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使用制药公司数据集研究已发表的PAINS警报的行为。

Investigating the Behavior of Published PAINS Alerts Using a Pharmaceutical Company Data Set.

作者信息

Vidler Lewis R, Watson Ian A, Margolis Brandon J, Cummins David J, Brunavs Michael

机构信息

Research and Development, Eli Lilly and Company, Ltd., Sunninghill Road, Windlesham, Surrey GU20 6PH, United Kingdom.

Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, United States.

出版信息

ACS Med Chem Lett. 2018 Jul 10;9(8):792-796. doi: 10.1021/acsmedchemlett.8b00097. eCollection 2018 Aug 9.

Abstract

Biochemical assay interference is becoming increasingly recognized as a significant waste of resource in drug discovery, both in industry and academia. A seminal publication from Baell and Holloway raised the awareness of this issue, and they published a set of alerts to identify what they described as PAINS (pan-assay interference compounds). These alerts have been taken up by drug discovery groups, even though the original paper had a somewhat limited data set. Here, we have taken Lilly's far larger internal data set to assess the PAINS alerts on four criteria: promiscuity (over six assay formats including AlphaScreen), compound stability, cytotoxicity, and presence of a high Hill slope as a surrogate for non-1:1 protein-ligand binding. It was found that only three of the alerts show pan-assay promiscuity, and the alerts appear to encode primarily AlphaScreen promiscuous molecules. Although not enriching for pan-assay promiscuity, many of the alerts do encode molecules that are unstable, show cytotoxicity, and increase the prevalence of high Hill slopes.

摘要

生化分析干扰在药物研发领域正日益被视为一种严重的资源浪费,无论是在制药行业还是学术界。Baell和Holloway发表的一篇开创性论文提高了人们对这个问题的认识,他们发布了一组警示信息来识别他们所称的PAINS(泛分析干扰化合物)。尽管原始论文的数据集在某种程度上有限,但这些警示信息已被药物研发团队采用。在此,我们利用礼来公司规模大得多的内部数据集,从四个标准评估PAINS警示信息:多反应性(超过六种分析形式,包括AlphaScreen)、化合物稳定性、细胞毒性以及作为非1:1蛋白质-配体结合替代指标的高希尔斜率的存在情况。结果发现,只有三种警示信息显示泛分析多反应性,而且这些警示信息似乎主要编码AlphaScreen多反应性分子。虽然这些警示信息并未富集泛分析多反应性,但许多警示信息确实编码了不稳定、具有细胞毒性且增加高希尔斜率发生率的分子。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9c6/6088356/2b6bbbb711c3/ml-2018-00097p_0001.jpg

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