Indeed, five first-generation EGFRi (18-22) exhibited lower activity against the two T790Mcontaining variants (pChEMBL values between 6.09-7.00, compared to 7.01-9.33), as this resistance substitution is known to appear as a response to treatment with first-and secondgeneration EGFRi. Despite high activity overall, afatinib exclusively showed a decrease in bioactivity for the double mutant L858R/T790M. In terms of the location with respect to the ligand binding site, T790 is one of the closest substituted residues, below 10 Å from the ligand centroid and effectively in the binding site of EGFR. Additionally, the threonine to methionine amino acid change is highly disruptive with an Epstein coefficient of difference over 0.80. The rest of the variants behaved more similarly to the WT, with two major compound clusters with low (pChEMBL values between 5.00 and 7.34) and high activity (between 7.01 and 10.00), respectively. From these, WT was the odd one with the least marked differences between the two groups of compounds, as seen in the hierarchical clustering per variant (Figure ). This was expected, as most EGFRi were developed to be variant-selective and reduce the side effects of anticancer therapies. The single substituted variant L858R behaved very differently from the double substituted T790M/L858R variant, in line with the different biological roles of these substitutions. Although the substitution to arginine is highly disruptive, L858 is further away from the ligand than T790. The Butina clustering performed on the 22 compounds showed that similar compounds exhibit similar effects across variants, as observed for clusters starting scaffolds with specific selectivity profiles (Supplementary Figure ); or to distinguish between compounds with different binding modes (Supplementary Figure ). The different effects observed for different chemical clusters in common subsets could also be expanded to bigger yet sparser subsets. This allowed us to analyse the overall effect of variants on different subsets of the chemical space tested for one protein. While this analysis is possible for the whole protein subset, in targets with a clear bias towards WT testing, selecting subsets of compounds tested on at least two variants was still preferred to increase the significance of comparisons across variants. Particularly for EGFR, the set of 1,219 compounds tested on at least two variants was clustered using the Butina algorithm 36 with a threshold of 0.5 resulting in 118 clusters. Clear differences in bioactivity across variants were observed among the top 10 biggest clusters (Figure ). Chemistry-related changes in bioactivity distribution were already somewhat apparent on the WT level (Figure ), with mean pChEMBL values between 6.43 and 7.66 from slightly divergent distributions. The compounds in the two most populated clusters (n=253 and n=236, respectively) were tested across 11 and 10 out of the 12 variants, respectively, with various rates of variant coverage (Figure ). These two clusters included approved first (cluster 2), second (cluster 2), and third generation (cluster 1) EGFRis, as well as pan-kinase inhibitors (cluster 2). Thirdgeneration EGFRis were not present in Figure and were developed to selectively target the L858R/T790M double substitution. Furthermore, the average differences in bioactivity compared to WT across variants were virtually the opposite between the two clusters, in line with the known selectivity profiles of different generations of EGFRi. For example, compounds tested on rare variants G719C, G719S, A750P, and P753S all showed lower activity than compounds tested on the WT in cluster 1 (0.54, 0.85, and 0.88 points below WT -6.74) but higher in cluster 2 (1.21, 1.11, and 1.06 points above WT -7.66). The opposite effect was observed for compounds tested on the double substituted T790M/L858R variant, which had a mean pChEMBL value 0.85 points higher than compounds tested on the WT in cluster 1 (7.59 vs. 6.74) and 0.27 points lower than compounds tested on the WT in cluster 2 (7.39 vs. 7.66).