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Skin cancer is one of the most common diseases, and studying its drugs is important for effective treatment and drug design. Drugs for melanoma, immunosuppressants, and topical drug administration have a bright future in the investigation of skin cancer drugs with possible anticancer properties. The use of chromatic topological descriptors is still the predominant strategy due to the notable progress being made in the field of drug creation. In this work, the investigation of regression models and chromatic hyper Zagreb topological descriptors for some skin cancer drugs is the main focus of this study. Together with the QSPR models, descriptors provide a numerical representation of a molecule’s chemical characteristics. Proper coloring is applied to the molecular graphs such that no two adjacent vertices share the same color. Regression models are constructed for the calculated index values while the physicochemical properties of skin cancer drugs are investigated. The framework that connects chemical composition to physical attributes is represented by numbers associated with chromatic topological indices. Based on the data collected, an analysis is conducted for a number of noteworthy findings.
Pavithra et al. (Fri,) studied this question.