Integrative pharmacological mechanism of vitamin C combined with glycyrrhizic acid against COVID-19: findings of bioinformatics analyses

Abstract

Objective: Coronavirus disease 2019 (COVID-19) is a fatal and fast-spreading viral infection. To date, the number of COVID-19 patients worldwide has crossed over six million with over three hundred and seventy thousand deaths (according to the data from World Health Organization; updated on 2 June 2020). Although COVID-19 can be rapidly diagnosed, efficient clinical treatment of COVID-19 remains unavailable, resulting in high fatality. Some clinical trials have identified vitamin C (VC) as a potent compound pneumonia management. In addition, glycyrrhizic acid (GA) is clinically as an anti-inflammatory medicine against pneumonia-induced inflammatory stress. We hypothesized that the combination of VC and GA is a potential option for treating COVID-19.

Methods: The aim of this study was to determine pharmacological targets and molecular mechanisms of VC + GA treatment for COVID-19, using bioinformational network pharmacology.

Results: We uncovered optimal targets, biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of VC + GA against COVID-19. Our findings suggested that combinatorial VC and GA treatment for COVID-19 was associated with elevation of immunity and suppression of inflammatory stress, including activation of the T cell receptor signaling pathway, regulation of Fc gamma R-mediated phagocytosis, ErbB signaling pathway and vascular endothelial growth factor signaling pathway. We also identified 17 core targets of VC + GA, which suggest as antimicrobial function.

Conclusions: For the first time, our study uncovered the pharmacological mechanism underlying combined VC and GA treatment for COVID-19. These results should benefit efforts to address the most pressing problem currently facing the world.

Keywords: COVID-19; bioinformatics analysis; biotarget; glycyrrhizic acid; vitamin C.

Figure 1

A stepwise workflow showed the combined antiviral activity of VC and GA against COVID-19 through network pharmacology. We identified candidate biotargets of VC and GA, then determined and mapped their combined core biotargets against COVID-19. A PPI diagram of VC + GA against COVID-19 was generated. Our analysis revealed the pharmacological functions and molecular pathways of VC + GA action against COVID-19.

Figure 2

Targets of sole VC or sole GA against COVID-19. (A) Venn diagram and PPI network showed the 34 targets of VC against COVID-19. (B) Venn diagram and PPI network exhibited the 28 targets of GA against COVID-19.

Figure 3

Biological processes and molecular pathways associated with core targets of VC against COVID-19. (A) Biological processes [from GO analysis] were presented by bubble diagrams with count algorithms and P-adjust values. (B) All core biotargets of VC against COVID-19 were linked to the top 10 most enriched GO terms in Circro diagrams. (C) Molecular pathways (from KEGG analysis) were presented by bubble diagrams based on count algorithms and P-adjust values. (D) Identified core biotargets of VC against COVID-19 were associated with the 10 most enriched KEGG terms in Circro diagrams.

Figure 3

Biological processes and molecular pathways associated with core targets of VC against COVID-19. (A) Biological processes [from GO analysis] were presented by bubble diagrams with count algorithms and P-adjust values. (B) All core biotargets of VC against COVID-19 were linked to the top 10 most enriched GO terms in Circro diagrams. (C) Molecular pathways (from KEGG analysis) were presented by bubble diagrams based on count algorithms and P-adjust values. (D) Identified core biotargets of VC against COVID-19 were associated with the 10 most enriched KEGG terms in Circro diagrams.

Figure 4

Biological processes and molecular pathways associated with core targets of GA against COVID-19. (A) Biological processes were presented by bubble diagrams generated through count algorithms and P-adjust calculation. (B) Core biotargets of GA against COVID-19 were related to the top 10 enriched GO terms in Circro diagrams. (C) Molecular pathways (from KEGG analysis) were presented by bubble diagrams based on count algorithms and P-adjust values. (D) Core biotargets of GA against COVID-19 were linked to the top 10 enriched KEGG terms in Circro diagrams.

Figure 4

Biological processes and molecular pathways associated with core targets of GA against COVID-19. (A) Biological processes were presented by bubble diagrams generated through count algorithms and P-adjust calculation. (B) Core biotargets of GA against COVID-19 were related to the top 10 enriched GO terms in Circro diagrams. (C) Molecular pathways (from KEGG analysis) were presented by bubble diagrams based on count algorithms and P-adjust values. (D) Core biotargets of GA against COVID-19 were linked to the top 10 enriched KEGG terms in Circro diagrams.

Figure 5

Targets of combined VC and GA against COVID-19. Venn diagram highlighted the intersecting targets of VC in combination with GA as a drug for COVID-19. Using online databases, we identified 19 shared biotargets of VC + GA against COVID-19.

Figure 6

Biological processes and molecular pathways associated with core targets of combined VC + GA against COVID-19. (A) Heatmap showed GO biological processes of VC + GA against COVID-19. Optimal prioritization was determined via the -log10 (P.adjust) algorithm for visualization. (B) Heatmap uncovered KEGG signaling pathways of VC + GA against COVID-19. Different colors represented optimal prioritization of molecular pathways determined using the -log10 (P.adjust) algorithm.

Figure 7

Interaction network of VC + GA target KEGG pathways against COVID-19. Detailed information on core biotargets, pharmacological functions and signaling pathways were presented.