Blood-brain barrier permeation models: Discriminating between potential CNS and non-CNS drugs including P-glycoprotein substrates
Blood-brain barrier permeation models: Discriminating between potential CNS and non-CNS drugs including P-glycoprotein substrates
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DOI：
10.1021/ci034205d
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发表时间：
2004-01-01
期刊：
影响因子：
--
通讯作者：
Lahana, R
中科院分区：
文献类型：
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作者：
Adenot, M;Lahana, R
本论文的目的是设计一个基于WDI的大型异构CNS药物库（类似于1700个化合物），并利用血脑屏障（BBB）渗透和P-gp底物的QSAR模型绘制CNS药物图谱。CNS文库最终包括1336种BBB-交叉药物（BBB+）、259种非BBB-交叉分子（BBB-）和91种P-gp底物（BBB+或BBB-）。判别分析和PLS-DA已被用来模拟血脑屏障渗透的被动扩散成分和P-gp底物的潜在理化要求。已建议使用三类解释变量（C-diff、BBB pred、PGP（pred））来表示连续标度内的渗透水平，从两类数据（BBB+/ BBB-）开始，允许使用隶属度评分给出每种化合物属于活性类别的程度。最后，统计数据分析表明，在大多数情况下，一些非常简单的描述符足以评估血脑屏障渗透，具有很高的分类药物的比率。此外，“中枢神经系统药物”地图，包括P-gp底物和准确地反映药物在体内的行为，提出作为中枢神经系统药物虚拟筛选的工具。
The aim of this article is to present the design of a large heterogeneous CNS library (similar to1700 compounds) from WDI and mapping CNS drugs using QSAR models of blood-brain barrier (BBB) permeation and P-gp substrates. The CNS library finally includes 1336 BBB-crossing drugs (BBB+), 259 molecules non-BBB-crossing (BBB-), and 91 P-gp substrates (either BBB+ or BBB-). Discriminant analysis and PLS-DA have been used to model the passive diffusion component of BBB permeation and potential physicochemical requirement of P-gp substrates. Three categories of explanatory variables (C-diff, BBBpred, PGP(pred)) have been suggested to express the level of permeation within a continuous scale, starting from two classes data (BBB+/ BBB-), allowing that the degree to Which each compound belongs to an activity class is given using a membership score. Finally, statistical data analyses have shown that some very simple descriptors are sufficient to evaluate BBB permeation in most cases, with a high rate of well-classified drugs. Moreover, a "CNS drugs" map, including P-gp substrates and accurately reflecting the in vivo behavior of drugs, is proposed as a tool for CNS drug virtual screening.