ABSTRACT
Aim: This study aimed to discover the most effective anti-cancer medicine for cancer patients infected with SARS-CoV-2. Background: The correlation between TP53 and SARS-CoV-2 was examined using biomolecular networking analysis. Objective: Cancer patients with TP53 gene mutations are more likely to be infected with the SARS-CoV-2 virus since it is the most frequently mutated tumor suppressor gene in human cancer. The main goal of this study is to discover the most effective and efficient anti-cancer therapy for patients with SARS-CoV-2 infection. Materials and Methods: Topp gene analysis was used to prioritize candidate genes based on molecular function, biological process, and pathway analysis. Biomolecular networking was carried out using Cytoscape 2.8.2. The protein-protein interaction network was used to identify the functionally associated proteins. The protein-drug interaction network was used to observe the molecular therapeutic efficiency of drugs. The network was further analyzed using CytoHubba to find the hub nodes. The molecular docking was used to study the protein-ligand interaction, and the protein-ligand complex was further evaluated through molecular dynamic simulation to determine its stability. Results: Functionally relevant genes were prioritized through Toppgene analysis. Using Cytohabba, it was found that the genes UBE2N, BRCA1, BARD1, TP53, and DPP4 had a high degree and centrality score. The drugs 5-fluorouracil, Methotrexate, Temozolomide, Favipiravir, and Levofloxacin have a substantial association with the hub protein, according to protein-drug interaction analysis. Finally, a docking study revealed that 5-fluorouracil has the highest connection value and stability compared to Methotrexate, Favipiravir, and Levofloxacin. Conclusion: The biomolecular networking study was used to discover the link between TP53 and SARS-CoV-2, and it was found that 5-fluorouracil had a higher affinity for binding to TP53 and its related genes, such as UBE2N, BRCA1, RARD1, and SARS-CoV-2 specific DPP4. For cancer patients with TP53 gene mutations and Covid-19 infection, this treatment is determined to be the most effective. © 2022 Bentham Science Publishers.