拓扑指数
数量结构-活动关系
索引(排版)
线性回归
拓扑(电路)
回归分析
分子描述符
数学
化学
计算机科学
立体化学
统计
组合数学
万维网
作者
Anil Kumar Soni,Gajendra Pal Singh,Vishnu Kumar Sahu
出处
期刊:Open Journal of Applied Sciences
[Scientific Research Publishing, Inc.]
日期:2021-01-01
卷期号:11 (05): 577-584
标识
DOI:10.4236/ojapps.2021.115041
摘要
Prediction of antagonistic activity of β-carboline and its thirteen derivatives has been made using topological descriptors viz, connectivity index, and kappa shape index of different orders. For evaluation of values of descriptor, molecular modeling and geometry optimization of all the compounds were carried out with CAChe Pro software by opting semiempirical PM3 method using MOPAC 2002. For prediction of activity multiple linear regression analysis (MLR) was performed. MLR analysis has been made by Project Leader Software associated with CAChe by using the above descriptors as independent variables and biological activity as dependent variables. We were performed leave-one-out methods and the result reflected a direct relationship between biological activity and connectivity index of zero order, while indirect relationship with connectivity index of second order and thus connectivity index is a reliable descriptor to predict the biological activity of β-carboline and its various derivatives.
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