DISTANCE-BASED TOPOLOGICAL INDICES OF THE MOLECULARSTRUCTURE OF SOME DRUGS FOR TREATING CANCER PATIENTS
Abstract
Topological descriptors are key tools for analyzing the intrinsic properties of chemical graphs and nanostructures, capturing molecular symmetry through graph invariants such as vertex degree, distance, and spectrum. This study investigates vertex-distance-based indices, namely: the Wiener and Hosoya indices, for selected anticancer drugs. Using linear regression models, the indices were correlated with the drugs’ physicochemical and biological properties through a Quantitative Structure–Property Relationship (QSPR) analysis, providing insight into their linear relationships and potential applications in drug design.
Fields of Study & Subjects
Graph theory and applications
Computational Drug Discovery Methods
Graph Labeling and Dimension Problems
Publication details
- Journal / source
- FULafia Journal of Science and Technology
- Publisher
- Faculty of Physical Sciences, Federal University of Lafia
- Volume
- 10
- Issue
- 1
- Pages
- 125–131
- Publication date
- 12 February 2026