To improve human health, researchers must understand disease mechanisms at a molecular level. Our proteomic technologies provide unprecedented views of how molecules interact, when they are mis-regulated, and where they are mutated during disease progression. With this detailed information chemists can design better drugs and clinicians can provide better diagnoses. Clinical proteomics study is typically done collaboratively with world-renowned scientists and physicians from across the country, e.g., Seoul National University Hospital, College of medicine-Seoul National University, Asan medical center, Bundang CHA hospital, among many others.

Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. Mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Conceptually, MS-based proteomics combines all possible hypothesis-driven biomarker studies for each disease into one and furthermore defines the relation of potential biomarkers to each other. In practice, the challenges of plasma proteomics have so far prevented in-depth and quantitative studies on large cohorts. Instead, a stepwise or “triangular” strategy for biomarker discovery has been advocated, with several phases in which the number of individuals increases from a few to many, whereas the number of proteins decreases from hundreds or thousands to just a few

We have described strategies for comprehensive analysis of numerous PTM types, including phosphorylation, acetylation, methylation, and ubiquitinylation, among others. At the same time we have pursued new methodology to allow deep, rapid sequencing of whole proteomes. We continue to innovate in this area and are currently working on profiling an entire human proteome on a rapid time scale. Furthermore, we have a goal to identify nearly complete proteome in clinical samples at nanogram scale.