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用于预测中枢神经系统药物研发中血脑屏障通透性的定量构效关系模型的现状与未来展望

Current State and Future Perspectives in QSAR Models to Predict Blood- Brain Barrier Penetration in Central Nervous System Drug R&D.

作者信息

Morales Juan F, Montoto Sebastian Scioli, Fagiolino Pietro, Ruiz Maria E

机构信息

Quality Control of Medications, Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata (B1900AJI), Buenos Aires,. Argentina.

出版信息

Mini Rev Med Chem. 2017;17(3):247-257. doi: 10.2174/1389557516666161013110813.

Abstract

The Blood-Brain Barrier (BBB) is a physical and biochemical barrier that restricts the entry of certain drugs to the Central Nervous System (CNS), while allowing the passage of others. The ability to predict the permeability of a given molecule through the BBB is a key aspect in CNS drug discovery and development, since neurotherapeutic agents with molecular targets in the CNS should be able to cross the BBB, whereas peripherally acting agents should not, to minimize the risk of CNS adverse effects. In this review we examine and discuss QSAR approaches and current availability of experimental data for the construction of BBB permeability predictive models, focusing on the modeling of the biorelevant parameter unbound partitioning coefficient (Kp,uu). Emphasis is made on two possible strategies to overcome the current limitations of in silico models: considering the prediction of brain penetration as a multifactorial problem, and increasing experimental datasets through accurate and standardized experimental techniques.

摘要

血脑屏障(BBB)是一种物理和生化屏障,它限制某些药物进入中枢神经系统(CNS),同时允许其他药物通过。预测给定分子通过血脑屏障的通透性的能力是中枢神经系统药物发现和开发的一个关键方面,因为在中枢神经系统中有分子靶点的神经治疗药物应该能够穿过血脑屏障,而外周作用药物则不应穿过,以尽量降低中枢神经系统不良反应的风险。在本综述中,我们研究并讨论了用于构建血脑屏障通透性预测模型的定量构效关系(QSAR)方法和当前可用的实验数据,重点是生物相关参数非结合分配系数(Kp,uu)的建模。强调了两种克服当前计算机模拟模型局限性的可能策略:将脑渗透预测视为一个多因素问题,以及通过准确和标准化的实验技术增加实验数据集。

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