It is common in cheminformatics to represent the properties of a ligand as a string of 1’s and 0’s, with the intention of
elucidating, inter alia, the relationship between the chemical structure of a ligand and its bioactivity. In this commentary
we note that, where relevant but non-redundant features are binary, they inevitably lead to a classifier capable
of capturing only a linear relationship between structural features and activity. If, instead, we were to use relevant
but non-redundant real-valued features, the resulting predictive model would be capable of describing a non-linear
structure-activity relationship. Hence, we suggest that real-valued features, where available, are to be preferred in this
scenario.