Center for Drug Delivery System, Shanghai Institute of Materia Medica, State Key Laboratory of Drug Research, Chinese Academy of Sciences, Shanghai 201203, China.
Biopharm Drug Dispos. 2011 Sep;32(6):333-42. doi: 10.1002/bdd.762. Epub 2011 Jul 29.
A novel method, named as the plasma protein-interaction QSAR analysis (PPI-QSAR) was used to construct the QSAR models for human plasma protein binding. The intra-molecular descriptors of drugs and inter-molecular interaction descriptors resulted from the docking simulation between drug molecules and human serum albumin were included as independent variables in this method. A structure-based in silico model for a data set of 65 antibiotic drugs was constructed by the multiple linear regression method and validated by the residual analysis, the normal Probability-Probability plot and Williams plot. The R(2) and Q(2) values of the entire data set were 0.87 and 0.77, respectively, for the training set were 0.86 and 0.72, respectively. The results indicated that the fitted model is robust, stable and satisfies all the prerequisites of the regression models. Combining intra-molecular descriptors with inter-molecular interaction descriptors between drug molecules and human serum albumin, the drug plasma protein binding could be modeled and predicted by the PPI-QSAR method successfully.
一种名为“血浆蛋白相互作用 QSAR 分析（PPI-QSAR）”的新方法被用于构建人血浆蛋白结合的 QSAR 模型。该方法将药物的分子内描述符和药物分子与人血清白蛋白之间的分子间相互作用描述符作为自变量纳入其中。通过多元线性回归方法，基于结构的计算模型构建了一个包含 65 种抗生素药物的数据集，并通过残差分析、正态概率-概率图和 Williams 图进行了验证。整个数据集的 R(2)和 Q(2)值分别为 0.87 和 0.77，对于训练集，R(2)和 Q(2)值分别为 0.86 和 0.72。结果表明，拟合模型是稳健的、稳定的，并且满足回归模型的所有前提条件。通过将分子内描述符与药物分子与人血清白蛋白之间的分子间相互作用描述符相结合，PPI-QSAR 方法成功地对药物血浆蛋白结合进行了建模和预测。
