ABSTRACT
Background: The outbreak of coronavirus disease 2019 (COVID-19) has posed a huge threat to human health. However, little is known regarding the risk factors associated with COVID-19 severity. We aimed to explore early-stage disease risk factors associated with eventual disease severity. Methods: This study enrolled 486 hospitalized, non-intensive care unit (ICU)-admitted adult patients with COVID-19 (age ≥ 18 years) treated at Wuhan Jinyintan Hospital, who were divided into three groups according to disease severity. The demographic, clinical, and laboratory data at admission and clinical outcomes were compared among severity groups, and the risk factors for disease severity were identified by multiple regression analysis. Results: Of 486 patients with COVID-19, 405 (83.33%) were discharged, 33 (6.71%) died outside of the ICU, and 48 (7.20%) were still being treated in the ICU by the time the study period ended. Significant differences in age, lymphocyte counts, and the levels of procalcitonin, aspartate aminotransferase, and D-dimer (P < 0.001 for all) among the three groups. Further analysis showed that older age, decreased lymphocyte counts, and increased procalcitonin, aspartate aminotransferase, and D-dimer levels were significantly associated with disease progression. Conclusion: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may impair the immune system, the blood coagulation system, and hepatic and cardiac function. Some clinical characteristics and laboratory findings can help identify patients with a high risk of disease severity, which can be significant for appropriate resource allocation during the COVID-19 pandemic.
ABSTRACT
Chlorogenic acid (CGA) is a potential inhibitor of Coronavirus Disease 2019 (COVID-19). ACE2 and its co-expressed proteins are SARS-CoV-2 receptors, which have been linked to SARS-CoV-2 infection and considered as the key target of SARS-CoV-2 in entering target cells. Here, network pharmacology was used to investigate the mechanism by which CGA affected COVID-19. A total of 70 potential targets related to the treatment of COVID-19 were obtained, among which NFE2L2, PPARG, ESR1, ACE, IL6, and HMOX1 might be the main potential targets. Finally, CGA and potential target proteins were scored by molecular docking, and the prediction results of network pharmacology were preliminarily verified. Moreover, CGA had potential anti-SARS-CoV-2 activity via integrating three common receptors in clinical practice compared with clinical trial drugs registered for the treatment of COVID-19, as shown by molecular docking. The mechanism of CGA against COVID-19 was initially investigated using network pharmacology, followed by molecular docking.
Subject(s)
Biological Products , COVID-19 Drug Treatment , Drugs, Chinese Herbal , Chlorogenic Acid/pharmacology , Drugs, Chinese Herbal/pharmacology , Humans , Molecular Docking Simulation , Network Pharmacology , SARS-CoV-2ABSTRACT
Objective: To investigate the mechanism of Qingkailing Injection in the treatment of coronavirus disease 2019 (COVID-19). Methods: The active components and target proteins of Gardeniae Fructus, Isatidis Radix, Lonicerae Japonicae Flos, and other materials in Qingkailing Injection were obtained by means of literature search and TCMSP. Uniprot database was used to search the target genes corresponding to the active ingredients, and Cytoscape 3.7.2 was used to construct the drug-compound-target network. The enrichment analysis of KEGG pathway was carried out with the help of DAVID database to predict its mechanism. Core active components and potential targets of anti-COVID-19 drugs were verified by molecular docking. Results: The drug-compound- target network consisted of five drugs, 62 compounds and 70 targets. The KEGG pathway enrichment analysis included 41 signaling pathways (P < 0.05), which were mainly involved in cell apoptosis, Fc epsilon RI signaling pathway, TNF signaling pathway, etc. Molecular docking results showed that acacetin and syrigin had strong affinity with potential targets of anti-COVID-19 drugs. Conclusion: In this study, the effect of Qingkailing Injection has the characteristics of multiple components, multiple targets and multiple pathways. The active component, acacetin, can regulate the apoptosis pathway and TNF pathway by acting on CASP3, CASP8, FASLG, and other targets, so as to realize the potential therapeutic effect on COVID-19.