A Computational-Based Drug Repurposing Method Targeting SARS-CoV-2 and its Neurological Manifestations Genes and Signaling Pathways

Abstract

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a global concern involves infections in multiple organs. Much of the research up to now has been descriptive on neurological manifestations followed by SARS-CoV-2 infection. Despite considerable efforts on effective SARS-CoV-2 vaccine, novel therapeutic options for COVID-19 comorbidities are warranted. One of the fast ways to introduce possible effective drugs for clinical trials is bioinformatics methods. We have conducted a comprehensive enrichment analysis of genes involved in SARS-CoV-2 and neurological disorders associated with COVID-19. For this purpose, gene sets were extracted from the GeneWeaver database. To find out some significant enriched findings for common genes between SARS-CoV-2 and its neurological disorders, several practical databases were used. Finally, to repurpose an efficient drug, DrugBank databases were used. Overall, we detected 139 common genes concerning SARS-CoV-2 and their neurological disorders. Interestingly, our study predicted around 6 existing drugs (ie, carvedilol, andrographolide, 2-methoxyestradiol, etanercept, polaprezinc, and arsenic trioxide) that can be used for repurposing. We found that polaprezinc (zinc l-carnosine) drug is not investigated in the context of COVID-19 till now and it could be used for the treatment of COVID-19 and its neurological manifestations. To summarize, enrichment and network data get us a coherent picture to predict drug repurposing to speed up clinical trials.

Keywords: Bioinformatics approach; COVID-19; neurological disorders; neurotropism; polaprezinc.

Figure 1.

The computational analysis flowchart for conducting over-representation analysis and repurposing potential therapeutic options for SARS-CoV-2-induced neurological disorders.

Figure 2.

Schematic overview of proposed work. All genes involved in SARS-CoV-2 and neurological disorders associated with COVID-19 were extracted from GeneWeaver. Then, common genes in both categories were isolated and proceeded for further computational analysis. Finally, cellular and molecular basis, and signaling pathways were enriched to repurpose the drug and predict possible mechanisms of neurotropism by SARS-CoV-2.

Figure 3.

SARS-CoV-2 associated genetic network. The large nodes indicate a higher degree. The color of each node is adjusted based on its betweenness centrality. Red, orange, yellow, and purple nodes represent a spectrum from greater to lesser betweenness centrality (red nodes have greater betweenness centrality). Unconnected nodes have been excluded.

Figure 4.

Neurological disorders genetic network. The large nodes indicate a high degree. The color of each node is adjusted based on its betweenness centrality. Red, orange, yellow, and purple nodes represent a spectrum from greater to lesser betweenness centrality (red nodes have greater betweenness centrality). Unconnected nodes have been excluded.

Figure 5.

Reconstructed genetic network for shared genes between neurological disorders and SARS-CoV-2 associated genes. The current network comprised 139 nodes (genes) and 451 edges (interactions). Dark red nodes involve in all predetermined neurological disorders. The light red, dark orange, light orange, green, and yellow nodes involve 7, 5, 4, 3, and 2 neurological disorders, respectively. Purple nodes involve in one neurological disorder. The size of all nodes adjusted based on their degrees into the network (larger nodes indicate higher degree). Nine peripheral nodes have a higher degree and greater closeness and betweenness centrality in the network.

Figure 6.

Heat map of differential expression of genes. The involvement of each SARS-CoV-2-related gene in each neurological disorder is adjusted with a color map. The columns represent SARS-CoV-2 associated genes, while rows represent the most important reported neurological disorders in COVID-19 patients. The dark red color indicates positive enrichment and light red indicates negative enrichment.

Figure 7.

Highest topological features of 9 shared genes between COVID-19 and its neurological manifestations. Quantitative data represented 3 main topological features including degree, closeness centrality, and betweenness centrality.

Figure 8.

Biological process, cellular component, Reactome pathway, and molecular function enrichment analysis of our target genes of SARS-CoV-2 and its neurological disorders. (A) The most significant biological processes that may involve in SARS-CoV-2-induced neurological disorders. (B) The important cellular components which can be interrupted by SARS-CoV-2. (C) The Reactome pathway enrichment analysis of shared genes between SARS-CoV-2 and its neurological manifestations. (D) The molecular function enrichment analysis of our target genes. All parameters were sorted according to the enrichment FDR from GO analysis.

Figure 9.

The gene-drug network and the schematic diagram of the possible effect of Polaprezinc on signaling pathways involved in SARS-CoV-2 and its neurological manifestation. (A) The relation between genes and their target drugs has been shown as a network. The size of each drug (orange diamond nodes) was adjusted based on its FDR significance level (biggest nodes indicate smallest FDR levels). (B) Based on drug repurposing and Reactome pathway analysis, 4 target genes, such as Fms related receptor tyrosine kinase 1 (FLT1), tumor necrosis factor (TNF), interleukin-6 (IL-6), and heme oxygenase 1 (HMOX1), as well as their mechanisms, were predicted by Polaprezinc in the context of COVID-19.