Futamura Yushi, Kawatani Makoto, Kazami Sayaka, Tanaka Kenichi, Muroi Makoto, Shimizu Takeshi, Tomita Koji, Watanabe Nobumoto, Osada Hiroyuki
Chemical Biology Core Facility, Chemical Biology Department, RIKEN Advanced Science Institute, Wako-shi, Saitama 351-0198, Japan.
Chem Biol. 2012 Dec 21;19(12):1620-30. doi: 10.1016/j.chembiol.2012.10.014.
Visual observation is a powerful approach for screening bioactive compounds that can facilitate the discovery of attractive druggable targets following their chemicobiological validation. So far, many high-content approaches, using sophisticated imaging technology and bioinformatics, have been developed. In our study, we aimed to develop a simpler method that focuses on intact cell images because we found that dynamic changes in morphology are informative, often reflecting the mechanism of action of a drug. Here, we constructed a chemical-genetic phenotype profiling system, based on the high-content cell morphology database Morphobase. This database compiles the phenotypes of cancer cell lines that are induced by hundreds of reference compounds, wherein those of well-characterized anticancer drugs are classified by mode of action. Furthermore, we demonstrate the applicability of this system in identifying NPD6689, NPD8617, and NPD8969 as tubulin inhibitors.
视觉观察是筛选生物活性化合物的一种有效方法,这些化合物在经过化学生物学验证后,有助于发现有吸引力的可成药靶点。到目前为止,已经开发出了许多使用先进成像技术和生物信息学的高内涵方法。在我们的研究中,我们旨在开发一种更简单的方法,该方法聚焦于完整细胞图像,因为我们发现形态学的动态变化具有信息价值,常常反映药物的作用机制。在此,我们基于高内涵细胞形态学数据库Morphobase构建了一个化学遗传表型分析系统。该数据库汇编了数百种参考化合物诱导的癌细胞系的表型,其中特征明确的抗癌药物的表型按作用方式分类。此外,我们证明了该系统在鉴定NPD6689、NPD8617和NPD8969为微管蛋白抑制剂方面的适用性。