A novel approach to drug discovery is being tested on an antiobesity G protein-coupled receptor target. Currently, a Combinatorial Chemistry (CC) library is screened against a receptor target by High Throughoutput Screening (HTS). We will randomize the receptor's binding site creating a Combinatorial Biology (CB) library. This CB library will contain multiple receptor variants with novel recognition properties. Screening the CC library against the CB library scales up the number of putative ligand-receptor interactions studied (and the number of leads identified) by the number of receptor variants (l00-l0(4) fold). This ligand-variant receptor data will be analyzed matching changes in chemical moieties with amino acid changes. This information should greatly facilitate developing a wild-type lead, and in general the lead optimization process. A Cre-mediated single-target site integration has been engineered in NIH3T3 cells, allowing expression of a single receptor per cell. The promiscuous G-alphal6 will be stably transfected to support coupling of the receptor to Ca++ signals. For this feasibility study, a 120 single receptor variants will be expressed in NIH3 T3-Cre-G16 cells. The ability to measure simultaneously different receptor variants responses to a selective agonist in our functional assay will support the feasibility of the Split-Maze approach.
Our goal is to discover a novel agonist to the melanocortin-4 receptor, which would be a potential antiobesity drug. Conservative estimates predict a $5 billion market of an antiobesity drug by the year 2005. We are developing a novel approach to drug discovery that incorporates combinatorial biology on the target receptor and can screen thousands of receptor variants in one step. The new approach has the potential to develop higher quality leads, faster and cheaper than current state of the art.
