Feng Qiushi, De Chavez Danjo, Kihlberg Jan, Poongavanam Vasanthanathan
Department of Chemistry-BMC, Uppsala University, SE-75123, Uppsala, Sweden.
Sci Data. 2025 Jan 3;12(1):10. doi: 10.1038/s41597-024-04302-z.
The process of developing new drugs is arduous and costly, particularly for targets classified as "difficult-to-drug." Macrocycles show a particular ability to modulate difficult-to-drug targets, including protein-protein interactions, while still allowing oral administration. However, the determination of membrane permeability, critical for reaching intracellular targets and for oral bioavailability, is laborious and expensive. In silico methods are a cost-effective alternative, enabling predictions prior to compound synthesis. Here, we present a comprehensive online database ( https://swemacrocycledb.com/ ), housing 5638 membrane permeability datapoints for 4216 nonpeptidic macrocycles, curated from the literature, patents, and bioactivity repositories. In addition, we present a new descriptor, the "amide ratio" (AR), that quantifies the peptidic nature of macrocyclic compounds, enabling the classification of peptidic, semipeptidic, and nonpeptidic macrocycles. Overall, this resource fills a gap among existing databases, offering valuable insights into the membrane permeability of nonpeptidic and semipeptidic macrocycles, and facilitating predictions for drug discovery projects.
开发新药的过程艰巨且成本高昂,对于被归类为“难成药”的靶点而言尤其如此。大环化合物显示出特别的能力来调节难成药靶点,包括蛋白质 - 蛋白质相互作用,同时仍允许口服给药。然而,膜通透性的测定对于实现细胞内靶点和口服生物利用度至关重要,这一过程既费力又昂贵。计算机模拟方法是一种经济高效的替代方案,能够在化合物合成之前进行预测。在此,我们展示了一个综合在线数据库(https://swemacrocycledb.com/),其中包含从文献、专利和生物活性库中整理出来的4216种非肽大环化合物的5638个膜通透性数据点。此外,我们提出了一种新的描述符,即“酰胺比”(AR),它可以量化大环化合物的肽性,从而对肽类、半肽类和非肽类大环化合物进行分类。总体而言,该资源填补了现有数据库之间的空白,为非肽类和半肽类大环化合物的膜通透性提供了有价值的见解,并有助于药物发现项目的预测。