PDF(Pubmed)
Abstract：
The chemical complexity of traditional Chinese medicines (TCMs) makes the active and functional annotation of natural compounds challenging. Herein, we developed the TCMs-Compounds Functional Annotation platform (TCMs-CFA) for large-scale predicting active compounds with potential mechanisms from TCM complex system, without isolating and activity testing every single compound one by one. The platform was established based on the integration of TCMs knowledge base, chemome profiling, and high-content imaging. It mainly included: (1) selection of herbal drugs of target based on TCMs knowledge base; (2) chemome profiling of TCMs extract library by LC‒MS; (3) cytological profiling of TCMs extract library by high-content cell-based imaging; (4) active compounds discovery by combining each mass signal and multi-parametric cell phenotypes; (5) construction of functional annotation map for predicting the potential mechanisms of lead compounds. In this stud TCMs with myocardial protection were applied as a case study, and validated for the feasibility and utility of the platform. Seven frequently used herbal drugs (Ginseng, etc.) were screened from 100,000 TCMs formulas for myocardial protection and subsequently prepared as a library of 700 extracts. By using TCMs-CFA platform, 81 lead compounds, including 10 novel bioactive ones, were quickly identified by correlating 8089 mass signals with 170,100 cytological parameters from an extract library. The TCMs-CFA platform described a new evidence-led tool for the rapid discovery process by data mining strategies, which is valuable for novel lead compounds from TCMs. All computations are done through Python and are publicly available on GitHub.
摘要：
中药（TCMs）的化学复杂性使天然化合物的活性和功能注释具有挑战性。在这里，我们开发了中药-化合物功能注释平台（TCMs-CFA），用于从中药复杂系统中大规模预测具有潜在机制的活性化合物，没有分离和活性测试每一个单一的化合物。该平台是基于TCM知识库的集成而建立的，化学组分析，和高含量的成像。主要包括：（1）基于TCM知识库选择目标草药；（2）通过LC-MS对TCM提取物库进行化学组分析；（3）通过基于高含量细胞的成像对TCM提取物库进行细胞学分析；（4）通过结合每个质量信号和多参数细胞表型来发现活性化合物；（5）构建功能注释图，以预测先导化合物的潜在机制。在这项具有心肌保护作用的TCM作为案例研究，并验证了该平台的可行性和实用性。七种常用的草药（人参，等。）从100,000个TCM配方中筛选用于心肌保护，随后制备为700种提取物的文库。通过使用TCM-CFA平台，81个铅化合物，包括10个新的生物活性物质，通过将8089质量信号与提取物文库中的170,100个细胞学参数相关联来快速鉴定。TCMs-CFA平台描述了一种新的证据导向工具，用于通过数据挖掘策略进行快速发现过程，这对于来自TCM的新型先导化合物是有价值的。所有计算都是通过Python完成的，并且可以在GitHub上公开获得。
