药品的计算建模,重点是穿越血脑屏障
Patrícia Alencar Alves1, Luana Cristina Camargo2, Gabriel Mendonça de Souza1
1In Silico Toxicology Laboratory (inSiliTox), Department of Pharmacy, Health Sciences School, University of Brasilia, Brasilia 71910-900, Brazil.
开发新药具有挑战性,特别是在大脑输送方面. 本综述探讨了计算方法和纳米技术,以改善通过血脑屏障 (BBB) 的药物透,以改善中枢神经系统 (CNS) 药物输送.
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
- 纳米技术纳米技术
背景情况:
- 药物发现是昂贵的,手动的,面临生物可用性挑战.
- 中枢神经系统药物开发受到血脑屏障 (BBB) 透的阻碍.
- 计算方法对于预测药物特性和克服输送障碍至关重要.
研究的目的:
- 审查用于评估BBB透性和目标交付的计算技术.
- 探索前药物和纳米粒子等配方策略,以增强中枢神经系统药物输送.
- 讨论用于合理药物设计的in silico和纳米技术方法的整合.
主要方法:
- 定量结构-活动关系 (QSAR)
- 机器学习模型的机器学习模型
- 分子动力学模拟的模拟.
- 运输机模型 运输机模型
- 基于原药和纳米粒子的输送系统.
主要成果:
- 各种计算方法提供了关于BBB透性的见解,具有明显的优点和局限性.
- 产药和纳米颗粒可以通过酶激活和输送器吸收来增强BBB透.
- 整合计算和配方策略有助于设计选择性,BBB透的药物.
结论:
- 计算和纳米技术策略对于改善整个BBB的药物输送至关重要.
- 合理的药物设计需要理解BBB选择性原则.
- 这些方法最大限度地减少了非目标效应,并促进了中枢神经系统 (CNS) 的治疗方法.
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