Quantitative profiling of protease specificity

Abstract

Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies. We have developed a concept of “selectome”; the set of substrate amino acid sequences that uniquely represent the specificity of a protease. We applied it to two closely related members of the Matrixin family–MMP-2 and MMP-9 by using substrate phage display coupled with Next Generation Sequencing and information theory-based data analysis. We have also derived a quantitative measure of substrate specificity, which accounts for both the number of substrates and their relative catalytic efficiencies. Using these advances greatly facilitates elucidation of substrate selectivity between closely related members of a protease family. The study also provides insight into the degree to which the catalytic cleft defines substrate recognition, thus providing basis for overcoming two of the major challenges in the field of proteolysis: 1) development of highly selective activity probes for studying proteases with overlapping specificities, and 2) distinguishing targeted proteolysis from bystander proteolytic events. Proteases and proteolysis are intimately involved in virtually all biological processes from embryonic development to programmed cell death and cellular protein recycling. As the only irreversible posttranslational modification, proteolysis represents a committed step in regulation of biological networks and pathways. Imbalance of proteolytic activity has catastrophic implications and is the basis of many genetic disorders as well as a multitude of pathological states of varying etiologies. To understand protease function, one must gain insight into the repertoires of substrates targeted by these enzymes. As many proteases recognize a wide variety of sequences in proteins, it is a challenge to establish if a particular cleavage represents a targeted or a bystander proteolytic event. In addition, since many proteases have overlapping specificities, especially among closely related members of the same gene families, it is a challenge to develop highly selective tools for studying or inhibition of these enzymes. In this work, we used two closely related proteases (MMP-2 and 9) as a model system for development of an information theory-based approach to quantification of substrate specificity and demonstrated its potential for distinguishing between the target and bystander proteolytic events as well as for uncovering selectivity between closely related proteases.