一种基于计算物理的方法来预测未结合的大脑与血分区系数,Kp,uu
Morgan Lawrenz1, Mats Svensson2, Mitsunori Kato2
1Schrödinger Inc., San Diego, California 92122, United States.
Journal of chemical information and modeling
|June 2, 2023
概括
使用量子力学的基于物理学的新计算方法预测了中枢神经系统 (CNS) 药物的血脑屏障 (BBB) 透. 这种方法可以准确预测药物分配,有助于开发有效的中枢神经系统治疗方法.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算化学计算化学
- 神经科学是一个神经科学.
背景情况:
- 血脑屏障 (BBB) 对于保护大脑免受有害物质的影响至关重要.
- 有效的中枢神经系统 (CNS) 药物输送需要最佳透BBB.
- 目前用于预测BBB透的方法,如药物化学策略和in silico模型,在直接预测未结合的大脑/血比率 (Kp,uu) 中存在局限性.
研究的目的:
- 引入一种新的基于物理的计算方法来预测Kp,uu.
- 评估这种新方法在中枢神经系统药物发现中的准确性和实用性.
主要方法:
- 开发了一种基于量子力学 (QM) 的溶解能量 (E-sol) 计算模型.
- 应用了E-sol方法来预测中枢神经系统候选药物的Kp,uu.
- 使用内部药物发现计划数据验证了模型的性能.
主要成果:
- 该E-sol方法显示了强大的预测能力为Kp,uu.
- 在预测中实现了79%的分类准确性.
- 线性回归分析得出了0.61的R值,表明模型适合.
结论:
- 基于QM的E-sol方法为预测BBB透提供了一个强大而准确的工具.
- 这种方法可以显著提高中枢神经系统药物发现计划的效率.
- 基于物理学的模型为Kp,uu.提供了对现有预测策略的有价值的替代方案.
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