Predictive modelling and ranking: Azadirachta indica compounds through indices and multi-criteria decision-making techniques - Anuradha, D. S.; Jaganathan, B. (Frontiers in Chemistry, 2025)
IntroductionAzadirachta indica (neem) shows medicinal potential against chronic diseases, but clinical translation is challenging. This study aimed to analyze neem compounds using topological indices (TIs) to predict physicochemical properties. MethodsValency-based indices, including Zagreb and atom bond connectivity indices, were used to characterize boiling point, vaporization, enthalpy, mass, and refractivity. Regression analysis and multi-criteria decision-making methods were employed for predictive modeling and compound ranking.ResultsStatistical metrics demonstrated the predictive power of the models. Ranking methods provided a hierarchical ordering of compounds based on therapeutic potential.DiscussionThis study contributes to analogous prediction, optimization, and virtual screening of neem compounds using a cost-effective approach. The findings offer insight into neem compound properties, potentially accelerating drug discovery and development.