Novel molecular hybrid geometric-harmonic-Zagreb degree based descriptors and their efficacy in QSPR studies of polycyclic aromatic hydrocarbons

• Published in: SAR and QSAR in environmental research Vol. 34; no. 7; pp. 569 - 589
• Main Authors: Arockiaraj, M., Paul, D., Clement, J., Tigga, S., Jacob, K., Balasubramanian, K.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 03.07.2023; Taylor & Francis Ltd
• Subjects: Aromatic compounds; Chemical equilibrium; coronene series; Environment models; Environmental modeling; Graphene; Hybrid geometric-harmonic-Zagreb descriptors; Mathematical models; Molecular structure; Octanol; Physicochemical properties; Polycyclic aromatic hydrocarbons; polycyclic benzenoid hydrocarbons; QSPR of thermodynamic properties; Scaling factors; topological descriptors; Hybrid geometric-harmonic-Zagreb descriptors; polycyclic benzenoid hydrocarbons; coronene series; QSPR of thermodynamic properties; topological descriptors
• ISSN: 1062-936X; 1029-046X; 1029-046X
• DOI: 10.1080/1062936X.2023.2239149

The physicochemical characteristics of polycyclic aromatic compounds critical to environmental modelling such as octanol partition coefficients, solubility, lipophilicity, polarity and several equilibrium constants are functions of their underlying molecular structures, prompting the development of mathematical models to predict such characteristics for which experimental results are difficult to obtain. We propose twelve novel descriptors derived from geometric, harmonic and Zagreb degree-based descriptors and then test the effectiveness of these descriptors on a data set consisting of 55 benzenoid hydrocarbons of environmental importance. Our computations show that the proposed descriptors have a good linear correlation and predictive power when compared to the degree and distance type descriptors. We have also derived the QSPR expressions for four properties of a large series of polycyclic aromatics arising from circumscribing coronenes and show that a scaling factor can be deduced to derive physicochemical properties of such series up to 2D graphene sheets.