Graph-theoretical analysis of peripheral molecular descriptors for phloroglucinol used in the treatment of spasmodicpain

This article presents a detailed mathematical analysis and computational approach to peripheral-based molecular descriptors of the phloroglucinol molecular graph, focusing on their relaionship with key chemical properties. Phloroglucinol, a polyphenolic compound with significant biochemical and pharmacological relevance, can be represented graph-theoretically, where molecular descriptors provide crutial insights into its structural and chemical behaviour. Using graph theory, we compute mostar index, that capture peripheral molecular features. The study highlights how these descriptors relate to phloroglucinol,s chemical properties, such as stability, reactivity, and potential biological activity. Furthermore, computational algorithms are employed to validate and optimize descriptor calculations, offering a comprehensive framework for studying the molecular characteristics of phloroglucinol. The findings contribute to the broader understanding of molecular graph theory applications in chemistry and pharmaceutical sciences.

Publication Details

Journal
Communications in Mathematical Biology and Neuroscience
Published
2025-01-01
DOI
https://doi.org/10.28919/cmbn/9190
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Graph-theoretical analysis of peripheral molecular descriptors for phloroglucinol used in the treatment of spasmodicpain

Communications in Mathematical Biology and Neuroscience
Computational Drug Discovery Methods
article

Graph-theoretical analysis of peripheral molecular descriptors for phloroglucinol used in the treatment of spasmodicpain

article en

Abstract

This article presents a detailed mathematical analysis and computational approach to peripheral-based molecular descriptors of the phloroglucinol molecular graph, focusing on their relaionship with key chemical properties. Phloroglucinol, a polyphenolic compound with significant biochemical and pharmacological relevance, can be represented graph-theoretically, where molecular descriptors provide crutial insights into its structural and chemical behaviour. Using graph theory, we compute mostar index, that capture peripheral molecular features. The study highlights how these descriptors relate to phloroglucinol,s chemical properties, such as stability, reactivity, and potential biological activity. Furthermore, computational algorithms are employed to validate and optimize descriptor calculations, offering a comprehensive framework for studying the molecular characteristics of phloroglucinol. The findings contribute to the broader understanding of molecular graph theory applications in chemistry and pharmaceutical sciences.

Communications in Mathematical Biology and Neuroscience
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Computational Drug Discovery Methods
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