Real-Time Biological Annotation of Synthetic Compounds.
Real-Time Biological Annotation of Synthetic Compounds.
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DOI：
10.1021/jacs.6b04614
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发表时间：
2016-07-20
影响因子：
15
通讯作者：
Schreiber SL
中科院分区：
文献类型：
--
作者：
Gerry CJ;Hua BK;Wawer MJ;Knowles JP;Nelson SD Jr;Verho O;Dandapani S;Wagner BK;Clemons PA;Booker-Milburn KI;Boskovic ZV;Schreiber SL
有机化学家能够合成的分子数量和化学复杂性比以往任何时候都多。然而，这些化合物中的大多数都没有在生物系统中进行测试，而那些测试过的化合物往往在化学家将结果纳入合成计划之后很久才进行测试。我们建议使用高维的“多重”检测，这是能够在一个实验中测量数以千计的细胞功能，注释快速和廉价的新合成的化合物的生物活性。这种容易获得且廉价的“实时”谱分析方法可以以前瞻性的方式用于促进例如富含生物活性物质的性能多样化的小分子文库的有效构建。在这里，我们证明了这一概念，通过合成10个三元组的结构异构化合物通过复杂性产生的光化学和热重排和测量化合物诱导的细胞形态的变化，通过基于成像的“细胞绘画”测定。我们的研究结果表明，实时生物注释可以通过阐明与生物活性相关的趋势来通知优化工作和文库合成，如果只考虑化学结构，则难以预测生物活性。我们预计，探针和药物的发现将受益于使用优化工作和图书馆，实现这种方法。
Organic chemists are able to synthesize molecules in greater number and chemical complexity than ever before. Yet, a majority of these compounds go untested in biological systems, and those that do are often tested long after the chemist can incorporate the results into synthetic planning. We propose the use of high-dimensional “multiplex” assays, which are capable of measuring thousands of cellular features in one experiment, to annotate rapidly and inexpensively the biological activities of newly synthesized compounds. This readily accessible and inexpensive “real-time” profiling method can be used in a prospective manner to facilitate, for example, the efficient construction of performance-diverse small-molecule libraries that are enriched in bioactives. Here, we demonstrate this concept by synthesizing ten triads of constitutionally isomeric compounds via complexity-generating photochemical and thermal rearrangements and measuring compound-induced changes in cellular morphology via an imaging-based “cell painting” assay. Our results indicate that real-time biological annotation can inform optimization efforts and library syntheses by illuminating trends relating to biological activity that would be difficult to predict if only chemical structure were considered. We anticipate that probe and drug discovery will benefit from the use of optimization efforts and libraries that implement this approach.