title: Prediction of placental barrier permeability: a model based on partial least squares variable selection procedure.
abstract: 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.
authors.affiliation: Medicine Engineering Research Center, School of Pharmacy, Chongqing Medical University, Chongqing 400016, China. zhyvonne26@126.com.
authors.forename: Yong-Hong
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400030, China. znxia@cqu.edu.cn.
authors.forename: Zhi-Ning
authors.initials: ZN
authors.lastname: Xia
authors.affiliation: Department of Chinese Traditional Medicine, Chongqing Medical University, Chongqing 400016, China. ly200802958@163.com.
authors.forename: Li
authors.initials: L
authors.lastname: Yan
authors.affiliation: State 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, China. ssliuhl@263.net.
authors.forename: Shu-Shen
authors.initials: SS
authors.lastname: Liu
mesh_terms: D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D008954:Models, Biological; D010539:Permeability; D010920:Placenta / Q000378:metabolism*; D011247:Pregnancy; D021281:Quantitative Structure-Activity Relationship