Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

被引:0
作者
Wang, Hui [1 ]
Yuan, Haijian [1 ]
Li, Shujun [1 ]
Li, Zhuo [1 ]
Jiang, Mingyue [1 ]
Tang, Jiafa [1 ]
机构
[1] Northeast Forestry Univ, Minist Educ, Key Lab Biobased Mat Sci & Technol, Harbin 150040, Peoples R China
来源
BIORESOURCES | 2015年 / 10卷 / 04期
基金
高等学校博士学科点专项科研基金;
关键词
Cinnamaldehyde analogues and derivatives; Molar concentration; Activity prediction; Quantitative structure-activity relationship (QSAR); Cinnamaldehyde Schiff base; ESSENTIAL OILS; WOOD; RETENTION;
D O I
10.15376/biores.10.4.7921-7935
中图分类号
TB3 [工程材料学]; TS [轻工业、手工业、生活服务业];
学科分类号
0805 ; 080502 ; 0822 ;
摘要
In past work, QSAR (quantitative structure-activity relationship) models of cinnamaldehyde analogues and derivatives (CADs) have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.
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页码:7921 / 7935
页数:15
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