Figure shows the distribution of NPL scores of the compounds in different databases analyzed. The NPL score is an approximate measure to describe and summarize the characteristics proper of NPs that differentiate them from synthetic molecules and can be attached by different approaches and model methodologies. The approach here used consists of the most classical method and is based on a Bayesian statistical model based on fragmentation patterns of common apparition in NPs. Positive values of the NPL score mean that the chemical structure of a compound resembles an NP structure (given the data set used to train the metric). In contrast, negative values of the score mean that the chemical is more associated with fragmentation patterns of synthetic organic compounds. In this study, profiling compound databases in terms of NPL scores aims to prioritize databases in terms of their coverage of the chemical space of NPs.