Quantitative structure–property relationship (QSPR) modeling for evaluating fluorescence attributes across various aromatic heterocyclic compounds with ve-degree-based Sombor indices

Abstract

Aromatic heterocyclic compounds have become highly sought-after for their diverse medicinal and biological uses. Their synthesis and adaptability have led to a surge in research interest, as they play a crucial role in the creation of over 90% of groundbreaking medications. These compounds bridge the gap between biology and chemistry, driving significant scientific progress. Heterocycles are utilized across various fields, including pharmaceutical chemistry and biochemistry. This article introduces the development of quantitative structure–property relationship models using ve-degree-based Sombor indices. Some linear regression models have been fitted that can be used for prediction purposes. Specifically, these models aim to predict the fluorescence properties of aromatic heterocyclic species based on their structural features. Such models provide researchers with the ability to estimate the fluorescence behavior of new molecules without the need for experimental measurements. It is noted that the maximum excitation wavelength ${(\lambda }_{\mathbf{e}\mathbf{x}})$ on the Sombor index type four (ST₄) has the highest coefficient of determinations (${R}^{2}=0.872$) and the smallest residual standard error ($s=53.673$). Thus, the physical property ${\lambda }_{\mathbf{e}\mathbf{x}}$ can be predicted by the sombor index ST₄ at the best level.