Construction and Analysis of Enzyme Centric Network of A. thaliana using Graph Theory

Graph comparisons, quantitative characterizations, computation of topological indices, clustering and partitioning are some of the major computations of graph that have yielded valuable results in various disciplines. Motivated by the potential benefits of graph theory application on biological data, we discuss the reconstruction and analysis of enzyme centric network of Arabidopsis thaliana using graph theory concepts. We had earlier constructed the metabolite network of Arabidopsis thaliana and witnessed the scale free and small world nature of the network. Compared to metabolites, the enzymes are more conserved in and across many pathways. So the aim of constructing the enzyme centric network is to see if the network follows similar network properties of the metabolite network and to look for additional details that a metabolite network cannot reveal. The enzyme flat file from KEGG FTP is used as the data set for the reconstruction of the enzyme centric network. We examined the network to find the relationship between topological connections among enzymes and their functions during evolution. The enzyme sequences of high degree and high betweenness enzymes belonged to ancient fold class and ancestry value showing evidence that they evolved very slowly.