Simple and reliable approaches to characterize the N-termini of proteins not only promise to provide insight into the regulation and functions of gene products, but they can also provide a convenient way to identify the cleavage products generated by proteases with poorly defined specificities.

The substrates of proteases often provide important insights into their in vivo biological roles. A good example of the value of understanding protease substrate specificity is the fibrinolytic system, where the protease, tissue-plasminogen activator (tPA), cleaves and activates plasminogen to plasmin, which in turn promotes clot dissolution. tPA is the most widely used drug to limit heart damage in the setting of a heart attack. Given such successes, research efforts are being directed toward delineating the substrate specificity of many proteases, and it is estimated that 5-10% of drug targets being evaluated for clinical use are proteases.

In spite of these efforts, substrates have not been identified for more than half of the proteases in man, i.e. these proteases are “orphans”. Current approaches to identify protease cleavage sites in the context of native proteins (as opposed to synthetic peptides) cannot survey all N-terminal fragments while simultaneously identifying N-terminal fragments generated by a protease of interest.

As reported in a recent report published in Nature Biotechnology, CBR investigators Chris Overall and Jay Kizhakkedathu collaborated to overcome this problem. Overall and colleagues devised a technique whereby they introduce terminal amine isotopic labeling of substrates (TAILS). The approach involves labeling control and protease-treated samples with different isotopes and then using a new class of amino-reactive dendritic polyglycerol aldehyde polymers developed by Kizhakkedathu’s group to enrich for all N-terminal fragments. When coupled with stringent bioinformatics criteria for proteases without a known consensus cleavage site, a single mass spectrometry analysis could identify protease substrates with high confidence. The technique could also be used to characterize post-translational modifications of proteins.

The authors validated the approach by identifying known and new substrates for two metalloproteases involved in tumor metastasis and diabetes.

Get the whole story in Nature Biotechnology 2010;28:281-291