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首页> 外文期刊>Combinatorial chemistry & high throughput screening >Compound ranking based on a new mathematical measure of effectiveness using time course data from cell-based assays.
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Compound ranking based on a new mathematical measure of effectiveness using time course data from cell-based assays.

机译:基于使用基于细胞的分析得出的时程数据基于有效性的新数学度量对化合物进行排名。

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摘要

The half maximal inhibitory concentration (IC50) has several limitations that make it unsuitable for examining a large number of compounds in cytotoxicity studies, particularly when multiple exposure periods are tested. This article proposes a new approach to measure drug effectiveness, which allows ranking compounds according to their toxic effects on live cells. This effectiveness measure, which combines all exposure times tested, compares the growth rates of a particular cell line in the presence of the compound with its growth rate in the presence of DMSO alone. Our approach allows measuring a wider spectrum of toxicity than the IC50 approach, and allows automatic analyses of a large number of compounds. It can be easily implemented in linear regression software, provides a comparable measure of effectiveness for each investigated compound (both toxic and non-toxic), and allows statistically testing the null hypothesis that a compound is non-toxic versus the alternative that it is toxic. Importantly, our approach allows defining an automated decision rule for deciding whether a compound is significantly toxic. As an illustration, we describe the results of a cellbased study of the cytotoxicity of 24 analogs of novobiocin, a C-terminal inhibitor of heat shock protein 90 (Hsp90); the compounds were ranked in order of cytotoxicity to a panel of 18 cancer cell lines and 1 normal cell line. Our approach may also be a good alternative to computing the half maximal effective concentration (EC50) in studies searching for compounds that promote cell growth.
机译:半数最大抑制浓度(IC50)具有几个局限性,使其不适合在细胞毒性研究中检查大量化合物,尤其是在测试了多个暴露时间时。本文提出了一种测量药物有效性的新方法,该方法可以根据化合物对活细胞的毒性作用对化合物进行排名。结合了测试的所有暴露时间的有效性测量方法,将化合物存在时特定细胞系的生长速率与仅存在DMSO时其生长速率进行了比较。与IC50方法相比,我们的方法可以测量更大范围的毒性,并且可以自动分析大量化合物。它可以在线性回归软件中轻松实现,可以为每种研究的化合物(有毒和无毒)提供可比较的有效性度量,并且可以通过统计学方法测试化合物无毒和其有毒替代假设。 。重要的是,我们的方法允许定义自动决定规则,以决定化合物是否具有明显毒性。作为说明,我们描述了基于细胞的新霉素24种类似物(热休克蛋白90(Hsp90)的C端抑制剂)的细胞毒性研究的结果;按照对18种癌细胞系和1种正常细胞系的细胞毒性的顺序对化合物进行排序。在寻找促进细胞生长的化合物的研究中,我们的方法也可能是计算半数最大有效浓度(EC50)的好选择。

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