Computational insights and predictive models for lung cancer molecular structures

Abstract

The structure-based investigation of the chemical and physical attributes of drugs administered for treating various forms of cancer has gained significant attention, particularly through the implication of topological indices derived from the molecular characteristics of the compounds. A deeper understanding of chemical and physical properties is crucial for drug development, and in this direction, topological indices help bridge the gap between chemistry and the pharmaceutical industry by providing a cost-effective way to determine the physical properties of molecules. This study aims to investigate the topological polynomials and indices of a series of drugs that are employed for the lung cancer treatment. These include adagrasib, alectinib, brigatinib, crizotinib, dacomitinib, entrectinib, gefitinib, lorlatinib, pralsetinib, and sotorasib. A QSPR analysis has been conducted to ascertain the mathematical relationship between the chemical and physical properties of drugs and their topological indices, including exact mass, molecular weight, heavy atom count, complexity, molar refractivity, and polarizability. The topological indices applied to the drugs under consideration exhibit a favorable correlation with the physicochemical properties in this context. Furthermore, a comparison is made between the actual values and those predicted by the QSPR models discussed.