COVID antiviral drug structures and their edge metric dimension

Abstract

The study of the characteristics and topologies of networks, including social, computer and biological networks, is known as graph theory. Numerous disciplines, such as epidemiology, which is the study of the transmission and management of infectious diseases like Covid-19, can benefit from the study of graph theory. Like, the first case of COVID-19 (Coronavirus) was reported in November of 2019; by the third week of April, 1,116,643 verified positive cases had been reported, with around 59,158 fatalities. All the meditational structures are symmetric, if we label to change the labels of graphs in either way the graph becomes symmetric and will be no change to it. So, there are many graph theoretical parameters to study the symmetric meditational structures, like metric and edge metric dimension. A notion known as edge metric dimension or edge metric basis states that with a chosen subset from the vertex set, known as the edge resolving set, the whole edge set of a structure uniquely recognised. This idea of vertices resolvability allows for the distinct identification of COVID antiviral medication structures and aids in the research of the structure's structural characteristics. The chosen resolving set and the computed edge metric dimension will be invariant due to the symmetry of the graphs. Arbidol, malaria, carboxylic, thalidomide and theaflavin are the names of these compounds which are discussed in this work.

GRAPHICAL ABSTRACT

KEYWORDS:

• COVID antiviral drugs
• edge metric dimension
• edge locating number
• edge locating set

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data Availability

All the data supporting the results are included in the manuscript.

Additional information

Funding

The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number ISP22-6.