Resolvability parameters in molecular graphs of antimalarial drugs

Chemical graph theory facilitates the understanding of the complex structure of molecules. Researchers can achieve a thorough understanding of the physical science, chemical properties, and bio-organic characteristics of pharmaceuticals through the calculation of resolvability and topological parameters in drug design. The resolvability constraints for graph $G=(V,E)$ constitute a complex domain in which the framework is structured so that each vertex (atom) or edge (bond) denotes a distinct position. This study aims to utilize molecular graph theory to identify specific graph-theoretic parameters associated with the molecular graphs of eight medications used in malaria treatment. This paper presents resolvability parameters, including metric dimension (MD) and edge metric dimension (EMD), for eight medications used in malaria treatment. We demonstrate that the resolvability parameters for the specified drugs are both bounded and constant. This property facilitates molecular identification, verifies graph isomorphism, and functions as a valuable topological descriptor in QSAR/QSPR modeling. Furthermore, it improves chemical database indexing and feature generation for machine learning, facilitating efficient structure-based analysis in drug discovery and material design.