As mentioned above, release of the METLIN small molecule retention time (SMRT) dataset led to an impressive boost in QSRR research . Currently, this dataset can be considered a "golden standard" for any model performance estimation. It contains 80,038 small molecules with corresponding retention time and PubChem compound identifiers (CID). The retention time varies from 0.0 up to 24.5 min (0.3-1471.7 s). The compounds released before 5 min have been typically excluded from the QSRR model creation since they are not retained on the column properly. To compare METLIN SMRT and EnamineRT datasets, we generated extended-connectivity fingerprints (ECFP) for each structure; in addition to that, 208 physicochemical descriptors were calculated using RDKit. In the case of physicochemical descriptors, the datasets underwent additional standardization steps (see the Methods section for more details). Both ECFP and physicochemical parameter-based chemical space representations were reduced using principal component analysis (PCA) followed by uniform manifold approximation and projection (UMAP). We found that METLIN SMRT and EnamineRT covered similar regions of the projected chemical space in ECFP representation, although there were few regions where METLIN completely overlaps with EnamineRT (see Figure ). This behavior could be expected since both EnamineRT and METLIN SMRT mostly contain small molecules (the average molar weight values are 341 Da and 382 Da, respectively). The compounds were concentrated in three wellseparated regions of the chemical space, with several observable conglomerates within each of them. The central region of the chemical space was enriched with lipophilic molecules.