To quantitatively assess which fingerprint correlation pairs change the most when considering the NP chemical space specifically, we first computed the correlation matrix for the Drug Repurposing Hub dataset (Figure ) and then calculated the Pearson R difference between the values obtained for NPs and the ones for drugs (Figure ). Most fingerprints are more correlated in the NP space than in the drug-like space, with an average Pearson R difference of around 0.1, except for PH2 and PH3, which instead are less correlated to the others. The correlation increase for the majority of fingerprints likely reflects the fact that many bits are less informative for NPs than they are for drugs, thus reducing the ability of different fingerprints to capture molecular similarity from different perspectives. Notably, the correlation difference between Avalon and KR, MAP4 and MHFP is especially high (0.4), indicating that their chemical space mapping is very similar with NPs but not with drug-like compounds. On the other hand, the correlation decrease observed for PH2 and PH3 hints at the fact that similarities computed using these encodings tend to be outliers in the NP chemical space, as observed when evaluating their distribution and as discussed below when analyzing their unsupervised embeddings.