基于特征值的指标利用新冠病毒药物结构的定量构效关系分析。
Quantitative structure-properties relationship analysis of Eigen-value-based indices using COVID-19 drugs structure.
作者信息
Rauf Abdul, Naeem Muhammad, Hanif Asia
机构信息
Department of Mathematics Air University, Multan Campus Multan Pakistan.
School of Natural Sciences (SNS) National University of Sciences and Technology (NUST) Islamabad Pakistan.
出版信息
Int J Quantum Chem. 2023 Feb 15;123(4):e27030. doi: 10.1002/qua.27030. Epub 2022 Nov 3.
Topological indices are an important method for understanding the fundamental topology of chemical structures. Quantitative structure properties relationship (QSPR) is an analytical approach for breaking down a molecule into a sequence of numerical values that describe the chemical and physical characteristics of the molecule. In this article, we have developed the QSPR analysis between eigenvalue-based topological indices and physical properties of COVID-19 drugs to predict the significance level of eigenvalue based indices. We have to use MATLAB for the computation of indices and SPSS for analysis. We show that positive interia index, signless Laplacian Estrada index and Randić energy are the best predictors of molar reactivity, polar surface area and molecular weight, respectively.
拓扑指数是理解化学结构基本拓扑的重要方法。定量结构-性质关系（QSPR）是一种分析方法，用于将分子分解为一系列描述分子化学和物理特性的数值。在本文中，我们开展了基于特征值的拓扑指数与新冠病毒药物物理性质之间的QSPR分析，以预测基于特征值的指数的显著水平。我们使用MATLAB计算指数，使用SPSS进行分析。我们表明，正惯性指数、无符号拉普拉斯 Estrada 指数和兰迪奇能量分别是摩尔反应性、极性表面积和分子量的最佳预测指标。
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