RESUMEN
Cytokine storm is a phenomenon whereby the overreaction of the human immune system leads to the release of inflammatory cytokines, which can lead to multiple organ dysfunction syndrome. At present, the existing drugs for the treatment of cytokine storm have limited efficacy and severe adverse effects. Here, we report a lymphatic targeting self-microemulsifying drug delivery system containing baicalein to effectively inhibit cytokine storm. Baicalein self-microemulsion with phospholipid complex as an intermediate carrier (BAPC-SME) prepared in this study could be spontaneously emulsified to form 12-nm oil-in-water nanoemulsion after administration. And then BAPC-SME underwent uptake by enterocyte through endocytosis mediated by lipid valve and clathrin, and had obvious characteristics of mesenteric lymph node targeting distribution. Oral administration of BAPC-SME could significantly inhibit the increase in plasma levels of 14 cytokines: TNF-α, IL-6, IFN-γ, MCP-1, IL-17A, IL-27, IL-1α, GM-CSF, MIG, IFN-ß, IL-12, MIP-3α, IL-23, and RANTES in mice experiencing systemic cytokine storm. BAPC-SME could also significantly improve the pathological injury and inflammatory cell infiltration of lung tissue in mice experiencing local cytokine storm. This study does not only provide a new lymphatic targeted drug delivery strategy for the treatment of cytokine storm but also has great practical significance for the clinical development of baicalein self-microemulsion therapies for cytokine storm.
RESUMEN
Objective: Shenling Baizhu San (SBS) was selected as the regimen for the treatment of COVID-19 in Guangdong Province. It is mainly used for the convalescent treatment of COVID-19 patients with deficiency of both lung and spleen. In this study, we aimed to explore the mechanism of SBS in the treatment of COVID-19 through network pharmacology combined with molecular docking. Methods: The targets of active components of SBS were collected through Traditional Chinese Medicine Systems Pharmacology (TCMSP) and ETCM databases. Using the Genecards, TTD, OMIM and other databases, the targets of COVID-19 were determined. The next step was to use a string database to build a protein?protein interactions (PPI) network between proteins, and use David database to perform gene ontology (GO) function enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct the active ingredients-core target-signaling pathway network, and finally the active ingredients of SBS were molecularly docked with the core targets to predict the mechanism of SBS in the treatment of COVID-19. Results: A total of 177 active compounds, 43 core targets and 58 signaling pathways were selected. Molecular docking results showed that the binding energies of the top six active components and the targets were all less than ?5?kcal/MOL. Conclusion: The potential mechanism of action of SBS in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with IL6, DPP4, PTGS2, PTGS1 and TNF.
RESUMEN
In the process of fighting against COVID-19 in China, Xingnaojing injection has been recommended for its clinical treatment, but the information about its active components and mechanism is still lacking. Therefore, in this work, using network pharmacology and molecular docking, we studied the active components of Xingnaojing injection having anti-COVID-19 properties. Using the DL parameter, TCMSP and CNKI databases were used to screen the active components of the Xingnaojing injection. Then, the SwissTargetPrediction webserver was used to collect the corresponding gene targets, and the gene targets related to COVID-19 were searched in the Genecards database. The DAVID database was used to enrich the function of gene targets, and the KOBAS3.0 database for the annotation of related KEGG pathways. The ?components?targets?pathways? network of Xingnaojing injection was constructed with Cytoscape 3.6.1 software. The protein?protein interaction networks were analyzed using the String database. Specific proteins, SARS-COV-2 3 Cl, ACE2, and the active components were imported into Discovery Studio 2016 Client for molecular docking studies. From the Xingnaojing injection, a total of 58 active components, including Divanillalaceton and Q27139023, were screened. These were linked to 53 gene targets including mitogen-activated protein kinase 1 (MAPK1), tumor necrosis factorTNF, epidermal growth factor receptor, MAPK3, and 196 signaling pathways related to COVID-19, such as apoptosis, C-type lectin receptor signaling pathway, and hypoxia-inducible factor 1 signaling pathway. Furthermore, molecular docking studies were performed to study potential binding between the key targets and selected active components. Xingnaojing injection exhibits anti-COVID-19 effects via multiple components, multiple targets, and multiple pathways. These results set a scientific basis for further elucidation of the anti-COVID-19 mechanism of Xingnaojing injection.
RESUMEN
There has been a large global outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), representing a major public health issue. In China, combination therapy, including traditional Chinese medicine (TCM) as a treatment for COVID-19 has been used widely. "Fei Yan No. 1" (QFDYG) is a formula recommended by the Hubei Government to treat COVID-19. A retrospective study of 84 COVID-19 patients from Hubei Provincial Hospital of TCM and Renmin Hospital of Hanchuan was conducted to explore the clinical efficacy of QFDYG combination therapy. TCMSP and YaTCM databases were used to determine the components of all Chinese herbs in QFDYG. Oral bioavailability (OB) ≥ 30% and drug-like (DL) quality ≥ 0.18 were selected as criteria for screening the active compounds identified within the TCMSP database. The targets of active components in QFDYG were determined using the Swiss TargetPrediction (SIB) and Targetnet databases. The STRING database and the Network Analyzer plugin in Cytoscape were used to obtain protein-protein interaction (PPI) network topology parameters and to identify hub targets. Gene Ontology (GO) enrichment was conducted using FunRich version 3.1.3, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment using ClueGO version 2.5.6 software. PPI and compound-pathway (C-T) networks were constructed using Cytoscape 3.6.0. Compared with the control group, combined treatment with QFDYG resulted in a significantly higher rate of patients recovering from symptoms and shorter the time. After 14 days of treatment, QFDYG combined treatment increased the proportion of patients testing negative for SARS-CoV-2 nucleic acid by RT-PCR. Compared with the control group, promoting focal absorption and inflammation as viewed on CT images. GO and KEGG pathway enrichment indicated that QFDYG principally regulated biological processes, such as inflammation, an immune response, and apoptosis. The present study revealed that QFDYG combination therapy offered particular therapeutic advantages, indicating that the theoretical basis for the treatment of COVID-19 by QFDYG may play an antiviral and immune response regulation through multiple components, targets, and pathways, providing reference for the clinical treatment of COVID-19.