In order to generate a visual representation of the chemical space of Nat-UV DB, the fingerprint ECFP4 (1024 bits) was calculated for each compound and the visualization was done using t-distributed stochastic neighbor embedding (t-SNE) . The selection of this visualization method was based on recent studies that support its utility for the systematic study of small and large datasets in terms of neighborhood preservation and visualization capabilities . The ECFP4 fingerprint and the t-SNE coordinates were calculated in KNIME software. The optimization parameters we used in t-SNE were dimensions (3), iterations (10,000), theta (0.3), perplexity (30.0), and number of threats (8), using 28 as the seed number. The interactive visualization was implemented using DataWarrior software, version 06 . The KNIME workflow and data generated are freely available in the Supplementary material.