TCMATCOV--a bioinformatics platform to predict efficacy of TCM against COVID-19.
10.19540/j.cnki.cjcmm.20200312.401
- Author:
Fei-Fei GUO
1
;
Yu-Qi ZHANG
2
;
Shi-Huan TANG
1
;
Xuan TANG
1
;
He XU
1
;
Zhong-Yang LIU
3
;
Rui-Li HUO
4
;
Dong LI
3
;
Hong-Jun YANG
4
Author Information
1. Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700, China.
2. Hebei University Baoding 071002, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center,Beijing) Beijing 102206, China.
3. State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center,Beijing) Beijing 102206, China.
4. China Academy of Chinese Medical Sciences Beijing 100700, China.
- Publication Type:Journal Article
- Keywords:
coronavirus disease 2019(COVID-19);
network pharmacology;
pharmacodynamic prediction;
traditional Chinese medicine
- MeSH:
Animals;
Betacoronavirus;
Computational Biology;
Coronavirus Infections;
Drugs, Chinese Herbal;
Humans;
Medicine, Chinese Traditional;
Mice;
Pandemics;
Pneumonia, Viral
- From:
China Journal of Chinese Materia Medica
2020;45(10):2257-2264
- CountryChina
- Language:Chinese
-
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.
