The distributions of physicochemical property values, like the octanol–water partition coefficient, are routinely calculated to describe and compare virtual chemical libraries. Traditionally, these distributions are derived by processing each member of a library individually and summarizing all values in a distribution. This process becomes impractical when operating on chemical spaces which surpass billions of compounds in size. In this work, we present a novel algorithmic method called SpaceProp for the property distribution calculation of large nonenumerable combinatorial fragment spaces. The novel method follows a combinatorial approach and is able to calculate physicochemical property distributions of prominent spaces like Enamine’s REAL Space, WuXi’s GalaXi Space, and OTAVA’s CHEMriya Space for the first time. Furthermore, we present a first approach of optimizing property distributions directly in combinatorial fragment spaces.

中文翻译：

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大组合片段空间理化性质分布的计算与优化

物理化学性质值的分布，如辛醇-水分配系数，通常被计算来描述和比较虚拟化学库。传统上，这些分布是通过单独处理库的每个成员并汇总分布中的所有值而得出的。当在超过数十亿个化合物的化学空间上操作时，这个过程变得不切实际。在这项工作中，我们提出了一种新的算法方法，称为 SpaceProp，用于大型不可数组合片段空间的属性分布计算。该方法采用组合方法，首次能够计算出Enamine的REAL Space、WuXi的GalaXi Space和OTAVA的CHEMriya Space等显着空间的理化性质分布。此外，