Structure‐based prediction of human intestinal membrane permeability for rapid in silico BCS classification
Structure‐based prediction of human intestinal membrane permeability for rapid in silico BCS classification
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DOI：
10.1002/bdd.1848
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发表时间：
2013-09
影响因子：
2.1
通讯作者：
Le Sun;Xiaohong Liu;Rongwu Xiang;Chunnuan Wu;Yongjun Wang;Yinghua Sun;Jin Sun;Zhonggui He
中科院分区：
文献类型：
--
作者：
Le Sun;Xiaohong Liu;Rongwu Xiang;Chunnuan Wu;Yongjun Wang;Yinghua Sun;Jin Sun;Zhonggui He
人体有效肠膜通透性是生物药物分类系统(BCS)对药物进行分类的两个重要指标之一，对药物口服吸收性能有重要影响。在这里，成功地开发了一个基于结构的PEF的电子预测模型，以便于在药物发现的早期阶段进行电子BCS分类，甚至在化合物合成之前。以7个结构参数为基础，建立了30种药物的定量构效关系。然后用多元线性回归方法建立模型，并用残差分析、正态概率-概率图和威廉姆斯图对模型进行内部验证。对于整个数据集，R2和调整后的R2值分别为0.782和0.712。结果表明，所建立的回归模型具有较好的稳健性和稳定性，满足回归模型的所有条件。对于102种受试药物，预测的PEF值与实验人体吸收分数(Fa)有很好的相关性。利用该模型对57种已按BCS分类的药物进行了高/低PEF分类，分类正确率为72%，表明该模型可用于药物发现早期的快速BCS分类。版权所有©2013 John Wiley&Sons，Ltd.
Human effective intestinal membrane permeability (Peff) is one of the two important indicators for drug classification according to the Biopharmaceutical Classification System (BCS), and contributes greatly to the performance of oral drug absorption. Here, a structure‐based in silico predictive model of Peff was developed successfully to facilitate in silico BCS classification in the early stage of drug discovery, even before the compound was synthesized. The quantitative structure–Peff relationship for 30 drugs was constructed based on seven structural parameters. Then the model was built by the multiple linear regression method and internally validated by the residual analysis, the normal probability–probability plot and the Williams plot. For the entire data set, the R2 and adjusted R2 values were 0.782 and 0.712, respectively. The results indicated that the fitted model was robust, stable and satisfied all the prerequisites of the regression models. As for the 102 tested drugs, the predicted Peff values had a good correlation with the experimental human absorbed fraction (Fa). This model was also used to perform high/low Peff classification for 57 drugs that have been classified according to the BCS, and 72% of drugs could be classified correctly, indicating that the developed model can be used for rapid BCS classification in the early stages of drug discovery. Copyright © 2013 John Wiley & Sons, Ltd.