Computational insights into flavonoid molecular structures and their QSPR modeling via degree based molecular descriptors

Topological indices are derived from the topology of the graph representation of the molecule and can be used to estimate various molecular properties. They are widely used in quantitative structure–property relationship (QSPR) analysis and computational chemistry studies. Flavonoids are natural compounds in sweet potatoes having various health benefits, including antioxidant and anti-inflammatory properties. By understanding the factors influencing the variation in flavonoid content, researchers can develop strategies to enhance the nutritional value of sweet Potato. Degree-based topological indices play a vital role in the QSPR analysis of molecular structures by providing molecular descriptors that help understand and predict the properties of these natural compounds. In this study, we initially computed several degree-based topological indices of five naturally occurring flavonoids (Myricetin, Quercetin, Luteolin, kaempferol, and Apigenin). Then, a QSPR analysis is performed by developing regression models. The results show that the considered topological indices have strong correlations with certain experimental physicochemical properties of flavonoids, which indicates their strong predictive ability. This confirms that the topological indices are the best alternatives to the laborious, time-consuming, and costly laboratory experiments.