Abstract:
The COVID-19 contagion commenced by the “Severe Acute Respiratory Syndrome
Coronavirus 2” has become a prime health concern. It has already meted out insuperable
damage to human lives and the global economy. Despite the pioneering development of
vaccines, the fluctuation in strain pattern of the novel coronavirus has led to immune evasion
and posed a challenge to the efficacy of vaccines primarily industrialized against the prototype
strain. Inclusive efforts are already underway at a war footing to find the best drugs or drug
combinations to address future attempts in sinking the disease. On this account, drug
repurposing strategies introduced ahead of time were employed to identify the potential drugs
intended to contain the disastrous virus outbreak. This study aims to define a network-based
approach to filter a set of approved and experimental drugs from the DrugBank database
redirected as competing treatments for the COVID-19 disease therapy. Our method described
the interaction networks of seventeen (17) repurposable drugs defining topological and
statistical features with shared biological processes of the host cells. The drug-gene interaction
data specifically outlined from the Drug Gene Interaction Database was followed by the
network construction through GeneMania and Cytoscape. The networks then underwent
enrichment analysis through the EnrichNet tool to observe the functional linkage between the
gene-sets and pathways, including the user-defined dataset and the reference dataset. Finally,
the drugs arrayed under the significance measure of pathways with overlapping genes
identified thirty-nine (39) drug-pathway interactions of statistical significance and
insignificant similarity scores for two drugs (Human-Interferon Beta and Elbasvir) against
cellular pathways. For comparative review and target assessment of all the drug interaction
modules, we first labeled the disease-associated genes and pathways from previously
extracted results of text mining resources and interactome studies on coronaviruses to compare
them with our findings. Our results illustrated drug-target interactions for fifteen (15) genes
contributed between the disease comorbidities and eight (8) pathways essential to
pathogenesis. This strategy concludes the importance of repurposing target-based drugs
against clinically significant genes and pathways for the COVID-19 disease therapy.
