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

Abstract

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

Keywords:

• Biological networks
• graph theory
• hypertree
• corona product
• topological features

Disclosure statement

No potential conflict of interest was reported by the author.

Authors’ contributions

All the authors have equally contributed to this manuscript in all stages, from conceptualization to the write up of final draft.

Consent for publication

All authors have approved the manuscript and given consent for publication.

Additional information

Funding

The authors gratefully acknowledge the financial support for this study derived from the Karakoram International University (Grant No. KIU-ORIC-1(2021)/) and Higher Education Commission of Pakistan (Grant No. 20-11682/NRPU/R& D/HEC/2020).