STRUCTURAL MODELING OF PLANT REGULATORS BASED ON TOPOLOGICALINDICES AND CURVE FITTING

Topological indices are important quantifiers of chemical graphs which are valuable tools to establish quantitative structureproperty relationship (QSPR) modeling. This work derives topological indices of plant growth regulators and their QSPR models. Plant growth regulators (PGRs) are substances, either organic or inorganic, that influence the metabolic and developmental activities of plants. Investigating the physiochemical and biological properties of various regulators is crucial for elucidating their theoretical char-acteristics with greater precision. This study employs degree-based topological indices to achieve a comprehensive structural analysis of PGRs. Thirteen of the plant regulators’ topological indices are used to construct a QSPR model after fifteen plant regulators are assessed for some of their physiochemical characteristics. Accord-ing to this QSPR model, properties including molar refractivity, complexity, flash point, molar volume of plant regulators are highly correlated to the indices. Moreover, we conducted a comparative analysis of curvilinear regression models and singled out best fit models of topological indices which give high prediction of phys-iochemical properties of the regulators. It gives an insight to the potential of topological indices (TIs) to better represent theoretical characteristics and exhibits effective computational approach to the structural analysis of PGRs.