title: A note on utilising binary features as ligand descriptors.
abstract: 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.
authors.affiliation: Centre for Molecular Informatics, Department of Chemistry, Cambridge University, Lensfield Road, Cambridge, CB2 1EW UK ; EaStCHEM School of Chemistry and Biomedical Sciences Research Complex, University of St Andrews, North Haugh, St Andrews, KY16 9ST St Andrews, Scotland.
authors.forename: Hamse Y
authors.initials: HY
authors.lastname: Mussa
authors.affiliation: EaStCHEM School of Chemistry and Biomedical Sciences Research Complex, University of St Andrews, North Haugh, St Andrews, KY16 9ST St Andrews, Scotland.
authors.forename: John B O
authors.initials: JB
authors.lastname: Mitchell
authors.affiliation: Centre for Molecular Informatics, Department of Chemistry, Cambridge University, Lensfield Road, Cambridge, CB2 1EW UK.
authors.forename: Robert C
authors.initials: RC
authors.lastname: Glen
keywords: Bernoulli distribution; Binary descriptors; Ligand chemical structure; Linear relationship