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胆红素转运蛋白转运活性的实验测定与预测。

Experimental determination and prediction of bilitranslocase transport activity.

机构信息

Laboratory of Chemometrics, National Institute of Chemistry, Hajdrihova 19, SI-1115 Ljubljana, Slovenia.

出版信息

Anal Chim Acta. 2011 Oct 31;705(1-2):322-33. doi: 10.1016/j.aca.2011.07.004. Epub 2011 Jul 14.

DOI:10.1016/j.aca.2011.07.004
PMID:21962375
Abstract

The transport activity of a membrane protein, bilitranslocase (T.C. # 2.A.65.1.1), which acts as a transporter of bilirubin from blood to liver cells, was experimentally determined for a large set of various endogenous compounds, drugs, purine and pyrimidine derivatives. On these grounds, the structure-activity models were developed following the OECD principles of QSAR models and their predictive ability for new chemicals was evaluated. The applicability domain of the models was estimated by Euclidean distances criteria according to the applied modeling method. The selection of the most influential structural variables was an important stage in the adopted modeling methodology. The interpretation of selected variables was performed in order to get an insight into the mechanism of transport through the cell membrane via bilitranslocase. Validation of the optimized models was performed by a previously determined validation set. The classification model was build to separate active from inactive compounds. The resulting accuracy, sensitivity, and specificity were 0.73, 0.89, and 0.64, respectively. Only active compounds were used to develop a predictive model for bilitranslocase inhibition constants. The model showed good predictive ability; Root Mean Squared error of the validation set, RMS(V)=0.29 log units.

摘要

一种膜蛋白(T.C. # 2.A.65.1.1)的转运活性被实验测定,该蛋白作为胆红素从血液到肝细胞的转运蛋白,用于一系列不同的内源性化合物、药物、嘌呤和嘧啶衍生物。基于这些结果,按照 OECD 定量构效关系模型的原则开发了结构-活性模型,并评估了它们对新化学物质的预测能力。模型的适用性域通过欧几里得距离标准根据应用的建模方法进行估计。在采用的建模方法中,选择最有影响力的结构变量是一个重要阶段。选择的变量的解释是为了深入了解通过胆红素转运蛋白穿过细胞膜的转运机制。通过先前确定的验证集对优化后的模型进行验证。分类模型用于分离活性和非活性化合物。所得的准确性、灵敏度和特异性分别为 0.73、0.89 和 0.64。仅使用活性化合物来开发预测胆红素转运蛋白抑制常数的模型。该模型显示出良好的预测能力;验证集的均方根误差,RMS(V)=0.29 个对数单位。

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