Analysis of medication regularity and pharmacodynamic characteristics of traditional Chinese medicine treatment in 444 severe cases of COVID-19 / 中国中药杂志

The coronavirus disease 2019(COVID-19) is developing rapidly and posing great threat to public health. There is no effective intervention for the severe patients, and their prognosis is poor. It is worth noting that in the fight against COVID-19, China has always put equal emphasis on both Chinese and Western medicine. Traditional Chinese medicine has played an important role in the whole process. It is of great significance to discuss the rules and characteristics of the prescription of traditional Chinese medicine in the treatment of COVID-19. In this study, information was collected from 444 severe COVID-19 patients who were admitted to a hospital designated to treat patients with severe COVID-19 in Wuhan before March 20, 2020. We collected traditional Chinese medicine prescriptions for patients with severe COVID-19, referred to Chinese Pharmacopoeia to standardize the names of traditional Chinese medicine, and extract the property, flavor and channel tropism of traditional Chinese medicines to analyze the rules of the prescriptions. IBM SPSS Modeler 18.0 software was used to conduct correlation analysis of traditional Chinese medicine. Effective traditional Chinese medicines against COVID-19 was identified by the TCMATCOV platform. In the end, 1 532 effective prescriptions were included. Among them, the high-frequency drugs are Poria, Astragali Radix, Pogostemonis Herba, Armeniacae Semen Amarum, Atractylodis Macrocephalae Rhizoma, Pinelliae Rhizoma, Glycyrrhizae Radix et Rhizoma, Magnoliae Officinalis Cortex, Ephedrae Herba, Cinna-momi Ramulus. Most of the drugs have the following functions: resolving dampness, replenishing deficiency, resolving phlegm, cough, and asthma. The core combinations are Pogostemonis Herba-Poria, Astragali Radix-Pogostemonis Herba-Poria, Amomi Fructus-Poria, Amomi Fructus-Pogostemonis Herba, Amomi Fructus-Astragali Radix. The majority of the medicines are with cold and warm properties, and the proportions are 41.03% and 38.46%, respectively. The medicinal flavors are mainly concentrated in sweet and bitter, and the proportions are 34.71% and 30.58%, respectively. The meridian of the drug is more into the lung, stomach and spleen, with lung accounting for 22.87%. From the analysis of high-frequency drugs to the core combinations, one can see that the main treatment principle for severe COVID-19 is to remove internal and external dampness, protect the spleen and stomach, remove evil energy, and support righteousness. TCMATCOV platform was used to calculate the network disturbances of the high-frequency drugs. It was found that the traditional Chinese medicine with a high disturbance score accounted for a high proportion of the classic anti-COVID-19 prescriptions used by clinicians. Among them, the drugs with top scores are Ephedrae Herba, Citri Reticulatae Pericarpium, Eupatorii Herba, Platycodonis Radix, Cinnamomi Ramulus, Astragali Radix, Magnoliae Officinalis Cortex, Atractylodis Macrocephalae Rhizoma, Pogostemonis Herba, Scutellariae Radix. After a further exploration of the action targets, it was showed that disease-specific factor TNF was the target of the above ten drugs, and traditional Chinese medicine can exert anti-inflammatory and immune-modulating effects.

Analysis of potential role of Chinese classic prescriptions in treatment of COVID-19 based on TCMATCOV platform / 中国中药杂志

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.