The <i>structure-function hypothesis</i> postulates that the functional characteristics in biomolecules are encoded in their structures. However, biomolecules such as proteins often do not adopt a single static structure, but an ensemble of dynamic states that rapidly interconvert in solution, and are selected for various functional tasks in cells. While many experimental techniques in structural biology have remarkably led to elucidation of a vast “structural universe” of proteins, the number of distinct conformations known for a given protein is several orders-of-magnitude low (in most cases only one). Therefore, our current knowledge of biomolecular function and disease is limited to a very few known conformational states, yet the knowledge of the entire accessible conformational space is potentially desired. To fill this gap, biophysical theory, modeling, and simulation techniques rooted in statistical mechanics are playing an increasingly important role in elucidating conformational dynamics in various proteins. Conventional simulation methods, however, remain limited in providing information on conformational statistics—particularly on transiently-populated and metastable states. In this talk, I will present successful applications of new and emerging all-atom simulation techniques that allow spontaneous observation of rare conformational transitions in proteins with minimally a single known-structure as input. This is significant because information on such transitions is encoded in the physical free-energy landscape of proteins, the robust sampling of which can provide key thermodynamic and kinetic information on conformational ensembles of various proteins. The simulation methodologies and concepts presented in this talk are potentially useful for understanding a broad spectrum of problems in protein dynamics and molecular biophysics.<br/>

All-atom simulation approaches to probe dynamics in proteins

251st National Meeting (2016)

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