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Predictive ability of physiochemical properties of benzene derivatives using Ve-degree of end vertices-based entropy
Topological indices relate chemical structure to chemical reactivity, physical properties, and biological activity. Quantitative structure-activity relationships (QSPR) are mathematical models proposed for the correlation of various types of chemical reactivity, biological activity, and physical pro...
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Published in: | Journal of biomolecular structure & dynamics 2024-12, Vol.42 (22), p.12342-12352 |
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container_title | Journal of biomolecular structure & dynamics |
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creator | Naeem, Muhammad Rauf, Abdul Mumtaz, Muhammad Waleed Ameen, Nimra |
description | Topological indices relate chemical structure to chemical reactivity, physical properties, and biological activity. Quantitative structure-activity relationships (QSPR) are mathematical models proposed for the correlation of various types of chemical reactivity, biological activity, and physical properties with topological indices/entropies. In this article, we have proposed the QSPR between the ve-degree of end vertices of edge based entropies and the physiochemical properties of benzene derivatives. We have designed a Maple-based algorithm for the computation of entropies. The relationship was analyzed using SPSS. We have shown that the physiochemical properties such as critical pressure, Henry's law, critical temperature, Gibb's energy, logP, critical volume, and molar refractivity can be predicted by entropies. All the results were highly positive and significant. The Randić, Balaban, and redefined third Zagreb entropies showed the best relations with physiochemical properties.
Communicated by Ramaswamy H. Sarma |
doi_str_mv | 10.1080/07391102.2023.2269419 |
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subjects | Algorithms Benzene - chemistry benzene derivatives Benzene Derivatives - chemistry Entropy physiochemical properties Quantitative Structure-Activity Relationship Quantitative structure-property relationship |
title | Predictive ability of physiochemical properties of benzene derivatives using Ve-degree of end vertices-based entropy |
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