The goal of this project, which is jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences and the Physics of Living Systems Program in the Division of Physics in the Mathematical and Physical Sciences Directorate, is to investigate how proteins share their energy landscape between folding and function. This research is guided by the dual goal of learning new physical principles governing protein landscapes and utilizing this theoretical machinery to move towards complex and not yet understood biological applications. It is amazing how cells have created a number of molecular machines specialized for undertaking tasks needed to control and maintain cellular functions with exquisite precision. Due to the fact that biomolecules fluctuate via thermal motion and their dynamics are diffusive, biological machines are fundamentally different from conventional heat engines or machines in the macroscopic world. One of the key features of biological machines is the conformational changes triggered by the thermal noise under weak environmental perturbation. Therefore their behavior can be explained using ideas borrowed from the energy landscape theory of protein folding and polymer dynamics. Under this framework, energy landscape theory can be generalized to investigate how proteins share their energy landscape between folding and function. The current SMOG suite of structure-based models (SBM) will be generalized to investigate important features necessary for complex biological function. Especially important will be to increase the ability of these models to incorporate the multiple conformations occupied by many functional proteins. To fully explore the interplay between energetic and geometrical contributions, SBM's will integrate multiple levels of coarse-graining; lower resolution models handle larger systems and longer times while higher resolution ones focus on details. At the same time, structural constraints will be reduced, requiring less structural but more physical information. A key step in this transition is the integration of SBM and explicit solvent simulations. SBM models probe long-time and large-length scale molecular motions while explicit solvent simulations deal with shorter times and smaller systems. A combination of this suite of methods with new state of the art experiments will be used to investigate problems that integrate folding and function.
The PI's energy landscape theory has had an enormous impact in the protein folding community. Software developed by the PI is freely disseminated, which is widely used by theoreticians and experimentalists. These advances will continue to drive successful collaborations with experimental groups. The PI has an outstanding track record in training students and postdoctoral fellows in the highly interdisciplinary field of molecular biophysics. Many of the PI's students and postdoctoral fellows are now professors at major universities. The PI has always had a good representation of women and members from underrepresented groups in his research. This strong training effort will continue during the next period.
