Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS.
Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS.
复制标题
DOI：
10.1021/acs.jcim.6b00465
复制
发表时间：
2017-03-27
影响因子：
5.6
通讯作者：
Tropsha A
中科院分区：
文献类型：
--
作者：
Capuzzi SJ;Muratov EN;Tropsha A
使用亚结构警报来识别泛测定干扰化合物（PAINS）已成为生物筛选活动中分类过程的常见组成部分。然而，这些警报最初来自仅使用AlphaScreen检测技术在仅六种测定蛋白质-蛋白质相互作用（PPI）抑制的试验中测试的专有库;此外，68%（480个警报中的328个）来自四种或更少的化合物。为了评估这些警报作为泛测定干扰指标的可靠性，我们使用PubChem中的公开数据，对PAINS警报对生物测定中化合物混杂性的影响进行了大规模分析。我们发现，在测量PPI抑制的AlphaScreen试验中，大多数（97%）含有PAINS警报的化合物实际上是不常见的命中物。我们还发现，与预期相反，PAINS警报的存在并未反映PubChem中所有检测试剂盒（包括AlphaScreen、荧光素酶、β-内酰胺酶或基于荧光的检测试剂盒）的任何升高的检测试剂盒活性趋势。此外，在3570种广泛测定但始终无活性的化合物（称为暗化学物质）中，存在109种疼痛警报。最后，我们观察到87种FDA批准的小分子药物含有PAINS警报，并分析了它们的生物测定活性。基于对非专利化合物库中PAINS警报的详细分析，我们警告不要盲目使用PAINS过滤器来检测和分类可能存在PAINS责任的化合物，并建议仅通过进行正交实验得出此类结论。
The use of substructural alerts to identify Pan-Assay INterference compoundS (PAINS) has become a common component of the triage process in biological screening campaigns. These alerts, however, were originally derived from a proprietary library tested in just six assays measuring protein–protein interaction (PPI) inhibition using the AlphaScreen detection technology only; moreover, 68% (328 out of the 480 alerts) were derived from four or fewer compounds. In an effort to assess the reliability of these alerts as indicators of pan-assay interference, we performed a large-scale analysis of the impact of PAINS alerts on compound promiscuity in bioassays using publicly available data in PubChem. We found that the majority (97%) of all compounds containing PAINS alerts were actually infrequent hitters in AlphaScreen assays measuring PPI inhibition. We also found that the presence of PAINS alerts, contrary to expectations, did not reflect any heightened assay activity trends across all assays in PubChem including AlphaScreen, luciferase, beta-lactamase, or fluorescence-based assays. In addition, 109 PAINS alerts were present in 3570 extensively assayed, but consistently inactive compounds called Dark Chemical Matter. Finally, we observed that 87 small molecule FDA-approved drugs contained PAINS alerts and profiled their bioassay activity. Based on this detailed analysis of PAINS alerts in nonproprietary compound libraries, we caution against the blind use of PAINS filters to detect and triage compounds with possible PAINS liabilities and recommend that such conclusions should be drawn only by conducting orthogonal experiments.