Development of Single-Cell Transcriptomics and Its Application in COVID-19.

Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Xuanfei Baidu granule (XFBD) significantly improved patient's clinical symptoms, the compound drug improves immunity by increasing the number of white blood cells and lymphocytes, and exerts anti-inflammatory effects. However, the analysis of the effective monomer components of XFBD and its mechanism of action in the treatment of COVID-19 is currently lacking. Therefore, this study used computer simulation to study the effective monomer components of XFBD and its therapeutic mechanism. Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.

Research on the mechanism of berberine in the treatment of COVID-19 pneumonia pulmonary fibrosis using network pharmacology and molecular docking.

Purpose Pulmonary fibrosis caused by COVID-19 pneumonia is a serious complication of COVID-19 infection, there is a lack of effective treatment methods clinically. This article explored the mechanism of action of berberine in the treatment of COVID-19 (Corona Virus Disease 2019, COVID-19) pneumonia pulmonary fibrosis with the help of the network pharmacology and molecular docking. Methods We predicted the role of berberine protein targets with the Pharmmapper database and the 3D structure of berberine in the Pubchem database. And GeneCards database was used in order to search disease target genes and screen common target genes. Then we used STRING web to construct PPI interaction network of common target protein. The common target genes were analyzed by GO and KEGG by DAVID database. The disease-core target gene-drug network was established and molecular docking was used for prediction. We also analyzed the binding free energy and simulates molecular dynamics of complexes. Results Berberine had 250 gene targets, COVID-19 pneumonia pulmonary fibrosis had 191 gene targets, the intersection of which was 23 in common gene targets. Molecular docking showed that berberine was associated with CCl2, IL-6, STAT3 and TNF-α. GO and KEGG analysis reveals that berberine mainly plays a vital role by the signaling pathways of influenza, inflammation and immune response. Conclusion Berberine acts on TNF-α, STAT3, IL-6, CCL2 and other targets to inhibit inflammation and the activation of fibrocytes to achieve the purpose of treating COVID-19 pneumonia pulmonary fibrosis.