A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters
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 (QSA...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Bioinorganic Chemistry and Applications |
| Online Access: | http://dx.doi.org/10.1155/2017/4914272 |
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| author | Li Wen Qing Li Wei Li Qiao Cai Yong-Ming Cai |
| author_facet | Li Wen Qing Li Wei Li Qiao Cai Yong-Ming Cai |
| author_sort | Li Wen |
| collection | DOAJ |
| description | 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 (SDEPext), fitting correlation coefficient (R2), and leave-one-out cross-validation (Q2LOO) are used to value the reliability, stability, and predictive ability of models. The results show that R2 and Q2LOO of 4 kinds of nonlinear models are more than 0.6 and SDEPext is 0.213, 0.222, 0.189, and 0.218, respectively. Compared with the multiple linear regression (MLR) model (R2=0.421, 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. |
| format | Article |
| id | doaj-art-ce1f8d4628e9442e857c0c74948d6366 |
| institution | Kabale University |
| issn | 1565-3633 1687-479X |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Bioinorganic Chemistry and Applications |
| spelling | doaj-art-ce1f8d4628e9442e857c0c74948d63662025-02-03T05:50:57ZengWileyBioinorganic Chemistry and Applications1565-36331687-479X2017-01-01201710.1155/2017/49142724914272A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic EstersLi Wen0Qing Li1Wei Li2Qiao Cai3Yong-Ming Cai4School of Public Health, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Centre, Guangzhou 510006, ChinaGuangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, ChinaSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Centre, Guangzhou 510006, ChinaSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Centre, Guangzhou 510006, ChinaSchool of Medical Information Engineering, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Centre, Guangzhou 510006, ChinaHydroxyl 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 (SDEPext), fitting correlation coefficient (R2), and leave-one-out cross-validation (Q2LOO) are used to value the reliability, stability, and predictive ability of models. The results show that R2 and Q2LOO of 4 kinds of nonlinear models are more than 0.6 and SDEPext is 0.213, 0.222, 0.189, and 0.218, respectively. Compared with the multiple linear regression (MLR) model (R2=0.421, 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.http://dx.doi.org/10.1155/2017/4914272 |
| spellingShingle | Li Wen Qing Li Wei Li Qiao Cai Yong-Ming Cai A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters Bioinorganic Chemistry and Applications |
| title | A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters |
| title_full | A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters |
| title_fullStr | A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters |
| title_full_unstemmed | A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters |
| title_short | A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters |
| title_sort | qsar study based on svm for the compound of hydroxyl benzoic esters |
| url | http://dx.doi.org/10.1155/2017/4914272 |
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