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关于某些抗新冠病毒药物线图的度依赖拓扑研究。

On degree-dependent topological study of line graph of some antiviral COVID-19 drugs.

作者信息

Das Shibsankar, Kumari Arti, Barman Jayjit

机构信息

Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India.

出版信息

Eur Phys J E Soft Matter. 2025 Jul 14;48(6-7):39. doi: 10.1140/epje/s10189-025-00503-5.

Abstract

A topological index is a numerical value that correlates with a chemical structure. A degree-based topological index of drug molecular structures is beneficial for researchers investigating in the fields of medicals and pharmaceuticals because it is significant for testing the physicochemical properties of drugs. Graph theory has proven to be quite useful in this field of study. Graph analysis reveals insights into chemical structures. In physical chemistry, a line graph has multiple applications. This article focuses on the topological characterization of a line graph for antiviral COVID-19 drugs, namely Nirmatrelvir, Molnupiravir, Thalidomide, Theaflavin, Remdesivir, Ritonavir, Chloroquine, Hydroxychloroquine, Arbidol and Lopinavir. The computation of degree-based topological indices is carried out using their M-polynomials. Numerical values of topological indices of line graphs and geometric representations of the polynomials are shown graphically. A comparative study between the obtained values of the line graph and the values of an actual graph is presented through numerical and graphical representation. Furthermore, we conduct a QSPR analysis between the degree-based topological indices of the line graph of certain COVID-19 drugs and their physicochemical properties using curvilinear regression models. A comparison is made between the squared correlation coefficients derived from our curvilinear regression models and those obtained from earlier research. These findings may aid the applicability of newly developed drugs of similar kind, in predicting their physicochemical properties and in improving the associated QSPR studies and hence pave a way to improve treatments against the COVID-19 disease.

摘要

拓扑指数是一种与化学结构相关的数值。基于度的药物分子结构拓扑指数对医学和制药领域的研究人员很有帮助,因为它对测试药物的物理化学性质具有重要意义。图论已被证明在这一研究领域非常有用。图分析揭示了化学结构的相关见解。在物理化学中,线图有多种应用。本文重点研究抗新冠病毒药物(即奈玛特韦、莫努匹拉韦、沙利度胺、茶黄素、瑞德西韦、利托那韦、氯喹、羟氯喹、阿比多尔和洛匹那韦)的线图的拓扑特征。基于度的拓扑指数的计算是利用它们的M - 多项式进行的。线图的拓扑指数数值和多项式的几何表示以图形方式展示。通过数值和图形表示对线图的所得值与实际图的值进行了比较研究。此外,我们使用曲线回归模型对某些新冠病毒药物线图的基于度的拓扑指数与其物理化学性质之间进行了定量构效关系(QSPR)分析。将我们的曲线回归模型得出的平方相关系数与早期研究获得的平方相关系数进行了比较。这些发现可能有助于同类新开发药物在预测其物理化学性质、改进相关的定量构效关系研究方面的适用性,从而为改善新冠病毒疾病的治疗铺平道路。

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