COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs

Abstract

Purpose: COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs.

Methods: We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb).

Results: Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16.

Conclusion: We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

Keywords: COVID-19; DEG; Drug Repurposing; Host Response; PPI; SARS-CoV.

Fig. 1

Represents a graphical workflow of the study

Fig. 2

Represents the Venn diagram of the shared DEGs between the top 10% of hubs and bottlenecks of the SARS and COVID-19 PPI networks

Fig. 3

MCODE clusters. A represents the significantly scored MCODE clusters in SARS PPI. B represents the significantly scored MCODE clusters in COVID-19 PPI. Nodes with the highest degree score (seeds) are represented in triangle form in each cluster, and nodes with a dual role (TF/Gene) are in green color

Fig. 4

Represents the shared DEGs that relate the MCODE clusters of each infection to the other infection PPI and their significantly enriched corresponding biochemical pathways. DEGs are depicted in orange circles, pathways in triangles, and diseases with purple circles. Edges related to SARS are shown with continuous lines, and COVID-19 with dashed lines. Clusters are labeled distinctly

Fig. 5

Represents the Drug-Gene interaction network. Purple diamonds show the crucial identified Genes, and circles depict our repurposed medications. The medicines previously registered for clinical trials against COVID-19 are distinct, using orange color