UCSF

Proteins are fascinating machines, and the investigation of their structures has led to many insights in biology and drug discovery. Proteins are not static, and their dynamics and their sub-populated states are often relevant to their natural function or regulation. During my PhD, I worked on several projects revolving around the concept that by modeling multiple conformations from structural data, and therefore capturing the flexibility of protein structure, that enhanced insight could be gained from the structural data. First, I was involved in a review that described the state of the field in what was known about the extent of protein dynamics and the state of the art for measuring and modeling the states sampled by the protein. From there, I solved the structure of several ubiquitin mutants that undergone design and selection to alter their function. By collecting high resolution room temperature crystal structures, we revealed the extent of change in conformational heterogeneity across the directed evolution of these mutants. Finally, due to advances in technology and algorithms, we moved on to modeling minor states that were the result of a ligand binding event at less than full occupancy. I was involved in the fragment screening experiment for the protein PTP1B, where we assessed the ligandability of the protein via both cryo and room-temperature data collection.