Substrate-Guided Proteomics Enhances Degradome Resolution

Abstract

High-throughput technologies offer unrecognized insights into the genesis of human disease, propelling innovation across a spectrum of biomedical specialties.1 The evolution of molecular diagnostics continues to shape deployment of modern therapies, including identification of markers of disease prognosis, predictors of therapeutic response, and determinants of optimal clinical management, all recognized cornerstones of modern medical practice.2 In the postgenomic era, proteomic paradigms have demonstrated particular utility in advancing the practice of personalized disease prediction, diagnosis, and therapy,3 with systems-based approaches facilitating functional deconvolution of proteomes despite their inherent biological complexity.4 The ever-expanding proteomics toolkit encompasses an array of sophisticated technologies with the flexibility to interrogate a totality of putative protein targets, thereby enabling systematic resolution of proteome structures and functions. Indeed, mapping and decoding of proteome landscapes in health and disease provide the foundation to iteratively collate, integrate, and prioritize large-scale raw data.5 Thus, high-throughput proteomics offers a robust, adaptable technological foundation from which to systematically comprehend the underpinnings of (patho)physiological processes. Article see p 106 Innovative proteomic methods are designed to separate and identify proteins with high fidelity and to assess protein abundance, structure, posttranslational modifications, and interactions, enabling charting of the global proteome (ie, the protein complement of a genome; Figure). Progress in proteomic research has benefitted from the application of stringent criteria in assigning peptide and protein identities for comprehensive proteome cartography, such that perturbed or modified subproteomes within reconstituted protein networks can now be extracted at unprecedented rates for interpretation of their biological relevance. Expansion of proteomic studies has also been propelled by the concomitant development of high-resolution, high-mass-accuracy instrumentation, together with next-generation bioinformatics platforms for data analysis and systems interpretation. Existing approaches, however, may fall short of offering adequate experimental solutions arising from particular protein physicochemical constraints, limiting the otherwise far-reaching …