A Novel Chemogenomics Knowledge-Based Ligand Design Strategy—Application to G Protein-Coupled Receptors

In the frame of the discussion of monoamine-related GPCRs, a novel knowledge-based ligand design strategy is presented. The strategy is founded on the integration of both, the deconvolution of known ligands into their component fragments and the structural bioinformatics comparison of the binding sites for the individual ligand fragments. Positioning analyses of monoamine-related GPCRs in 1) the sequence space of the seven transmembrane domains of the receptors, and 2) in the sequence spaces of the previously identified three distinct ligand fragment binding regions of the monoamine GPCRs, are carried out in the perspective to characterize orphan receptors and monoamine receptors for which no specific ligands are yet known. Compared to the commonly accepted strategy to analyze the overall sequence identity of the seven transmembrane domains in order to find starting points for lead finding and ligand design programs, the strategy to localize the sequence homology to the different ligand fragment binding sites clearly enhances the identification of putative similarities for the orphan receptors. Correspondingly, in the ligand space, by the analysis of both, the ligand architectures and the structures of the component “one-site filling” fragments of known GPCR ligands, it is then possible, by referring to the locally most directly related and characterized receptors, to identify those component ligand fragments which based on the binding site similarities are potentially best suited for the design of ligands tailored to the new target receptor. Predictions are made for several orphan GPCRs, including GPR7, GPR8, GPR14, GPR24, GPR57, GPR58 and AF021818, as well as for the 5HT1E and 5HT5 serotonin receptors for which no specific agonists and antagonists are yet known. Although the method is herein discussed with a focus on GPCRs, it is expected that such chemogenomics knowledge-based strategies – bridging the chem- and bioinformatics worlds – should open novel perspectives in drug discovery for orphan targets revealed by the human genome project belonging to other therapeutic target families.