An important issue that is rarely taken into consideration is the uncertainty associated with experimental ∆∆G predictions and its consequences. The experimental predictions of relative free energy differences have statistical uncertainties that often go unreported as is the case here and the vast majority of such publications. A direct consequence of this is a phenomenon called regression dilution that is well known in statistics. It means that uncertainty in the known variable (∆∆G exp in this case) causes biasing of the linear regression slope towards zero. This phenomenon has been reported in more detail in a recent publication where different statistical methods are used to demonstrate the biased least square regression slope and the extent of underestimation in predicted values has been quantified. It is possible to correct for such deviations when both the known and unknown variables are normally distributed. But in the case of free energy predictions (whether calculated or experimental), the distributions are not guaranteed to be normal (see section 5.