-分泌酶检测方法限制了特异性靶向Notch信号通路的γ-分泌酶抑制剂的鉴定和开发。在此,我们报告了一种使用生物素化重组Notch1底物的1536孔γ-分泌酶检测方法的开发。我们有效地将这种新开发的Notch1底物与AlphaLISA检测技术进行了整合和小型化,并通过计算得出的Z'值为0.66证明了其稳健性。我们通过对一个由约5600种化学物质组成的化学文库进行初步筛选,进一步验证了这种优化后的检测方法,并鉴定出了已知的γ-分泌酶抑制剂,如DAPT和Calpeptin;以及一种新型的γ-分泌酶抑制剂KD-I-085。该检测方法是首次报道的1536孔AlphaLISA形式,代表了一种新型的高通量Notch1-γ-分泌酶检测方法,为发现可潜在用于治疗癌症和其他人类疾病的Notch选择性γ-分泌酶抑制剂提供了前所未有的机会。