[TCMATCOV--a bioinformatics platform to predict efficacy of TCM against COVID-19].

Abstract

There is urgent need to discover effective traditional Chinese medicine(TCM) for treating coronavirus disease 2019(COVID-19). The development of a bioinformatic tool is beneficial to predict the efficacy of TCM against COVID-19. Here we deve-loped a prediction platform TCMATCOV to predict the efficacy of the anti-coronavirus pneumonia effect of TCM, based on the interaction network imitating the disease network of COVID-19. This COVID-19 network model was constructed by protein-protein interactions of differentially expressed genes in mouse pneumonia caused by SARS-CoV and cytokines specifically up-regulated by COVID-19. TCMATCOV adopted quantitative evaluation algorithm of disease network disturbance after multi-target drug attack to predict potential drug effects. Based on the TCMATCOV platform, 106 TCM were calculated and predicted. Among them, the TCM with a high disturbance score account for a high proportion of the classic anti-COVID-19 prescriptions used by clinicians, suggesting that TCMATCOV has a good prediction ability to discover the effective TCM. The five flavors of Chinese medicine with a disturbance score greater than 1 are mainly spicy and bitter. The main meridian of these TCM is lung, heart, spleen, liver, and stomach meridian. The TCM related with QI and warm TCM have higher disturbance score. As a prediction tool for anti-COVID-19 TCM prescription, TCMATCOV platform possesses the potential to discovery possible effective TCM against COVID-19.

• Authors: Fei-Fei Guo, Yu-Qi Zhang, Shi-Huan Tang, Xuan Tang, He Xu, Zhong-Yang Liu, Rui-Li Huo, Dong Li, Hong-Jun Yang
• Journal: Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica (Zhongguo Zhong Yao Za Zhi) Vol. 45 Issue 10 Pg. 2257-2264 (May 2020) ISSN: 1001-5302 [Print] China
• PMID: 32495578 (Publication Type: Journal Article)

Chemical References

• Drugs, Chinese Herbal

Topics

• Animals
• Betacoronavirus
• COVID-19
• Computational Biology
• Coronavirus Infections
• Drugs, Chinese Herbal
• Humans
• Medicine, Chinese Traditional
• Mice
• Pandemics
• Pneumonia, Viral
• SARS-CoV-2