Affiliation:
1. Computational Chemistry Group (CCG), Amrita Molecular Modeling and Synthesis Research Lab, Amrita
School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India
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 SARSCoV-
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 SARSCoV-
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.
Publisher
Bentham Science Publishers Ltd.
Subject
Genetics (clinical),Pharmacology,Genetics,Molecular Biology,Molecular Medicine