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A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters.
Bioinorganic Chemistry and Applications ( IF 3.8 ) Pub Date : 2017-07-03 , DOI: 10.1155/2017/4914272
Li Wen 1 , Qing Li 2 , Wei Li 1 , Qiao Cai 1 , Yong-Ming Cai 3
Affiliation  

Hydroxyl benzoic esters are preservative, being widely used in food, medicine, and cosmetics. To explore the relationship between the molecular structure and antibacterial activity of these compounds and predict the compounds with similar structures, Quantitative Structure-Activity Relationship (QSAR) models of 25 kinds of hydroxyl benzoic esters with the quantum chemical parameters and molecular connectivity indexes are built based on support vector machine (SVM) by using R language. The External Standard Deviation Error of Prediction (), fitting correlation coefficient (), and leave-one-out cross-validation () are used to value the reliability, stability, and predictive ability of models. The results show that and of 4 kinds of nonlinear models are more than 0.6 and is 0.213, 0.222, 0.189, and 0.218, respectively. Compared with the multiple linear regression (MLR) model (, RSD = 0.260), the correlation coefficient and the standard deviation are both better than MLR. The reliability, stability, robustness, and external predictive ability of models are good, particularly of the model of linear kernel function and eps-regression type. This model can predict the antimicrobial activity of the compounds with similar structure in the applicability domain.

中文翻译:

基于SVM的羟基苯甲酸酯类化合物的QSAR研究。

羟基苯甲酸酯是防腐剂,被广泛用于食品,药品和化妆品中。为了探索这些化合物的分子结构与抗菌活性之间的关系并预测具有相似结构的化合物,建立了具有量子化学参数和分子连通性指数的25种羟基苯甲酸酯的定量结构-活性关系(QSAR)模型。使用R语言在支持向量机(SVM)上运行。预测的外部标准偏差(),拟合相关系数()和留一法交叉验证()用于评估模型的可靠性,稳定性和预测能力。结果表明,与4种非线性模型均超过0.6,分别为0.213、0.222、0.189和0.218。与多元线性回归(MLR)模型(RSD = 0.260)相比,相关系数和标准差均优于MLR。模型的可靠性,稳定性,鲁棒性和外部预测能力都很好,尤其是线性核函数和eps回归类型的模型。该模型可以预测适用范围内结构相似的化合物的抗菌活性。
更新日期:2017-07-03
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