We present enhancements to the Compass algorithm that automatically deduce interchemotype relationships and generate predictive quantitative models of receptor binding based solely on structure-activity data. We applied the technique to a series of compounds assayed for 5-HT1A binding. A model was constructed from 20 compounds of two chemotypes and used to predict the affinities and bioactive conformation of 35 new compounds, most of which had new underlying scaffolds and/or functional groups. The model's mean error of prediction was 0.5 log units (essentially the assay resolution), even on quite divergent series. The predictions are supported by an interpretable hypothesis for the binding determinants of the receptor and the geometric relationships of the chemotypes.