Iyer Manisha, Tseng Y J, Senese C L, Liu Jianzhong, Hopfinger A J
Laboratory of Molecular Modeling and Design, College of Pharmacy, University of Illinois at Chicago, Chicago, IL 60612-7231, USA.
Mol Pharm. 2007 Mar-Apr;4(2):218-31. doi: 10.1021/mp0600900.
Membrane-interaction [MI]-QSAR analysis, which includes descriptors explicitly derived from simulations of solutes [drugs] interacting with phospholipid membrane models, was used to construct QSAR models for human oral intestinal drug absorption. A data set of 188 compounds, which are mainly drugs, was divided into a parent training set of 164 compounds and a test set of 24 compounds. Stable, but not highly fit [R2 = 0.68] MI-QSAR models could be built for all 188 compounds. However, the relatively large number [47] of drugs having 100% absorption, as well as all zwitterionic compounds [11], had to be eliminated from the training set in order to construct a linear five-term oral absorption diffusion model for 106 compounds which was both stable [R2 = 0.82, Q2 = 0.79] and predictive given the test set compounds were predicted with nearly the same average accuracy as the compounds of the training set. Intermolecular membrane-solute descriptors are essential to building good oral absorption models, and these intermolecular descriptors are displaced in model optimizations and intramolecular solute descriptors found in published oral absorption QSAR models. A general form for all of the oral intestinal absorption MI-QSAR models has three classes of descriptors indicative of three thermodynamic processes: (1) solubility and partitioning, (2) membrane-solute interactions, and (3) flexibility of the solute and/or membrane. The intestinal oral absorption MI-QSAR models were compared to MI-QSAR models previously developed for Caco-2 cell permeation and for blood-brain barrier penetration. The MI-QSAR models for all three of these ADME endpoints share several common descriptors, and suggest a common mechanism of transport across all three barriers. A further analysis of these three types of MI-QSAR models has been done to identify descriptor-term differences across these three models, and the corresponding differences in thermodynamic transport behavior of the three barriers.
膜相互作用[MI]-定量构效关系分析，包括从溶质[药物]与磷脂膜模型相互作用的模拟中明确推导出来的描述符，被用于构建人类口服肠道药物吸收的定量构效关系模型。一个包含188种化合物（主要是药物）的数据集被分为一个由164种化合物组成的母本训练集和一个由24种化合物组成的测试集。可以为所有188种化合物构建稳定但拟合度不高（R2 = 0.68）的MI-定量构效关系模型。然而，为了构建一个针对106种化合物的线性五项口服吸收扩散模型，必须从训练集中剔除相对大量（47种）具有100%吸收率的药物以及所有两性离子化合物（11种），该模型既稳定（R2 = 0.82，Q2 = 0.79），又具有预测性，因为测试集化合物的预测平均准确率与训练集化合物相近。分子间膜-溶质描述符对于构建良好的口服吸收模型至关重要，并且这些分子间描述符在模型优化中被取代，而在已发表的口服吸收定量构效关系模型中发现的是分子内溶质描述符。所有口服肠道吸收MI-定量构效关系模型的一般形式有三类描述符，分别指示三个热力学过程：(1) 溶解度和分配，(2) 膜-溶质相互作用，以及(3) 溶质和/或膜的柔韧性。将肠道口服吸收MI-定量构效关系模型与先前为Caco-2细胞渗透和血脑屏障穿透开发的MI-定量构效关系模型进行了比较。这三个ADME终点的MI-定量构效关系模型共享几个共同的描述符，并暗示了跨越所有三个屏障的共同转运机制。对这三种类型的MI-定量构效关系模型进行了进一步分析，以确定这三个模型之间描述符项的差异，以及三个屏障在热力学转运行为方面的相应差异。
