Biomolecular recognition has long been an important theme in artificial sensing technologies. A current limitation of protein- and nucleic acid-based recognition, however, is that the useful dynamic range of single-site binding typically spans an 81-fold change in target concentration, an effect that limits the utility of biosensors in applications calling for either great sensitivity (a steeper relationship between target concentration and output signal) or the quantification of more wide-ranging concentrations. In response, we have adapted strategies employed by nature to modulate the input output response of its biorecognition systems to rationally edit the useful dynamic range of an artificial biosensor. By engineering a structure-switching mechanism to tune the affinity of a receptor molecule, we first generated a set of receptor variants displaying similar specificities but different target affinities. Using combinations of these receptor variants (signaling and nonsignaling), we then rationally extended (to 900000-fold), narrowed (to 5-fold), and edited (three-state) the normally 81-fold dynamic range of a representative biosensor. We believe that these strategies may be widely applicable to technologies reliant on biorecognition.