Identifying potential treatments of COVID-19 from Traditional Chinese Medicine (TCM) by using a data-driven approach

• Published in: Journal of ethnopharmacology 2020-08, Vol.258, p.112932-112932, Article 112932
• Main Authors: Ren, Xia, Shao, Xin-Xin, Li, Xiu-Xue, Jia, Xin-Hua, Song, Tao, Zhou, Wu-Yi, Wang, Peng, Li, Yang, Wang, Xiao-Long, Cui, Qing-Hua, Qiu, Pei-Ju, Zhao, Yan-Gang, Li, Xue-Bo, Zhang, Feng-Cong, Li, Zhen-Yang, Zhong, Yue, Wang, Zhen-Guo, Fu, Xian-Jun
• Format: Article
• Language: English
• Subjects: Betacoronavirus - drug effects; Chinese medicine (CM); Coronavirus Infections - drug therapy; Coronavirus Infections - virology; COVID-19; Data Mining; Drugs, Chinese Herbal - pharmacology; Drugs, Chinese Herbal - therapeutic use; Humans; Medicine, Chinese Traditional; Models, Molecular; Molecular docking; Network pharmacology; Pandemics; Plant Extracts; Pneumonia, Viral - drug therapy; Pneumonia, Viral - virology; Protein Conformation; SARS-CoV-2; Viral Proteins
• ISSN: 0378-8741; 1872-7573; 1872-7573
• DOI: 10.1016/j.jep.2020.112932

Traditional Chinese Medicine (TCM) has been widely used as an approach worldwide. Chinese Medicines (CMs) had been used to treat and prevent viral infection pneumonia diseases for thousands of years and had accumulated a large number of clinical experiences and effective prescriptions. This research aimed to systematically excavate the classical prescriptions of Chinese Medicine (CM), which have been used to prevent and treat Pestilence (Wenbing, Wenyi, Shiyi or Yibing) for long history in China, to obtain the potential prescriptions and ingredients to alternatively treat COVID-19. We developed the screening system based on data mining, molecular docking and network pharmacology. Data mining and association network were used to mine the high-frequency herbs and formulas from ancient prescriptions. Virtual screening for the effective components of high frequency CMs and compatibility Chinese Medicine was explored by a molecular docking approach. Furthermore, network pharmacology method was used to preliminarily uncover the molecule mechanism. 574 prescriptions were obtained from 96,606 classical prescriptions with the key words to treat “Warm diseases (Wenbing)”, “Pestilence (Wenyi or Yibing)” or “Epidemic diseases (Shiyi)”. Meanwhile, 40 kinds of CMs, 36 CMs-pairs, 6 triple-CMs-groups existed with high frequency among the 574 prescriptions. Additionally, the key targets of SARS-COV-2, namely 3CL hydrolase (Mpro) and angiotensin-converting enzyme 2(ACE2), were used to dock the main ingredients from the 40 kinds by the LigandFitDock method. A total of 66 compounds components with higher frequency were docked with the COVID-19 targets, which were distributed in 26 kinds of CMs, among which Gancao (Glycyrrhizae Radix Et Rhizoma), HuangQin (Scutellariae Radix), Dahuang (Rhei Radix Et Rhizome) and Chaihu (Bupleuri Radix) contain more potential compounds. Network pharmacology results showed that Gancao (Glycyrrhizae Radix Et Rhizoma) and HuangQin (Scutellariae Radix) CMs-pairs could also interact with the targets involving in immune and inflammation diseases. These results we obtained probably provided potential candidate CMs formulas or active ingredients to overcome COVID-19. Prospectively, animal experiment and rigorous clinic studies are needed to confirm the potential preventive and treat effect of these CMs and compounds. [Display omitted]