Böcker Alexander, Bonneau Pierre R, Edwards Paul J
Evotec AG, Hamburg, Germany.
J Biomol Screen. 2011 Aug;16(7):765-74. doi: 10.1177/1087057111407763. Epub 2011 Jun 16.
Frequent hitters are compounds that are detected as a "hit" in multiple high-throughput screening (HTS) assays. Such behavior is specific (e.g., target family related) or unspecific (e.g., reactive compounds) or can result from a combination of such behaviors. Detecting such hits while predicting the underlying reason behind their promiscuous behavior is desirable because it provides valuable information not only about the compounds themselves but also about the assay methodology and target classes at hand. This information can also greatly reduce cost and time during HTS hit profiling. The present study exemplifies how to mine large HTS data repositories, such as the one at Boehringer Ingelheim, to identify frequent hitters, gain further insights into the causes of promiscuous behavior, and generate models for predicting promiscuous compounds. Applications of this approach are demonstrated using two recent large-scale HTS assays. The authors believe this analysis and its concrete applications are valuable tools for streamlining and accelerating decision-making processes during the course of hit discovery.
频繁命中化合物是指在多个高通量筛选（HTS）试验中被检测为“命中”的化合物。这种行为可能是特异性的（例如，与靶标家族相关）或非特异性的（例如，反应性化合物），也可能是这些行为的组合导致的。在预测其混杂行为背后的潜在原因的同时检测到这些命中是很有必要的，因为这不仅能提供有关化合物本身的有价值信息，还能提供有关手头的试验方法和靶标类别的信息。这些信息还可以大大降低高通量筛选命中分析过程中的成本和时间。本研究举例说明了如何挖掘大型高通量筛选数据存储库，例如勃林格殷格翰公司的数据库，以识别频繁命中化合物，进一步深入了解混杂行为的原因，并生成预测混杂化合物的模型。使用最近的两项大规模高通量筛选试验展示了这种方法的应用。作者认为，这种分析及其具体应用是在命中发现过程中简化和加速决策过程的有价值工具。
