The long-term goal of our research is to understand the structural and dynamic information encoded in the linear sequence of amino acids. Proteins undergo an incredible transformation from one-dimensional sequence information into complex three-dimensional shapes that carry out intricate cellular functions. We still, however, don’t have enough biophysical knowledge to translate this sequence information into functional insights. For instance, many proteins share the same native structure yet their cellular dynamics and function, in other words their energy landscapes, are different. Our laboratory uses a combination of biophysical, structural and computational techniques to understand these features.
In addition to the native conformation, a protein sequence populates small fluctuations around the native state, partially unfolded forms and even the globally unfolded conformation. Such non-native states on the energy landscape are thought to play a determining function in many cellular processes such as translocation, protein synthesis, degradation, signaling and allostery. They are also prone to aggregation, a phenomena which has been implicated for many diseases (the so-called misfolding and amyloid diseases). Understanding the sequence determinants of the energy landscape is therefore fundamental to the biological process that proteins carry out as well as protein folding itself.