STRUCTURAL MODELING OF PLANT REGULATORS BASED ON TOPOLOGICAL INDICES AND CURVE FITTING

Abstract

Topological indices are important quantifiers of chemical  graphs which are valuable tools to establish quantitative structure property relationship (QSPR) modeling. This work derives topo logical 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