With the availability of complete genome sequences, emphasis has shifted toward the understanding of protein function. We have developed a functional proteomic methodology that makes use of chemically reactive fluorescent probes to profile and identify enzymes in complex mixtures by virtue of their catalytic activity. This methodology allows a comparison of changes in activity of multiple enzymes under a variety of conditions using a single two-dimensional separation. The probes can also be used to localize active enzymes in intact cells using fluorescence microscopy. Furthermore, the probes enable screens for selective small molecule inhibitors of each enzyme family member within crude lysates or intact cells. Ultimately, this technology allows the rapid identification of potential drug targets and small molecule lead compounds targeted to them.

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Classifying proteins into functionally distinct families based only on primary sequence information remains a difficult task. We describe here a method to generate a large data set of small molecule affinity fingerprints for a group of closely related enzymes, the papain family of cysteine proteases. Binding data was generated for a library of inhibitors based on the ability of each compound to block active-site labeling of the target proteases by a covalent activity based probe (ABP). Clustering algorithms were used to automatically classify a reference group of proteases into subfamilies based on their small molecule affinity fingerprints. This approach was also used to identify cysteine protease targets modified by the ABP in complex proteomes by direct comparison of target affinity fingerprints with those of the reference library of proteases. Finally, experimental data were used to guide the development of a computational method that predicts small molecule inhibitors based on reported crystal structures. This method could ultimately be used with large enzyme families to aid in the design of selective inhibitors of targets based on limited structural/function information.