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从两个类先导化合物库的性能分析中定位筛选命中的最佳点和评估通用分析干扰滤光片。

Locating sweet spots for screening hits and evaluating pan-assay interference filters from the performance analysis of two lead-like libraries.

机构信息

Drug Discovery Unit, Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee , Dow Street, Dundee DD1 5EH, U.K.

出版信息

J Chem Inf Model. 2013 Mar 25;53(3):534-44. doi: 10.1021/ci300382f. Epub 2013 Mar 4.

Abstract

The efficiency of automated compound screening is heavily influenced by the design and the quality of the screening libraries used. We recently reported on the assembly of one diverse and one target-focused lead-like screening library. Using data from 15 enzyme-based screenings conducted using these libraries, their performance was investigated. Both libraries delivered screening hits across a range of targets, with the hits distributed across the entire chemical space represented by both libraries. On closer inspection, however, hit distribution was uneven across the chemical space, with enrichments observed in octants characterized by compounds at the higher end of the molecular weight and lipophilicity spectrum for lead-like compounds, while polar and sp(3)-carbon atom rich compounds were underrepresented among the screening hits. Based on these observations, we propose that screening libraries should not be evenly distributed in lead-like chemical space but be enriched in polar, aliphatic compounds. In conjunction with variable concentration screening, this could lead to more balanced hit rates across the chemical space and screening hits of higher ligand efficiency will be captured. Apart from chemical diversity, both screening libraries were shown to be clean from any pan-assay interference (PAINS) behavior. Even though some compounds were flagged to contain PAINS structural motifs, some of these motifs were demonstrated to be less problematic than previously suggested. To maximize the diversity of the chemical space sampled in a screening campaign, we therefore consider it justifiable to retain compounds containing PAINS structural motifs that were apparently clean in this analysis when assembling screening libraries.

摘要

自动化化合物筛选的效率受到所使用的筛选库的设计和质量的极大影响。我们最近报道了一个多样化的和一个靶向的类先导化合物筛选库的组装。使用这两个文库进行的 15 个酶基筛选的数据,对它们的性能进行了研究。这两个文库都在一系列靶点中提供了筛选命中,命中分布在两个文库所代表的整个化学空间中。然而,经过仔细检查,命中分布在化学空间中并不均匀,在特征为分子量和类先导化合物亲脂性较高的化合物的八角形区域观察到富集,而极性和富含 sp(3)-碳原子的化合物在筛选命中中代表性不足。基于这些观察结果,我们提出筛选库不应在类先导化合物化学空间中均匀分布,而应富含极性、脂肪族化合物。与可变浓度筛选相结合,这可能会导致整个化学空间的命中率更加平衡,并且会捕获到更高配体效率的命中。除了化学多样性,这两个筛选库都显示出没有任何 pan-assay interference (PAINS) 行为。尽管有些化合物被标记为含有 PAINS 结构基序,但其中一些基序的问题比以前的建议要小。为了最大限度地增加筛选活动中采样的化学空间的多样性,因此,当组装筛选库时,我们认为保留那些在这种分析中明显干净的含有 PAINS 结构基序的化合物是合理的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a451/3739413/1db74f30edf0/ci-2012-00382f_0002.jpg

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