Computational aspects of two important biochemical networks with respect to some novel molecular descriptors

Quantitative structure-activity relationship (QSAR) represents quantitative correlation of biological structural features (called as topological indices) and pharmacological activity as response endpoints. Topological index is a molecular descriptor extensively used to study QSAR of pharmaceutical to assess their molecular characteristics by numerical computation. Meanwhile, the topological indices are numerical functions which are used to predict the growth rate of microorganisms in biological networks. Theoretical assessment of microorganism, such as bacteria and viruses help to expedite the vaccine design and discovery process by rationalizing the lead identification, lead optimization and understanding their mechanism of actions. Hypertree, a network structure derived from graph theory, has a great importance in biological networks for growth of microorganisms, such as bacteria and viruses. In this article, some novel eccentric and degree based topological features of two important biological networks (hypertree and its corona product) are obtained on h-level and derived closed formulas for them. Based on the obtained topological features, the biological properties of these networks are investigated.Communicated by Ramaswamy H. Sarma

Automated summary

Quantitative structure-activity relationship (QSAR) is a method that correlates the biological structural features (topological indices) with pharmacological activity. Topological indices are numerical functions used to predict the growth rate of microorganisms in biological networks. Theoretical assessment of microorganisms helps in vaccine design and discovery by understanding their mechanism of actions. This article investigates the biological properties of two important biological networks (hypertree and its corona product) by obtaining novel topological features and deriving closed formulas for them.