Search

Combinatorial chemistry is being applied to diverse problems in the biological and pharmaceutical sciences. This review will describe an emerging application called "chemical genetics" or "chemical genomics" - genetics and genomics are often used interchangeably in this context. In forward chemical genomics, chemical libraries are tested in living systems to discover compounds that cause a desirable effect. Subsequently, the protein target is identified using various biochemical and molecular biological tools. By this method, we gain insights into the inner workings of life, and indeed, in some forms this has been the path by which most of the pharmacopoeia was discovered. In reverse chemical genetics, proteins of interest are used to probe compound collections, and those compounds that bind the proteins of interest are used to treat living systems and observed for interesting biological responses. Plausible biological roles of these proteins are inferred from the effects of the compounds because they are assumed to generally inhibit, or more rarely, stimulate, the protein's functions. Interestingly, the reverse genetic approach is emerging as the leading model for drug discovery today. Different methods and cases will be described to illustrate forward and reverse paradigms, including those developed in the author's laboratory.

Genomics has caused an explosion in the number of potential therapeutic targets with varying degrees of validated pathophysiology. Among the first applications of combinatorial chemistry in genomics-driven drug discovery is the search for surrogate ligands or substrates. In the event that no surrogate is found for molecular assays, more exotic functional screens in whole cells or model organisms are used. Protein-protein interaction mapping by yeast and mammalian two-hybrid systems dominates empirical functional genomics, and this will lead to a bias for screening projects targeting this type of interaction. Drug discovery for protein-protein interactions has a poor track record, and this will challenge prevailing views on the design of combinatorial libraries. Genomics based on structural homology will yield many putative kinases, receptors, enzymes, transporter proteins, ion channels and GPCRs. Most of these projects will require new surrogate agonists, ligands or substrates, and then pharmaceutically useful agonists or antagonists will need to be found. Again, combinatorial chemistry might be essential to these studies. Given the need to screen hundreds of targets at great risk of irrelevance to pathophysiology, combined with the challenge of finding surrogate or natural ligands for these new targets, there is an urgent need for efficiency. Different groups are addressing these concerns by developing biologically-driven combinatorial libraries in order to achieve a higher density of bioactivity. Early efforts in this regard will be described.