Dynamics in computational protein engineering

BIOT 430

Nikolay V. Dokholyan, dokh@med.unc.edu, Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Campus Box #7260, Chapel Hill, NC 27599-7260
Some of the emerging goals in modern medicine are to uncover the molecular origins of human diseases, and ultimately contribute to the development of new therapeutic strategies to rationally abate disease. Of immediate interests are the roles of molecular structure and dynamics in certain cellular processes leading to human diseases and the ability to rationally manipulate these processes. Despite recent revolutionary advances in experimental methodologies, we are still limited in our ability to sample and decipher the structural and dynamic aspects of single molecules that are critical for their biological function. Thus, there is a crucial need for new and unorthodox techniques to uncover the fundamentals of molecular structure and interactions. We follow a hypothesis-driven approach which is based on tailoring simplified protein models to the systems of interest. Such an approach allows significantly extending the length and time scales for studies of complex biological systems. I will describe several recent studies that signify the predictive power of simplified protein models within the hypothesis-driven modeling approach.