Membrane proteins are notoriously difficult to study. It’s why scientists have turned to computational methods to try to predict their characteristics. For her thesis research, Samantha Anderson of the Senes Lab investigated a specific motif — a short sequence common among membrane proteins — and how it impacts the way membrane proteins interact with each other. Using a computational method, she successfully predicted the structure and strength of association of a set of membrane proteins that contained the motif, discovering some of the important rules that govern their association. As a next step, she collaborated with the Raman Lab to develop a method for gathering high throughput data on membrane protein association. This highly needed data will enable researchers to dissect the secrets of membrane protein association in even better detail.
To learn more about her research, attend her Thesis Defense on Friday, Oct. 18 in Room 1211 of the HFD Biochemical Sciences Building.