一个非性宏循环的膜透性数据库
Qiushi Feng1, Danjo De Chavez1, Jan Kihlberg2
1Department of Chemistry-BMC, Uppsala University, SE-75123, Uppsala, Sweden.
Scientific data
|January 3, 2025
概括
开发新药对困难的目标来说是具有挑战性的. 这项研究引入了一个数据库和一个新的指标来预测宏循环膜透性,帮助药物发现.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 药物开发是昂贵的,特别是对于难以获得的药物目标.
- 宏观循环对调节具有挑战性的目标和口服管理具有前景.
- 评估膜透性用于药物开发是艰苦而昂贵的.
研究的目的:
- 创建一个全面的在线数据库的宏循环膜透性数据.
- 引入一种新的描述符,即胺比率 (AR),用于分类宏循环.
- 为了在药物发现中促进膜透性的in silico预测.
主要方法:
- 从文献,专利和存储库中对4216个非性宏循环进行了精选,共计5638个膜透度数据点.
- 开发了胺比率 (AR) 描述符,以量化宏循环的性质.
- 建立了一个在线数据库 (https://swemacrocycledb.com/) 提供可访问的数据和预测.
主要成果:
- 该数据库提供了对非基和半基宏循环的广泛的膜透性数据.
- 胺比率有效地将宏循环分为性,半性和非性类别.
- 使用数据库和AR进行in silico预测可以加速药物发现.
结论:
- 开发的数据库和AR描述符解决了宏循环药物发现资源的关键缺口.
- 这种资源使膜透率的成本有效预测成为可能,这对于口服生物可用性和细胞内向性至关重要.
- 为难以获得的药物目标设计和选择宏循环药物候选剂提供便利.
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