Wroclaw University of Science and Technology, Faculty of Computer Science and Management, 50-371 Wrocław, I. Łukasiewicza Street 5, Poland.
Jagiellonian University Medical College, Department of Technology and Biotechnology of Drugs, 30-688 Kraków, 9 Medyczna Street, Poland; Maj Institute of Pharmacology, Polish Academy of Sciences, Department of Medicinal Chemistry, 31-343 Kraków, Smętna Street 12, Poland.
Comput Biol Chem. 2020 Oct;88:107367. doi: 10.1016/j.compbiolchem.2020.107367. Epub 2020 Aug 26.
Comparison of compounds similarity is one of the main strategies of virtual screening protocols. Both similarity and dissimilarity concepts are of great importance during the search for new active compounds. Similarity is important due to the assumption that underlies the process of searching for new drug candidates: structurally similar compounds should induce similar biological response. On the other hand, we are also interested in dissimilarity, as we usually aim to find structurally novel ligands. In the study, we compared several approaches of evaluating compound similarity. Various representations and metrics were applied and we indicated the rate of variation of the results that can occur when shifting from one strategy to another. We compared both general similarity of datasets using different approaches, as well as examined the changes in the set of nearest neighbors when changing one compound representation into another, and the influence of representation/metric settings on the clustering outcome. We hope that the study will be of great help during the preparation of virtual screening experiments, stressing the need for careful selection of the way, the compound similarity is assessed. The differences in the results that can be obtained via the application of particular strategy can significantly influence the outcome of comparison studies; therefore, its settings should be carefully selected beforerunning the comparison.
化合物相似性比较是虚拟筛选方案的主要策略之一。在寻找新的活性化合物时，相似性和相异性的概念都非常重要。相似性很重要，因为它基于寻找新药物候选物的过程中的一个假设：结构相似的化合物应该诱导相似的生物学反应。另一方面，我们也对相异性感兴趣，因为我们通常旨在寻找结构新颖的配体。在研究中，我们比较了几种评估化合物相似性的方法。应用了各种表示法和指标，并指出了从一种策略转变为另一种策略时可能发生的结果变化率。我们比较了使用不同方法的数据集的一般相似性，以及当将一种化合物表示转换为另一种表示时，最近邻集的变化，以及表示/指标设置对聚类结果的影响。我们希望该研究将在虚拟筛选实验的准备过程中提供很大帮助，强调需要仔细选择评估化合物相似性的方法。通过应用特定策略可以获得的结果差异会极大地影响比较研究的结果；因此，在运行比较之前，应仔细选择其设置。
