Next, we analysed all DFT-computed descriptors in the database using both linear and nonlinear dimensionality reduction techniques, specifically Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) (Fig. ). In the PCA analysis, the principal components with the greatest variances consist of atomic charge descriptors (PC1, explaining 28% of variance) and quadrupole moments, dispersion, and steric (PC2, 19% of variance). The PCA plots of PC1 versus PC2 show broader distributions of properties across each heteroaryl class (purple, red, yellow, and green for 5-, 6-membered rings, and 5,6-and 6,6-fused cycles, respectively) than those of aryl groups (black colour) (Fig. ). Similarly, the UMAP projection (Fig. ) revealed that many heteroaryl groups occupy distinct property space not accessible by aryl substituents. Heteroaromatic compounds are known to have distinct electronic and steric properties affected by their heteroarene cores. We selected a subset of common heteroaryl groups and plotted their average steric and electronic properties based on the heteroarene core (Fig. ). We chose a commonly used steric descriptor, fraction buried volume (VBur), and our newly developed Hammett-type substituent constants (σHet) as an electronic descriptor to illustrate the properties of the heteroaryl groups. Each point represents the average value of all heteroaryls with the same heteroarene core shown in the top of Fig. . This plot revealed several general trends that could be qualitatively validated by previous experimental observations. In terms of steric effects, five-membered heteroaryls are generally less hindered due to the smaller size of the ring, and sulphur-containing heteroaryls often have larger fraction buried volumes due to the longer C-S bond (e.g., compare thiophenyl 10 with other five-membered heteroaryls). As expected, substituting a C-H moiety in phenyl or naphthyl with a nitrogen atom decreases the fraction buried volume (e.g., benzene 14 > pyridine 15 > pyridazine 16 > triazines 18 and 19). In terms of electronic properties, five-membered heteroaryls exhibited more diverse electronic effects than other ring sizes. Based on σHet values, pyrrole ( ) is more electron-rich than benzene (14), consistent with its higher reactivity in electrophilic aromatic substitution reactions. On the other hand, 1,3,4-thiadiazole (13) and 1,2,4-oxadiazole (9) are among the most electron-deficient heteroaryls, which are consistent with previous experimental observations. With a wide array of DFT-computed electronic, steric, and geometrical descriptors for diverse heteroaryl groups in the HArD database, we set out to explore whether the computed descriptors correlate with previously reported experimental reactivity and selectivity data. In 2022, the Leitch group published an extensive set of experimentally determined free energies of activation (ΔG ‡ SNAr) of nucleophilic aromatic substitution (SNAr) of benzyl alcohol reacting with 2-chloropyridines, 4-chloropyridines, and other chloro-substituted (hetero)aryl compounds (Fig. ). In another recent work, the Baud group performed a systematic kinetics study of 2-sulphonylpyrimidines as thiol-reactive covalent warheads that can undergo SNAr reactions with biologically relevant thiols in selective protein arylation (Fig. ). The second-order rate constants for each warhead indicated a wide range of reactivity with the glutathione (GSH) nucleophile by altering the substituents at the 4-and 5-positions of the pyrimidinyl group and exchanging the pyrimidine ring for different parent heteroaryl groups. Both sets of experimental reactivity data strongly correlate with the DFT-computed CM5 charge of heteroaryl group, q(Het)-CM5 (Fig. and), illustrating the capability of the q(Het)-CM5 descriptor for quantitative SNAr reactivity prediction. Next, we examined whether the computed electronic descriptors correlate with experimental site-selectivity trends in radical-mediated heteroaryl C-H functionalization from Baran et al. (Fig. ). The computed ipso carbon LUMO coefficients in the HArD database could qualitatively predict the preferred