ABSTRACT
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.
Subject(s)
COVID-19 Drug Treatment , Drugs, Chinese Herbal , Hepatitis C, Chronic , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Artificial Intelligence , China , Drugs, Chinese Herbal/chemistry , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/therapeutic use , Hepatitis C, Chronic/drug therapy , Humans , Medicine, Chinese Traditional , Molecular Docking Simulation , Phytochemicals/pharmacologyABSTRACT
BACKGROUND: More than 210,000 medical workers have fought against the outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei in China since December 2019. However, the prevalence of mental health problems in frontline medical staff after fighting COVID-19 is still unknown. METHODS: Medical workers in Wuhan and other cities in Hubei Province were invited to participate a cross-sectional and convenience sampling online survey, which assessed the prevalence of anxiety, insomnia, depression, and post-traumatic stress disorder (PTSD). RESULTS: A total of 1,091 responses (33% male and 67% female) were valid for statistical analysis. The prevalence was anxiety 53%, insomnia 79%, depression 56%, and PTSD 11%. Healthcare workers in Wuhan were more likely to face risks of anxiety (56% vs. 52%, P = 0.03) and PTSD (15% vs. 9%, P = 0.03) than those in other cities of Hubei. In terms of educational attainment, those with doctoral and masters' (D/M) degrees may experience more anxiety (median of 7.0, [interquartile range (IQR) 2.0-8.5] vs. median 5.0 [IQR 5.0-8.0], P = 0.02) and PTSD (median 26.0 [IQR 19.5-33.0] vs. median 23.0 [IQR 19.0-31.0], P = 0.04) than those with lower educational degrees. CONCLUSIONS: The mental problems were an important issue for the healthcare workers after COVID-19. Thus, an early intervention on such mental problems is necessary for healthcare workers.