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ISSN 1000-6818CN 11-1892/O6CODEN WHXUEU
物理化学学报 >> 2017,Vol.33>> Issue(6)>> 1160-1170     doi: 10.3866/PKU.WHXB201704051         English Abstract
Prediction of Blood-to-Brain Barrier Partitioning of Drugs and Organic Compounds Using a QSPR Approach
GOLMOHAMMADI Hassan1, DASHTBOZORGI Zahra2, KHOOSHECHIN Sajad2
1 Young Researchers and Elite Club, Yadegar-e-Imam Khomeini(RAH) Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran;
2 Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran
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The purpose of this study was to develop a quantitative structure-property relationship (QSPR) model based on the enhanced replacement method (ERM) and support vector machine (SVM) to predict the blood-to-brain barrier partitioning behavior (logBB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method (ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R2, between experimental results and predicted logBB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the logBB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.



关键词: Quantitative structure-activity relationship   Blood-to-brain barrier partitioning   Drug   Enhanced replacement method   Support vector machine  
收稿日期 2017-02-05 修回日期 2017-03-02 网出版日期 2017-04-05
通讯作者: GOLMOHAMMADI Hassan Email: Hassan.gol@gmail.com


引用文本: GOLMOHAMMADI Hassan, DASHTBOZORGI Zahra, KHOOSHECHIN Sajad. Prediction of Blood-to-Brain Barrier Partitioning of Drugs and Organic Compounds Using a QSPR Approach[J]. 物理化学学报, 2017,33(6): 1160-1170.
GOLMOHAMMADI Hassan, DASHTBOZORGI Zahra, KHOOSHECHIN Sajad. Prediction of Blood-to-Brain Barrier Partitioning of Drugs and Organic Compounds Using a QSPR Approach[J]. Acta Phys. -Chim. Sin., 2017, 33(6): 1160-1170.    doi: 10.3866/PKU.WHXB201704051

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