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首页> 外文期刊>Current topics in medicinal chemistry >In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life.
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In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life.

机译:在计算机模拟中对大脑暴露的预测:无药物分数,未结合的大脑与血浆的浓度比和平衡半衰期。

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The focus of CNS drug pharmacokinetics programs has recently shifted from determining the total concentrations in brain and blood to considering also unbound fractions and concentrations. Unfortunately, assessing unbound brain exposure experimentally requires demanding in vivo and in vitro studies. We propose a physical model, based on lipid binding and pH partitioning, to predict in silico the unbound volume of distribution in the brain. The model takes into account the partition of a drug into lipids, interstitial fluid and intracellular compartments of the brain. The results are in good agreement with the experimental data, suggesting that the contributions of lipid binding and pH partitioning are important in determining drug exposure in brain. The predicted values are used, together with predictions for plasma protein binding, as corrective terms in a second model to derive the unbound brain to plasma concentration ratio starting from experimental values of total concentration ratio. The calculated values of brain free fraction and passive permeability are also used to qualitatively determine the brain to plasma equilibration time in a model that shows promising results but is limited to a very small set of compounds. The models we propose are a step forward in understanding and predicting pharmacologically relevant exposure in brain starting from compounds' chemical structure and neuropharmacokinetics, by using experimental total brain to plasma ratios, in silico calculated properties and simple physics-based approaches. The models can be used in central nervous system drug discovery programs for a fast and cheap assessment of unbound brain exposure. For existing compounds, the unbound ratios can be derived from experimental values of total brain to plasma ratios. For both existing and hypothetical compounds, the unbound volume of distribution due to lipid binding and pH partitioning can be calculated starting only from the chemical structure.
机译:最近,CNS药物药代动力学计划的重点已经从确定脑和血液中的总浓度转移到也考虑了未结合的分数和浓度。不幸的是,通过实验评估未绑定的大脑暴露量需要进行体内和体外研究。我们提出了一种基于脂质结合和pH分配的物理模型,以计算机模拟预测大脑中未分配的分布量。该模型考虑了将药物分配到大脑的脂质,间质液和细胞内区室。结果与实验数据非常吻合,表明脂质结合和pH分配的贡献对于确定大脑中的药物暴露很重要。预测值与血浆蛋白结合预测一起用作第二个模型中的校正项,从总浓度比的实验值开始推导未结合的脑与血浆的浓度比。脑自由分数和被动通透性的计算值还用于定性确定模型中脑到血浆的平衡时间,该模型显示出令人鼓舞的结果,但仅限于非常少量的化合物。我们提出的模型是通过使用实验性总脑与血浆的比率,计算机计算的特性和简单的基于物理的方法,从化合物的化学结构和神经药代动力学出发,从理解和预测脑中与药理学相关的暴露方面迈出的一步。该模型可用于中枢神经系统药物发现程序,以快速,廉价地评估未受约束的大脑暴露。对于现有化合物,未结合比率可以从总脑与血浆比率的实验值中得出。对于现有化合物和假设化合物,都可以仅从化学结构开始计算由于脂质结合和pH分配导致的未结合分布体积。

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