In order to quantitatively demonstrate the causal-relevance of our predictors, we compared the predictive-performances of models M1-3 with those of three alternatives (A1-3); the latter have been constructed to incorporate a similar number of independent variables (1,4, and 5, respectively), while the specific values "calculated" for each of the ligands considered are random numbers found within the range of corresponding quantities used in M1-3. Thus, the single predictor used in A1 spans randomly-generated values between 20-1440 (corresponding to the smallest and largest calculated binding energies used in M1). Similarly, Models A2-3 were established to include random numbers found within the range of the corresponding LED components used in M2-3. It turns out that for a given n (n=1-3), the predictive power of An is substantially lower than that of Mn: A3, for instance, covers just 21% of the SSQ for experimentally-measured Ki values (compared to 96% for M3). Hence, putting chemical intuition aside -the latter findings may indeed be considered as a fair testimony for the true informative value of our calculated energetic properties (which is not related to some statistical-pragmatic notion of causality): it means that the predictive potential of M1-3 cannot be fully-rationalized by means of fitting regression coefficients to match a number of observed values.