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A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.

ABSTRACT: Coronavirus disease-2019 (COVID-19) has become a major global epidemic. Facilitated by HTS² technology, we evaluated the effects of 578 herbs and all 338 reported anti-COVID-19 TCM formulae on cytokine storm-related signaling pathways, and identified the key targets of the relevant pathways and potential active ingredients in these herbs. This large-scale transcriptional study innovatively combines HTS² technology with bioinformatics methods and computer-aided drug design. For the first time, it systematically explores the molecular mechanism of TCM in regulating the COVID-19-related cytokine storm, providing an important scientific basis for elucidating the mechanism of action of TCM in treating COVID-19.

SUBMITTER: Dai Y

PROVIDER: S-EPMC7803147 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.

Dai Yifei Y Qiang Weijie W Gui Yu Y Tan Xue X Pei Tianli T Lin Kequan K Cai Siwei S Sun Liang L Ning Guochen G Wang Jianxun J Guo Hongyan H Sun Yimin Y Cheng Jing J Xie Lan L Lan Xun X Wang Dong D

Science bulletin 20210112 9

Coronavirus disease-2019 (COVID-19) has become a major global epidemic. Facilitated by HTS<sup>2</sup> technology, we evaluated the effects of 578 herbs and all 338 reported anti-COVID-19 TCM formulae on cytokine storm-related signaling pathways, and identified the key targets of the relevant pathways and potential active ingredients in these herbs. This large-scale transcriptional study innovatively combines HTS<sup>2</sup> technology with bioinformatics methods and computer-aided drug design. ...[more]

PMID: 33457042

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Project description:Traditional Chinese medicines (TCMs) represent one form of complementary and alternative medicine. The popularity and complexity in production make them attractive and vulnerable to adulteration in stages ranging from planting to production. Adulteration refers to the addition of extraneous, improper, or inferior ingredients that should not be present in TCMs. To detect and combat adulterated TCMs, supplementary testing methods (STMs), which expand the capability of routine testing standards, have been applied in China since 2003. From 2003 to 2017, a total of 184 STMs for TCMs were approved by the Chinese national drug regulatory authority. By assessing these STMs, this research intends to identify those TCMs vulnerable to adulteration, to list common adulterants, and to characterize the techniques of analysis. The results show that adulteration of TCMs can be classified into three main categories: the addition of undeclared drugs/chemical substances, substitution with non-drug components, and the addition of foreign non-drug materials. The top five therapeutic areas of TCMs vulnerable to adulteration are diabetes, calm and sleep, sexual dysfunction, pain relief, and rheumatism. A total of 166 adulterants were detected in the adulterated TCM preparations and herbal products studied here, with 158 adulterants in TCM preparations and 43 in herbal products, with 35 adulterants in common. Each STM consists of different pharmaceutical analysis techniques, including tests for physical-chemical properties, chromatography, spectroscopic techniques, and mass spectrometry. The analytical methodology of STMs relies on the combination of these techniques, with HPLC ranking the highest percentage (76.1%) and physical-chemical techniques the lowest percentage (11.4%). This research shows that STMs have played a crucial role in combating adulterated TCMs. However, STMs represent merely a product testing-centered regulatory strategy. The inspection of cultivation and manufacturing processes should also be strengthened. More importantly, the awareness and self-discipline of TCM manufacturers in implementing good manufacturing practices and regulating the planting and cultivation of raw materials should be improved.

Project description:Experiential and sensory evaluation is an ancient method that remains important in the current quality control system of Traditional Chinese Medicines (TCMs). The process is rapid and convenient when evaluating the quality of crude materials in TCM markets. However, sensory evaluation has been met with skepticism because it is mainly based on experience and lacks a scientific basis. In this study, rhubarb was selected to demonstrate how color-based sensory evaluation could differentiate the quality of herbal medicines objectively. The colors of the rhubarb samples, expressed as RGB values, were obtained from different parts and forms of the plant, including the plant's surface, fracture surface color, and a powdered form with or without treatment with a color-developing reagent. We first divided the rhubarb samples into three grades based on the total content of five hydroxyanthraquinone derivatives, the major pharmacological components in rhubarb. Then, a three-layer back-propagation artificial neural network (BP-ANN), calibrated with selected training samples, was used to correlate the quality of the rhubarb with its color. The color of the rhubarb powder after coloration attained the highest accuracy (92.3%) in predicting the quality grade of the test samples with the established artificial neural networks. Finally, a standardized colorimetric grading scale was created based on the spatial distribution of the rhubarb samples in a two-dimensional chromaticity diagram according to the colors of the powdered rhubarb after color enhancement. By comparing the color between the scale and the tested samples, similar to performing a pH test with indicator paper, subjects without sensory evaluation experience could quickly determine the quality grade of rhubarb. This work illustrates the technical feasibility of the color-based grading of rhubarb quality and offers references for quantifying and standardizing the sensory evaluation of TCMs, foods and other products.

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A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.

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A large-scale transcriptional study reveals inhibition of COVID-19 related cytokine storm by traditional Chinese medicines.

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