基于曲线回归模型和拓扑指标的QSPR分析

IF 1 Q4 CHEMISTRY, MULTIDISCIPLINARY Iranian journal of mathematical chemistry Pub Date : 2019-12-01 DOI:10.22052/IJMC.2019.191865.1448
Ozge Colakoglu Havare
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引用次数: 8

摘要

拓扑指数是通过分子图g得到的分子结构的实数。拓扑指数用于化学、纳米技术和药理学领域的QSPR、QSAR和结构设计。此外,物理化学性质,如沸点,蒸发焓和稳定性可以通过QSAR/QSPR模型估计。本研究采用Gutman指数、产品连通性Banhatti指数、度方差指数和Sigma指数设计了QSPR (Quantitative Structure-Property Relationship)模型来预测单羧酸的热力学性质。利用曲线回归方法分析了热力学性质与拓扑指标之间的关系。它与曲线回归模型的线性、二次和三次方程一起使用。然后比较这些回归模型。
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QSPR Analysis with Curvilinear Regression Modeling and Topological Indices
Topological indices are the real number of a molecular structure obtained via molecular graph G. Topological indices are used for QSPR, QSAR and structural design in chemistry, nanotechnology, and pharmacology. Moreover, physicochemical properties such as the boiling point, the enthalpy of vaporization, and stability can be estimated by QSAR/QSPR models. In this study, the QSPR (Quantitative Structure-Property Relationship) models were designed using the Gutman index, the product connectivity Banhatti index, the Variance of degree index, and the Sigma index to predict the thermodynamic properties of monocarboxylic acids. The relationship analyses between the thermodynamic properties and the topological indices were done by using the curvilinear regression method. It is used with the linear, quadratic and cubic equations of the curvilinear regression model. These regression models were then compared.
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来源期刊
Iranian journal of mathematical chemistry
Iranian journal of mathematical chemistry CHEMISTRY, MULTIDISCIPLINARY-
CiteScore
2.10
自引率
7.70%
发文量
0
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