Chemogenomics, the identification of all possible drugs for all possible targets, has recently emerged as a new paradigm in drug discovery in which efficiency in the compound design and optimization process is achieved through the gain and reuse of targeted knowledge. As targeted knowledge resides at the interface between chemistry and biology, computational tools aimed at integrating the chemical and biological spaces play a central role in chemogenomics. This review covers the recent progress made in integrative computational approaches to data annotation and knowledge generation for the systematic knowledge-based design and screening of chemical libraries.