A noteworthy feature of ChemPlot is the application of tailored similarity for the visualization of chemical spaces. Before discussing this similarity feature, it is important to understand the similarity concept. Similarity is relative and it depends on the target and the population, therefore there is no globally applicable definition of similarity . The traditionally used form is the structural similarity that attempts to evaluate the similarity using all possible aspects of the given molecular datasets and without taking the target property into account. This approach is truly suitable when one wants to have a general overview of the dataset . However, structural similarity often fails when searching for new molecules with target properties. For example, when searching for molecules with a desired aqueous solubility value, one can expect that the neighboring molecules on the visualized chemical space would have close solubility values. Neighboring molecules, however, are more likely to have closer solubility values when, instead of the similarity defined by all the features, the similarity is defined essentially by the features that are known to affect the solubility. In relation to this, ChemPlot includes the tailored similarity option, which automatically identifies the correlated features with the given target and visualizes the chemical space based on them. The chemical spaces that are visualized by using the tailored similarity are less likely to be affected by the APC issue. Inline with this, for the majority of the datasets shown in Table , the tailored similarity produced lower DPR scores than the structural similarity.