Graph coloring–driven topological indices for QSPR modeling and MCDM prioritization of brain tumor drugs

A drug molecule can be represented as an isomorphic molecular graph G ( V, E ), where the atoms form the vertex set V ( G ) and bonds between atoms constitute the edge set E ( G ). Topological indices are numerical values computed from isomorphic molecular graphs and the coloring-based topological indices are derived from isomorphic molecular graphs through systematic coloring of the atoms (vertices) or bonds (edges) of the molecular graphs. Brain tumors are aggressive cancers with low survival rates despite significant medical advances. Several drugs, including Belzutifan, Afinitor, Carmustine, Lomustine, Tovorafenib, Dabrafenib, Temozolomide, Etoposide, Procarbazine and Irinotecan, have been approved by the Food and Drug Administration (FDA) for the treatment of brain tumors. In this article, the two types of coloring-based topological indices viz., chromatic and induced color-based topological indices are computed for the isomorphic molecular graphs of the aforementioned drugs. These index values are employed in QSPR analysis to explore the physicochemical properties of the drugs. The comparative analysis between these types of indices reveals that the induced color-based indices exhibit a strong correlation with the physicochemical properties of the drugs. The robustness of the results is confirmed using the Leave-One-Out Cross-Validation (LOOCV) and Y-randomization techniques. Furthermore, the Multi-Criteria Decision Making (MCDM) methods are employed to prioritize the brain tumor drugs using the computed indices. Overall, the results demonstrate that the induced color-based topological indices serve as effective molecular descriptors for the physicochemical properties in QSPR analysis and prioritization of the brain tumor drugs.