Haopeng Xiao

We combine mass spectrometry-based proteomics and metabolomics with machine learning to uncover mechanisms of metabolic regulation over protein function in health and disease. We aim to use this as a basis to develop translational therapeutics for aging, metabolic disease, and cancer.

Our current research directions include:

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 prone to 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 Leucine-Rich Repeat-Containing Protein 58 (LRRC58)-a protein we deorphanized-in physiology and disease, and developing chemical leads to target LRRC58 for therapeutic benefit.