Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure
Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR) method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfu...
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doaj-b424ed68685d4732b8ac97b261e4bc452020-11-24T22:51:22ZengMDPI AGMolecules1420-30492015-05-012058270828610.3390/molecules20058270molecules20058270Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection ProcedureYong-Hong Zhang0Zhi-Ning Xia1Li Yan2Shu-Shen Liu3Medicine Engineering Research Center, School of Pharmacy, Chongqing Medical University, Chongqing 400016, ChinaCollege of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400030, ChinaDepartment of Chinese Traditional Medicine, Chongqing Medical University, Chongqing 400016, ChinaState Key Laboratory of Pollution Control and Resources Reuse, Key Laboratory of Yangtze River Water Environment, Ministry of Education, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, ChinaAssessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR) method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS) variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI). The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14). The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.http://www.mdpi.com/1420-3049/20/5/8270placental barrier permeabilitydescriptors based on Dragon softwarePLS regressionvariable importance in projection (VIP)validationapplication domain |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yong-Hong Zhang Zhi-Ning Xia Li Yan Shu-Shen Liu |
spellingShingle |
Yong-Hong Zhang Zhi-Ning Xia Li Yan Shu-Shen Liu Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure Molecules placental barrier permeability descriptors based on Dragon software PLS regression variable importance in projection (VIP) validation application domain |
author_facet |
Yong-Hong Zhang Zhi-Ning Xia Li Yan Shu-Shen Liu |
author_sort |
Yong-Hong Zhang |
title |
Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure |
title_short |
Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure |
title_full |
Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure |
title_fullStr |
Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure |
title_full_unstemmed |
Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure |
title_sort |
prediction of placental barrier permeability: a model based on partial least squares variable selection procedure |
publisher |
MDPI AG |
series |
Molecules |
issn |
1420-3049 |
publishDate |
2015-05-01 |
description |
Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR) method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS) variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI). The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14). The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs. |
topic |
placental barrier permeability descriptors based on Dragon software PLS regression variable importance in projection (VIP) validation application domain |
url |
http://www.mdpi.com/1420-3049/20/5/8270 |
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