We extracted the per residue scores for the R1 and R4 variants generated by our models (Figure ), and used this to determine the difference (Δ) in per residue scores for these variants (Figures and). We note that another approach could be to calculate the "mutual information gain", by identifying the largest differences in the MI values for each feature/contact between the two enzymes. That said, the approach taken still allows for the easy identification of those residues that have notably changed. By analyzing these differences, we identified four residues that became (relatively) "more important" in R4 (K222, I7D, H201 and G202R) alongside four residues that were (relatively) "more important" in R1 (W50, T104, N224D and H228). Further, whilst the catalytic residues K222 and W50 show a notable change in score, the corresponding values for E101 and Y128 are close to 0 (Figure ), suggesting the role these residues play in regulating the W50 conformational state was not notably impacted by these mutations. Finally, by comparing the top per feature scores obtained for the R1 and R4 variants, we observed that the top features in R4 are substantially more correlated to the target variable than those in R1, and that this is true for both metrics used (Figure ). This would suggest that the overall enzyme scaffold is overall playing a more active role in regulating the conformational state of W50 in the R4 than in the R1 variant.