Computational tools for the large-scale analysis and prediction of ligand-target interactions and the identification of small molecules having different selectivity profiles within target protein families complement research in chemical genetics and chemogenomics. For computational analysis and design, such tasks require a departure from the traditional focus on single targets, hit identification, and lead optimization. Recently, studies have been reported that profile compounds in silico against arrays of targets or systematically map ligand-target space. In order to identify small molecular probes that are suitable for chemical genetics applications, molecular diversity needs to be viewed in a way that partly differs from principles guiding conventional library design.