Research Starter Grant: New Physics-Based Approaches to Predictive Protein Modeling, with Applications to Cellular Regulation

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The objective of this project is to develop new computational methods for protein structure prediction that are based on all-atom physics based models, with the specific goal of providing new computational tools to investigate the structural mechanisms of cellular regulation. All though there are numerous examples of all-atom physical chemical models that are being used to elucidate the function of specific proteins, such models currently play a very limited role in predictive modeling. From the standpoint of algorithmic development, the central emphasis is on the implementation of new sampling methods, which complement molecular dynamics, for efficiently exploring the energetic landscape of a protein starting from a suitable initial guess (for example, homology model), and on the validation and refinement of energetic models for protein structure prediction. Specific applications include homology modeling of kinases, the prediction of structural/dynamical changes due to phosphorylation, and prediction of the packing arrangements of multi-domain proteins.