Current Research and Scholarly Interests
Our lab develops mass spectrometry (MS)-based chemical systems biology approaches, combined with machine learning and biochemistry, to uncover the molecular mechanisms of metabolic control in physiology and disease. In parallel, we recognize that endogenous metabolite regulation of protein function is conceptually analogous to chemical perturbation by small molecules such as chemical probes and drugs. In both cases, small molecules bind proteins and modulate their activity. The key distinction is that metabolites have evolved to function as physiological signals, conveying intracellular and environmental metabolic states to specific pathways to elicit appropriate cellular responses, whereas synthetic compounds are designed to rapidly alter protein function for mechanistic investigation or therapeutic benefit. Building on this conceptual framework, we develop MS- and data science-driven technologies to systematically map the ligandability and druggability of the human proteome, providing a foundation for the discovery of new therapeutic strategies for aging, metabolic disease, and cancer.
We are currently pursuing the following directions:
1. Developing mass spectrometry and machine learning approaches to elucidate molecular mechanisms of metabolic rewiring in cancer and aging.
2. Designing activity-based proteome profiling (ABPP) strategies to guide the development of chemical leads that target undrugged proteins or proteins known to develop drug resistance.
3. Combining mass spectrometry with genetic perturbations to mechanistically define protein functions at scale.
4. Creating automation strategies for large-scale proteomics and metabolomics.
5. Defining the role of protein LRRC58 in physiology and disease, and developing chemical leads to target LRRC58 for potential therapeutic applications.
