[Analysis of potential role of Chinese classic prescriptions in treatment of COVID-19 based on TCMATCOV platform].

With the global outbreak of coronavirus disease 2019(COVID-19), screening of effective drugs has became the emphasis of research today; furthermore, screening of Chinese classic prescriptions has became one of the directions for drug development. This study analyzed the application of classic prescriptions in the diagnosis and treatment schemes based on the Diagnosis and Treatment Schemes for Coronavirus Disease at the country, provincial and municipal levels, and further explored its disrobing effect on COVID-19 disease severe phase network, and selected representative prescriptions for core target screening and gene enrichment analysis, so as to reveal its mechanism of action. Among them, 13 prescriptions were found to be used for 10 times or more, including Maxing Shigan Tang, Yinqiao San, Shengjiang San, Dayuan Drink, Xuanbai Chengqi Decoction. In addition, the COVID-19 efficacy prediction analysis platform(TCMATCOV platform) was used to calculate the network disturbances of the Chinese classic prescriptions involved. Based on the prediction results, 68 classic prescriptions were assessed on the COVID-19 disease network robustness disturbance. The average disturbance scores for the interaction confidence scores were ranked to be 0.4, 0.5, and 0.6 from the highest to the lowest. There were 7 prescriptions with a score of 17 or more, and 50 prescriptions with a score of 13 or more. Among them, the top three prescriptions were Ganlu Xiaodu Dan(18.19), Lengxiao Wan(17.74), and Maxing Shigan Tang(17.62). After further mining the action targets of these three prescriptions, it was found that COVID-19 disease-specific factors Ccl2, IL10, IL6 and TNF were all the targets of three prescriptions. Through the enrichment analysis of the biological processes of the core targets, it was found that the three prescriptions may prevent the development of the disease by affecting cell-to-cell adhesion, cytokine-mediated signaling pathway, and chronic inflammatory responses to COVID-19 at the severe phase. This study showed that the TCMATCOV platform could evaluate the disturbance effect of different prescriptions on the COVID-19 disease network, and predict potential effectiveness based on the robustness of drug-interfered pneumonia disease networks, so as to provide a reference for further experiments or clinical verification.

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

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.

[Treatment of COVID-19 guided by holistic view of traditional Chinese medicine--therapy aimed at both viral and host].

The global outbreak of coronavirus disease 2019(COVID-19) has further spread, and there is an increasing number of confirmed cases in many countries. On February 28, 2020 of Geneva time, the World Health Organization has raised global risk level to the very high level in view of outbreak of COVID-19. Since some patients' condition appeared to deteriorate rapidly after infection of this 2019 novel coronavirus(2019-nCoV), a variety of treatments should be considered. Holistic view and syndrome differentiation are the two characteristics of traditional Chinese medicine(TCM). Therefore, under the guidance of the holistic view, syndrome diffe-rentiation of TCM has achieved good effects in the treatment of COVID-19. This treatment mainly aimed at eliminating pathogens and strengthening overall health, regulating the balance of body and coordinating various of functions of Zangfu organs. In addition, modern medical proposes host-directed therapy(HDT), a strategy aims to interfere with host cell mechanism, enhance immune responses, and reduce exacerbated inflammation. To some extent, the combined application of HDT and antiviral therapy is highly consistent with the therapeutic concept of the holistic view of TCM. Therefore, under the guidance of the holistic view, syndrome differentiation of TCM uses treatments, such as clearing heat, detoxification, relieving asthma, clearing damp and phlegm, together with Lianhua Qingwen Capsules, Maxing Shigan Decoction, and Haoqin Qingdan Decoction under the guidance of these therapeutic methods. These therapeutic methods and prescriptions intervened with both virus and host at the same time in the treatment of COVID-19, which has important implications for the effective clinical treatment of COVID-19.

[Intervention mechanism of Qingwen Baidu Yin on cytokine storm based on network pharmacology].

The aim of this paper was to explore the intervention mechanism of Qingwen Baidu Yin in cytokine storm based on network pharmacology. TCMSP and TCMIP V2.0 server were used to predict all chemical components and action targets of Qingwen Baidu Yin. Diseases that could be treated by Qingwen Baidu Yin were predicted through Enrichr database. A compound target interaction(PPI) network diagram was constructed using STRING 11.0. OmicShare was used to analyzed the gene ontology(GO) enrichment and enrichment of the Kyoto encyclopedia of genes and genomes(KEGG) pathway of core targets. Component-target-path network diagram was constructed with Cytoscape 3.6.0 software. After analysis of the database, 267 compounds were screened for Qingwen Baidu Yin, involving 1 450 targets, and a protein interaction network was constructed. Total 219 core target proteins were predicted, such as NFKB1, STAT1, RAF1, IL2, JAK1, IL6, TNF, BCL2 and other important targets, and 221 core target pathways were enriched, including cancer pathway, Kaposi's sarcoma-associated herpes virus infection, chemokine signal pathway, PI3 K-AKT signal pathway, EB virus infection, virus carcinogenesis and T cell receptor signaling pathways, a collection of which were highly related to cytokine storms. GO annotation analysis suggested that Qingwen Baidu Yin Decoction may exert therapeutic effects by regulating protein phosphorylation, cell response to cytokine stimulation, cell proliferation, inflammatory response, transmembrane receptor protein tyrosine kinase signaling pathway, and cytokine-mediated signaling pathways. This study revealed potential active components of Qingwen Baidu Yin in defending against cytokine storm and its possible mechanism of action, and provided theoretical basis and technical support for further clinical application of this prescription.