A review on computational approaches that support the researches on traditional Chinese medicines (TCM) against COVID-19.

BACKGROUND: COVID-19 highly caused contagious infections and massive deaths worldwide as well as unprecedentedly disrupting global economies and societies, and the urgent development of new antiviral medications are required. Medicinal herbs are promising resources for the discovery of prophylactic candidate against COVID-19. Considerable amounts of experimental efforts have been made on vaccines and direct-acting antiviral agents (DAAs), but neither of them was fast and fully developed. PURPOSE: This study examined the computational approaches that have played a significant role in drug discovery and development against COVID-19, and these computational methods and tools will be helpful for the discovery of lead compounds from phytochemicals and understanding the molecular mechanism of action of TCM in the prevention and control of the other diseases. METHODS: A search conducting in scientific databases (PubMed, Science Direct, ResearchGate, Google Scholar, and Web of Science) found a total of 2172 articles, which were retrieved via web interface of the following websites. After applying some inclusion and exclusion criteria and full-text screening, only 292 articles were collected as eligible articles. RESULTS: In this review, we highlight three main categories of computational approaches including structure-based, knowledge-mining (artificial intelligence) and network-based approaches. The most commonly used database, molecular docking tool, and MD simulation software include TCMSP, AutoDock Vina, and GROMACS, respectively. Network-based approaches were mainly provided to help readers understanding the complex mechanisms of multiple TCM ingredients, targets, diseases, and networks. CONCLUSION: Computational approaches have been broadly applied to the research of phytochemicals and TCM against COVID-19, and played a significant role in drug discovery and development in terms of the financial and time saving.

Identification of anti-inflammatory compounds from Zhongjing formulae by knowledge mining and high-content screening in a zebrafish model of inflammatory bowel diseases.

BACKGROUND: Inflammatory bowel diseases (IBD) are chronic relapsing intestinal inflammations with increasing global incidence, and new drug development remains in urgent demand for IBD management. To identify effective traditional Chinese medicine (TCM) formulae and compounds in IBD treatment, we innovatively combined the techniques of knowledge mining, high-content screening and high-resolution mass spectrometry, to conduct a systematic screening in Zhongjing formulae, which is a large collection of TCM prescriptions with most abundant clinical evidences. METHODS: Using Word2vec-based text learning, the correlations between 248 Zhongjing formulae and IBD typical symptoms were analyzed. Next, from the top three formulae with predicted relationship with IBD, TCM fractions were prepared and screened on a transgenic zebrafish IBD model for their therapeutic effects. Subsequently, the chemical compositions of the fraction hits were analyzed by mass spectrometry, and the major compounds were further studied for their anti-IBD effects and potential mechanisms. RESULTS: Through knowledge mining, Peach Blossom Decoction, Pulsatilla Decoction, and Gegen Qinlian Decoction were predicted to be the three Zhongjing formulae mostly related to symptoms typical of IBD. Seventy-four fractions were prepared from the three formulae and screened in TNBS-induced zebrafish IBD model by high-content analysis, with the inhibition on the intestinal neutrophil accumulation and ROS level quantified as the screening criteria. Six herbal fractions showed significant effects on both pathological processes, which were subsequently analyzed by mass spectrometry to determine their chemical composition. Based on the major compounds identified by mass spectrometry, a second-round screen was conducted and six compounds (palmatine, daidzin, oroxyloside, chlorogenic acid, baicalin, aesculin) showed strong inhibitory effects on the intestinal inflammation phenotypes. The expression of multiple inflammatory factors, including il1ß, clcx8a, mmp and tnfα, were increased in TNBS-treated fish, which were variously inhibited by the compounds, with aesculin showing the most potent effects. Moreover, aesculin and daidzin also upregulated e-cadherin's expression. CONCLUSION: Taken together, we demonstrated the regulatory effects of several TCM formulae and their active compounds in the treatment of IBD, through a highly efficient research strategy, which can be applied in the discovery of effective TCM formulae and components in other diseases.

Ononin, sec-O-ß-d-glucosylhamaudol and astragaloside I: antiviral lead compounds identified via high throughput screening and biological validation from traditional Chinese medicine Zhongjing formulary.

Traditional medicine (TM) is a valuable source for drug discovery. The knowledge in healing traditions has led to the success of some of the best-known drugs. However, the concept of ancient medical knowledge, such as herbal remedies and their therapeutic experience is rarely used in the current methodologies for developing therapeutics from TM. As a result, the screening procedure of TM compounds remains tough and labor-intensive. This study aimed to develop a new strategy that is capable of efficiently identifying antiviral leads from complex traditional Chinese medicine (TCM) by integrating knowledge from ancient healing practices with luciferase-based high-throughput screening (HTS). 'Shanghan Zabing Lun', an ancient TCM treatise which contains over 200 formulae was selected for knowledge mining based on its antiviral activity. Thirty formulae were rationally selected and utilized for the preparation of a 1306-fraction herbal formulae extract library by standardized chromatographic fractionation. The antiviral activity of the library was screened on a HEK293T cell model carrying a luciferase-driven interferon stimulated response element (ISRE). Hit compounds were further identified using liquid chromatography mass spectrometry analysis, and the mechanism of action of which were preliminarily explored through western blotting and immunofluorescence. A total of 18 fractions and 3 compounds were found activating ISRE. The three compounds, namely ononin, sec-O-ß-d-glucosylhamaudol and astragaloside I could activate p65 phosphorylation and nuclear translocation. By doing so, a new strategy termed Knowledge-Based High Throughput Screening (KB-HTS) has been established, which provides an alternative approach to unearth antiviral lead compounds from TM. This new discovery pipeline can expedite the discovery process by improving dereplication and lead prioritization strategies, which is valuable for novel lead discovery from traditional medicine.