López-Pérez Kenneth, Kim Taewon D, Miranda-Quintana Ramón Alain
Department of Chemistry and Quantum Theory Project, University of Florida Gainesville Florida 32611 USA
Digit Discov. 2024 May 7;3(6):1160-1171. doi: 10.1039/d4dd00041b. eCollection 2024 Jun 12.
The quantification of molecular similarity has been present since the beginning of cheminformatics. Although several similarity indices and molecular representations have been reported, all of them ultimately reduce to the calculation of molecular similarities of only two objects at a time. Hence, to obtain the average similarity of a set of molecules, all the pairwise comparisons need to be computed, which demands a quadratic scaling in the number of computational resources. Here we propose an exact alternative to this problem: iSIM (instant similarity). iSIM performs comparisons of multiple molecules at the same time and yields the same value as the average pairwise comparisons of molecules represented by binary fingerprints and real-value descriptors. In this work, we introduce the mathematical framework and several applications of iSIM in chemical sampling, visualization, diversity selection, and clustering.
自化学信息学诞生之初，分子相似性的量化就已存在。尽管已经报道了多种相似性指数和分子表示方法，但它们最终都归结为每次仅计算两个对象之间的分子相似性。因此，为了获得一组分子的平均相似性，需要计算所有的成对比较，这需要与计算资源数量成二次方比例的计算量。在此，我们针对此问题提出了一种精确的替代方法：即时相似性（iSIM）。iSIM 可同时对多个分子进行比较，并产生与由二进制指纹和实值描述符表示的分子的平均成对比较相同的值。在这项工作中，我们介绍了 iSIM 的数学框架及其在化学采样、可视化、多样性选择和聚类中的若干应用。
