  The Worldwide spread of the Omicron lineage variants has now been confirmed.
It is crucial to understand the process of cellular life and to discover new
drugs need to identify the important proteins in a protein interaction network
(PPIN). PPINs are often represented by graphs in bioinformatics, which describe
cell processes. There are some proteins that have significant influences on
these tissues, and which play a crucial role in regulating them. The discovery
of new drugs is aided by the study of significant proteins. These significant
proteins can be found by reducing the graph and using graph analysis. Studies
examining protein interactions in the Omicron lineage (B.1.1.529) and its
variants (BA.5, BA.4, BA.3, BA.2, BA.1.1, BA.1) are not yet available. Studying
Omicron has been intended to find a significant protein. 68 nodes represent 68
proteins and 52 edges represent the relationship among the protein in the
network. A few entrality measures are computed namely page rank centrality
(PRC), degree centrality (DC), closeness centrality (CC), and betweenness
centrality (BC) together with node degree and Local Clustering Co-efficient
(LCC). We also discover 18 network clusters using Markov clustering. 8
significant proteins (candidate gene of Omicron lineage variants) were detected
among the 68 proteins, including AHSG, KCNK1, KCNQ1, MAPT, NR1H4, PSMC2, PTPN11
and, UBE21 which scored the highest among the Omicron proteins. It is found
that in the variant of Omicron protein-protein interaction networks, the MAPT
protein's impact is the most significant.
