Computational approaches in chemogenomics and chemical biology: current and future impact on drug discovery

Chemical biology and chemogenomics are rapidly evolving disciplines at interfaces between chemistry and the life sciences and are highly interdisciplinary in nature. Chemogenomics has a strong conceptional link to modern drug discovery research, whereas chemical biology focuses more on the use of small molecules as probes for exploring biological functions, rather than drug candidates. However, the boundaries between these areas are fluid, as they should be, given their strong interdisciplinary orientation.

Recently, computational approaches have been introduced for the analysis of research topics that are of considerable relevance for these disciplines including, for example, the systematic study of ligand-target interactions or mapping of pharmacologically relevant chemical space. This contribution introduces key investigations in computational chemical biology and chemogenomics and critically evaluates their current and future potential to impact drug discovery.

Computational methods of high relevance for chemogenomics and chemical biology either derive knowledge from large-scale analysis of available drug and target data or interface experimental programs with predictive methods. Approaches for drug target prediction and the systematic analysis of polypharmacology substantially impact research in this area.