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首页> 外文期刊>The Canadian Journal of Neurological Sciences: le Journal Canadien des Sciences Neurologiques >A mathematical model for prediction of drug molecule diffusion across the blood-brain barrier.
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A mathematical model for prediction of drug molecule diffusion across the blood-brain barrier.

机译:用于预测药物分子跨血脑屏障扩散的数学模型。

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BACKGROUND: Predicting the ability of drugs to enter the brain is a longstanding problem in neuropharmacology. The first step in creating a much-needed computational algorithm for predicting whether a drug will enter brain is to devise a rigorous mathematical model. METHODS: Employing two experimental measures of blood-brain barrier (BBB) penetrability (brain/plasma ratio and the brain-uptake index) and 14 theoretically derived biophysical predictors, a mathematical model was developed to quantitatively correlate molecular structure with ability to traverse the BBB. RESULTS: This mathematical model employs Stein's hydrogen bonding number and Randic's topological descriptors to correlate structure with ability to cross the BBB. The final model accurately predicts the ability of test molecules to cross the BBB. CONCLUSIONS: A mathematical method to predict blood-brain barrier penetrability of drug molecules has been successfully devised. As a result of bioinformatics, chemoinformatics and other informatics-based technologies, the number of small molecules being developed as potential therapeutics is increasing exponentially. A biophysically rigorous method to predict BBB penetrability will be a much-needed tool for the evaluation of these molecules.
机译:背景:预测药物进入大脑的能力是神经药理学中一个长期存在的问题。创建用于预测药物是否会进入大脑的急需的计算算法的第一步是设计一个严格的数学模型。方法:采用两种实验方法测量血脑屏障(BBB)的渗透性(脑/血浆比例和脑摄取指数)和14种理论得出的生物物理预测因子,建立了数学模型以定量关联分子结构与穿越BBB的能力。结果:该数学模型利用斯坦因的氢键数和兰迪奇的拓扑描述符将结构与穿越血脑屏障的能力联系起来。最终模型可以准确预测测试分子穿过血脑屏障的能力。结论:已经成功设计了一种预测药物分子血脑屏障穿透性的数学方法。由于生物信息学,化学信息学和其他基于信息学的技术的发展,作为潜在疗法的小分子的数量呈指数增长。严格的生物物理方法来预测BBB的渗透性将是评估这些分子的急需工具。

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