Chemogenomic approaches, which link ligand chemistry to bioactivity against targets (and, by extension, to phenotypes) are becoming more and more important due to the increasing number of bioactivity data available both in proprietary databases as well as in the public domain. In this article we review chemogenomics approaches applied in four different domains: Firstly, due to the relationship between protein targets from which an approximate relation between their respective bioactive ligands can be inferred, we investigate the extent to which chemogenomics approaches can be applied to receptor deorphanization. In this case it was found that by using knowledge about active compounds of related proteins, in 93% of all cases enrichment better than random could be obtained. Secondly, we analyze different cheminformatics analysis methods with respect to their behavior in chemogenomics studies, such as subgraph mining and Bayesian models. Thirdly, we illustrate how chemogenomics, in its particular flavor of 'proteochemometrics', can be applied to extrapolate bioactivity predictions from given data points to related targets. Finally, we extend the concept of 'chemogenomics' approaches, relating ligand chemistry to bioactivity against related targets, into phenotypic space which then falls into the area of 'chemical genomics' and 'chemical genetics'; given that this is very often the desired endpoint of approaches in not only the pharmaceutical industry, but also in academic probe discovery, this is often the endpoint the experimental scientist is most interested in.
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