Predicting a Drug's Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data
Predicting a Drug's Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data
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DOI：
10.1021/acs.jpcb.7b02914
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发表时间：
2017-05-25
影响因子：
3.3
通讯作者：
Carpenter, Timothy S.
中科院分区：
文献类型：
--
作者：
Bennion, Brian J.;Be, Nicholas A.;Carpenter, Timothy S.
膜渗透性是药物设计过程中要考虑的关键特性，在处理具有细胞内靶点的小分子时尤其重要，因为它们的功效高度依赖于它们穿过膜的能力。在这项工作中，我们描述了使用伞采样分子动力学（MD）的计算建模，全面评估的被动渗透性档案的范围内的化合物通过脂质双层。该模型最初通过采用平行人工膜渗透性试验（PAMPA）的体外验证研究进行校准。该模型随后进行了评估，其定量预测的渗透率曲线的一系列定制合成和密切相关的化合物。结果显示，与PAMPA数据，相对于替代现有的方法，大大提高了协议。我们的工作介绍了一个计算模型，经历了渐进的成型和微调，作为其协同合作的结果，与许多在体外PAMPA渗透性测定。所提出的计算模型介绍了自己作为一个有用的，预测性的渗透率预测工具。
Membrane permeability is a key property to consider during the drug design process, and particularly vital when dealing with small molecules that have intracellular targets as their efficacy highly depends on their ability to cross the membrane. In this work, we describe the use of umbrella sampling molecular dynamics (MD) computational modeling to comprehensively assess the passive permeability profile of a range of compounds through a lipid bilayer. The model was initially calibrated through in vitro validation studies employing a parallel artificial membrane permeability assay (PAMPA). The model was subsequently evaluated for its quantitative prediction of permeability profiles for a series of custom synthesized and closely related compounds. The results exhibited substantially improved agreement with the PAMPA data, relative to alternative existing methods. Our work introduces a computational model that underwent progressive molding and fine-tuning as a result of its synergistic collaboration with numerous in vitro PAMPA permeability assays. The presented computational model introduces itself as a useful, predictive tool for permeability prediction.