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Abstract：
In CNS drug discovery, the estimation of brain exposure to lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro, and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand unbound brain exposure by deriving the Kp,uu parameter and the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. The MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores, and various machine learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds, building of a CNS penetrable compounds library, and optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand the reliability and ability of these methods to predict CNS penetration. We review the in silico, in vitro, and in vivo data and their correlation with each other, as well as assess published experimental and computational approaches to predict the BBB penetrability of compounds.
摘要：
在中枢神经系统药物发现中，估计大脑暴露于铅化合物对其优化至关重要。化合物需要穿过血脑屏障(BBB)以达到CNS中的药理学靶标。BBB是一个复杂的系统，涉及转运和外排转运蛋白如P-糖蛋白（P-gp）和乳腺癌耐药蛋白（BCRP）的被动和主动机制，在小分子的中枢神经系统渗透中起着至关重要的作用。几个在体内，在体外，和计算机模拟方法可用于估计人脑穿透力。临床前物种用作体内模型，通过推导Kp来了解未结合的大脑暴露，用血浆和脑游离分数校正的uu参数和脑/血浆暴露比。MDCK-mdr1（用编码人P-gp的MDR1基因转染的MadinDarby犬肾细胞）测定法是常用的体外测定法，用于评估化合物的通透性和人外排。预测大脑暴露的计算机模拟方法，如CNSMPO，CNSBBB评分,和各种机器学习模型，帮助节省成本，加快化合物发现和优化的所有阶段。这些方法可以筛选虚拟化合物，建立中枢神经系统可穿透的化合物库，和优化中枢神经系统渗透的铅分子。因此,了解这些方法预测中枢神经系统渗透的可靠性和能力至关重要。我们审查计算机，在体外，和体内数据以及它们之间的相关性，以及评估已发表的实验和计算方法来预测化合物的BBB渗透性。
