Journal of Applied Bioinformatics & Computational BiologyISSN: 2329-9533

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Mutation Based Network Analysis to Predict the Affected Pathways for Sars Cov-2 Variants Isolated from the Kingdom of Bahrain

SARS-associated coronavirus (SARS-CoV) causes respiratory illness called severe acute respiratory syndrome (SARS). We have identified the SARS-COV2 variants from the kingdom of Bahrain. In this study, we applied network theory to predict the effect of a mutation in the SARS-COV2 protein interaction network with the human interactome. For the lineage analysis, first, we have downloaded the FASTA file of 874 variants identified in the Kingdom of Bahrain by comparing with hCoV-19/Wuhan/WIV04/2019 strain (isolated from Wuhan, China) as a reference for variant. Our network analysis predicts the drug target by constructing a protein-protein interaction network of SARS-COV2 with the human interactome and eventually get 36 mutations on spike protein. We have a total of 929 unique interactions among the human proteins that are interacting with SARS-COV2 proteins. This gives us the actual view of how SARS-COV2 interacts with human interactome. We find out the point mutations in the available SARS-COV2 variants which are still a potential threat for the vaccinated people. Nine SARS-COV2 proteins that are reported in the SARS-COV2 protein-protein interaction network. The variants are associated with a mutation in S, NSP12, N, N, NSP6, NSP1, NSP15, NSP13, NSP2, NSP5 and NSP8. We have selected only those proteins which undergo a change inbetweenness centrality >=0.01. The effect of these variant’s on the human interactome are associated to affect different regulatory pathways of the cell. A number of research laboratories are making a major effort to develop therapeutic strategies for controlling COVID-19. These variants can be a potential therapeutic target to develop a drug that will prevent viral entry into target cells and virus replication.

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