Conformational selection emerges as a theme in macromolecular interactions. Data validate it as a prevailing mechanism in protein–protein, protein–DNA, protein–RNA, and protein–small molecule drug recognition. This raises the question of whether this fundamental biomolecular binding mechanism can be used to improve drug docking and discovery. Actually, in practice this has already been taking place for some years in increasing numbers. Essentially, it argues for using not a single conformer, but an ensemble. The paradigm of conformational selection holds that because the ensemble is heterogeneous, within it there will be states whose conformation matches that of the ligand. Even if the population of this state is low, since it is favorable for binding the ligand, it will bind to it with a subsequent population shift toward this conformer. Here we suggest expanding it by first modeling all protein interactions in the cell by using Prism, an efficient motif-based protein–protein interaction modeling strategy, followed by ensemble generation. Such a strategy could be particularly useful for signaling proteins, which are major targets in drug discovery and bind multiple partners through a shared binding site, each with some—minor or major—conformational change.