On Press:

Finding Selective Reversible Inhibitors In Vivo

By Jason Socrates Bardi

Sequencing the human genome promises to be a great investment for society. Like buying a house, the monumental public and private effort that is the human genome promises to be profitable over time—except the profit will be in the currency of better medications and methods to fight diseases.

Realizing these benefits is going to take a lot of work. We still have to do things like identify all the genes in the genome, find out which ones are linked to particular disease states, and find ways to modulate the effect of those genes at the microscopic level.

Much of this work comes down to identifying small molecules that can selectively modulate the activity of proteins that are relevant in diseases like cancer, and certain tools are emerging at The Scripps Research Institute (TSRI) and in laboratories across the world that might allow us to do just that.

One of these tools is proteomics, a way of interrogating particular cells and tissues to see which genes and proteins might be involved in a disease. Another tool is combinatorial libraries of small molecules, which synthetic chemists and other scientists make (often with tens of thousands of drug-like compounds) and then screen for potent inhibitors against the disease-related genes identified through proteomics.

However, screening combinatorial libraries for inhibitors generally requires purified proteins, which can be complicated and time-consuming to produce. Also, many proteins belong to structurally related "families," and often times inhibiting one with a drug will inhibit another as well. There is no guarantee that inhibitors that work well against a protein in the test tube will not fail as drugs because they interact with too many other, similar proteins in the body. This problem creates bottlenecks in the discovery of new drugs.

Now, a team of researchers at The Skaggs Institute for Chemical Biology at TSRI have combined the tools of proteomics and combinatorial libraries in an attempt to circumvent this bottleneck. Research Associates Donmienne Leung and Christophe Hardouin, with Professor Dale Boger (who is Richard and Alice Cramer Professor of Chemistry) and Associate Professor Benjamin Cravatt have developed a proteomic method for the discovery of reversible enzyme inhibitors from libraries of compounds.

The TSRI team has found a way to look for specific inhibitors against particular serine hydrolases, a broad class of enzymes, by using a technique they call competitive profiling. Competitive profiling entails testing inhibitors against numerous enzymes in parallel by subjecting whole proteomes to a competition reaction between these inhibitors and activity-based chemical probes. Inhibitors that displace probes off of particular enzyme targets, but not other enzymes from the same family, are identified as specific agents and chosen for further analysis in vivo.

Using this marriage of techniques, the TSRI team reports, in a recent article in the journal Nature Biotechnology, the identification of reversible inhibitors of several enzymes that bind with nanomolar affinity, including inhibitors for the endocannabinoid-degrading enzyme fatty acid amide hydrolase (FAAH), the enzyme triacylglycerol hydrolase (TGH), and an uncharacterized membrane-associated hydrolase enzyme that lacks known substrates.

This sort of approach, suggest the authors, should accelerate the discovery of specific inhibitors against enzymes with known and unknown function.

To read the article, "Discovering potent and selective reversible inhibitors of enzymes in complex proteomes" by Donmienne Leung,Christophe Hardouin, Dale L Boger, and Benjamin F Cravatt, please see:
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nbt/journal/vaop/ncurrent/abs/nbt826.html

 

 

 


Competitive proteomic profiling of a library of candidate serine hydrolase inhibitors with an activity-based fluorescent probe. Inhibitor-sensitive enzymes are detected by reduction in their fluorescence labeling intensities. Single and double arrowheads highlight enzymes from the mouse brain proteome that show unique inhibitor sensitivity profiles.