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利用剑桥结构数据库(CSD)上的数据挖掘技术探索水合物的情况。

Exploring the hydrate landscape using data mining on the Cambridge structural database (CSD).

作者信息

Fu Minqi, Dai Jiayu, Xu Jingtao, Madsen Anders Østergaard, Rantanen Jukka

机构信息

Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, 2100 Copenhagen, Denmark.

Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, 2100 Copenhagen, Denmark; School of Chemical Engineering and Technology, State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin 300072, China.

出版信息

Int J Pharm. 2025 Feb 25;671:125075. doi: 10.1016/j.ijpharm.2024.125075. Epub 2024 Dec 17.

Abstract

With the continued relevance of drug hydrates in pharmaceutical sciences, a comprehensive understanding of hydrate and anhydrate forms is essential, not only through individual case studies but also from a broader, systematic perspective. The Cambridge Structural Database (CSD) is a well-established database for crystal structures of organic molecules and here, the structural features of pharmaceutically relevant compounds forming hydrates were explored. Drug anhydrate and hydrate subsets were generated and further classified into separate anhydrate and hydrate sets for free drug, cocrystal/solvate, salt, multicomponent cocrystal/solvate, and salt cocrystal/solvate systems. A thorough understanding of these sets was documented at molecular and structural levels. The CSD drug subset contains 24% of entries as hydrates and 76% as anhydrates. Only 6% of anhydrates have corresponding hydrate forms in the CSD drug subset. The formation of hydrates seems to be still less documented in multicomponent drug hydrates, as well as polymorphism of hydrates is less explored for these increasingly complicated systems with a high number of components. The presence of water molecules or additional components does not necessarily lead to a higher degree of crystal packing. Water is involved in 44% of hydrogen bonds (H-bond) in drug hydrate set, where water prefers to act as H-bond donor. H-bonds formed only by water show a relatively high bond strength. This work demonstrates the potential of data science in analyzing pharmaceutically relevant databases to uncover hidden patterns, and more specifically utilizing the CSD for understanding structural aspects and the role of water in H-bond patterns in drug hydrates.

摘要

随着药物水合物在药学领域的持续重要性,全面了解水合物和无水物形式至关重要,这不仅需要通过个别案例研究,还需要从更广泛、系统的角度进行。剑桥结构数据库(CSD)是一个成熟的有机分子晶体结构数据库,在此,我们探索了形成水合物的药学相关化合物的结构特征。生成了药物无水物和水合物子集,并进一步分为游离药物、共晶体/溶剂化物、盐、多组分共晶体/溶剂化物以及盐共晶体/溶剂化物体系的单独无水物和水合物集合。在分子和结构层面记录了对这些集合的深入理解。CSD药物子集中24%的条目为水合物,76%为无水物。在CSD药物子集中,只有6%的无水物有相应的水合物形式。在多组分药物水合物中,水合物的形成似乎仍缺乏记录,而且对于这些组分数量众多、日益复杂的体系,水合物的多晶型研究也较少。水分子或其他组分的存在并不一定导致更高程度的晶体堆积。在药物水合物集合中,44%的氢键(H键)涉及水,其中水更倾向于作为H键供体。仅由水形成的H键显示出相对较高的键强度。这项工作展示了数据科学在分析药学相关数据库以发现隐藏模式方面的潜力,更具体地说,利用CSD来理解药物水合物的结构方面以及水在H键模式中的作用。

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